Amazon Kinesis Data Streams is a managed service that scales elastically for real-time processing of streaming big data.
", "operations": { - "AddTagsToStream": "Adds or updates tags for the specified Kinesis data stream. You can assign up to 50 tags to a data stream.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
If tags have already been assigned to the stream, AddTagsToStream overwrites any existing tags that correspond to the specified tag keys.
AddTagsToStream has a limit of five transactions per second per account.
", + "AddTagsToStream": "Adds or updates tags for the specified Kinesis data stream. You can assign up to 50 tags to a data stream.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
If tags have already been assigned to the stream, AddTagsToStream overwrites any existing tags that correspond to the specified tag keys.
AddTagsToStream has a limit of five transactions per second per account.
", "CreateStream": "Creates a Kinesis data stream. A stream captures and transports data records that are continuously emitted from different data sources or producers. Scale-out within a stream is explicitly supported by means of shards, which are uniquely identified groups of data records in a stream.
You can create your data stream using either on-demand or provisioned capacity mode. Data streams with an on-demand mode require no capacity planning and automatically scale to handle gigabytes of write and read throughput per minute. With the on-demand mode, Kinesis Data Streams automatically manages the shards in order to provide the necessary throughput. For the data streams with a provisioned mode, you must specify the number of shards for the data stream. Each shard can support reads up to five transactions per second, up to a maximum data read total of 2 MiB per second. Each shard can support writes up to 1,000 records per second, up to a maximum data write total of 1 MiB per second. If the amount of data input increases or decreases, you can add or remove shards.
The stream name identifies the stream. The name is scoped to the Amazon Web Services account used by the application. It is also scoped by Amazon Web Services Region. That is, two streams in two different accounts can have the same name, and two streams in the same account, but in two different Regions, can have the same name.
CreateStream is an asynchronous operation. Upon receiving a CreateStream request, Kinesis Data Streams immediately returns and sets the stream status to CREATING. After the stream is created, Kinesis Data Streams sets the stream status to ACTIVE. You should perform read and write operations only on an ACTIVE stream.
You receive a LimitExceededException when making a CreateStream request when you try to do one of the following:
Have more than five streams in the CREATING state at any point in time.
Create more shards than are authorized for your account.
For the default shard limit for an Amazon Web Services account, see Amazon Kinesis Data Streams Limits in the Amazon Kinesis Data Streams Developer Guide. To increase this limit, contact Amazon Web Services Support.
You can use DescribeStreamSummary to check the stream status, which is returned in StreamStatus.
CreateStream has a limit of five transactions per second per account.
", - "DecreaseStreamRetentionPeriod": "Decreases the Kinesis data stream's retention period, which is the length of time data records are accessible after they are added to the stream. The minimum value of a stream's retention period is 24 hours.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
This operation may result in lost data. For example, if the stream's retention period is 48 hours and is decreased to 24 hours, any data already in the stream that is older than 24 hours is inaccessible.
", - "DeleteStream": "Deletes a Kinesis data stream and all its shards and data. You must shut down any applications that are operating on the stream before you delete the stream. If an application attempts to operate on a deleted stream, it receives the exception ResourceNotFoundException.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
If the stream is in the ACTIVE state, you can delete it. After a DeleteStream request, the specified stream is in the DELETING state until Kinesis Data Streams completes the deletion.
Note: Kinesis Data Streams might continue to accept data read and write operations, such as PutRecord, PutRecords, and GetRecords, on a stream in the DELETING state until the stream deletion is complete.
When you delete a stream, any shards in that stream are also deleted, and any tags are dissociated from the stream.
You can use the DescribeStreamSummary operation to check the state of the stream, which is returned in StreamStatus.
DeleteStream has a limit of five transactions per second per account.
", + "DecreaseStreamRetentionPeriod": "Decreases the Kinesis data stream's retention period, which is the length of time data records are accessible after they are added to the stream. The minimum value of a stream's retention period is 24 hours.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
This operation may result in lost data. For example, if the stream's retention period is 48 hours and is decreased to 24 hours, any data already in the stream that is older than 24 hours is inaccessible.
", + "DeleteResourcePolicy": "Delete a policy for the specified data stream or consumer. Request patterns can be one of the following:
Data stream pattern: arn:aws.*:kinesis:.*:\\d{12}:.*stream/\\S+
Consumer pattern: ^(arn):aws.*:kinesis:.*:\\d{12}:.*stream\\/[a-zA-Z0-9_.-]+\\/consumer\\/[a-zA-Z0-9_.-]+:[0-9]+
Deletes a Kinesis data stream and all its shards and data. You must shut down any applications that are operating on the stream before you delete the stream. If an application attempts to operate on a deleted stream, it receives the exception ResourceNotFoundException.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
If the stream is in the ACTIVE state, you can delete it. After a DeleteStream request, the specified stream is in the DELETING state until Kinesis Data Streams completes the deletion.
Note: Kinesis Data Streams might continue to accept data read and write operations, such as PutRecord, PutRecords, and GetRecords, on a stream in the DELETING state until the stream deletion is complete.
When you delete a stream, any shards in that stream are also deleted, and any tags are dissociated from the stream.
You can use the DescribeStreamSummary operation to check the state of the stream, which is returned in StreamStatus.
DeleteStream has a limit of five transactions per second per account.
", "DeregisterStreamConsumer": "To deregister a consumer, provide its ARN. Alternatively, you can provide the ARN of the data stream and the name you gave the consumer when you registered it. You may also provide all three parameters, as long as they don't conflict with each other. If you don't know the name or ARN of the consumer that you want to deregister, you can use the ListStreamConsumers operation to get a list of the descriptions of all the consumers that are currently registered with a given data stream. The description of a consumer contains its name and ARN.
This operation has a limit of five transactions per second per stream.
", "DescribeLimits": "Describes the shard limits and usage for the account.
If you update your account limits, the old limits might be returned for a few minutes.
This operation has a limit of one transaction per second per account.
", - "DescribeStream": "Describes the specified Kinesis data stream.
This API has been revised. It's highly recommended that you use the DescribeStreamSummary API to get a summarized description of the specified Kinesis data stream and the ListShards API to list the shards in a specified data stream and obtain information about each shard.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
The information returned includes the stream name, Amazon Resource Name (ARN), creation time, enhanced metric configuration, and shard map. The shard map is an array of shard objects. For each shard object, there is the hash key and sequence number ranges that the shard spans, and the IDs of any earlier shards that played in a role in creating the shard. Every record ingested in the stream is identified by a sequence number, which is assigned when the record is put into the stream.
You can limit the number of shards returned by each call. For more information, see Retrieving Shards from a Stream in the Amazon Kinesis Data Streams Developer Guide.
There are no guarantees about the chronological order shards returned. To process shards in chronological order, use the ID of the parent shard to track the lineage to the oldest shard.
This operation has a limit of 10 transactions per second per account.
", - "DescribeStreamConsumer": "To get the description of a registered consumer, provide the ARN of the consumer. Alternatively, you can provide the ARN of the data stream and the name you gave the consumer when you registered it. You may also provide all three parameters, as long as they don't conflict with each other. If you don't know the name or ARN of the consumer that you want to describe, you can use the ListStreamConsumers operation to get a list of the descriptions of all the consumers that are currently registered with a given data stream.
This operation has a limit of 20 transactions per second per stream.
", - "DescribeStreamSummary": "Provides a summarized description of the specified Kinesis data stream without the shard list.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
The information returned includes the stream name, Amazon Resource Name (ARN), status, record retention period, approximate creation time, monitoring, encryption details, and open shard count.
DescribeStreamSummary has a limit of 20 transactions per second per account.
", - "DisableEnhancedMonitoring": "Disables enhanced monitoring.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
Enables enhanced Kinesis data stream monitoring for shard-level metrics.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
Gets data records from a Kinesis data stream's shard.
When invoking this API, it is recommended you use the StreamARN input parameter in addition to the ShardIterator parameter.
Specify a shard iterator using the ShardIterator parameter. The shard iterator specifies the position in the shard from which you want to start reading data records sequentially. If there are no records available in the portion of the shard that the iterator points to, GetRecords returns an empty list. It might take multiple calls to get to a portion of the shard that contains records.
You can scale by provisioning multiple shards per stream while considering service limits (for more information, see Amazon Kinesis Data Streams Limits in the Amazon Kinesis Data Streams Developer Guide). Your application should have one thread per shard, each reading continuously from its stream. To read from a stream continually, call GetRecords in a loop. Use GetShardIterator to get the shard iterator to specify in the first GetRecords call. GetRecords returns a new shard iterator in NextShardIterator. Specify the shard iterator returned in NextShardIterator in subsequent calls to GetRecords. If the shard has been closed, the shard iterator can't return more data and GetRecords returns null in NextShardIterator. You can terminate the loop when the shard is closed, or when the shard iterator reaches the record with the sequence number or other attribute that marks it as the last record to process.
Each data record can be up to 1 MiB in size, and each shard can read up to 2 MiB per second. You can ensure that your calls don't exceed the maximum supported size or throughput by using the Limit parameter to specify the maximum number of records that GetRecords can return. Consider your average record size when determining this limit. The maximum number of records that can be returned per call is 10,000.
The size of the data returned by GetRecords varies depending on the utilization of the shard. It is recommended that consumer applications retrieve records via the GetRecords command using the 5 TPS limit to remain caught up. Retrieving records less frequently can lead to consumer applications falling behind. The maximum size of data that GetRecords can return is 10 MiB. If a call returns this amount of data, subsequent calls made within the next 5 seconds throw ProvisionedThroughputExceededException. If there is insufficient provisioned throughput on the stream, subsequent calls made within the next 1 second throw ProvisionedThroughputExceededException. GetRecords doesn't return any data when it throws an exception. For this reason, we recommend that you wait 1 second between calls to GetRecords. However, it's possible that the application will get exceptions for longer than 1 second.
To detect whether the application is falling behind in processing, you can use the MillisBehindLatest response attribute. You can also monitor the stream using CloudWatch metrics and other mechanisms (see Monitoring in the Amazon Kinesis Data Streams Developer Guide).
Each Amazon Kinesis record includes a value, ApproximateArrivalTimestamp, that is set when a stream successfully receives and stores a record. This is commonly referred to as a server-side time stamp, whereas a client-side time stamp is set when a data producer creates or sends the record to a stream (a data producer is any data source putting data records into a stream, for example with PutRecords). The time stamp has millisecond precision. There are no guarantees about the time stamp accuracy, or that the time stamp is always increasing. For example, records in a shard or across a stream might have time stamps that are out of order.
This operation has a limit of five transactions per second per shard.
", - "GetShardIterator": "Gets an Amazon Kinesis shard iterator. A shard iterator expires 5 minutes after it is returned to the requester.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
A shard iterator specifies the shard position from which to start reading data records sequentially. The position is specified using the sequence number of a data record in a shard. A sequence number is the identifier associated with every record ingested in the stream, and is assigned when a record is put into the stream. Each stream has one or more shards.
You must specify the shard iterator type. For example, you can set the ShardIteratorType parameter to read exactly from the position denoted by a specific sequence number by using the AT_SEQUENCE_NUMBER shard iterator type. Alternatively, the parameter can read right after the sequence number by using the AFTER_SEQUENCE_NUMBER shard iterator type, using sequence numbers returned by earlier calls to PutRecord, PutRecords, GetRecords, or DescribeStream. In the request, you can specify the shard iterator type AT_TIMESTAMP to read records from an arbitrary point in time, TRIM_HORIZON to cause ShardIterator to point to the last untrimmed record in the shard in the system (the oldest data record in the shard), or LATEST so that you always read the most recent data in the shard.
When you read repeatedly from a stream, use a GetShardIterator request to get the first shard iterator for use in your first GetRecords request and for subsequent reads use the shard iterator returned by the GetRecords request in NextShardIterator. A new shard iterator is returned by every GetRecords request in NextShardIterator, which you use in the ShardIterator parameter of the next GetRecords request.
If a GetShardIterator request is made too often, you receive a ProvisionedThroughputExceededException. For more information about throughput limits, see GetRecords, and Streams Limits in the Amazon Kinesis Data Streams Developer Guide.
If the shard is closed, GetShardIterator returns a valid iterator for the last sequence number of the shard. A shard can be closed as a result of using SplitShard or MergeShards.
GetShardIterator has a limit of five transactions per second per account per open shard.
", - "IncreaseStreamRetentionPeriod": "Increases the Kinesis data stream's retention period, which is the length of time data records are accessible after they are added to the stream. The maximum value of a stream's retention period is 8760 hours (365 days).
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
If you choose a longer stream retention period, this operation increases the time period during which records that have not yet expired are accessible. However, it does not make previous, expired data (older than the stream's previous retention period) accessible after the operation has been called. For example, if a stream's retention period is set to 24 hours and is increased to 168 hours, any data that is older than 24 hours remains inaccessible to consumer applications.
", - "ListShards": "Lists the shards in a stream and provides information about each shard. This operation has a limit of 1000 transactions per second per data stream.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
This action does not list expired shards. For information about expired shards, see Data Routing, Data Persistence, and Shard State after a Reshard.
This API is a new operation that is used by the Amazon Kinesis Client Library (KCL). If you have a fine-grained IAM policy that only allows specific operations, you must update your policy to allow calls to this API. For more information, see Controlling Access to Amazon Kinesis Data Streams Resources Using IAM.
Describes the specified Kinesis data stream.
This API has been revised. It's highly recommended that you use the DescribeStreamSummary API to get a summarized description of the specified Kinesis data stream and the ListShards API to list the shards in a specified data stream and obtain information about each shard.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
The information returned includes the stream name, Amazon Resource Name (ARN), creation time, enhanced metric configuration, and shard map. The shard map is an array of shard objects. For each shard object, there is the hash key and sequence number ranges that the shard spans, and the IDs of any earlier shards that played in a role in creating the shard. Every record ingested in the stream is identified by a sequence number, which is assigned when the record is put into the stream.
You can limit the number of shards returned by each call. For more information, see Retrieving Shards from a Stream in the Amazon Kinesis Data Streams Developer Guide.
There are no guarantees about the chronological order shards returned. To process shards in chronological order, use the ID of the parent shard to track the lineage to the oldest shard.
This operation has a limit of 10 transactions per second per account.
", + "DescribeStreamConsumer": "To get the description of a registered consumer, provide the ARN of the consumer. Alternatively, you can provide the ARN of the data stream and the name you gave the consumer when you registered it. You may also provide all three parameters, as long as they don't conflict with each other. If you don't know the name or ARN of the consumer that you want to describe, you can use the ListStreamConsumers operation to get a list of the descriptions of all the consumers that are currently registered with a given data stream.
This operation has a limit of 20 transactions per second per stream.
When making a cross-account call with DescribeStreamConsumer, make sure to provide the ARN of the consumer.
Provides a summarized description of the specified Kinesis data stream without the shard list.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
The information returned includes the stream name, Amazon Resource Name (ARN), status, record retention period, approximate creation time, monitoring, encryption details, and open shard count.
DescribeStreamSummary has a limit of 20 transactions per second per account.
", + "DisableEnhancedMonitoring": "Disables enhanced monitoring.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
Enables enhanced Kinesis data stream monitoring for shard-level metrics.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
Gets data records from a Kinesis data stream's shard.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
Specify a shard iterator using the ShardIterator parameter. The shard iterator specifies the position in the shard from which you want to start reading data records sequentially. If there are no records available in the portion of the shard that the iterator points to, GetRecords returns an empty list. It might take multiple calls to get to a portion of the shard that contains records.
You can scale by provisioning multiple shards per stream while considering service limits (for more information, see Amazon Kinesis Data Streams Limits in the Amazon Kinesis Data Streams Developer Guide). Your application should have one thread per shard, each reading continuously from its stream. To read from a stream continually, call GetRecords in a loop. Use GetShardIterator to get the shard iterator to specify in the first GetRecords call. GetRecords returns a new shard iterator in NextShardIterator. Specify the shard iterator returned in NextShardIterator in subsequent calls to GetRecords. If the shard has been closed, the shard iterator can't return more data and GetRecords returns null in NextShardIterator. You can terminate the loop when the shard is closed, or when the shard iterator reaches the record with the sequence number or other attribute that marks it as the last record to process.
Each data record can be up to 1 MiB in size, and each shard can read up to 2 MiB per second. You can ensure that your calls don't exceed the maximum supported size or throughput by using the Limit parameter to specify the maximum number of records that GetRecords can return. Consider your average record size when determining this limit. The maximum number of records that can be returned per call is 10,000.
The size of the data returned by GetRecords varies depending on the utilization of the shard. It is recommended that consumer applications retrieve records via the GetRecords command using the 5 TPS limit to remain caught up. Retrieving records less frequently can lead to consumer applications falling behind. The maximum size of data that GetRecords can return is 10 MiB. If a call returns this amount of data, subsequent calls made within the next 5 seconds throw ProvisionedThroughputExceededException. If there is insufficient provisioned throughput on the stream, subsequent calls made within the next 1 second throw ProvisionedThroughputExceededException. GetRecords doesn't return any data when it throws an exception. For this reason, we recommend that you wait 1 second between calls to GetRecords. However, it's possible that the application will get exceptions for longer than 1 second.
To detect whether the application is falling behind in processing, you can use the MillisBehindLatest response attribute. You can also monitor the stream using CloudWatch metrics and other mechanisms (see Monitoring in the Amazon Kinesis Data Streams Developer Guide).
Each Amazon Kinesis record includes a value, ApproximateArrivalTimestamp, that is set when a stream successfully receives and stores a record. This is commonly referred to as a server-side time stamp, whereas a client-side time stamp is set when a data producer creates or sends the record to a stream (a data producer is any data source putting data records into a stream, for example with PutRecords). The time stamp has millisecond precision. There are no guarantees about the time stamp accuracy, or that the time stamp is always increasing. For example, records in a shard or across a stream might have time stamps that are out of order.
This operation has a limit of five transactions per second per shard.
", + "GetResourcePolicy": "Returns a policy attached to the specified data stream or consumer. Request patterns can be one of the following:
Data stream pattern: arn:aws.*:kinesis:.*:\\d{12}:.*stream/\\S+
Consumer pattern: ^(arn):aws.*:kinesis:.*:\\d{12}:.*stream\\/[a-zA-Z0-9_.-]+\\/consumer\\/[a-zA-Z0-9_.-]+:[0-9]+
Gets an Amazon Kinesis shard iterator. A shard iterator expires 5 minutes after it is returned to the requester.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
A shard iterator specifies the shard position from which to start reading data records sequentially. The position is specified using the sequence number of a data record in a shard. A sequence number is the identifier associated with every record ingested in the stream, and is assigned when a record is put into the stream. Each stream has one or more shards.
You must specify the shard iterator type. For example, you can set the ShardIteratorType parameter to read exactly from the position denoted by a specific sequence number by using the AT_SEQUENCE_NUMBER shard iterator type. Alternatively, the parameter can read right after the sequence number by using the AFTER_SEQUENCE_NUMBER shard iterator type, using sequence numbers returned by earlier calls to PutRecord, PutRecords, GetRecords, or DescribeStream. In the request, you can specify the shard iterator type AT_TIMESTAMP to read records from an arbitrary point in time, TRIM_HORIZON to cause ShardIterator to point to the last untrimmed record in the shard in the system (the oldest data record in the shard), or LATEST so that you always read the most recent data in the shard.
When you read repeatedly from a stream, use a GetShardIterator request to get the first shard iterator for use in your first GetRecords request and for subsequent reads use the shard iterator returned by the GetRecords request in NextShardIterator. A new shard iterator is returned by every GetRecords request in NextShardIterator, which you use in the ShardIterator parameter of the next GetRecords request.
If a GetShardIterator request is made too often, you receive a ProvisionedThroughputExceededException. For more information about throughput limits, see GetRecords, and Streams Limits in the Amazon Kinesis Data Streams Developer Guide.
If the shard is closed, GetShardIterator returns a valid iterator for the last sequence number of the shard. A shard can be closed as a result of using SplitShard or MergeShards.
GetShardIterator has a limit of five transactions per second per account per open shard.
", + "IncreaseStreamRetentionPeriod": "Increases the Kinesis data stream's retention period, which is the length of time data records are accessible after they are added to the stream. The maximum value of a stream's retention period is 8760 hours (365 days).
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
If you choose a longer stream retention period, this operation increases the time period during which records that have not yet expired are accessible. However, it does not make previous, expired data (older than the stream's previous retention period) accessible after the operation has been called. For example, if a stream's retention period is set to 24 hours and is increased to 168 hours, any data that is older than 24 hours remains inaccessible to consumer applications.
", + "ListShards": "Lists the shards in a stream and provides information about each shard. This operation has a limit of 1000 transactions per second per data stream.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
This action does not list expired shards. For information about expired shards, see Data Routing, Data Persistence, and Shard State after a Reshard.
This API is a new operation that is used by the Amazon Kinesis Client Library (KCL). If you have a fine-grained IAM policy that only allows specific operations, you must update your policy to allow calls to this API. For more information, see Controlling Access to Amazon Kinesis Data Streams Resources Using IAM.
Lists the consumers registered to receive data from a stream using enhanced fan-out, and provides information about each consumer.
This operation has a limit of 5 transactions per second per stream.
", "ListStreams": "Lists your Kinesis data streams.
The number of streams may be too large to return from a single call to ListStreams. You can limit the number of returned streams using the Limit parameter. If you do not specify a value for the Limit parameter, Kinesis Data Streams uses the default limit, which is currently 100.
You can detect if there are more streams available to list by using the HasMoreStreams flag from the returned output. If there are more streams available, you can request more streams by using the name of the last stream returned by the ListStreams request in the ExclusiveStartStreamName parameter in a subsequent request to ListStreams. The group of stream names returned by the subsequent request is then added to the list. You can continue this process until all the stream names have been collected in the list.
ListStreams has a limit of five transactions per second per account.
", - "ListTagsForStream": "Lists the tags for the specified Kinesis data stream. This operation has a limit of five transactions per second per account.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
Merges two adjacent shards in a Kinesis data stream and combines them into a single shard to reduce the stream's capacity to ingest and transport data. This API is only supported for the data streams with the provisioned capacity mode. Two shards are considered adjacent if the union of the hash key ranges for the two shards form a contiguous set with no gaps. For example, if you have two shards, one with a hash key range of 276...381 and the other with a hash key range of 382...454, then you could merge these two shards into a single shard that would have a hash key range of 276...454. After the merge, the single child shard receives data for all hash key values covered by the two parent shards.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
MergeShards is called when there is a need to reduce the overall capacity of a stream because of excess capacity that is not being used. You must specify the shard to be merged and the adjacent shard for a stream. For more information about merging shards, see Merge Two Shards in the Amazon Kinesis Data Streams Developer Guide.
If the stream is in the ACTIVE state, you can call MergeShards. If a stream is in the CREATING, UPDATING, or DELETING state, MergeShards returns a ResourceInUseException. If the specified stream does not exist, MergeShards returns a ResourceNotFoundException.
You can use DescribeStreamSummary to check the state of the stream, which is returned in StreamStatus.
MergeShards is an asynchronous operation. Upon receiving a MergeShards request, Amazon Kinesis Data Streams immediately returns a response and sets the StreamStatus to UPDATING. After the operation is completed, Kinesis Data Streams sets the StreamStatus to ACTIVE. Read and write operations continue to work while the stream is in the UPDATING state.
You use DescribeStreamSummary and the ListShards APIs to determine the shard IDs that are specified in the MergeShards request.
If you try to operate on too many streams in parallel using CreateStream, DeleteStream, MergeShards, or SplitShard, you receive a LimitExceededException.
MergeShards has a limit of five transactions per second per account.
Writes a single data record into an Amazon Kinesis data stream. Call PutRecord to send data into the stream for real-time ingestion and subsequent processing, one record at a time. Each shard can support writes up to 1,000 records per second, up to a maximum data write total of 1 MiB per second.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
You must specify the name of the stream that captures, stores, and transports the data; a partition key; and the data blob itself.
The data blob can be any type of data; for example, a segment from a log file, geographic/location data, website clickstream data, and so on.
The partition key is used by Kinesis Data Streams to distribute data across shards. Kinesis Data Streams segregates the data records that belong to a stream into multiple shards, using the partition key associated with each data record to determine the shard to which a given data record belongs.
Partition keys are Unicode strings, with a maximum length limit of 256 characters for each key. An MD5 hash function is used to map partition keys to 128-bit integer values and to map associated data records to shards using the hash key ranges of the shards. You can override hashing the partition key to determine the shard by explicitly specifying a hash value using the ExplicitHashKey parameter. For more information, see Adding Data to a Stream in the Amazon Kinesis Data Streams Developer Guide.
PutRecord returns the shard ID of where the data record was placed and the sequence number that was assigned to the data record.
Sequence numbers increase over time and are specific to a shard within a stream, not across all shards within a stream. To guarantee strictly increasing ordering, write serially to a shard and use the SequenceNumberForOrdering parameter. For more information, see Adding Data to a Stream in the Amazon Kinesis Data Streams Developer Guide.
After you write a record to a stream, you cannot modify that record or its order within the stream.
If a PutRecord request cannot be processed because of insufficient provisioned throughput on the shard involved in the request, PutRecord throws ProvisionedThroughputExceededException.
By default, data records are accessible for 24 hours from the time that they are added to a stream. You can use IncreaseStreamRetentionPeriod or DecreaseStreamRetentionPeriod to modify this retention period.
", - "PutRecords": "Writes multiple data records into a Kinesis data stream in a single call (also referred to as a PutRecords request). Use this operation to send data into the stream for data ingestion and processing.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
Each PutRecords request can support up to 500 records. Each record in the request can be as large as 1 MiB, up to a limit of 5 MiB for the entire request, including partition keys. Each shard can support writes up to 1,000 records per second, up to a maximum data write total of 1 MiB per second.
You must specify the name of the stream that captures, stores, and transports the data; and an array of request Records, with each record in the array requiring a partition key and data blob. The record size limit applies to the total size of the partition key and data blob.
The data blob can be any type of data; for example, a segment from a log file, geographic/location data, website clickstream data, and so on.
The partition key is used by Kinesis Data Streams as input to a hash function that maps the partition key and associated data to a specific shard. An MD5 hash function is used to map partition keys to 128-bit integer values and to map associated data records to shards. As a result of this hashing mechanism, all data records with the same partition key map to the same shard within the stream. For more information, see Adding Data to a Stream in the Amazon Kinesis Data Streams Developer Guide.
Each record in the Records array may include an optional parameter, ExplicitHashKey, which overrides the partition key to shard mapping. This parameter allows a data producer to determine explicitly the shard where the record is stored. For more information, see Adding Multiple Records with PutRecords in the Amazon Kinesis Data Streams Developer Guide.
The PutRecords response includes an array of response Records. Each record in the response array directly correlates with a record in the request array using natural ordering, from the top to the bottom of the request and response. The response Records array always includes the same number of records as the request array.
The response Records array includes both successfully and unsuccessfully processed records. Kinesis Data Streams attempts to process all records in each PutRecords request. A single record failure does not stop the processing of subsequent records. As a result, PutRecords doesn't guarantee the ordering of records. If you need to read records in the same order they are written to the stream, use PutRecord instead of PutRecords, and write to the same shard.
A successfully processed record includes ShardId and SequenceNumber values. The ShardId parameter identifies the shard in the stream where the record is stored. The SequenceNumber parameter is an identifier assigned to the put record, unique to all records in the stream.
An unsuccessfully processed record includes ErrorCode and ErrorMessage values. ErrorCode reflects the type of error and can be one of the following values: ProvisionedThroughputExceededException or InternalFailure. ErrorMessage provides more detailed information about the ProvisionedThroughputExceededException exception including the account ID, stream name, and shard ID of the record that was throttled. For more information about partially successful responses, see Adding Multiple Records with PutRecords in the Amazon Kinesis Data Streams Developer Guide.
After you write a record to a stream, you cannot modify that record or its order within the stream.
By default, data records are accessible for 24 hours from the time that they are added to a stream. You can use IncreaseStreamRetentionPeriod or DecreaseStreamRetentionPeriod to modify this retention period.
", + "ListTagsForStream": "Lists the tags for the specified Kinesis data stream. This operation has a limit of five transactions per second per account.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
Merges two adjacent shards in a Kinesis data stream and combines them into a single shard to reduce the stream's capacity to ingest and transport data. This API is only supported for the data streams with the provisioned capacity mode. Two shards are considered adjacent if the union of the hash key ranges for the two shards form a contiguous set with no gaps. For example, if you have two shards, one with a hash key range of 276...381 and the other with a hash key range of 382...454, then you could merge these two shards into a single shard that would have a hash key range of 276...454. After the merge, the single child shard receives data for all hash key values covered by the two parent shards.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
MergeShards is called when there is a need to reduce the overall capacity of a stream because of excess capacity that is not being used. You must specify the shard to be merged and the adjacent shard for a stream. For more information about merging shards, see Merge Two Shards in the Amazon Kinesis Data Streams Developer Guide.
If the stream is in the ACTIVE state, you can call MergeShards. If a stream is in the CREATING, UPDATING, or DELETING state, MergeShards returns a ResourceInUseException. If the specified stream does not exist, MergeShards returns a ResourceNotFoundException.
You can use DescribeStreamSummary to check the state of the stream, which is returned in StreamStatus.
MergeShards is an asynchronous operation. Upon receiving a MergeShards request, Amazon Kinesis Data Streams immediately returns a response and sets the StreamStatus to UPDATING. After the operation is completed, Kinesis Data Streams sets the StreamStatus to ACTIVE. Read and write operations continue to work while the stream is in the UPDATING state.
You use DescribeStreamSummary and the ListShards APIs to determine the shard IDs that are specified in the MergeShards request.
If you try to operate on too many streams in parallel using CreateStream, DeleteStream, MergeShards, or SplitShard, you receive a LimitExceededException.
MergeShards has a limit of five transactions per second per account.
Writes a single data record into an Amazon Kinesis data stream. Call PutRecord to send data into the stream for real-time ingestion and subsequent processing, one record at a time. Each shard can support writes up to 1,000 records per second, up to a maximum data write total of 1 MiB per second.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
You must specify the name of the stream that captures, stores, and transports the data; a partition key; and the data blob itself.
The data blob can be any type of data; for example, a segment from a log file, geographic/location data, website clickstream data, and so on.
The partition key is used by Kinesis Data Streams to distribute data across shards. Kinesis Data Streams segregates the data records that belong to a stream into multiple shards, using the partition key associated with each data record to determine the shard to which a given data record belongs.
Partition keys are Unicode strings, with a maximum length limit of 256 characters for each key. An MD5 hash function is used to map partition keys to 128-bit integer values and to map associated data records to shards using the hash key ranges of the shards. You can override hashing the partition key to determine the shard by explicitly specifying a hash value using the ExplicitHashKey parameter. For more information, see Adding Data to a Stream in the Amazon Kinesis Data Streams Developer Guide.
PutRecord returns the shard ID of where the data record was placed and the sequence number that was assigned to the data record.
Sequence numbers increase over time and are specific to a shard within a stream, not across all shards within a stream. To guarantee strictly increasing ordering, write serially to a shard and use the SequenceNumberForOrdering parameter. For more information, see Adding Data to a Stream in the Amazon Kinesis Data Streams Developer Guide.
After you write a record to a stream, you cannot modify that record or its order within the stream.
If a PutRecord request cannot be processed because of insufficient provisioned throughput on the shard involved in the request, PutRecord throws ProvisionedThroughputExceededException.
By default, data records are accessible for 24 hours from the time that they are added to a stream. You can use IncreaseStreamRetentionPeriod or DecreaseStreamRetentionPeriod to modify this retention period.
", + "PutRecords": "Writes multiple data records into a Kinesis data stream in a single call (also referred to as a PutRecords request). Use this operation to send data into the stream for data ingestion and processing.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
Each PutRecords request can support up to 500 records. Each record in the request can be as large as 1 MiB, up to a limit of 5 MiB for the entire request, including partition keys. Each shard can support writes up to 1,000 records per second, up to a maximum data write total of 1 MiB per second.
You must specify the name of the stream that captures, stores, and transports the data; and an array of request Records, with each record in the array requiring a partition key and data blob. The record size limit applies to the total size of the partition key and data blob.
The data blob can be any type of data; for example, a segment from a log file, geographic/location data, website clickstream data, and so on.
The partition key is used by Kinesis Data Streams as input to a hash function that maps the partition key and associated data to a specific shard. An MD5 hash function is used to map partition keys to 128-bit integer values and to map associated data records to shards. As a result of this hashing mechanism, all data records with the same partition key map to the same shard within the stream. For more information, see Adding Data to a Stream in the Amazon Kinesis Data Streams Developer Guide.
Each record in the Records array may include an optional parameter, ExplicitHashKey, which overrides the partition key to shard mapping. This parameter allows a data producer to determine explicitly the shard where the record is stored. For more information, see Adding Multiple Records with PutRecords in the Amazon Kinesis Data Streams Developer Guide.
The PutRecords response includes an array of response Records. Each record in the response array directly correlates with a record in the request array using natural ordering, from the top to the bottom of the request and response. The response Records array always includes the same number of records as the request array.
The response Records array includes both successfully and unsuccessfully processed records. Kinesis Data Streams attempts to process all records in each PutRecords request. A single record failure does not stop the processing of subsequent records. As a result, PutRecords doesn't guarantee the ordering of records. If you need to read records in the same order they are written to the stream, use PutRecord instead of PutRecords, and write to the same shard.
A successfully processed record includes ShardId and SequenceNumber values. The ShardId parameter identifies the shard in the stream where the record is stored. The SequenceNumber parameter is an identifier assigned to the put record, unique to all records in the stream.
An unsuccessfully processed record includes ErrorCode and ErrorMessage values. ErrorCode reflects the type of error and can be one of the following values: ProvisionedThroughputExceededException or InternalFailure. ErrorMessage provides more detailed information about the ProvisionedThroughputExceededException exception including the account ID, stream name, and shard ID of the record that was throttled. For more information about partially successful responses, see Adding Multiple Records with PutRecords in the Amazon Kinesis Data Streams Developer Guide.
After you write a record to a stream, you cannot modify that record or its order within the stream.
By default, data records are accessible for 24 hours from the time that they are added to a stream. You can use IncreaseStreamRetentionPeriod or DecreaseStreamRetentionPeriod to modify this retention period.
", + "PutResourcePolicy": "Attaches a resource-based policy to a data stream or registered consumer. If you are using an identity other than the root user of the Amazon Web Services account that owns the resource, the calling identity must have the PutResourcePolicy permissions on the specified Kinesis Data Streams resource and belong to the owner's account in order to use this operation. If you don't have PutResourcePolicy permissions, Amazon Kinesis Data Streams returns a 403 Access Denied error. If you receive a ResourceNotFoundException, check to see if you passed a valid stream or consumer resource.
Request patterns can be one of the following:
Data stream pattern: arn:aws.*:kinesis:.*:\\d{12}:.*stream/\\S+
Consumer pattern: ^(arn):aws.*:kinesis:.*:\\d{12}:.*stream\\/[a-zA-Z0-9_.-]+\\/consumer\\/[a-zA-Z0-9_.-]+:[0-9]+
For more information, see Controlling Access to Amazon Kinesis Data Streams Resources Using IAM.
", "RegisterStreamConsumer": "Registers a consumer with a Kinesis data stream. When you use this operation, the consumer you register can then call SubscribeToShard to receive data from the stream using enhanced fan-out, at a rate of up to 2 MiB per second for every shard you subscribe to. This rate is unaffected by the total number of consumers that read from the same stream.
You can register up to 20 consumers per stream. A given consumer can only be registered with one stream at a time.
For an example of how to use this operations, see Enhanced Fan-Out Using the Kinesis Data Streams API.
The use of this operation has a limit of five transactions per second per account. Also, only 5 consumers can be created simultaneously. In other words, you cannot have more than 5 consumers in a CREATING status at the same time. Registering a 6th consumer while there are 5 in a CREATING status results in a LimitExceededException.
Removes tags from the specified Kinesis data stream. Removed tags are deleted and cannot be recovered after this operation successfully completes.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
If you specify a tag that does not exist, it is ignored.
RemoveTagsFromStream has a limit of five transactions per second per account.
", - "SplitShard": "Splits a shard into two new shards in the Kinesis data stream, to increase the stream's capacity to ingest and transport data. SplitShard is called when there is a need to increase the overall capacity of a stream because of an expected increase in the volume of data records being ingested. This API is only supported for the data streams with the provisioned capacity mode.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
You can also use SplitShard when a shard appears to be approaching its maximum utilization; for example, the producers sending data into the specific shard are suddenly sending more than previously anticipated. You can also call SplitShard to increase stream capacity, so that more Kinesis Data Streams applications can simultaneously read data from the stream for real-time processing.
You must specify the shard to be split and the new hash key, which is the position in the shard where the shard gets split in two. In many cases, the new hash key might be the average of the beginning and ending hash key, but it can be any hash key value in the range being mapped into the shard. For more information, see Split a Shard in the Amazon Kinesis Data Streams Developer Guide.
You can use DescribeStreamSummary and the ListShards APIs to determine the shard ID and hash key values for the ShardToSplit and NewStartingHashKey parameters that are specified in the SplitShard request.
SplitShard is an asynchronous operation. Upon receiving a SplitShard request, Kinesis Data Streams immediately returns a response and sets the stream status to UPDATING. After the operation is completed, Kinesis Data Streams sets the stream status to ACTIVE. Read and write operations continue to work while the stream is in the UPDATING state.
You can use DescribeStreamSummary to check the status of the stream, which is returned in StreamStatus. If the stream is in the ACTIVE state, you can call SplitShard.
If the specified stream does not exist, DescribeStreamSummary returns a ResourceNotFoundException. If you try to create more shards than are authorized for your account, you receive a LimitExceededException.
For the default shard limit for an Amazon Web Services account, see Kinesis Data Streams Limits in the Amazon Kinesis Data Streams Developer Guide. To increase this limit, contact Amazon Web Services Support.
If you try to operate on too many streams simultaneously using CreateStream, DeleteStream, MergeShards, and/or SplitShard, you receive a LimitExceededException.
SplitShard has a limit of five transactions per second per account.
Enables or updates server-side encryption using an Amazon Web Services KMS key for a specified stream.
Starting encryption is an asynchronous operation. Upon receiving the request, Kinesis Data Streams returns immediately and sets the status of the stream to UPDATING. After the update is complete, Kinesis Data Streams sets the status of the stream back to ACTIVE. Updating or applying encryption normally takes a few seconds to complete, but it can take minutes. You can continue to read and write data to your stream while its status is UPDATING. Once the status of the stream is ACTIVE, encryption begins for records written to the stream.
API Limits: You can successfully apply a new Amazon Web Services KMS key for server-side encryption 25 times in a rolling 24-hour period.
Note: It can take up to 5 seconds after the stream is in an ACTIVE status before all records written to the stream are encrypted. After you enable encryption, you can verify that encryption is applied by inspecting the API response from PutRecord or PutRecords.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
Disables server-side encryption for a specified stream.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
Stopping encryption is an asynchronous operation. Upon receiving the request, Kinesis Data Streams returns immediately and sets the status of the stream to UPDATING. After the update is complete, Kinesis Data Streams sets the status of the stream back to ACTIVE. Stopping encryption normally takes a few seconds to complete, but it can take minutes. You can continue to read and write data to your stream while its status is UPDATING. Once the status of the stream is ACTIVE, records written to the stream are no longer encrypted by Kinesis Data Streams.
API Limits: You can successfully disable server-side encryption 25 times in a rolling 24-hour period.
Note: It can take up to 5 seconds after the stream is in an ACTIVE status before all records written to the stream are no longer subject to encryption. After you disabled encryption, you can verify that encryption is not applied by inspecting the API response from PutRecord or PutRecords.
Removes tags from the specified Kinesis data stream. Removed tags are deleted and cannot be recovered after this operation successfully completes.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
If you specify a tag that does not exist, it is ignored.
RemoveTagsFromStream has a limit of five transactions per second per account.
", + "SplitShard": "Splits a shard into two new shards in the Kinesis data stream, to increase the stream's capacity to ingest and transport data. SplitShard is called when there is a need to increase the overall capacity of a stream because of an expected increase in the volume of data records being ingested. This API is only supported for the data streams with the provisioned capacity mode.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
You can also use SplitShard when a shard appears to be approaching its maximum utilization; for example, the producers sending data into the specific shard are suddenly sending more than previously anticipated. You can also call SplitShard to increase stream capacity, so that more Kinesis Data Streams applications can simultaneously read data from the stream for real-time processing.
You must specify the shard to be split and the new hash key, which is the position in the shard where the shard gets split in two. In many cases, the new hash key might be the average of the beginning and ending hash key, but it can be any hash key value in the range being mapped into the shard. For more information, see Split a Shard in the Amazon Kinesis Data Streams Developer Guide.
You can use DescribeStreamSummary and the ListShards APIs to determine the shard ID and hash key values for the ShardToSplit and NewStartingHashKey parameters that are specified in the SplitShard request.
SplitShard is an asynchronous operation. Upon receiving a SplitShard request, Kinesis Data Streams immediately returns a response and sets the stream status to UPDATING. After the operation is completed, Kinesis Data Streams sets the stream status to ACTIVE. Read and write operations continue to work while the stream is in the UPDATING state.
You can use DescribeStreamSummary to check the status of the stream, which is returned in StreamStatus. If the stream is in the ACTIVE state, you can call SplitShard.
If the specified stream does not exist, DescribeStreamSummary returns a ResourceNotFoundException. If you try to create more shards than are authorized for your account, you receive a LimitExceededException.
For the default shard limit for an Amazon Web Services account, see Kinesis Data Streams Limits in the Amazon Kinesis Data Streams Developer Guide. To increase this limit, contact Amazon Web Services Support.
If you try to operate on too many streams simultaneously using CreateStream, DeleteStream, MergeShards, and/or SplitShard, you receive a LimitExceededException.
SplitShard has a limit of five transactions per second per account.
Enables or updates server-side encryption using an Amazon Web Services KMS key for a specified stream.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
Starting encryption is an asynchronous operation. Upon receiving the request, Kinesis Data Streams returns immediately and sets the status of the stream to UPDATING. After the update is complete, Kinesis Data Streams sets the status of the stream back to ACTIVE. Updating or applying encryption normally takes a few seconds to complete, but it can take minutes. You can continue to read and write data to your stream while its status is UPDATING. Once the status of the stream is ACTIVE, encryption begins for records written to the stream.
API Limits: You can successfully apply a new Amazon Web Services KMS key for server-side encryption 25 times in a rolling 24-hour period.
Note: It can take up to 5 seconds after the stream is in an ACTIVE status before all records written to the stream are encrypted. After you enable encryption, you can verify that encryption is applied by inspecting the API response from PutRecord or PutRecords.
Disables server-side encryption for a specified stream.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
Stopping encryption is an asynchronous operation. Upon receiving the request, Kinesis Data Streams returns immediately and sets the status of the stream to UPDATING. After the update is complete, Kinesis Data Streams sets the status of the stream back to ACTIVE. Stopping encryption normally takes a few seconds to complete, but it can take minutes. You can continue to read and write data to your stream while its status is UPDATING. Once the status of the stream is ACTIVE, records written to the stream are no longer encrypted by Kinesis Data Streams.
API Limits: You can successfully disable server-side encryption 25 times in a rolling 24-hour period.
Note: It can take up to 5 seconds after the stream is in an ACTIVE status before all records written to the stream are no longer subject to encryption. After you disabled encryption, you can verify that encryption is not applied by inspecting the API response from PutRecord or PutRecords.
This operation establishes an HTTP/2 connection between the consumer you specify in the ConsumerARN parameter and the shard you specify in the ShardId parameter. After the connection is successfully established, Kinesis Data Streams pushes records from the shard to the consumer over this connection. Before you call this operation, call RegisterStreamConsumer to register the consumer with Kinesis Data Streams.
When the SubscribeToShard call succeeds, your consumer starts receiving events of type SubscribeToShardEvent over the HTTP/2 connection for up to 5 minutes, after which time you need to call SubscribeToShard again to renew the subscription if you want to continue to receive records.
You can make one call to SubscribeToShard per second per registered consumer per shard. For example, if you have a 4000 shard stream and two registered stream consumers, you can make one SubscribeToShard request per second for each combination of shard and registered consumer, allowing you to subscribe both consumers to all 4000 shards in one second.
If you call SubscribeToShard again with the same ConsumerARN and ShardId within 5 seconds of a successful call, you'll get a ResourceInUseException. If you call SubscribeToShard 5 seconds or more after a successful call, the second call takes over the subscription and the previous connection expires or fails with a ResourceInUseException.
For an example of how to use this operations, see Enhanced Fan-Out Using the Kinesis Data Streams API.
", - "UpdateShardCount": "Updates the shard count of the specified stream to the specified number of shards. This API is only supported for the data streams with the provisioned capacity mode.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
Updating the shard count is an asynchronous operation. Upon receiving the request, Kinesis Data Streams returns immediately and sets the status of the stream to UPDATING. After the update is complete, Kinesis Data Streams sets the status of the stream back to ACTIVE. Depending on the size of the stream, the scaling action could take a few minutes to complete. You can continue to read and write data to your stream while its status is UPDATING.
To update the shard count, Kinesis Data Streams performs splits or merges on individual shards. This can cause short-lived shards to be created, in addition to the final shards. These short-lived shards count towards your total shard limit for your account in the Region.
When using this operation, we recommend that you specify a target shard count that is a multiple of 25% (25%, 50%, 75%, 100%). You can specify any target value within your shard limit. However, if you specify a target that isn't a multiple of 25%, the scaling action might take longer to complete.
This operation has the following default limits. By default, you cannot do the following:
Scale more than ten times per rolling 24-hour period per stream
Scale up to more than double your current shard count for a stream
Scale down below half your current shard count for a stream
Scale up to more than 10000 shards in a stream
Scale a stream with more than 10000 shards down unless the result is less than 10000 shards
Scale up to more than the shard limit for your account
For the default limits for an Amazon Web Services account, see Streams Limits in the Amazon Kinesis Data Streams Developer Guide. To request an increase in the call rate limit, the shard limit for this API, or your overall shard limit, use the limits form.
", + "UpdateShardCount": "Updates the shard count of the specified stream to the specified number of shards. This API is only supported for the data streams with the provisioned capacity mode.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
Updating the shard count is an asynchronous operation. Upon receiving the request, Kinesis Data Streams returns immediately and sets the status of the stream to UPDATING. After the update is complete, Kinesis Data Streams sets the status of the stream back to ACTIVE. Depending on the size of the stream, the scaling action could take a few minutes to complete. You can continue to read and write data to your stream while its status is UPDATING.
To update the shard count, Kinesis Data Streams performs splits or merges on individual shards. This can cause short-lived shards to be created, in addition to the final shards. These short-lived shards count towards your total shard limit for your account in the Region.
When using this operation, we recommend that you specify a target shard count that is a multiple of 25% (25%, 50%, 75%, 100%). You can specify any target value within your shard limit. However, if you specify a target that isn't a multiple of 25%, the scaling action might take longer to complete.
This operation has the following default limits. By default, you cannot do the following:
Scale more than ten times per rolling 24-hour period per stream
Scale up to more than double your current shard count for a stream
Scale down below half your current shard count for a stream
Scale up to more than 10000 shards in a stream
Scale a stream with more than 10000 shards down unless the result is less than 10000 shards
Scale up to more than the shard limit for your account
Make over 10 TPS. TPS over 10 will trigger the LimitExceededException
For the default limits for an Amazon Web Services account, see Streams Limits in the Amazon Kinesis Data Streams Developer Guide. To request an increase in the call rate limit, the shard limit for this API, or your overall shard limit, use the limits form.
", "UpdateStreamMode": "Updates the capacity mode of the data stream. Currently, in Kinesis Data Streams, you can choose between an on-demand capacity mode and a provisioned capacity mode for your data stream.
" }, "shapes": { @@ -135,6 +138,11 @@ "refs": { } }, + "DeleteResourcePolicyInput": { + "base": null, + "refs": { + } + }, "DeleteStreamInput": { "base": "Represents the input for DeleteStream.
", "refs": { @@ -285,6 +293,16 @@ "refs": { } }, + "GetResourcePolicyInput": { + "base": null, + "refs": { + } + }, + "GetResourcePolicyOutput": { + "base": null, + "refs": { + } + }, "GetShardIteratorInput": { "base": "Represents the input for GetShardIterator.
Identifies which shard in the stream the data record is assigned to.
" } }, + "Policy": { + "base": null, + "refs": { + "GetResourcePolicyOutput$Policy": "Details of the resource policy. This is formatted as a JSON string.
", + "PutResourcePolicyInput$Policy": "Details of the resource policy. It must include the identity of the principal and the actions allowed on this resource. This is formatted as a JSON string.
" + } + }, "PositiveIntegerObject": { "base": null, "refs": { @@ -560,6 +585,11 @@ "PutRecordsOutput$Records": "An array of successfully and unsuccessfully processed record results. A record that is successfully added to a stream includes SequenceNumber and ShardId in the result. A record that fails to be added to a stream includes ErrorCode and ErrorMessage in the result.
The unit of data of the Kinesis data stream, which is composed of a sequence number, a partition key, and a data blob.
", "refs": { @@ -588,6 +618,14 @@ "refs": { } }, + "ResourceARN": { + "base": null, + "refs": { + "DeleteResourcePolicyInput$ResourceARN": "The Amazon Resource Name (ARN) of the data stream or consumer.
", + "GetResourcePolicyInput$ResourceARN": "The Amazon Resource Name (ARN) of the data stream or consumer.
", + "PutResourcePolicyInput$ResourceARN": "The Amazon Resource Name (ARN) of the data stream or consumer.
" + } + }, "ResourceInUseException": { "base": "The resource is not available for this operation. For successful operation, the resource must be in the ACTIVE state.
Amazon Kinesis Data Streams is a managed service that scales elastically for real-time processing of streaming big data.
', 'operations' => [ 'AddTagsToStream' => 'Adds or updates tags for the specified Kinesis data stream. You can assign up to 50 tags to a data stream.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
If tags have already been assigned to the stream, AddTagsToStream overwrites any existing tags that correspond to the specified tag keys.
AddTagsToStream has a limit of five transactions per second per account.
', 'CreateStream' => 'Creates a Kinesis data stream. A stream captures and transports data records that are continuously emitted from different data sources or producers. Scale-out within a stream is explicitly supported by means of shards, which are uniquely identified groups of data records in a stream.
You can create your data stream using either on-demand or provisioned capacity mode. Data streams with an on-demand mode require no capacity planning and automatically scale to handle gigabytes of write and read throughput per minute. With the on-demand mode, Kinesis Data Streams automatically manages the shards in order to provide the necessary throughput. For the data streams with a provisioned mode, you must specify the number of shards for the data stream. Each shard can support reads up to five transactions per second, up to a maximum data read total of 2 MiB per second. Each shard can support writes up to 1,000 records per second, up to a maximum data write total of 1 MiB per second. If the amount of data input increases or decreases, you can add or remove shards.
The stream name identifies the stream. The name is scoped to the Amazon Web Services account used by the application. It is also scoped by Amazon Web Services Region. That is, two streams in two different accounts can have the same name, and two streams in the same account, but in two different Regions, can have the same name.
CreateStream is an asynchronous operation. Upon receiving a CreateStream request, Kinesis Data Streams immediately returns and sets the stream status to CREATING. After the stream is created, Kinesis Data Streams sets the stream status to ACTIVE. You should perform read and write operations only on an ACTIVE stream.
You receive a LimitExceededException when making a CreateStream request when you try to do one of the following:
Have more than five streams in the CREATING state at any point in time.
Create more shards than are authorized for your account.
For the default shard limit for an Amazon Web Services account, see Amazon Kinesis Data Streams Limits in the Amazon Kinesis Data Streams Developer Guide. To increase this limit, contact Amazon Web Services Support.
You can use DescribeStreamSummary to check the stream status, which is returned in StreamStatus.
CreateStream has a limit of five transactions per second per account.
', 'DecreaseStreamRetentionPeriod' => 'Decreases the Kinesis data stream\'s retention period, which is the length of time data records are accessible after they are added to the stream. The minimum value of a stream\'s retention period is 24 hours.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
This operation may result in lost data. For example, if the stream\'s retention period is 48 hours and is decreased to 24 hours, any data already in the stream that is older than 24 hours is inaccessible.
', 'DeleteStream' => 'Deletes a Kinesis data stream and all its shards and data. You must shut down any applications that are operating on the stream before you delete the stream. If an application attempts to operate on a deleted stream, it receives the exception ResourceNotFoundException.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
If the stream is in the ACTIVE state, you can delete it. After a DeleteStream request, the specified stream is in the DELETING state until Kinesis Data Streams completes the deletion.
Note: Kinesis Data Streams might continue to accept data read and write operations, such as PutRecord, PutRecords, and GetRecords, on a stream in the DELETING state until the stream deletion is complete.
When you delete a stream, any shards in that stream are also deleted, and any tags are dissociated from the stream.
You can use the DescribeStreamSummary operation to check the state of the stream, which is returned in StreamStatus.
DeleteStream has a limit of five transactions per second per account.
', 'DeregisterStreamConsumer' => 'To deregister a consumer, provide its ARN. Alternatively, you can provide the ARN of the data stream and the name you gave the consumer when you registered it. You may also provide all three parameters, as long as they don\'t conflict with each other. If you don\'t know the name or ARN of the consumer that you want to deregister, you can use the ListStreamConsumers operation to get a list of the descriptions of all the consumers that are currently registered with a given data stream. The description of a consumer contains its name and ARN.
This operation has a limit of five transactions per second per stream.
', 'DescribeLimits' => 'Describes the shard limits and usage for the account.
If you update your account limits, the old limits might be returned for a few minutes.
This operation has a limit of one transaction per second per account.
', 'DescribeStream' => 'Describes the specified Kinesis data stream.
This API has been revised. It\'s highly recommended that you use the DescribeStreamSummary API to get a summarized description of the specified Kinesis data stream and the ListShards API to list the shards in a specified data stream and obtain information about each shard.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
The information returned includes the stream name, Amazon Resource Name (ARN), creation time, enhanced metric configuration, and shard map. The shard map is an array of shard objects. For each shard object, there is the hash key and sequence number ranges that the shard spans, and the IDs of any earlier shards that played in a role in creating the shard. Every record ingested in the stream is identified by a sequence number, which is assigned when the record is put into the stream.
You can limit the number of shards returned by each call. For more information, see Retrieving Shards from a Stream in the Amazon Kinesis Data Streams Developer Guide.
There are no guarantees about the chronological order shards returned. To process shards in chronological order, use the ID of the parent shard to track the lineage to the oldest shard.
This operation has a limit of 10 transactions per second per account.
', 'DescribeStreamConsumer' => 'To get the description of a registered consumer, provide the ARN of the consumer. Alternatively, you can provide the ARN of the data stream and the name you gave the consumer when you registered it. You may also provide all three parameters, as long as they don\'t conflict with each other. If you don\'t know the name or ARN of the consumer that you want to describe, you can use the ListStreamConsumers operation to get a list of the descriptions of all the consumers that are currently registered with a given data stream.
This operation has a limit of 20 transactions per second per stream.
', 'DescribeStreamSummary' => 'Provides a summarized description of the specified Kinesis data stream without the shard list.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
The information returned includes the stream name, Amazon Resource Name (ARN), status, record retention period, approximate creation time, monitoring, encryption details, and open shard count.
DescribeStreamSummary has a limit of 20 transactions per second per account.
', 'DisableEnhancedMonitoring' => 'Disables enhanced monitoring.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
Enables enhanced Kinesis data stream monitoring for shard-level metrics.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
Gets data records from a Kinesis data stream\'s shard.
When invoking this API, it is recommended you use the StreamARN input parameter in addition to the ShardIterator parameter.
Specify a shard iterator using the ShardIterator parameter. The shard iterator specifies the position in the shard from which you want to start reading data records sequentially. If there are no records available in the portion of the shard that the iterator points to, GetRecords returns an empty list. It might take multiple calls to get to a portion of the shard that contains records.
You can scale by provisioning multiple shards per stream while considering service limits (for more information, see Amazon Kinesis Data Streams Limits in the Amazon Kinesis Data Streams Developer Guide). Your application should have one thread per shard, each reading continuously from its stream. To read from a stream continually, call GetRecords in a loop. Use GetShardIterator to get the shard iterator to specify in the first GetRecords call. GetRecords returns a new shard iterator in NextShardIterator. Specify the shard iterator returned in NextShardIterator in subsequent calls to GetRecords. If the shard has been closed, the shard iterator can\'t return more data and GetRecords returns null in NextShardIterator. You can terminate the loop when the shard is closed, or when the shard iterator reaches the record with the sequence number or other attribute that marks it as the last record to process.
Each data record can be up to 1 MiB in size, and each shard can read up to 2 MiB per second. You can ensure that your calls don\'t exceed the maximum supported size or throughput by using the Limit parameter to specify the maximum number of records that GetRecords can return. Consider your average record size when determining this limit. The maximum number of records that can be returned per call is 10,000.
The size of the data returned by GetRecords varies depending on the utilization of the shard. It is recommended that consumer applications retrieve records via the GetRecords command using the 5 TPS limit to remain caught up. Retrieving records less frequently can lead to consumer applications falling behind. The maximum size of data that GetRecords can return is 10 MiB. If a call returns this amount of data, subsequent calls made within the next 5 seconds throw ProvisionedThroughputExceededException. If there is insufficient provisioned throughput on the stream, subsequent calls made within the next 1 second throw ProvisionedThroughputExceededException. GetRecords doesn\'t return any data when it throws an exception. For this reason, we recommend that you wait 1 second between calls to GetRecords. However, it\'s possible that the application will get exceptions for longer than 1 second.
To detect whether the application is falling behind in processing, you can use the MillisBehindLatest response attribute. You can also monitor the stream using CloudWatch metrics and other mechanisms (see Monitoring in the Amazon Kinesis Data Streams Developer Guide).
Each Amazon Kinesis record includes a value, ApproximateArrivalTimestamp, that is set when a stream successfully receives and stores a record. This is commonly referred to as a server-side time stamp, whereas a client-side time stamp is set when a data producer creates or sends the record to a stream (a data producer is any data source putting data records into a stream, for example with PutRecords). The time stamp has millisecond precision. There are no guarantees about the time stamp accuracy, or that the time stamp is always increasing. For example, records in a shard or across a stream might have time stamps that are out of order.
This operation has a limit of five transactions per second per shard.
', 'GetShardIterator' => 'Gets an Amazon Kinesis shard iterator. A shard iterator expires 5 minutes after it is returned to the requester.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
A shard iterator specifies the shard position from which to start reading data records sequentially. The position is specified using the sequence number of a data record in a shard. A sequence number is the identifier associated with every record ingested in the stream, and is assigned when a record is put into the stream. Each stream has one or more shards.
You must specify the shard iterator type. For example, you can set the ShardIteratorType parameter to read exactly from the position denoted by a specific sequence number by using the AT_SEQUENCE_NUMBER shard iterator type. Alternatively, the parameter can read right after the sequence number by using the AFTER_SEQUENCE_NUMBER shard iterator type, using sequence numbers returned by earlier calls to PutRecord, PutRecords, GetRecords, or DescribeStream. In the request, you can specify the shard iterator type AT_TIMESTAMP to read records from an arbitrary point in time, TRIM_HORIZON to cause ShardIterator to point to the last untrimmed record in the shard in the system (the oldest data record in the shard), or LATEST so that you always read the most recent data in the shard.
When you read repeatedly from a stream, use a GetShardIterator request to get the first shard iterator for use in your first GetRecords request and for subsequent reads use the shard iterator returned by the GetRecords request in NextShardIterator. A new shard iterator is returned by every GetRecords request in NextShardIterator, which you use in the ShardIterator parameter of the next GetRecords request.
If a GetShardIterator request is made too often, you receive a ProvisionedThroughputExceededException. For more information about throughput limits, see GetRecords, and Streams Limits in the Amazon Kinesis Data Streams Developer Guide.
If the shard is closed, GetShardIterator returns a valid iterator for the last sequence number of the shard. A shard can be closed as a result of using SplitShard or MergeShards.
GetShardIterator has a limit of five transactions per second per account per open shard.
', 'IncreaseStreamRetentionPeriod' => 'Increases the Kinesis data stream\'s retention period, which is the length of time data records are accessible after they are added to the stream. The maximum value of a stream\'s retention period is 8760 hours (365 days).
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
If you choose a longer stream retention period, this operation increases the time period during which records that have not yet expired are accessible. However, it does not make previous, expired data (older than the stream\'s previous retention period) accessible after the operation has been called. For example, if a stream\'s retention period is set to 24 hours and is increased to 168 hours, any data that is older than 24 hours remains inaccessible to consumer applications.
', 'ListShards' => 'Lists the shards in a stream and provides information about each shard. This operation has a limit of 1000 transactions per second per data stream.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
This action does not list expired shards. For information about expired shards, see Data Routing, Data Persistence, and Shard State after a Reshard.
This API is a new operation that is used by the Amazon Kinesis Client Library (KCL). If you have a fine-grained IAM policy that only allows specific operations, you must update your policy to allow calls to this API. For more information, see Controlling Access to Amazon Kinesis Data Streams Resources Using IAM.
Lists the consumers registered to receive data from a stream using enhanced fan-out, and provides information about each consumer.
This operation has a limit of 5 transactions per second per stream.
', 'ListStreams' => 'Lists your Kinesis data streams.
The number of streams may be too large to return from a single call to ListStreams. You can limit the number of returned streams using the Limit parameter. If you do not specify a value for the Limit parameter, Kinesis Data Streams uses the default limit, which is currently 100.
You can detect if there are more streams available to list by using the HasMoreStreams flag from the returned output. If there are more streams available, you can request more streams by using the name of the last stream returned by the ListStreams request in the ExclusiveStartStreamName parameter in a subsequent request to ListStreams. The group of stream names returned by the subsequent request is then added to the list. You can continue this process until all the stream names have been collected in the list.
ListStreams has a limit of five transactions per second per account.
', 'ListTagsForStream' => 'Lists the tags for the specified Kinesis data stream. This operation has a limit of five transactions per second per account.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
Merges two adjacent shards in a Kinesis data stream and combines them into a single shard to reduce the stream\'s capacity to ingest and transport data. This API is only supported for the data streams with the provisioned capacity mode. Two shards are considered adjacent if the union of the hash key ranges for the two shards form a contiguous set with no gaps. For example, if you have two shards, one with a hash key range of 276...381 and the other with a hash key range of 382...454, then you could merge these two shards into a single shard that would have a hash key range of 276...454. After the merge, the single child shard receives data for all hash key values covered by the two parent shards.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
MergeShards is called when there is a need to reduce the overall capacity of a stream because of excess capacity that is not being used. You must specify the shard to be merged and the adjacent shard for a stream. For more information about merging shards, see Merge Two Shards in the Amazon Kinesis Data Streams Developer Guide.
If the stream is in the ACTIVE state, you can call MergeShards. If a stream is in the CREATING, UPDATING, or DELETING state, MergeShards returns a ResourceInUseException. If the specified stream does not exist, MergeShards returns a ResourceNotFoundException.
You can use DescribeStreamSummary to check the state of the stream, which is returned in StreamStatus.
MergeShards is an asynchronous operation. Upon receiving a MergeShards request, Amazon Kinesis Data Streams immediately returns a response and sets the StreamStatus to UPDATING. After the operation is completed, Kinesis Data Streams sets the StreamStatus to ACTIVE. Read and write operations continue to work while the stream is in the UPDATING state.
You use DescribeStreamSummary and the ListShards APIs to determine the shard IDs that are specified in the MergeShards request.
If you try to operate on too many streams in parallel using CreateStream, DeleteStream, MergeShards, or SplitShard, you receive a LimitExceededException.
MergeShards has a limit of five transactions per second per account.
Writes a single data record into an Amazon Kinesis data stream. Call PutRecord to send data into the stream for real-time ingestion and subsequent processing, one record at a time. Each shard can support writes up to 1,000 records per second, up to a maximum data write total of 1 MiB per second.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
You must specify the name of the stream that captures, stores, and transports the data; a partition key; and the data blob itself.
The data blob can be any type of data; for example, a segment from a log file, geographic/location data, website clickstream data, and so on.
The partition key is used by Kinesis Data Streams to distribute data across shards. Kinesis Data Streams segregates the data records that belong to a stream into multiple shards, using the partition key associated with each data record to determine the shard to which a given data record belongs.
Partition keys are Unicode strings, with a maximum length limit of 256 characters for each key. An MD5 hash function is used to map partition keys to 128-bit integer values and to map associated data records to shards using the hash key ranges of the shards. You can override hashing the partition key to determine the shard by explicitly specifying a hash value using the ExplicitHashKey parameter. For more information, see Adding Data to a Stream in the Amazon Kinesis Data Streams Developer Guide.
PutRecord returns the shard ID of where the data record was placed and the sequence number that was assigned to the data record.
Sequence numbers increase over time and are specific to a shard within a stream, not across all shards within a stream. To guarantee strictly increasing ordering, write serially to a shard and use the SequenceNumberForOrdering parameter. For more information, see Adding Data to a Stream in the Amazon Kinesis Data Streams Developer Guide.
After you write a record to a stream, you cannot modify that record or its order within the stream.
If a PutRecord request cannot be processed because of insufficient provisioned throughput on the shard involved in the request, PutRecord throws ProvisionedThroughputExceededException.
By default, data records are accessible for 24 hours from the time that they are added to a stream. You can use IncreaseStreamRetentionPeriod or DecreaseStreamRetentionPeriod to modify this retention period.
', 'PutRecords' => 'Writes multiple data records into a Kinesis data stream in a single call (also referred to as a PutRecords request). Use this operation to send data into the stream for data ingestion and processing.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
Each PutRecords request can support up to 500 records. Each record in the request can be as large as 1 MiB, up to a limit of 5 MiB for the entire request, including partition keys. Each shard can support writes up to 1,000 records per second, up to a maximum data write total of 1 MiB per second.
You must specify the name of the stream that captures, stores, and transports the data; and an array of request Records, with each record in the array requiring a partition key and data blob. The record size limit applies to the total size of the partition key and data blob.
The data blob can be any type of data; for example, a segment from a log file, geographic/location data, website clickstream data, and so on.
The partition key is used by Kinesis Data Streams as input to a hash function that maps the partition key and associated data to a specific shard. An MD5 hash function is used to map partition keys to 128-bit integer values and to map associated data records to shards. As a result of this hashing mechanism, all data records with the same partition key map to the same shard within the stream. For more information, see Adding Data to a Stream in the Amazon Kinesis Data Streams Developer Guide.
Each record in the Records array may include an optional parameter, ExplicitHashKey, which overrides the partition key to shard mapping. This parameter allows a data producer to determine explicitly the shard where the record is stored. For more information, see Adding Multiple Records with PutRecords in the Amazon Kinesis Data Streams Developer Guide.
The PutRecords response includes an array of response Records. Each record in the response array directly correlates with a record in the request array using natural ordering, from the top to the bottom of the request and response. The response Records array always includes the same number of records as the request array.
The response Records array includes both successfully and unsuccessfully processed records. Kinesis Data Streams attempts to process all records in each PutRecords request. A single record failure does not stop the processing of subsequent records. As a result, PutRecords doesn\'t guarantee the ordering of records. If you need to read records in the same order they are written to the stream, use PutRecord instead of PutRecords, and write to the same shard.
A successfully processed record includes ShardId and SequenceNumber values. The ShardId parameter identifies the shard in the stream where the record is stored. The SequenceNumber parameter is an identifier assigned to the put record, unique to all records in the stream.
An unsuccessfully processed record includes ErrorCode and ErrorMessage values. ErrorCode reflects the type of error and can be one of the following values: ProvisionedThroughputExceededException or InternalFailure. ErrorMessage provides more detailed information about the ProvisionedThroughputExceededException exception including the account ID, stream name, and shard ID of the record that was throttled. For more information about partially successful responses, see Adding Multiple Records with PutRecords in the Amazon Kinesis Data Streams Developer Guide.
After you write a record to a stream, you cannot modify that record or its order within the stream.
By default, data records are accessible for 24 hours from the time that they are added to a stream. You can use IncreaseStreamRetentionPeriod or DecreaseStreamRetentionPeriod to modify this retention period.
', 'RegisterStreamConsumer' => 'Registers a consumer with a Kinesis data stream. When you use this operation, the consumer you register can then call SubscribeToShard to receive data from the stream using enhanced fan-out, at a rate of up to 2 MiB per second for every shard you subscribe to. This rate is unaffected by the total number of consumers that read from the same stream.
You can register up to 20 consumers per stream. A given consumer can only be registered with one stream at a time.
For an example of how to use this operations, see Enhanced Fan-Out Using the Kinesis Data Streams API.
The use of this operation has a limit of five transactions per second per account. Also, only 5 consumers can be created simultaneously. In other words, you cannot have more than 5 consumers in a CREATING status at the same time. Registering a 6th consumer while there are 5 in a CREATING status results in a LimitExceededException.
Removes tags from the specified Kinesis data stream. Removed tags are deleted and cannot be recovered after this operation successfully completes.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
If you specify a tag that does not exist, it is ignored.
RemoveTagsFromStream has a limit of five transactions per second per account.
', 'SplitShard' => 'Splits a shard into two new shards in the Kinesis data stream, to increase the stream\'s capacity to ingest and transport data. SplitShard is called when there is a need to increase the overall capacity of a stream because of an expected increase in the volume of data records being ingested. This API is only supported for the data streams with the provisioned capacity mode.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
You can also use SplitShard when a shard appears to be approaching its maximum utilization; for example, the producers sending data into the specific shard are suddenly sending more than previously anticipated. You can also call SplitShard to increase stream capacity, so that more Kinesis Data Streams applications can simultaneously read data from the stream for real-time processing.
You must specify the shard to be split and the new hash key, which is the position in the shard where the shard gets split in two. In many cases, the new hash key might be the average of the beginning and ending hash key, but it can be any hash key value in the range being mapped into the shard. For more information, see Split a Shard in the Amazon Kinesis Data Streams Developer Guide.
You can use DescribeStreamSummary and the ListShards APIs to determine the shard ID and hash key values for the ShardToSplit and NewStartingHashKey parameters that are specified in the SplitShard request.
SplitShard is an asynchronous operation. Upon receiving a SplitShard request, Kinesis Data Streams immediately returns a response and sets the stream status to UPDATING. After the operation is completed, Kinesis Data Streams sets the stream status to ACTIVE. Read and write operations continue to work while the stream is in the UPDATING state.
You can use DescribeStreamSummary to check the status of the stream, which is returned in StreamStatus. If the stream is in the ACTIVE state, you can call SplitShard.
If the specified stream does not exist, DescribeStreamSummary returns a ResourceNotFoundException. If you try to create more shards than are authorized for your account, you receive a LimitExceededException.
For the default shard limit for an Amazon Web Services account, see Kinesis Data Streams Limits in the Amazon Kinesis Data Streams Developer Guide. To increase this limit, contact Amazon Web Services Support.
If you try to operate on too many streams simultaneously using CreateStream, DeleteStream, MergeShards, and/or SplitShard, you receive a LimitExceededException.
SplitShard has a limit of five transactions per second per account.
Enables or updates server-side encryption using an Amazon Web Services KMS key for a specified stream.
Starting encryption is an asynchronous operation. Upon receiving the request, Kinesis Data Streams returns immediately and sets the status of the stream to UPDATING. After the update is complete, Kinesis Data Streams sets the status of the stream back to ACTIVE. Updating or applying encryption normally takes a few seconds to complete, but it can take minutes. You can continue to read and write data to your stream while its status is UPDATING. Once the status of the stream is ACTIVE, encryption begins for records written to the stream.
API Limits: You can successfully apply a new Amazon Web Services KMS key for server-side encryption 25 times in a rolling 24-hour period.
Note: It can take up to 5 seconds after the stream is in an ACTIVE status before all records written to the stream are encrypted. After you enable encryption, you can verify that encryption is applied by inspecting the API response from PutRecord or PutRecords.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
Disables server-side encryption for a specified stream.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
Stopping encryption is an asynchronous operation. Upon receiving the request, Kinesis Data Streams returns immediately and sets the status of the stream to UPDATING. After the update is complete, Kinesis Data Streams sets the status of the stream back to ACTIVE. Stopping encryption normally takes a few seconds to complete, but it can take minutes. You can continue to read and write data to your stream while its status is UPDATING. Once the status of the stream is ACTIVE, records written to the stream are no longer encrypted by Kinesis Data Streams.
API Limits: You can successfully disable server-side encryption 25 times in a rolling 24-hour period.
Note: It can take up to 5 seconds after the stream is in an ACTIVE status before all records written to the stream are no longer subject to encryption. After you disabled encryption, you can verify that encryption is not applied by inspecting the API response from PutRecord or PutRecords.
This operation establishes an HTTP/2 connection between the consumer you specify in the ConsumerARN parameter and the shard you specify in the ShardId parameter. After the connection is successfully established, Kinesis Data Streams pushes records from the shard to the consumer over this connection. Before you call this operation, call RegisterStreamConsumer to register the consumer with Kinesis Data Streams.
When the SubscribeToShard call succeeds, your consumer starts receiving events of type SubscribeToShardEvent over the HTTP/2 connection for up to 5 minutes, after which time you need to call SubscribeToShard again to renew the subscription if you want to continue to receive records.
You can make one call to SubscribeToShard per second per registered consumer per shard. For example, if you have a 4000 shard stream and two registered stream consumers, you can make one SubscribeToShard request per second for each combination of shard and registered consumer, allowing you to subscribe both consumers to all 4000 shards in one second.
If you call SubscribeToShard again with the same ConsumerARN and ShardId within 5 seconds of a successful call, you\'ll get a ResourceInUseException. If you call SubscribeToShard 5 seconds or more after a successful call, the second call takes over the subscription and the previous connection expires or fails with a ResourceInUseException.
For an example of how to use this operations, see Enhanced Fan-Out Using the Kinesis Data Streams API.
', 'UpdateShardCount' => 'Updates the shard count of the specified stream to the specified number of shards. This API is only supported for the data streams with the provisioned capacity mode.
When invoking this API, it is recommended you use the StreamARN input parameter rather than the StreamName input parameter.
Updating the shard count is an asynchronous operation. Upon receiving the request, Kinesis Data Streams returns immediately and sets the status of the stream to UPDATING. After the update is complete, Kinesis Data Streams sets the status of the stream back to ACTIVE. Depending on the size of the stream, the scaling action could take a few minutes to complete. You can continue to read and write data to your stream while its status is UPDATING.
To update the shard count, Kinesis Data Streams performs splits or merges on individual shards. This can cause short-lived shards to be created, in addition to the final shards. These short-lived shards count towards your total shard limit for your account in the Region.
When using this operation, we recommend that you specify a target shard count that is a multiple of 25% (25%, 50%, 75%, 100%). You can specify any target value within your shard limit. However, if you specify a target that isn\'t a multiple of 25%, the scaling action might take longer to complete.
This operation has the following default limits. By default, you cannot do the following:
Scale more than ten times per rolling 24-hour period per stream
Scale up to more than double your current shard count for a stream
Scale down below half your current shard count for a stream
Scale up to more than 10000 shards in a stream
Scale a stream with more than 10000 shards down unless the result is less than 10000 shards
Scale up to more than the shard limit for your account
For the default limits for an Amazon Web Services account, see Streams Limits in the Amazon Kinesis Data Streams Developer Guide. To request an increase in the call rate limit, the shard limit for this API, or your overall shard limit, use the limits form.
', 'UpdateStreamMode' => 'Updates the capacity mode of the data stream. Currently, in Kinesis Data Streams, you can choose between an on-demand capacity mode and a provisioned capacity mode for your data stream.
', ], 'shapes' => [ 'AccessDeniedException' => [ 'base' => 'Specifies that you do not have the permissions required to perform this operation.
', 'refs' => [], ], 'AddTagsToStreamInput' => [ 'base' => 'Represents the input for AddTagsToStream.
If this parameter is unset (null) or if you set it to false, and the stream has registered consumers, the call to DeleteStream fails with a ResourceInUseException.
If set to true, there are more streams available to list.
If set to true, more tags are available. To request additional tags, set ExclusiveStartTagKey to the key of the last tag returned.
If set to true, more shards in the stream are available to describe.
Output parameter of the GetRecords API. The existing child shard of the current shard.
', 'refs' => [ 'ChildShardList$member' => NULL, ], ], 'ChildShardList' => [ 'base' => NULL, 'refs' => [ 'GetRecordsOutput$ChildShards' => 'The list of the current shard\'s child shards, returned in the GetRecords API\'s response only when the end of the current shard is reached.
The list of the child shards of the current shard, returned only at the end of the current shard.
', ], ], 'Consumer' => [ 'base' => 'An object that represents the details of the consumer you registered. This type of object is returned by RegisterStreamConsumer.
', 'refs' => [ 'ConsumerList$member' => NULL, 'RegisterStreamConsumerOutput$Consumer' => 'An object that represents the details of the consumer you registered. When you register a consumer, it gets an ARN that is generated by Kinesis Data Streams.
', ], ], 'ConsumerARN' => [ 'base' => NULL, 'refs' => [ 'Consumer$ConsumerARN' => 'When you register a consumer, Kinesis Data Streams generates an ARN for it. You need this ARN to be able to call SubscribeToShard.
If you delete a consumer and then create a new one with the same name, it won\'t have the same ARN. That\'s because consumer ARNs contain the creation timestamp. This is important to keep in mind if you have IAM policies that reference consumer ARNs.
', 'ConsumerDescription$ConsumerARN' => 'When you register a consumer, Kinesis Data Streams generates an ARN for it. You need this ARN to be able to call SubscribeToShard.
If you delete a consumer and then create a new one with the same name, it won\'t have the same ARN. That\'s because consumer ARNs contain the creation timestamp. This is important to keep in mind if you have IAM policies that reference consumer ARNs.
', 'DeregisterStreamConsumerInput$ConsumerARN' => 'The ARN returned by Kinesis Data Streams when you registered the consumer. If you don\'t know the ARN of the consumer that you want to deregister, you can use the ListStreamConsumers operation to get a list of the descriptions of all the consumers that are currently registered with a given data stream. The description of a consumer contains its ARN.
', 'DescribeStreamConsumerInput$ConsumerARN' => 'The ARN returned by Kinesis Data Streams when you registered the consumer.
', 'SubscribeToShardInput$ConsumerARN' => 'For this parameter, use the value you obtained when you called RegisterStreamConsumer.
', ], ], 'ConsumerCountObject' => [ 'base' => NULL, 'refs' => [ 'StreamDescriptionSummary$ConsumerCount' => 'The number of enhanced fan-out consumers registered with the stream.
', ], ], 'ConsumerDescription' => [ 'base' => 'An object that represents the details of a registered consumer. This type of object is returned by DescribeStreamConsumer.
', 'refs' => [ 'DescribeStreamConsumerOutput$ConsumerDescription' => 'An object that represents the details of the consumer.
', ], ], 'ConsumerList' => [ 'base' => NULL, 'refs' => [ 'ListStreamConsumersOutput$Consumers' => 'An array of JSON objects. Each object represents one registered consumer.
', ], ], 'ConsumerName' => [ 'base' => NULL, 'refs' => [ 'Consumer$ConsumerName' => 'The name of the consumer is something you choose when you register the consumer.
', 'ConsumerDescription$ConsumerName' => 'The name of the consumer is something you choose when you register the consumer.
', 'DeregisterStreamConsumerInput$ConsumerName' => 'The name that you gave to the consumer.
', 'DescribeStreamConsumerInput$ConsumerName' => 'The name that you gave to the consumer.
', 'RegisterStreamConsumerInput$ConsumerName' => 'For a given Kinesis data stream, each consumer must have a unique name. However, consumer names don\'t have to be unique across data streams.
', ], ], 'ConsumerStatus' => [ 'base' => NULL, 'refs' => [ 'Consumer$ConsumerStatus' => 'A consumer can\'t read data while in the CREATING or DELETING states.
A consumer can\'t read data while in the CREATING or DELETING states.
Represents the input for CreateStream.
The data blob to put into the record, which is base64-encoded when the blob is serialized. When the data blob (the payload before base64-encoding) is added to the partition key size, the total size must not exceed the maximum record size (1 MiB).
', 'PutRecordsRequestEntry$Data' => 'The data blob to put into the record, which is base64-encoded when the blob is serialized. When the data blob (the payload before base64-encoding) is added to the partition key size, the total size must not exceed the maximum record size (1 MiB).
', 'Record$Data' => 'The data blob. The data in the blob is both opaque and immutable to Kinesis Data Streams, which does not inspect, interpret, or change the data in the blob in any way. When the data blob (the payload before base64-encoding) is added to the partition key size, the total size must not exceed the maximum record size (1 MiB).
', ], ], 'DecreaseStreamRetentionPeriodInput' => [ 'base' => 'Represents the input for DecreaseStreamRetentionPeriod.
', 'refs' => [], ], 'DeleteStreamInput' => [ 'base' => 'Represents the input for DeleteStream.
', 'refs' => [], ], 'DeregisterStreamConsumerInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeLimitsInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeLimitsOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeStreamConsumerInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeStreamConsumerOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeStreamInput' => [ 'base' => 'Represents the input for DescribeStream.
The maximum number of shards to return in a single call. The default value is 100. If you specify a value greater than 100, at most 100 results are returned.
', ], ], 'DescribeStreamOutput' => [ 'base' => 'Represents the output for DescribeStream.
Represents the input for DisableEnhancedMonitoring.
', 'refs' => [], ], 'EnableEnhancedMonitoringInput' => [ 'base' => 'Represents the input for EnableEnhancedMonitoring.
', 'refs' => [], ], 'EncryptionType' => [ 'base' => NULL, 'refs' => [ 'PutRecordOutput$EncryptionType' => 'The encryption type to use on the record. This parameter can be one of the following values:
NONE: Do not encrypt the records in the stream.
KMS: Use server-side encryption on the records in the stream using a customer-managed Amazon Web Services KMS key.
The encryption type used on the records. This parameter can be one of the following values:
NONE: Do not encrypt the records.
KMS: Use server-side encryption on the records using a customer-managed Amazon Web Services KMS key.
The encryption type used on the record. This parameter can be one of the following values:
NONE: Do not encrypt the records in the stream.
KMS: Use server-side encryption on the records in the stream using a customer-managed Amazon Web Services KMS key.
The encryption type to use. The only valid value is KMS.
The encryption type. The only valid value is KMS.
The server-side encryption type used on the stream. This parameter can be one of the following values:
NONE: Do not encrypt the records in the stream.
KMS: Use server-side encryption on the records in the stream using a customer-managed Amazon Web Services KMS key.
The encryption type used. This value is one of the following:
KMS
NONE
Represents enhanced metrics types.
', 'refs' => [ 'EnhancedMonitoringList$member' => NULL, ], ], 'EnhancedMonitoringList' => [ 'base' => NULL, 'refs' => [ 'StreamDescription$EnhancedMonitoring' => 'Represents the current enhanced monitoring settings of the stream.
', 'StreamDescriptionSummary$EnhancedMonitoring' => 'Represents the current enhanced monitoring settings of the stream.
', ], ], 'EnhancedMonitoringOutput' => [ 'base' => 'Represents the output for EnableEnhancedMonitoring and DisableEnhancedMonitoring.
', 'refs' => [], ], 'ErrorCode' => [ 'base' => NULL, 'refs' => [ 'PutRecordsResultEntry$ErrorCode' => 'The error code for an individual record result. ErrorCodes can be either ProvisionedThroughputExceededException or InternalFailure.
A message that provides information about the error.
', 'ExpiredNextTokenException$message' => NULL, 'InternalFailureException$message' => NULL, 'InvalidArgumentException$message' => 'A message that provides information about the error.
', 'KMSAccessDeniedException$message' => 'A message that provides information about the error.
', 'KMSDisabledException$message' => 'A message that provides information about the error.
', 'KMSInvalidStateException$message' => 'A message that provides information about the error.
', 'KMSNotFoundException$message' => 'A message that provides information about the error.
', 'KMSOptInRequired$message' => 'A message that provides information about the error.
', 'KMSThrottlingException$message' => 'A message that provides information about the error.
', 'LimitExceededException$message' => 'A message that provides information about the error.
', 'ProvisionedThroughputExceededException$message' => 'A message that provides information about the error.
', 'PutRecordsResultEntry$ErrorMessage' => 'The error message for an individual record result. An ErrorCode value of ProvisionedThroughputExceededException has an error message that includes the account ID, stream name, and shard ID. An ErrorCode value of InternalFailure has the error message "Internal Service Failure".
A message that provides information about the error.
', 'ResourceNotFoundException$message' => 'A message that provides information about the error.
', 'ValidationException$message' => NULL, ], ], 'ExpiredIteratorException' => [ 'base' => 'The provided iterator exceeds the maximum age allowed.
', 'refs' => [], ], 'ExpiredNextTokenException' => [ 'base' => 'The pagination token passed to the operation is expired.
', 'refs' => [], ], 'GetRecordsInput' => [ 'base' => 'Represents the input for GetRecords.
', 'refs' => [], ], 'GetRecordsInputLimit' => [ 'base' => NULL, 'refs' => [ 'GetRecordsInput$Limit' => 'The maximum number of records to return. Specify a value of up to 10,000. If you specify a value that is greater than 10,000, GetRecords throws InvalidArgumentException. The default value is 10,000.
Represents the output for GetRecords.
', 'refs' => [], ], 'GetShardIteratorInput' => [ 'base' => 'Represents the input for GetShardIterator.
Represents the output for GetShardIterator.
The starting hash key of the hash key range.
', 'HashKeyRange$EndingHashKey' => 'The ending hash key of the hash key range.
', 'PutRecordInput$ExplicitHashKey' => 'The hash value used to explicitly determine the shard the data record is assigned to by overriding the partition key hash.
', 'PutRecordsRequestEntry$ExplicitHashKey' => 'The hash value used to determine explicitly the shard that the data record is assigned to by overriding the partition key hash.
', 'SplitShardInput$NewStartingHashKey' => 'A hash key value for the starting hash key of one of the child shards created by the split. The hash key range for a given shard constitutes a set of ordered contiguous positive integers. The value for NewStartingHashKey must be in the range of hash keys being mapped into the shard. The NewStartingHashKey hash key value and all higher hash key values in hash key range are distributed to one of the child shards. All the lower hash key values in the range are distributed to the other child shard.
The range of possible hash key values for the shard, which is a set of ordered contiguous positive integers.
', 'refs' => [ 'ChildShard$HashKeyRange' => NULL, 'Shard$HashKeyRange' => 'The range of possible hash key values for the shard, which is a set of ordered contiguous positive integers.
', ], ], 'IncreaseStreamRetentionPeriodInput' => [ 'base' => 'Represents the input for IncreaseStreamRetentionPeriod.
', 'refs' => [], ], 'InternalFailureException' => [ 'base' => 'The processing of the request failed because of an unknown error, exception, or failure.
', 'refs' => [ 'SubscribeToShardEventStream$InternalFailureException' => 'The processing of the request failed because of an unknown error, exception, or failure.
', ], ], 'InvalidArgumentException' => [ 'base' => 'A specified parameter exceeds its restrictions, is not supported, or can\'t be used. For more information, see the returned message.
', 'refs' => [], ], 'KMSAccessDeniedException' => [ 'base' => 'The ciphertext references a key that doesn\'t exist or that you don\'t have access to.
', 'refs' => [ 'SubscribeToShardEventStream$KMSAccessDeniedException' => NULL, ], ], 'KMSDisabledException' => [ 'base' => 'The request was rejected because the specified customer master key (CMK) isn\'t enabled.
', 'refs' => [ 'SubscribeToShardEventStream$KMSDisabledException' => NULL, ], ], 'KMSInvalidStateException' => [ 'base' => 'The request was rejected because the state of the specified resource isn\'t valid for this request. For more information, see How Key State Affects Use of a Customer Master Key in the Amazon Web Services Key Management Service Developer Guide.
', 'refs' => [ 'SubscribeToShardEventStream$KMSInvalidStateException' => NULL, ], ], 'KMSNotFoundException' => [ 'base' => 'The request was rejected because the specified entity or resource can\'t be found.
', 'refs' => [ 'SubscribeToShardEventStream$KMSNotFoundException' => NULL, ], ], 'KMSOptInRequired' => [ 'base' => 'The Amazon Web Services access key ID needs a subscription for the service.
', 'refs' => [ 'SubscribeToShardEventStream$KMSOptInRequired' => NULL, ], ], 'KMSThrottlingException' => [ 'base' => 'The request was denied due to request throttling. For more information about throttling, see Limits in the Amazon Web Services Key Management Service Developer Guide.
', 'refs' => [ 'SubscribeToShardEventStream$KMSThrottlingException' => NULL, ], ], 'KeyId' => [ 'base' => NULL, 'refs' => [ 'StartStreamEncryptionInput$KeyId' => 'The GUID for the customer-managed Amazon Web Services KMS key to use for encryption. This value can be a globally unique identifier, a fully specified Amazon Resource Name (ARN) to either an alias or a key, or an alias name prefixed by "alias/".You can also use a master key owned by Kinesis Data Streams by specifying the alias aws/kinesis.
Key ARN example: arn:aws:kms:us-east-1:123456789012:key/12345678-1234-1234-1234-123456789012
Alias ARN example: arn:aws:kms:us-east-1:123456789012:alias/MyAliasName
Globally unique key ID example: 12345678-1234-1234-1234-123456789012
Alias name example: alias/MyAliasName
Master key owned by Kinesis Data Streams: alias/aws/kinesis
The GUID for the customer-managed Amazon Web Services KMS key to use for encryption. This value can be a globally unique identifier, a fully specified Amazon Resource Name (ARN) to either an alias or a key, or an alias name prefixed by "alias/".You can also use a master key owned by Kinesis Data Streams by specifying the alias aws/kinesis.
Key ARN example: arn:aws:kms:us-east-1:123456789012:key/12345678-1234-1234-1234-123456789012
Alias ARN example: arn:aws:kms:us-east-1:123456789012:alias/MyAliasName
Globally unique key ID example: 12345678-1234-1234-1234-123456789012
Alias name example: alias/MyAliasName
Master key owned by Kinesis Data Streams: alias/aws/kinesis
The GUID for the customer-managed Amazon Web Services KMS key to use for encryption. This value can be a globally unique identifier, a fully specified ARN to either an alias or a key, or an alias name prefixed by "alias/".You can also use a master key owned by Kinesis Data Streams by specifying the alias aws/kinesis.
Key ARN example: arn:aws:kms:us-east-1:123456789012:key/12345678-1234-1234-1234-123456789012
Alias ARN example: arn:aws:kms:us-east-1:123456789012:alias/MyAliasName
Globally unique key ID example: 12345678-1234-1234-1234-123456789012
Alias name example: alias/MyAliasName
Master key owned by Kinesis Data Streams: alias/aws/kinesis
The GUID for the customer-managed Amazon Web Services KMS key to use for encryption. This value can be a globally unique identifier, a fully specified ARN to either an alias or a key, or an alias name prefixed by "alias/".You can also use a master key owned by Kinesis Data Streams by specifying the alias aws/kinesis.
Key ARN example: arn:aws:kms:us-east-1:123456789012:key/12345678-1234-1234-1234-123456789012
Alias ARN example: arn:aws:kms:us-east-1:123456789012:alias/MyAliasName
Globally unique key ID example: 12345678-1234-1234-1234-123456789012
Alias name example: alias/MyAliasName
Master key owned by Kinesis Data Streams: alias/aws/kinesis
The requested resource exceeds the maximum number allowed, or the number of concurrent stream requests exceeds the maximum number allowed.
', 'refs' => [], ], 'ListShardsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListShardsInputLimit' => [ 'base' => NULL, 'refs' => [ 'ListShardsInput$MaxResults' => 'The maximum number of shards to return in a single call to ListShards. The maximum number of shards to return in a single call. The default value is 1000. If you specify a value greater than 1000, at most 1000 results are returned.
When the number of shards to be listed is greater than the value of MaxResults, the response contains a NextToken value that you can use in a subsequent call to ListShards to list the next set of shards.
The maximum number of consumers that you want a single call of ListStreamConsumers to return. The default value is 100. If you specify a value greater than 100, at most 100 results are returned.
Represents the input for ListStreams.
The maximum number of streams to list. The default value is 100. If you specify a value greater than 100, at most 100 results are returned.
', ], ], 'ListStreamsOutput' => [ 'base' => 'Represents the output for ListStreams.
Represents the input for ListTagsForStream.
The number of tags to return. If this number is less than the total number of tags associated with the stream, HasMoreTags is set to true. To list additional tags, set ExclusiveStartTagKey to the last key in the response.
Represents the output for ListTagsForStream.
Represents the input for MergeShards.
List of shard-level metrics to disable.
The following are the valid shard-level metrics. The value "ALL" disables every metric.
IncomingBytes
IncomingRecords
OutgoingBytes
OutgoingRecords
WriteProvisionedThroughputExceeded
ReadProvisionedThroughputExceeded
IteratorAgeMilliseconds
ALL
For more information, see Monitoring the Amazon Kinesis Data Streams Service with Amazon CloudWatch in the Amazon Kinesis Data Streams Developer Guide.
', 'EnableEnhancedMonitoringInput$ShardLevelMetrics' => 'List of shard-level metrics to enable.
The following are the valid shard-level metrics. The value "ALL" enables every metric.
IncomingBytes
IncomingRecords
OutgoingBytes
OutgoingRecords
WriteProvisionedThroughputExceeded
ReadProvisionedThroughputExceeded
IteratorAgeMilliseconds
ALL
For more information, see Monitoring the Amazon Kinesis Data Streams Service with Amazon CloudWatch in the Amazon Kinesis Data Streams Developer Guide.
', 'EnhancedMetrics$ShardLevelMetrics' => 'List of shard-level metrics.
The following are the valid shard-level metrics. The value "ALL" enhances every metric.
IncomingBytes
IncomingRecords
OutgoingBytes
OutgoingRecords
WriteProvisionedThroughputExceeded
ReadProvisionedThroughputExceeded
IteratorAgeMilliseconds
ALL
For more information, see Monitoring the Amazon Kinesis Data Streams Service with Amazon CloudWatch in the Amazon Kinesis Data Streams Developer Guide.
', 'EnhancedMonitoringOutput$CurrentShardLevelMetrics' => 'Represents the current state of the metrics that are in the enhanced state before the operation.
', 'EnhancedMonitoringOutput$DesiredShardLevelMetrics' => 'Represents the list of all the metrics that would be in the enhanced state after the operation.
', ], ], 'MillisBehindLatest' => [ 'base' => NULL, 'refs' => [ 'GetRecordsOutput$MillisBehindLatest' => 'The number of milliseconds the GetRecords response is from the tip of the stream, indicating how far behind current time the consumer is. A value of zero indicates that record processing is caught up, and there are no new records to process at this moment.
', 'SubscribeToShardEvent$MillisBehindLatest' => 'The number of milliseconds the read records are from the tip of the stream, indicating how far behind current time the consumer is. A value of zero indicates that record processing is caught up, and there are no new records to process at this moment.
', ], ], 'NextToken' => [ 'base' => NULL, 'refs' => [ 'ListShardsInput$NextToken' => 'When the number of shards in the data stream is greater than the default value for the MaxResults parameter, or if you explicitly specify a value for MaxResults that is less than the number of shards in the data stream, the response includes a pagination token named NextToken. You can specify this NextToken value in a subsequent call to ListShards to list the next set of shards.
Don\'t specify StreamName or StreamCreationTimestamp if you specify NextToken because the latter unambiguously identifies the stream.
You can optionally specify a value for the MaxResults parameter when you specify NextToken. If you specify a MaxResults value that is less than the number of shards that the operation returns if you don\'t specify MaxResults, the response will contain a new NextToken value. You can use the new NextToken value in a subsequent call to the ListShards operation.
Tokens expire after 300 seconds. When you obtain a value for NextToken in the response to a call to ListShards, you have 300 seconds to use that value. If you specify an expired token in a call to ListShards, you get ExpiredNextTokenException.
When the number of shards in the data stream is greater than the default value for the MaxResults parameter, or if you explicitly specify a value for MaxResults that is less than the number of shards in the data stream, the response includes a pagination token named NextToken. You can specify this NextToken value in a subsequent call to ListShards to list the next set of shards. For more information about the use of this pagination token when calling the ListShards operation, see ListShardsInput$NextToken.
Tokens expire after 300 seconds. When you obtain a value for NextToken in the response to a call to ListShards, you have 300 seconds to use that value. If you specify an expired token in a call to ListShards, you get ExpiredNextTokenException.
When the number of consumers that are registered with the data stream is greater than the default value for the MaxResults parameter, or if you explicitly specify a value for MaxResults that is less than the number of consumers that are registered with the data stream, the response includes a pagination token named NextToken. You can specify this NextToken value in a subsequent call to ListStreamConsumers to list the next set of registered consumers.
Don\'t specify StreamName or StreamCreationTimestamp if you specify NextToken because the latter unambiguously identifies the stream.
You can optionally specify a value for the MaxResults parameter when you specify NextToken. If you specify a MaxResults value that is less than the number of consumers that the operation returns if you don\'t specify MaxResults, the response will contain a new NextToken value. You can use the new NextToken value in a subsequent call to the ListStreamConsumers operation to list the next set of consumers.
Tokens expire after 300 seconds. When you obtain a value for NextToken in the response to a call to ListStreamConsumers, you have 300 seconds to use that value. If you specify an expired token in a call to ListStreamConsumers, you get ExpiredNextTokenException.
When the number of consumers that are registered with the data stream is greater than the default value for the MaxResults parameter, or if you explicitly specify a value for MaxResults that is less than the number of registered consumers, the response includes a pagination token named NextToken. You can specify this NextToken value in a subsequent call to ListStreamConsumers to list the next set of registered consumers. For more information about the use of this pagination token when calling the ListStreamConsumers operation, see ListStreamConsumersInput$NextToken.
Tokens expire after 300 seconds. When you obtain a value for NextToken in the response to a call to ListStreamConsumers, you have 300 seconds to use that value. If you specify an expired token in a call to ListStreamConsumers, you get ExpiredNextTokenException.
The maximum number of data streams with the on-demand capacity mode.
', ], ], 'OnDemandStreamCountObject' => [ 'base' => NULL, 'refs' => [ 'DescribeLimitsOutput$OnDemandStreamCount' => 'Indicates the number of data streams with the on-demand capacity mode.
', ], ], 'PartitionKey' => [ 'base' => NULL, 'refs' => [ 'PutRecordInput$PartitionKey' => 'Determines which shard in the stream the data record is assigned to. Partition keys are Unicode strings with a maximum length limit of 256 characters for each key. Amazon Kinesis Data Streams uses the partition key as input to a hash function that maps the partition key and associated data to a specific shard. Specifically, an MD5 hash function is used to map partition keys to 128-bit integer values and to map associated data records to shards. As a result of this hashing mechanism, all data records with the same partition key map to the same shard within the stream.
', 'PutRecordsRequestEntry$PartitionKey' => 'Determines which shard in the stream the data record is assigned to. Partition keys are Unicode strings with a maximum length limit of 256 characters for each key. Amazon Kinesis Data Streams uses the partition key as input to a hash function that maps the partition key and associated data to a specific shard. Specifically, an MD5 hash function is used to map partition keys to 128-bit integer values and to map associated data records to shards. As a result of this hashing mechanism, all data records with the same partition key map to the same shard within the stream.
', 'Record$PartitionKey' => 'Identifies which shard in the stream the data record is assigned to.
', ], ], 'PositiveIntegerObject' => [ 'base' => NULL, 'refs' => [ 'CreateStreamInput$ShardCount' => 'The number of shards that the stream will use. The throughput of the stream is a function of the number of shards; more shards are required for greater provisioned throughput.
', 'PutRecordsOutput$FailedRecordCount' => 'The number of unsuccessfully processed records in a PutRecords request.
The new number of shards. This value has the following default limits. By default, you cannot do the following:
Set this value to more than double your current shard count for a stream.
Set this value below half your current shard count for a stream.
Set this value to more than 10000 shards in a stream (the default limit for shard count per stream is 10000 per account per region), unless you request a limit increase.
Scale a stream with more than 10000 shards down unless you set this value to less than 10000 shards.
The current number of shards.
', 'UpdateShardCountOutput$TargetShardCount' => 'The updated number of shards.
', ], ], 'ProvisionedThroughputExceededException' => [ 'base' => 'The request rate for the stream is too high, or the requested data is too large for the available throughput. Reduce the frequency or size of your requests. For more information, see Streams Limits in the Amazon Kinesis Data Streams Developer Guide, and Error Retries and Exponential Backoff in Amazon Web Services in the Amazon Web Services General Reference.
', 'refs' => [], ], 'PutRecordInput' => [ 'base' => 'Represents the input for PutRecord.
Represents the output for PutRecord.
A PutRecords request.
PutRecords results.
Represents the output for PutRecords.
The records associated with the request.
', ], ], 'PutRecordsResultEntry' => [ 'base' => 'Represents the result of an individual record from a PutRecords request. A record that is successfully added to a stream includes SequenceNumber and ShardId in the result. A record that fails to be added to the stream includes ErrorCode and ErrorMessage in the result.
An array of successfully and unsuccessfully processed record results. A record that is successfully added to a stream includes SequenceNumber and ShardId in the result. A record that fails to be added to a stream includes ErrorCode and ErrorMessage in the result.
The unit of data of the Kinesis data stream, which is composed of a sequence number, a partition key, and a data blob.
', 'refs' => [ 'RecordList$member' => NULL, ], ], 'RecordList' => [ 'base' => NULL, 'refs' => [ 'GetRecordsOutput$Records' => 'The data records retrieved from the shard.
', 'SubscribeToShardEvent$Records' => '', ], ], 'RegisterStreamConsumerInput' => [ 'base' => NULL, 'refs' => [], ], 'RegisterStreamConsumerOutput' => [ 'base' => NULL, 'refs' => [], ], 'RemoveTagsFromStreamInput' => [ 'base' => 'Represents the input for RemoveTagsFromStream.
The resource is not available for this operation. For successful operation, the resource must be in the ACTIVE state.
The requested resource could not be found. The stream might not be specified correctly.
', 'refs' => [ 'SubscribeToShardEventStream$ResourceNotFoundException' => NULL, ], ], 'RetentionPeriodHours' => [ 'base' => NULL, 'refs' => [ 'DecreaseStreamRetentionPeriodInput$RetentionPeriodHours' => 'The new retention period of the stream, in hours. Must be less than the current retention period.
', 'IncreaseStreamRetentionPeriodInput$RetentionPeriodHours' => 'The new retention period of the stream, in hours. Must be more than the current retention period.
', 'StreamDescription$RetentionPeriodHours' => 'The current retention period, in hours. Minimum value of 24. Maximum value of 168.
', 'StreamDescriptionSummary$RetentionPeriodHours' => 'The current retention period, in hours.
', ], ], 'ScalingType' => [ 'base' => NULL, 'refs' => [ 'UpdateShardCountInput$ScalingType' => 'The scaling type. Uniform scaling creates shards of equal size.
', ], ], 'SequenceNumber' => [ 'base' => NULL, 'refs' => [ 'GetShardIteratorInput$StartingSequenceNumber' => 'The sequence number of the data record in the shard from which to start reading. Used with shard iterator type AT_SEQUENCE_NUMBER and AFTER_SEQUENCE_NUMBER.
', 'PutRecordInput$SequenceNumberForOrdering' => 'Guarantees strictly increasing sequence numbers, for puts from the same client and to the same partition key. Usage: set the SequenceNumberForOrdering of record n to the sequence number of record n-1 (as returned in the result when putting record n-1). If this parameter is not set, records are coarsely ordered based on arrival time.
The sequence number identifier that was assigned to the put data record. The sequence number for the record is unique across all records in the stream. A sequence number is the identifier associated with every record put into the stream.
', 'PutRecordsResultEntry$SequenceNumber' => 'The sequence number for an individual record result.
', 'Record$SequenceNumber' => 'The unique identifier of the record within its shard.
', 'SequenceNumberRange$StartingSequenceNumber' => 'The starting sequence number for the range.
', 'SequenceNumberRange$EndingSequenceNumber' => 'The ending sequence number for the range. Shards that are in the OPEN state have an ending sequence number of null.
The sequence number of the data record in the shard from which to start streaming. To specify a sequence number, set StartingPosition to AT_SEQUENCE_NUMBER or AFTER_SEQUENCE_NUMBER.
Use this as SequenceNumber in the next call to SubscribeToShard, with StartingPosition set to AT_SEQUENCE_NUMBER or AFTER_SEQUENCE_NUMBER. Use ContinuationSequenceNumber for checkpointing because it captures your shard progress even when no data is written to the shard.
The range of possible sequence numbers for the shard.
', 'refs' => [ 'Shard$SequenceNumberRange' => 'The range of possible sequence numbers for the shard.
', ], ], 'Shard' => [ 'base' => 'A uniquely identified group of data records in a Kinesis data stream.
', 'refs' => [ 'ShardList$member' => NULL, ], ], 'ShardCountObject' => [ 'base' => NULL, 'refs' => [ 'DescribeLimitsOutput$ShardLimit' => 'The maximum number of shards.
', 'DescribeLimitsOutput$OpenShardCount' => 'The number of open shards.
', 'StreamDescriptionSummary$OpenShardCount' => 'The number of open shards in the stream.
', ], ], 'ShardFilter' => [ 'base' => 'The request parameter used to filter out the response of the ListShards API.
Enables you to filter out the response of the ListShards API. You can only specify one filter at a time.
If you use the ShardFilter parameter when invoking the ListShards API, the Type is the required property and must be specified. If you specify the AT_TRIM_HORIZON, FROM_TRIM_HORIZON, or AT_LATEST types, you do not need to specify either the ShardId or the Timestamp optional properties.
If you specify the AFTER_SHARD_ID type, you must also provide the value for the optional ShardId property. The ShardId property is identical in fuctionality to the ExclusiveStartShardId parameter of the ListShards API. When ShardId property is specified, the response includes the shards starting with the shard whose ID immediately follows the ShardId that you provided.
If you specify the AT_TIMESTAMP or FROM_TIMESTAMP_ID type, you must also provide the value for the optional Timestamp property. If you specify the AT_TIMESTAMP type, then all shards that were open at the provided timestamp are returned. If you specify the FROM_TIMESTAMP type, then all shards starting from the provided timestamp to TIP are returned.
The shard type specified in the ShardFilter parameter. This is a required property of the ShardFilter parameter.
You can specify the following valid values:
AFTER_SHARD_ID - the response includes all the shards, starting with the shard whose ID immediately follows the ShardId that you provided.
AT_TRIM_HORIZON - the response includes all the shards that were open at TRIM_HORIZON.
FROM_TRIM_HORIZON - (default), the response includes all the shards within the retention period of the data stream (trim to tip).
AT_LATEST - the response includes only the currently open shards of the data stream.
AT_TIMESTAMP - the response includes all shards whose start timestamp is less than or equal to the given timestamp and end timestamp is greater than or equal to the given timestamp or still open.
FROM_TIMESTAMP - the response incldues all closed shards whose end timestamp is greater than or equal to the given timestamp and also all open shards. Corrected to TRIM_HORIZON of the data stream if FROM_TIMESTAMP is less than the TRIM_HORIZON value.
The shard ID of the existing child shard of the current shard.
', 'DescribeStreamInput$ExclusiveStartShardId' => 'The shard ID of the shard to start with.
Specify this parameter to indicate that you want to describe the stream starting with the shard whose ID immediately follows ExclusiveStartShardId.
If you don\'t specify this parameter, the default behavior for DescribeStream is to describe the stream starting with the first shard in the stream.
The shard ID of the Kinesis Data Streams shard to get the iterator for.
', 'ListShardsInput$ExclusiveStartShardId' => 'Specify this parameter to indicate that you want to list the shards starting with the shard whose ID immediately follows ExclusiveStartShardId.
If you don\'t specify this parameter, the default behavior is for ListShards to list the shards starting with the first one in the stream.
You cannot specify this parameter if you specify NextToken.
The shard ID of the shard to combine with the adjacent shard for the merge.
', 'MergeShardsInput$AdjacentShardToMerge' => 'The shard ID of the adjacent shard for the merge.
', 'PutRecordOutput$ShardId' => 'The shard ID of the shard where the data record was placed.
', 'PutRecordsResultEntry$ShardId' => 'The shard ID for an individual record result.
', 'Shard$ShardId' => 'The unique identifier of the shard within the stream.
', 'Shard$ParentShardId' => 'The shard ID of the shard\'s parent.
', 'Shard$AdjacentParentShardId' => 'The shard ID of the shard adjacent to the shard\'s parent.
', 'ShardFilter$ShardId' => 'The exclusive start shardID speified in the ShardFilter parameter. This property can only be used if the AFTER_SHARD_ID shard type is specified.
The shard ID of the shard to split.
', 'SubscribeToShardInput$ShardId' => 'The ID of the shard you want to subscribe to. To see a list of all the shards for a given stream, use ListShards.
', ], ], 'ShardIdList' => [ 'base' => NULL, 'refs' => [ 'ChildShard$ParentShards' => 'The current shard that is the parent of the existing child shard.
', ], ], 'ShardIterator' => [ 'base' => NULL, 'refs' => [ 'GetRecordsInput$ShardIterator' => 'The position in the shard from which you want to start sequentially reading data records. A shard iterator specifies this position using the sequence number of a data record in the shard.
', 'GetRecordsOutput$NextShardIterator' => 'The next position in the shard from which to start sequentially reading data records. If set to null, the shard has been closed and the requested iterator does not return any more data.
The position in the shard from which to start reading data records sequentially. A shard iterator specifies this position using the sequence number of a data record in a shard.
', ], ], 'ShardIteratorType' => [ 'base' => NULL, 'refs' => [ 'GetShardIteratorInput$ShardIteratorType' => 'Determines how the shard iterator is used to start reading data records from the shard.
The following are the valid Amazon Kinesis shard iterator types:
AT_SEQUENCE_NUMBER - Start reading from the position denoted by a specific sequence number, provided in the value StartingSequenceNumber.
AFTER_SEQUENCE_NUMBER - Start reading right after the position denoted by a specific sequence number, provided in the value StartingSequenceNumber.
AT_TIMESTAMP - Start reading from the position denoted by a specific time stamp, provided in the value Timestamp.
TRIM_HORIZON - Start reading at the last untrimmed record in the shard in the system, which is the oldest data record in the shard.
LATEST - Start reading just after the most recent record in the shard, so that you always read the most recent data in the shard.
You can set the starting position to one of the following values:
AT_SEQUENCE_NUMBER: Start streaming from the position denoted by the sequence number specified in the SequenceNumber field.
AFTER_SEQUENCE_NUMBER: Start streaming right after the position denoted by the sequence number specified in the SequenceNumber field.
AT_TIMESTAMP: Start streaming from the position denoted by the time stamp specified in the Timestamp field.
TRIM_HORIZON: Start streaming at the last untrimmed record in the shard, which is the oldest data record in the shard.
LATEST: Start streaming just after the most recent record in the shard, so that you always read the most recent data in the shard.
An array of JSON objects. Each object represents one shard and specifies the IDs of the shard, the shard\'s parent, and the shard that\'s adjacent to the shard\'s parent. Each object also contains the starting and ending hash keys and the starting and ending sequence numbers for the shard.
', 'StreamDescription$Shards' => 'The shards that comprise the stream.
', ], ], 'SplitShardInput' => [ 'base' => 'Represents the input for SplitShard.
The starting position in the data stream from which to start streaming.
', 'refs' => [ 'SubscribeToShardInput$StartingPosition' => 'The starting position in the data stream from which to start streaming.
', ], ], 'StopStreamEncryptionInput' => [ 'base' => NULL, 'refs' => [], ], 'StreamARN' => [ 'base' => NULL, 'refs' => [ 'AddTagsToStreamInput$StreamARN' => 'The ARN of the stream.
', 'ConsumerDescription$StreamARN' => 'The ARN of the stream with which you registered the consumer.
', 'DecreaseStreamRetentionPeriodInput$StreamARN' => 'The ARN of the stream.
', 'DeleteStreamInput$StreamARN' => 'The ARN of the stream.
', 'DeregisterStreamConsumerInput$StreamARN' => 'The ARN of the Kinesis data stream that the consumer is registered with. For more information, see Amazon Resource Names (ARNs) and Amazon Web Services Service Namespaces.
', 'DescribeStreamConsumerInput$StreamARN' => 'The ARN of the Kinesis data stream that the consumer is registered with. For more information, see Amazon Resource Names (ARNs) and Amazon Web Services Service Namespaces.
', 'DescribeStreamInput$StreamARN' => 'The ARN of the stream.
', 'DescribeStreamSummaryInput$StreamARN' => 'The ARN of the stream.
', 'DisableEnhancedMonitoringInput$StreamARN' => 'The ARN of the stream.
', 'EnableEnhancedMonitoringInput$StreamARN' => 'The ARN of the stream.
', 'EnhancedMonitoringOutput$StreamARN' => 'The ARN of the stream.
', 'GetRecordsInput$StreamARN' => 'The ARN of the stream.
', 'GetShardIteratorInput$StreamARN' => 'The ARN of the stream.
', 'IncreaseStreamRetentionPeriodInput$StreamARN' => 'The ARN of the stream.
', 'ListShardsInput$StreamARN' => 'The ARN of the stream.
', 'ListStreamConsumersInput$StreamARN' => 'The ARN of the Kinesis data stream for which you want to list the registered consumers. For more information, see Amazon Resource Names (ARNs) and Amazon Web Services Service Namespaces.
', 'ListTagsForStreamInput$StreamARN' => 'The ARN of the stream.
', 'MergeShardsInput$StreamARN' => 'The ARN of the stream.
', 'PutRecordInput$StreamARN' => 'The ARN of the stream.
', 'PutRecordsInput$StreamARN' => 'The ARN of the stream.
', 'RegisterStreamConsumerInput$StreamARN' => 'The ARN of the Kinesis data stream that you want to register the consumer with. For more info, see Amazon Resource Names (ARNs) and Amazon Web Services Service Namespaces.
', 'RemoveTagsFromStreamInput$StreamARN' => 'The ARN of the stream.
', 'SplitShardInput$StreamARN' => 'The ARN of the stream.
', 'StartStreamEncryptionInput$StreamARN' => 'The ARN of the stream.
', 'StopStreamEncryptionInput$StreamARN' => 'The ARN of the stream.
', 'StreamDescription$StreamARN' => 'The Amazon Resource Name (ARN) for the stream being described.
', 'StreamDescriptionSummary$StreamARN' => 'The Amazon Resource Name (ARN) for the stream being described.
', 'StreamSummary$StreamARN' => 'The ARN of the stream.
', 'UpdateShardCountInput$StreamARN' => 'The ARN of the stream.
', 'UpdateShardCountOutput$StreamARN' => 'The ARN of the stream.
', 'UpdateStreamModeInput$StreamARN' => 'Specifies the ARN of the data stream whose capacity mode you want to update.
', ], ], 'StreamDescription' => [ 'base' => 'Represents the output for DescribeStream.
', 'refs' => [ 'DescribeStreamOutput$StreamDescription' => 'The current status of the stream, the stream Amazon Resource Name (ARN), an array of shard objects that comprise the stream, and whether there are more shards available.
', ], ], 'StreamDescriptionSummary' => [ 'base' => 'Represents the output for DescribeStreamSummary
', 'refs' => [ 'DescribeStreamSummaryOutput$StreamDescriptionSummary' => 'A StreamDescriptionSummary containing information about the stream.
', ], ], 'StreamMode' => [ 'base' => NULL, 'refs' => [ 'StreamModeDetails$StreamMode' => 'Specifies the capacity mode to which you want to set your data stream. Currently, in Kinesis Data Streams, you can choose between an on-demand capacity mode and a provisioned capacity mode for your data streams.
', ], ], 'StreamModeDetails' => [ 'base' => 'Specifies the capacity mode to which you want to set your data stream. Currently, in Kinesis Data Streams, you can choose between an on-demand capacity mode and a provisioned capacity mode for your data streams.
', 'refs' => [ 'CreateStreamInput$StreamModeDetails' => 'Indicates the capacity mode of the data stream. Currently, in Kinesis Data Streams, you can choose between an on-demand capacity mode and a provisioned capacity mode for your data streams.
', 'StreamDescription$StreamModeDetails' => 'Specifies the capacity mode to which you want to set your data stream. Currently, in Kinesis Data Streams, you can choose between an on-demand capacity mode and a provisioned capacity mode for your data streams.
', 'StreamDescriptionSummary$StreamModeDetails' => 'Specifies the capacity mode to which you want to set your data stream. Currently, in Kinesis Data Streams, you can choose between an on-demand ycapacity mode and a provisioned capacity mode for your data streams.
', 'StreamSummary$StreamModeDetails' => NULL, 'UpdateStreamModeInput$StreamModeDetails' => 'Specifies the capacity mode to which you want to set your data stream. Currently, in Kinesis Data Streams, you can choose between an on-demand capacity mode and a provisioned capacity mode for your data streams.
', ], ], 'StreamName' => [ 'base' => NULL, 'refs' => [ 'AddTagsToStreamInput$StreamName' => 'The name of the stream.
', 'CreateStreamInput$StreamName' => 'A name to identify the stream. The stream name is scoped to the Amazon Web Services account used by the application that creates the stream. It is also scoped by Amazon Web Services Region. That is, two streams in two different Amazon Web Services accounts can have the same name. Two streams in the same Amazon Web Services account but in two different Regions can also have the same name.
', 'DecreaseStreamRetentionPeriodInput$StreamName' => 'The name of the stream to modify.
', 'DeleteStreamInput$StreamName' => 'The name of the stream to delete.
', 'DescribeStreamInput$StreamName' => 'The name of the stream to describe.
', 'DescribeStreamSummaryInput$StreamName' => 'The name of the stream to describe.
', 'DisableEnhancedMonitoringInput$StreamName' => 'The name of the Kinesis data stream for which to disable enhanced monitoring.
', 'EnableEnhancedMonitoringInput$StreamName' => 'The name of the stream for which to enable enhanced monitoring.
', 'EnhancedMonitoringOutput$StreamName' => 'The name of the Kinesis data stream.
', 'GetShardIteratorInput$StreamName' => 'The name of the Amazon Kinesis data stream.
', 'IncreaseStreamRetentionPeriodInput$StreamName' => 'The name of the stream to modify.
', 'ListShardsInput$StreamName' => 'The name of the data stream whose shards you want to list.
You cannot specify this parameter if you specify the NextToken parameter.
The name of the stream to start the list with.
', 'ListTagsForStreamInput$StreamName' => 'The name of the stream.
', 'MergeShardsInput$StreamName' => 'The name of the stream for the merge.
', 'PutRecordInput$StreamName' => 'The name of the stream to put the data record into.
', 'PutRecordsInput$StreamName' => 'The stream name associated with the request.
', 'RemoveTagsFromStreamInput$StreamName' => 'The name of the stream.
', 'SplitShardInput$StreamName' => 'The name of the stream for the shard split.
', 'StartStreamEncryptionInput$StreamName' => 'The name of the stream for which to start encrypting records.
', 'StopStreamEncryptionInput$StreamName' => 'The name of the stream on which to stop encrypting records.
', 'StreamDescription$StreamName' => 'The name of the stream being described.
', 'StreamDescriptionSummary$StreamName' => 'The name of the stream being described.
', 'StreamNameList$member' => NULL, 'StreamSummary$StreamName' => 'The name of a stream.
', 'UpdateShardCountInput$StreamName' => 'The name of the stream.
', 'UpdateShardCountOutput$StreamName' => 'The name of the stream.
', ], ], 'StreamNameList' => [ 'base' => NULL, 'refs' => [ 'ListStreamsOutput$StreamNames' => 'The names of the streams that are associated with the Amazon Web Services account making the ListStreams request.
The current status of the stream being described. The stream status is one of the following states:
CREATING - The stream is being created. Kinesis Data Streams immediately returns and sets StreamStatus to CREATING.
DELETING - The stream is being deleted. The specified stream is in the DELETING state until Kinesis Data Streams completes the deletion.
ACTIVE - The stream exists and is ready for read and write operations or deletion. You should perform read and write operations only on an ACTIVE stream.
UPDATING - Shards in the stream are being merged or split. Read and write operations continue to work while the stream is in the UPDATING state.
The current status of the stream being described. The stream status is one of the following states:
CREATING - The stream is being created. Kinesis Data Streams immediately returns and sets StreamStatus to CREATING.
DELETING - The stream is being deleted. The specified stream is in the DELETING state until Kinesis Data Streams completes the deletion.
ACTIVE - The stream exists and is ready for read and write operations or deletion. You should perform read and write operations only on an ACTIVE stream.
UPDATING - Shards in the stream are being merged or split. Read and write operations continue to work while the stream is in the UPDATING state.
The status of the stream.
', ], ], 'StreamSummary' => [ 'base' => 'The summary of a stream.
', 'refs' => [ 'StreamSummaryList$member' => NULL, ], ], 'StreamSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListStreamsOutput$StreamSummaries' => '', ], ], 'SubscribeToShardEvent' => [ 'base' => 'After you call SubscribeToShard, Kinesis Data Streams sends events of this type over an HTTP/2 connection to your consumer.
', 'refs' => [ 'SubscribeToShardEventStream$SubscribeToShardEvent' => 'After you call SubscribeToShard, Kinesis Data Streams sends events of this type to your consumer. For an example of how to handle these events, see Enhanced Fan-Out Using the Kinesis Data Streams API.
', ], ], 'SubscribeToShardEventStream' => [ 'base' => 'This is a tagged union for all of the types of events an enhanced fan-out consumer can receive over HTTP/2 after a call to SubscribeToShard.
', 'refs' => [ 'SubscribeToShardOutput$EventStream' => 'The event stream that your consumer can use to read records from the shard.
', ], ], 'SubscribeToShardInput' => [ 'base' => NULL, 'refs' => [], ], 'SubscribeToShardOutput' => [ 'base' => NULL, 'refs' => [], ], 'Tag' => [ 'base' => 'Metadata assigned to the stream, consisting of a key-value pair.
', 'refs' => [ 'TagList$member' => NULL, ], ], 'TagKey' => [ 'base' => NULL, 'refs' => [ 'ListTagsForStreamInput$ExclusiveStartTagKey' => 'The key to use as the starting point for the list of tags. If this parameter is set, ListTagsForStream gets all tags that occur after ExclusiveStartTagKey.
A unique identifier for the tag. Maximum length: 128 characters. Valid characters: Unicode letters, digits, white space, _ . / = + - % @
', 'TagKeyList$member' => NULL, 'TagMap$key' => NULL, ], ], 'TagKeyList' => [ 'base' => NULL, 'refs' => [ 'RemoveTagsFromStreamInput$TagKeys' => 'A list of tag keys. Each corresponding tag is removed from the stream.
', ], ], 'TagList' => [ 'base' => NULL, 'refs' => [ 'ListTagsForStreamOutput$Tags' => 'A list of tags associated with StreamName, starting with the first tag after ExclusiveStartTagKey and up to the specified Limit.
A set of up to 10 key-value pairs to use to create the tags.
', ], ], 'TagValue' => [ 'base' => NULL, 'refs' => [ 'Tag$Value' => 'An optional string, typically used to describe or define the tag. Maximum length: 256 characters. Valid characters: Unicode letters, digits, white space, _ . / = + - % @
', 'TagMap$value' => NULL, ], ], 'Timestamp' => [ 'base' => NULL, 'refs' => [ 'Consumer$ConsumerCreationTimestamp' => '', 'ConsumerDescription$ConsumerCreationTimestamp' => '', 'GetShardIteratorInput$Timestamp' => 'The time stamp of the data record from which to start reading. Used with shard iterator type AT_TIMESTAMP. A time stamp is the Unix epoch date with precision in milliseconds. For example, 2016-04-04T19:58:46.480-00:00 or 1459799926.480. If a record with this exact time stamp does not exist, the iterator returned is for the next (later) record. If the time stamp is older than the current trim horizon, the iterator returned is for the oldest untrimmed data record (TRIM_HORIZON).
Specify this input parameter to distinguish data streams that have the same name. For example, if you create a data stream and then delete it, and you later create another data stream with the same name, you can use this input parameter to specify which of the two streams you want to list the shards for.
You cannot specify this parameter if you specify the NextToken parameter.
Specify this input parameter to distinguish data streams that have the same name. For example, if you create a data stream and then delete it, and you later create another data stream with the same name, you can use this input parameter to specify which of the two streams you want to list the consumers for.
You can\'t specify this parameter if you specify the NextToken parameter.
', 'Record$ApproximateArrivalTimestamp' => 'The approximate time that the record was inserted into the stream.
', 'ShardFilter$Timestamp' => 'The timestamps specified in the ShardFilter parameter. A timestamp is a Unix epoch date with precision in milliseconds. For example, 2016-04-04T19:58:46.480-00:00 or 1459799926.480. This property can only be used if FROM_TIMESTAMP or AT_TIMESTAMP shard types are specified.
The time stamp of the data record from which to start reading. To specify a time stamp, set StartingPosition to Type AT_TIMESTAMP. A time stamp is the Unix epoch date with precision in milliseconds. For example, 2016-04-04T19:58:46.480-00:00 or 1459799926.480. If a record with this exact time stamp does not exist, records will be streamed from the next (later) record. If the time stamp is older than the current trim horizon, records will be streamed from the oldest untrimmed data record (TRIM_HORIZON).
The approximate time that the stream was created.
', 'StreamDescriptionSummary$StreamCreationTimestamp' => 'The approximate time that the stream was created.
', 'StreamSummary$StreamCreationTimestamp' => 'The timestamp at which the stream was created.
', ], ], 'UpdateShardCountInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateShardCountOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateStreamModeInput' => [ 'base' => NULL, 'refs' => [], ], 'ValidationException' => [ 'base' => 'Specifies that you tried to invoke this API for a data stream with the on-demand capacity mode. This API is only supported for data streams with the provisioned capacity mode.
', 'refs' => [], ], ],]; +return [ 'version' => '2.0', 'service' => 'Amazon Kinesis Data Streams is a managed service that scales elastically for real-time processing of streaming big data.
', 'operations' => [ 'AddTagsToStream' => 'Adds or updates tags for the specified Kinesis data stream. You can assign up to 50 tags to a data stream.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
If tags have already been assigned to the stream, AddTagsToStream overwrites any existing tags that correspond to the specified tag keys.
AddTagsToStream has a limit of five transactions per second per account.
', 'CreateStream' => 'Creates a Kinesis data stream. A stream captures and transports data records that are continuously emitted from different data sources or producers. Scale-out within a stream is explicitly supported by means of shards, which are uniquely identified groups of data records in a stream.
You can create your data stream using either on-demand or provisioned capacity mode. Data streams with an on-demand mode require no capacity planning and automatically scale to handle gigabytes of write and read throughput per minute. With the on-demand mode, Kinesis Data Streams automatically manages the shards in order to provide the necessary throughput. For the data streams with a provisioned mode, you must specify the number of shards for the data stream. Each shard can support reads up to five transactions per second, up to a maximum data read total of 2 MiB per second. Each shard can support writes up to 1,000 records per second, up to a maximum data write total of 1 MiB per second. If the amount of data input increases or decreases, you can add or remove shards.
The stream name identifies the stream. The name is scoped to the Amazon Web Services account used by the application. It is also scoped by Amazon Web Services Region. That is, two streams in two different accounts can have the same name, and two streams in the same account, but in two different Regions, can have the same name.
CreateStream is an asynchronous operation. Upon receiving a CreateStream request, Kinesis Data Streams immediately returns and sets the stream status to CREATING. After the stream is created, Kinesis Data Streams sets the stream status to ACTIVE. You should perform read and write operations only on an ACTIVE stream.
You receive a LimitExceededException when making a CreateStream request when you try to do one of the following:
Have more than five streams in the CREATING state at any point in time.
Create more shards than are authorized for your account.
For the default shard limit for an Amazon Web Services account, see Amazon Kinesis Data Streams Limits in the Amazon Kinesis Data Streams Developer Guide. To increase this limit, contact Amazon Web Services Support.
You can use DescribeStreamSummary to check the stream status, which is returned in StreamStatus.
CreateStream has a limit of five transactions per second per account.
', 'DecreaseStreamRetentionPeriod' => 'Decreases the Kinesis data stream\'s retention period, which is the length of time data records are accessible after they are added to the stream. The minimum value of a stream\'s retention period is 24 hours.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
This operation may result in lost data. For example, if the stream\'s retention period is 48 hours and is decreased to 24 hours, any data already in the stream that is older than 24 hours is inaccessible.
', 'DeleteResourcePolicy' => 'Delete a policy for the specified data stream or consumer. Request patterns can be one of the following:
Data stream pattern: arn:aws.*:kinesis:.*:\\d{12}:.*stream/\\S+
Consumer pattern: ^(arn):aws.*:kinesis:.*:\\d{12}:.*stream\\/[a-zA-Z0-9_.-]+\\/consumer\\/[a-zA-Z0-9_.-]+:[0-9]+
Deletes a Kinesis data stream and all its shards and data. You must shut down any applications that are operating on the stream before you delete the stream. If an application attempts to operate on a deleted stream, it receives the exception ResourceNotFoundException.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
If the stream is in the ACTIVE state, you can delete it. After a DeleteStream request, the specified stream is in the DELETING state until Kinesis Data Streams completes the deletion.
Note: Kinesis Data Streams might continue to accept data read and write operations, such as PutRecord, PutRecords, and GetRecords, on a stream in the DELETING state until the stream deletion is complete.
When you delete a stream, any shards in that stream are also deleted, and any tags are dissociated from the stream.
You can use the DescribeStreamSummary operation to check the state of the stream, which is returned in StreamStatus.
DeleteStream has a limit of five transactions per second per account.
', 'DeregisterStreamConsumer' => 'To deregister a consumer, provide its ARN. Alternatively, you can provide the ARN of the data stream and the name you gave the consumer when you registered it. You may also provide all three parameters, as long as they don\'t conflict with each other. If you don\'t know the name or ARN of the consumer that you want to deregister, you can use the ListStreamConsumers operation to get a list of the descriptions of all the consumers that are currently registered with a given data stream. The description of a consumer contains its name and ARN.
This operation has a limit of five transactions per second per stream.
', 'DescribeLimits' => 'Describes the shard limits and usage for the account.
If you update your account limits, the old limits might be returned for a few minutes.
This operation has a limit of one transaction per second per account.
', 'DescribeStream' => 'Describes the specified Kinesis data stream.
This API has been revised. It\'s highly recommended that you use the DescribeStreamSummary API to get a summarized description of the specified Kinesis data stream and the ListShards API to list the shards in a specified data stream and obtain information about each shard.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
The information returned includes the stream name, Amazon Resource Name (ARN), creation time, enhanced metric configuration, and shard map. The shard map is an array of shard objects. For each shard object, there is the hash key and sequence number ranges that the shard spans, and the IDs of any earlier shards that played in a role in creating the shard. Every record ingested in the stream is identified by a sequence number, which is assigned when the record is put into the stream.
You can limit the number of shards returned by each call. For more information, see Retrieving Shards from a Stream in the Amazon Kinesis Data Streams Developer Guide.
There are no guarantees about the chronological order shards returned. To process shards in chronological order, use the ID of the parent shard to track the lineage to the oldest shard.
This operation has a limit of 10 transactions per second per account.
', 'DescribeStreamConsumer' => 'To get the description of a registered consumer, provide the ARN of the consumer. Alternatively, you can provide the ARN of the data stream and the name you gave the consumer when you registered it. You may also provide all three parameters, as long as they don\'t conflict with each other. If you don\'t know the name or ARN of the consumer that you want to describe, you can use the ListStreamConsumers operation to get a list of the descriptions of all the consumers that are currently registered with a given data stream.
This operation has a limit of 20 transactions per second per stream.
When making a cross-account call with DescribeStreamConsumer, make sure to provide the ARN of the consumer.
Provides a summarized description of the specified Kinesis data stream without the shard list.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
The information returned includes the stream name, Amazon Resource Name (ARN), status, record retention period, approximate creation time, monitoring, encryption details, and open shard count.
DescribeStreamSummary has a limit of 20 transactions per second per account.
', 'DisableEnhancedMonitoring' => 'Disables enhanced monitoring.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
Enables enhanced Kinesis data stream monitoring for shard-level metrics.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
Gets data records from a Kinesis data stream\'s shard.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
Specify a shard iterator using the ShardIterator parameter. The shard iterator specifies the position in the shard from which you want to start reading data records sequentially. If there are no records available in the portion of the shard that the iterator points to, GetRecords returns an empty list. It might take multiple calls to get to a portion of the shard that contains records.
You can scale by provisioning multiple shards per stream while considering service limits (for more information, see Amazon Kinesis Data Streams Limits in the Amazon Kinesis Data Streams Developer Guide). Your application should have one thread per shard, each reading continuously from its stream. To read from a stream continually, call GetRecords in a loop. Use GetShardIterator to get the shard iterator to specify in the first GetRecords call. GetRecords returns a new shard iterator in NextShardIterator. Specify the shard iterator returned in NextShardIterator in subsequent calls to GetRecords. If the shard has been closed, the shard iterator can\'t return more data and GetRecords returns null in NextShardIterator. You can terminate the loop when the shard is closed, or when the shard iterator reaches the record with the sequence number or other attribute that marks it as the last record to process.
Each data record can be up to 1 MiB in size, and each shard can read up to 2 MiB per second. You can ensure that your calls don\'t exceed the maximum supported size or throughput by using the Limit parameter to specify the maximum number of records that GetRecords can return. Consider your average record size when determining this limit. The maximum number of records that can be returned per call is 10,000.
The size of the data returned by GetRecords varies depending on the utilization of the shard. It is recommended that consumer applications retrieve records via the GetRecords command using the 5 TPS limit to remain caught up. Retrieving records less frequently can lead to consumer applications falling behind. The maximum size of data that GetRecords can return is 10 MiB. If a call returns this amount of data, subsequent calls made within the next 5 seconds throw ProvisionedThroughputExceededException. If there is insufficient provisioned throughput on the stream, subsequent calls made within the next 1 second throw ProvisionedThroughputExceededException. GetRecords doesn\'t return any data when it throws an exception. For this reason, we recommend that you wait 1 second between calls to GetRecords. However, it\'s possible that the application will get exceptions for longer than 1 second.
To detect whether the application is falling behind in processing, you can use the MillisBehindLatest response attribute. You can also monitor the stream using CloudWatch metrics and other mechanisms (see Monitoring in the Amazon Kinesis Data Streams Developer Guide).
Each Amazon Kinesis record includes a value, ApproximateArrivalTimestamp, that is set when a stream successfully receives and stores a record. This is commonly referred to as a server-side time stamp, whereas a client-side time stamp is set when a data producer creates or sends the record to a stream (a data producer is any data source putting data records into a stream, for example with PutRecords). The time stamp has millisecond precision. There are no guarantees about the time stamp accuracy, or that the time stamp is always increasing. For example, records in a shard or across a stream might have time stamps that are out of order.
This operation has a limit of five transactions per second per shard.
', 'GetResourcePolicy' => 'Returns a policy attached to the specified data stream or consumer. Request patterns can be one of the following:
Data stream pattern: arn:aws.*:kinesis:.*:\\d{12}:.*stream/\\S+
Consumer pattern: ^(arn):aws.*:kinesis:.*:\\d{12}:.*stream\\/[a-zA-Z0-9_.-]+\\/consumer\\/[a-zA-Z0-9_.-]+:[0-9]+
Gets an Amazon Kinesis shard iterator. A shard iterator expires 5 minutes after it is returned to the requester.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
A shard iterator specifies the shard position from which to start reading data records sequentially. The position is specified using the sequence number of a data record in a shard. A sequence number is the identifier associated with every record ingested in the stream, and is assigned when a record is put into the stream. Each stream has one or more shards.
You must specify the shard iterator type. For example, you can set the ShardIteratorType parameter to read exactly from the position denoted by a specific sequence number by using the AT_SEQUENCE_NUMBER shard iterator type. Alternatively, the parameter can read right after the sequence number by using the AFTER_SEQUENCE_NUMBER shard iterator type, using sequence numbers returned by earlier calls to PutRecord, PutRecords, GetRecords, or DescribeStream. In the request, you can specify the shard iterator type AT_TIMESTAMP to read records from an arbitrary point in time, TRIM_HORIZON to cause ShardIterator to point to the last untrimmed record in the shard in the system (the oldest data record in the shard), or LATEST so that you always read the most recent data in the shard.
When you read repeatedly from a stream, use a GetShardIterator request to get the first shard iterator for use in your first GetRecords request and for subsequent reads use the shard iterator returned by the GetRecords request in NextShardIterator. A new shard iterator is returned by every GetRecords request in NextShardIterator, which you use in the ShardIterator parameter of the next GetRecords request.
If a GetShardIterator request is made too often, you receive a ProvisionedThroughputExceededException. For more information about throughput limits, see GetRecords, and Streams Limits in the Amazon Kinesis Data Streams Developer Guide.
If the shard is closed, GetShardIterator returns a valid iterator for the last sequence number of the shard. A shard can be closed as a result of using SplitShard or MergeShards.
GetShardIterator has a limit of five transactions per second per account per open shard.
', 'IncreaseStreamRetentionPeriod' => 'Increases the Kinesis data stream\'s retention period, which is the length of time data records are accessible after they are added to the stream. The maximum value of a stream\'s retention period is 8760 hours (365 days).
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
If you choose a longer stream retention period, this operation increases the time period during which records that have not yet expired are accessible. However, it does not make previous, expired data (older than the stream\'s previous retention period) accessible after the operation has been called. For example, if a stream\'s retention period is set to 24 hours and is increased to 168 hours, any data that is older than 24 hours remains inaccessible to consumer applications.
', 'ListShards' => 'Lists the shards in a stream and provides information about each shard. This operation has a limit of 1000 transactions per second per data stream.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
This action does not list expired shards. For information about expired shards, see Data Routing, Data Persistence, and Shard State after a Reshard.
This API is a new operation that is used by the Amazon Kinesis Client Library (KCL). If you have a fine-grained IAM policy that only allows specific operations, you must update your policy to allow calls to this API. For more information, see Controlling Access to Amazon Kinesis Data Streams Resources Using IAM.
Lists the consumers registered to receive data from a stream using enhanced fan-out, and provides information about each consumer.
This operation has a limit of 5 transactions per second per stream.
', 'ListStreams' => 'Lists your Kinesis data streams.
The number of streams may be too large to return from a single call to ListStreams. You can limit the number of returned streams using the Limit parameter. If you do not specify a value for the Limit parameter, Kinesis Data Streams uses the default limit, which is currently 100.
You can detect if there are more streams available to list by using the HasMoreStreams flag from the returned output. If there are more streams available, you can request more streams by using the name of the last stream returned by the ListStreams request in the ExclusiveStartStreamName parameter in a subsequent request to ListStreams. The group of stream names returned by the subsequent request is then added to the list. You can continue this process until all the stream names have been collected in the list.
ListStreams has a limit of five transactions per second per account.
', 'ListTagsForStream' => 'Lists the tags for the specified Kinesis data stream. This operation has a limit of five transactions per second per account.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
Merges two adjacent shards in a Kinesis data stream and combines them into a single shard to reduce the stream\'s capacity to ingest and transport data. This API is only supported for the data streams with the provisioned capacity mode. Two shards are considered adjacent if the union of the hash key ranges for the two shards form a contiguous set with no gaps. For example, if you have two shards, one with a hash key range of 276...381 and the other with a hash key range of 382...454, then you could merge these two shards into a single shard that would have a hash key range of 276...454. After the merge, the single child shard receives data for all hash key values covered by the two parent shards.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
MergeShards is called when there is a need to reduce the overall capacity of a stream because of excess capacity that is not being used. You must specify the shard to be merged and the adjacent shard for a stream. For more information about merging shards, see Merge Two Shards in the Amazon Kinesis Data Streams Developer Guide.
If the stream is in the ACTIVE state, you can call MergeShards. If a stream is in the CREATING, UPDATING, or DELETING state, MergeShards returns a ResourceInUseException. If the specified stream does not exist, MergeShards returns a ResourceNotFoundException.
You can use DescribeStreamSummary to check the state of the stream, which is returned in StreamStatus.
MergeShards is an asynchronous operation. Upon receiving a MergeShards request, Amazon Kinesis Data Streams immediately returns a response and sets the StreamStatus to UPDATING. After the operation is completed, Kinesis Data Streams sets the StreamStatus to ACTIVE. Read and write operations continue to work while the stream is in the UPDATING state.
You use DescribeStreamSummary and the ListShards APIs to determine the shard IDs that are specified in the MergeShards request.
If you try to operate on too many streams in parallel using CreateStream, DeleteStream, MergeShards, or SplitShard, you receive a LimitExceededException.
MergeShards has a limit of five transactions per second per account.
Writes a single data record into an Amazon Kinesis data stream. Call PutRecord to send data into the stream for real-time ingestion and subsequent processing, one record at a time. Each shard can support writes up to 1,000 records per second, up to a maximum data write total of 1 MiB per second.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
You must specify the name of the stream that captures, stores, and transports the data; a partition key; and the data blob itself.
The data blob can be any type of data; for example, a segment from a log file, geographic/location data, website clickstream data, and so on.
The partition key is used by Kinesis Data Streams to distribute data across shards. Kinesis Data Streams segregates the data records that belong to a stream into multiple shards, using the partition key associated with each data record to determine the shard to which a given data record belongs.
Partition keys are Unicode strings, with a maximum length limit of 256 characters for each key. An MD5 hash function is used to map partition keys to 128-bit integer values and to map associated data records to shards using the hash key ranges of the shards. You can override hashing the partition key to determine the shard by explicitly specifying a hash value using the ExplicitHashKey parameter. For more information, see Adding Data to a Stream in the Amazon Kinesis Data Streams Developer Guide.
PutRecord returns the shard ID of where the data record was placed and the sequence number that was assigned to the data record.
Sequence numbers increase over time and are specific to a shard within a stream, not across all shards within a stream. To guarantee strictly increasing ordering, write serially to a shard and use the SequenceNumberForOrdering parameter. For more information, see Adding Data to a Stream in the Amazon Kinesis Data Streams Developer Guide.
After you write a record to a stream, you cannot modify that record or its order within the stream.
If a PutRecord request cannot be processed because of insufficient provisioned throughput on the shard involved in the request, PutRecord throws ProvisionedThroughputExceededException.
By default, data records are accessible for 24 hours from the time that they are added to a stream. You can use IncreaseStreamRetentionPeriod or DecreaseStreamRetentionPeriod to modify this retention period.
', 'PutRecords' => 'Writes multiple data records into a Kinesis data stream in a single call (also referred to as a PutRecords request). Use this operation to send data into the stream for data ingestion and processing.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
Each PutRecords request can support up to 500 records. Each record in the request can be as large as 1 MiB, up to a limit of 5 MiB for the entire request, including partition keys. Each shard can support writes up to 1,000 records per second, up to a maximum data write total of 1 MiB per second.
You must specify the name of the stream that captures, stores, and transports the data; and an array of request Records, with each record in the array requiring a partition key and data blob. The record size limit applies to the total size of the partition key and data blob.
The data blob can be any type of data; for example, a segment from a log file, geographic/location data, website clickstream data, and so on.
The partition key is used by Kinesis Data Streams as input to a hash function that maps the partition key and associated data to a specific shard. An MD5 hash function is used to map partition keys to 128-bit integer values and to map associated data records to shards. As a result of this hashing mechanism, all data records with the same partition key map to the same shard within the stream. For more information, see Adding Data to a Stream in the Amazon Kinesis Data Streams Developer Guide.
Each record in the Records array may include an optional parameter, ExplicitHashKey, which overrides the partition key to shard mapping. This parameter allows a data producer to determine explicitly the shard where the record is stored. For more information, see Adding Multiple Records with PutRecords in the Amazon Kinesis Data Streams Developer Guide.
The PutRecords response includes an array of response Records. Each record in the response array directly correlates with a record in the request array using natural ordering, from the top to the bottom of the request and response. The response Records array always includes the same number of records as the request array.
The response Records array includes both successfully and unsuccessfully processed records. Kinesis Data Streams attempts to process all records in each PutRecords request. A single record failure does not stop the processing of subsequent records. As a result, PutRecords doesn\'t guarantee the ordering of records. If you need to read records in the same order they are written to the stream, use PutRecord instead of PutRecords, and write to the same shard.
A successfully processed record includes ShardId and SequenceNumber values. The ShardId parameter identifies the shard in the stream where the record is stored. The SequenceNumber parameter is an identifier assigned to the put record, unique to all records in the stream.
An unsuccessfully processed record includes ErrorCode and ErrorMessage values. ErrorCode reflects the type of error and can be one of the following values: ProvisionedThroughputExceededException or InternalFailure. ErrorMessage provides more detailed information about the ProvisionedThroughputExceededException exception including the account ID, stream name, and shard ID of the record that was throttled. For more information about partially successful responses, see Adding Multiple Records with PutRecords in the Amazon Kinesis Data Streams Developer Guide.
After you write a record to a stream, you cannot modify that record or its order within the stream.
By default, data records are accessible for 24 hours from the time that they are added to a stream. You can use IncreaseStreamRetentionPeriod or DecreaseStreamRetentionPeriod to modify this retention period.
', 'PutResourcePolicy' => 'Attaches a resource-based policy to a data stream or registered consumer. If you are using an identity other than the root user of the Amazon Web Services account that owns the resource, the calling identity must have the PutResourcePolicy permissions on the specified Kinesis Data Streams resource and belong to the owner\'s account in order to use this operation. If you don\'t have PutResourcePolicy permissions, Amazon Kinesis Data Streams returns a 403 Access Denied error. If you receive a ResourceNotFoundException, check to see if you passed a valid stream or consumer resource.
Request patterns can be one of the following:
Data stream pattern: arn:aws.*:kinesis:.*:\\d{12}:.*stream/\\S+
Consumer pattern: ^(arn):aws.*:kinesis:.*:\\d{12}:.*stream\\/[a-zA-Z0-9_.-]+\\/consumer\\/[a-zA-Z0-9_.-]+:[0-9]+
For more information, see Controlling Access to Amazon Kinesis Data Streams Resources Using IAM.
', 'RegisterStreamConsumer' => 'Registers a consumer with a Kinesis data stream. When you use this operation, the consumer you register can then call SubscribeToShard to receive data from the stream using enhanced fan-out, at a rate of up to 2 MiB per second for every shard you subscribe to. This rate is unaffected by the total number of consumers that read from the same stream.
You can register up to 20 consumers per stream. A given consumer can only be registered with one stream at a time.
For an example of how to use this operations, see Enhanced Fan-Out Using the Kinesis Data Streams API.
The use of this operation has a limit of five transactions per second per account. Also, only 5 consumers can be created simultaneously. In other words, you cannot have more than 5 consumers in a CREATING status at the same time. Registering a 6th consumer while there are 5 in a CREATING status results in a LimitExceededException.
Removes tags from the specified Kinesis data stream. Removed tags are deleted and cannot be recovered after this operation successfully completes.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
If you specify a tag that does not exist, it is ignored.
RemoveTagsFromStream has a limit of five transactions per second per account.
', 'SplitShard' => 'Splits a shard into two new shards in the Kinesis data stream, to increase the stream\'s capacity to ingest and transport data. SplitShard is called when there is a need to increase the overall capacity of a stream because of an expected increase in the volume of data records being ingested. This API is only supported for the data streams with the provisioned capacity mode.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
You can also use SplitShard when a shard appears to be approaching its maximum utilization; for example, the producers sending data into the specific shard are suddenly sending more than previously anticipated. You can also call SplitShard to increase stream capacity, so that more Kinesis Data Streams applications can simultaneously read data from the stream for real-time processing.
You must specify the shard to be split and the new hash key, which is the position in the shard where the shard gets split in two. In many cases, the new hash key might be the average of the beginning and ending hash key, but it can be any hash key value in the range being mapped into the shard. For more information, see Split a Shard in the Amazon Kinesis Data Streams Developer Guide.
You can use DescribeStreamSummary and the ListShards APIs to determine the shard ID and hash key values for the ShardToSplit and NewStartingHashKey parameters that are specified in the SplitShard request.
SplitShard is an asynchronous operation. Upon receiving a SplitShard request, Kinesis Data Streams immediately returns a response and sets the stream status to UPDATING. After the operation is completed, Kinesis Data Streams sets the stream status to ACTIVE. Read and write operations continue to work while the stream is in the UPDATING state.
You can use DescribeStreamSummary to check the status of the stream, which is returned in StreamStatus. If the stream is in the ACTIVE state, you can call SplitShard.
If the specified stream does not exist, DescribeStreamSummary returns a ResourceNotFoundException. If you try to create more shards than are authorized for your account, you receive a LimitExceededException.
For the default shard limit for an Amazon Web Services account, see Kinesis Data Streams Limits in the Amazon Kinesis Data Streams Developer Guide. To increase this limit, contact Amazon Web Services Support.
If you try to operate on too many streams simultaneously using CreateStream, DeleteStream, MergeShards, and/or SplitShard, you receive a LimitExceededException.
SplitShard has a limit of five transactions per second per account.
Enables or updates server-side encryption using an Amazon Web Services KMS key for a specified stream.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
Starting encryption is an asynchronous operation. Upon receiving the request, Kinesis Data Streams returns immediately and sets the status of the stream to UPDATING. After the update is complete, Kinesis Data Streams sets the status of the stream back to ACTIVE. Updating or applying encryption normally takes a few seconds to complete, but it can take minutes. You can continue to read and write data to your stream while its status is UPDATING. Once the status of the stream is ACTIVE, encryption begins for records written to the stream.
API Limits: You can successfully apply a new Amazon Web Services KMS key for server-side encryption 25 times in a rolling 24-hour period.
Note: It can take up to 5 seconds after the stream is in an ACTIVE status before all records written to the stream are encrypted. After you enable encryption, you can verify that encryption is applied by inspecting the API response from PutRecord or PutRecords.
Disables server-side encryption for a specified stream.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
Stopping encryption is an asynchronous operation. Upon receiving the request, Kinesis Data Streams returns immediately and sets the status of the stream to UPDATING. After the update is complete, Kinesis Data Streams sets the status of the stream back to ACTIVE. Stopping encryption normally takes a few seconds to complete, but it can take minutes. You can continue to read and write data to your stream while its status is UPDATING. Once the status of the stream is ACTIVE, records written to the stream are no longer encrypted by Kinesis Data Streams.
API Limits: You can successfully disable server-side encryption 25 times in a rolling 24-hour period.
Note: It can take up to 5 seconds after the stream is in an ACTIVE status before all records written to the stream are no longer subject to encryption. After you disabled encryption, you can verify that encryption is not applied by inspecting the API response from PutRecord or PutRecords.
This operation establishes an HTTP/2 connection between the consumer you specify in the ConsumerARN parameter and the shard you specify in the ShardId parameter. After the connection is successfully established, Kinesis Data Streams pushes records from the shard to the consumer over this connection. Before you call this operation, call RegisterStreamConsumer to register the consumer with Kinesis Data Streams.
When the SubscribeToShard call succeeds, your consumer starts receiving events of type SubscribeToShardEvent over the HTTP/2 connection for up to 5 minutes, after which time you need to call SubscribeToShard again to renew the subscription if you want to continue to receive records.
You can make one call to SubscribeToShard per second per registered consumer per shard. For example, if you have a 4000 shard stream and two registered stream consumers, you can make one SubscribeToShard request per second for each combination of shard and registered consumer, allowing you to subscribe both consumers to all 4000 shards in one second.
If you call SubscribeToShard again with the same ConsumerARN and ShardId within 5 seconds of a successful call, you\'ll get a ResourceInUseException. If you call SubscribeToShard 5 seconds or more after a successful call, the second call takes over the subscription and the previous connection expires or fails with a ResourceInUseException.
For an example of how to use this operations, see Enhanced Fan-Out Using the Kinesis Data Streams API.
', 'UpdateShardCount' => 'Updates the shard count of the specified stream to the specified number of shards. This API is only supported for the data streams with the provisioned capacity mode.
When invoking this API, you must use either the StreamARN or the StreamName parameter, or both. It is recommended that you use the StreamARN input parameter when you invoke this API.
Updating the shard count is an asynchronous operation. Upon receiving the request, Kinesis Data Streams returns immediately and sets the status of the stream to UPDATING. After the update is complete, Kinesis Data Streams sets the status of the stream back to ACTIVE. Depending on the size of the stream, the scaling action could take a few minutes to complete. You can continue to read and write data to your stream while its status is UPDATING.
To update the shard count, Kinesis Data Streams performs splits or merges on individual shards. This can cause short-lived shards to be created, in addition to the final shards. These short-lived shards count towards your total shard limit for your account in the Region.
When using this operation, we recommend that you specify a target shard count that is a multiple of 25% (25%, 50%, 75%, 100%). You can specify any target value within your shard limit. However, if you specify a target that isn\'t a multiple of 25%, the scaling action might take longer to complete.
This operation has the following default limits. By default, you cannot do the following:
Scale more than ten times per rolling 24-hour period per stream
Scale up to more than double your current shard count for a stream
Scale down below half your current shard count for a stream
Scale up to more than 10000 shards in a stream
Scale a stream with more than 10000 shards down unless the result is less than 10000 shards
Scale up to more than the shard limit for your account
Make over 10 TPS. TPS over 10 will trigger the LimitExceededException
For the default limits for an Amazon Web Services account, see Streams Limits in the Amazon Kinesis Data Streams Developer Guide. To request an increase in the call rate limit, the shard limit for this API, or your overall shard limit, use the limits form.
', 'UpdateStreamMode' => 'Updates the capacity mode of the data stream. Currently, in Kinesis Data Streams, you can choose between an on-demand capacity mode and a provisioned capacity mode for your data stream.
', ], 'shapes' => [ 'AccessDeniedException' => [ 'base' => 'Specifies that you do not have the permissions required to perform this operation.
', 'refs' => [], ], 'AddTagsToStreamInput' => [ 'base' => 'Represents the input for AddTagsToStream.
If this parameter is unset (null) or if you set it to false, and the stream has registered consumers, the call to DeleteStream fails with a ResourceInUseException.
If set to true, there are more streams available to list.
If set to true, more tags are available. To request additional tags, set ExclusiveStartTagKey to the key of the last tag returned.
If set to true, more shards in the stream are available to describe.
Output parameter of the GetRecords API. The existing child shard of the current shard.
', 'refs' => [ 'ChildShardList$member' => NULL, ], ], 'ChildShardList' => [ 'base' => NULL, 'refs' => [ 'GetRecordsOutput$ChildShards' => 'The list of the current shard\'s child shards, returned in the GetRecords API\'s response only when the end of the current shard is reached.
The list of the child shards of the current shard, returned only at the end of the current shard.
', ], ], 'Consumer' => [ 'base' => 'An object that represents the details of the consumer you registered. This type of object is returned by RegisterStreamConsumer.
', 'refs' => [ 'ConsumerList$member' => NULL, 'RegisterStreamConsumerOutput$Consumer' => 'An object that represents the details of the consumer you registered. When you register a consumer, it gets an ARN that is generated by Kinesis Data Streams.
', ], ], 'ConsumerARN' => [ 'base' => NULL, 'refs' => [ 'Consumer$ConsumerARN' => 'When you register a consumer, Kinesis Data Streams generates an ARN for it. You need this ARN to be able to call SubscribeToShard.
If you delete a consumer and then create a new one with the same name, it won\'t have the same ARN. That\'s because consumer ARNs contain the creation timestamp. This is important to keep in mind if you have IAM policies that reference consumer ARNs.
', 'ConsumerDescription$ConsumerARN' => 'When you register a consumer, Kinesis Data Streams generates an ARN for it. You need this ARN to be able to call SubscribeToShard.
If you delete a consumer and then create a new one with the same name, it won\'t have the same ARN. That\'s because consumer ARNs contain the creation timestamp. This is important to keep in mind if you have IAM policies that reference consumer ARNs.
', 'DeregisterStreamConsumerInput$ConsumerARN' => 'The ARN returned by Kinesis Data Streams when you registered the consumer. If you don\'t know the ARN of the consumer that you want to deregister, you can use the ListStreamConsumers operation to get a list of the descriptions of all the consumers that are currently registered with a given data stream. The description of a consumer contains its ARN.
', 'DescribeStreamConsumerInput$ConsumerARN' => 'The ARN returned by Kinesis Data Streams when you registered the consumer.
', 'SubscribeToShardInput$ConsumerARN' => 'For this parameter, use the value you obtained when you called RegisterStreamConsumer.
', ], ], 'ConsumerCountObject' => [ 'base' => NULL, 'refs' => [ 'StreamDescriptionSummary$ConsumerCount' => 'The number of enhanced fan-out consumers registered with the stream.
', ], ], 'ConsumerDescription' => [ 'base' => 'An object that represents the details of a registered consumer. This type of object is returned by DescribeStreamConsumer.
', 'refs' => [ 'DescribeStreamConsumerOutput$ConsumerDescription' => 'An object that represents the details of the consumer.
', ], ], 'ConsumerList' => [ 'base' => NULL, 'refs' => [ 'ListStreamConsumersOutput$Consumers' => 'An array of JSON objects. Each object represents one registered consumer.
', ], ], 'ConsumerName' => [ 'base' => NULL, 'refs' => [ 'Consumer$ConsumerName' => 'The name of the consumer is something you choose when you register the consumer.
', 'ConsumerDescription$ConsumerName' => 'The name of the consumer is something you choose when you register the consumer.
', 'DeregisterStreamConsumerInput$ConsumerName' => 'The name that you gave to the consumer.
', 'DescribeStreamConsumerInput$ConsumerName' => 'The name that you gave to the consumer.
', 'RegisterStreamConsumerInput$ConsumerName' => 'For a given Kinesis data stream, each consumer must have a unique name. However, consumer names don\'t have to be unique across data streams.
', ], ], 'ConsumerStatus' => [ 'base' => NULL, 'refs' => [ 'Consumer$ConsumerStatus' => 'A consumer can\'t read data while in the CREATING or DELETING states.
A consumer can\'t read data while in the CREATING or DELETING states.
Represents the input for CreateStream.
The data blob to put into the record, which is base64-encoded when the blob is serialized. When the data blob (the payload before base64-encoding) is added to the partition key size, the total size must not exceed the maximum record size (1 MiB).
', 'PutRecordsRequestEntry$Data' => 'The data blob to put into the record, which is base64-encoded when the blob is serialized. When the data blob (the payload before base64-encoding) is added to the partition key size, the total size must not exceed the maximum record size (1 MiB).
', 'Record$Data' => 'The data blob. The data in the blob is both opaque and immutable to Kinesis Data Streams, which does not inspect, interpret, or change the data in the blob in any way. When the data blob (the payload before base64-encoding) is added to the partition key size, the total size must not exceed the maximum record size (1 MiB).
', ], ], 'DecreaseStreamRetentionPeriodInput' => [ 'base' => 'Represents the input for DecreaseStreamRetentionPeriod.
', 'refs' => [], ], 'DeleteResourcePolicyInput' => [ 'base' => NULL, 'refs' => [], ], 'DeleteStreamInput' => [ 'base' => 'Represents the input for DeleteStream.
', 'refs' => [], ], 'DeregisterStreamConsumerInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeLimitsInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeLimitsOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeStreamConsumerInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeStreamConsumerOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeStreamInput' => [ 'base' => 'Represents the input for DescribeStream.
The maximum number of shards to return in a single call. The default value is 100. If you specify a value greater than 100, at most 100 results are returned.
', ], ], 'DescribeStreamOutput' => [ 'base' => 'Represents the output for DescribeStream.
Represents the input for DisableEnhancedMonitoring.
', 'refs' => [], ], 'EnableEnhancedMonitoringInput' => [ 'base' => 'Represents the input for EnableEnhancedMonitoring.
', 'refs' => [], ], 'EncryptionType' => [ 'base' => NULL, 'refs' => [ 'PutRecordOutput$EncryptionType' => 'The encryption type to use on the record. This parameter can be one of the following values:
NONE: Do not encrypt the records in the stream.
KMS: Use server-side encryption on the records in the stream using a customer-managed Amazon Web Services KMS key.
The encryption type used on the records. This parameter can be one of the following values:
NONE: Do not encrypt the records.
KMS: Use server-side encryption on the records using a customer-managed Amazon Web Services KMS key.
The encryption type used on the record. This parameter can be one of the following values:
NONE: Do not encrypt the records in the stream.
KMS: Use server-side encryption on the records in the stream using a customer-managed Amazon Web Services KMS key.
The encryption type to use. The only valid value is KMS.
The encryption type. The only valid value is KMS.
The server-side encryption type used on the stream. This parameter can be one of the following values:
NONE: Do not encrypt the records in the stream.
KMS: Use server-side encryption on the records in the stream using a customer-managed Amazon Web Services KMS key.
The encryption type used. This value is one of the following:
KMS
NONE
Represents enhanced metrics types.
', 'refs' => [ 'EnhancedMonitoringList$member' => NULL, ], ], 'EnhancedMonitoringList' => [ 'base' => NULL, 'refs' => [ 'StreamDescription$EnhancedMonitoring' => 'Represents the current enhanced monitoring settings of the stream.
', 'StreamDescriptionSummary$EnhancedMonitoring' => 'Represents the current enhanced monitoring settings of the stream.
', ], ], 'EnhancedMonitoringOutput' => [ 'base' => 'Represents the output for EnableEnhancedMonitoring and DisableEnhancedMonitoring.
', 'refs' => [], ], 'ErrorCode' => [ 'base' => NULL, 'refs' => [ 'PutRecordsResultEntry$ErrorCode' => 'The error code for an individual record result. ErrorCodes can be either ProvisionedThroughputExceededException or InternalFailure.
A message that provides information about the error.
', 'ExpiredNextTokenException$message' => NULL, 'InternalFailureException$message' => NULL, 'InvalidArgumentException$message' => 'A message that provides information about the error.
', 'KMSAccessDeniedException$message' => 'A message that provides information about the error.
', 'KMSDisabledException$message' => 'A message that provides information about the error.
', 'KMSInvalidStateException$message' => 'A message that provides information about the error.
', 'KMSNotFoundException$message' => 'A message that provides information about the error.
', 'KMSOptInRequired$message' => 'A message that provides information about the error.
', 'KMSThrottlingException$message' => 'A message that provides information about the error.
', 'LimitExceededException$message' => 'A message that provides information about the error.
', 'ProvisionedThroughputExceededException$message' => 'A message that provides information about the error.
', 'PutRecordsResultEntry$ErrorMessage' => 'The error message for an individual record result. An ErrorCode value of ProvisionedThroughputExceededException has an error message that includes the account ID, stream name, and shard ID. An ErrorCode value of InternalFailure has the error message "Internal Service Failure".
A message that provides information about the error.
', 'ResourceNotFoundException$message' => 'A message that provides information about the error.
', 'ValidationException$message' => NULL, ], ], 'ExpiredIteratorException' => [ 'base' => 'The provided iterator exceeds the maximum age allowed.
', 'refs' => [], ], 'ExpiredNextTokenException' => [ 'base' => 'The pagination token passed to the operation is expired.
', 'refs' => [], ], 'GetRecordsInput' => [ 'base' => 'Represents the input for GetRecords.
', 'refs' => [], ], 'GetRecordsInputLimit' => [ 'base' => NULL, 'refs' => [ 'GetRecordsInput$Limit' => 'The maximum number of records to return. Specify a value of up to 10,000. If you specify a value that is greater than 10,000, GetRecords throws InvalidArgumentException. The default value is 10,000.
Represents the output for GetRecords.
', 'refs' => [], ], 'GetResourcePolicyInput' => [ 'base' => NULL, 'refs' => [], ], 'GetResourcePolicyOutput' => [ 'base' => NULL, 'refs' => [], ], 'GetShardIteratorInput' => [ 'base' => 'Represents the input for GetShardIterator.
Represents the output for GetShardIterator.
The starting hash key of the hash key range.
', 'HashKeyRange$EndingHashKey' => 'The ending hash key of the hash key range.
', 'PutRecordInput$ExplicitHashKey' => 'The hash value used to explicitly determine the shard the data record is assigned to by overriding the partition key hash.
', 'PutRecordsRequestEntry$ExplicitHashKey' => 'The hash value used to determine explicitly the shard that the data record is assigned to by overriding the partition key hash.
', 'SplitShardInput$NewStartingHashKey' => 'A hash key value for the starting hash key of one of the child shards created by the split. The hash key range for a given shard constitutes a set of ordered contiguous positive integers. The value for NewStartingHashKey must be in the range of hash keys being mapped into the shard. The NewStartingHashKey hash key value and all higher hash key values in hash key range are distributed to one of the child shards. All the lower hash key values in the range are distributed to the other child shard.
The range of possible hash key values for the shard, which is a set of ordered contiguous positive integers.
', 'refs' => [ 'ChildShard$HashKeyRange' => NULL, 'Shard$HashKeyRange' => 'The range of possible hash key values for the shard, which is a set of ordered contiguous positive integers.
', ], ], 'IncreaseStreamRetentionPeriodInput' => [ 'base' => 'Represents the input for IncreaseStreamRetentionPeriod.
', 'refs' => [], ], 'InternalFailureException' => [ 'base' => 'The processing of the request failed because of an unknown error, exception, or failure.
', 'refs' => [ 'SubscribeToShardEventStream$InternalFailureException' => 'The processing of the request failed because of an unknown error, exception, or failure.
', ], ], 'InvalidArgumentException' => [ 'base' => 'A specified parameter exceeds its restrictions, is not supported, or can\'t be used. For more information, see the returned message.
', 'refs' => [], ], 'KMSAccessDeniedException' => [ 'base' => 'The ciphertext references a key that doesn\'t exist or that you don\'t have access to.
', 'refs' => [ 'SubscribeToShardEventStream$KMSAccessDeniedException' => NULL, ], ], 'KMSDisabledException' => [ 'base' => 'The request was rejected because the specified customer master key (CMK) isn\'t enabled.
', 'refs' => [ 'SubscribeToShardEventStream$KMSDisabledException' => NULL, ], ], 'KMSInvalidStateException' => [ 'base' => 'The request was rejected because the state of the specified resource isn\'t valid for this request. For more information, see How Key State Affects Use of a Customer Master Key in the Amazon Web Services Key Management Service Developer Guide.
', 'refs' => [ 'SubscribeToShardEventStream$KMSInvalidStateException' => NULL, ], ], 'KMSNotFoundException' => [ 'base' => 'The request was rejected because the specified entity or resource can\'t be found.
', 'refs' => [ 'SubscribeToShardEventStream$KMSNotFoundException' => NULL, ], ], 'KMSOptInRequired' => [ 'base' => 'The Amazon Web Services access key ID needs a subscription for the service.
', 'refs' => [ 'SubscribeToShardEventStream$KMSOptInRequired' => NULL, ], ], 'KMSThrottlingException' => [ 'base' => 'The request was denied due to request throttling. For more information about throttling, see Limits in the Amazon Web Services Key Management Service Developer Guide.
', 'refs' => [ 'SubscribeToShardEventStream$KMSThrottlingException' => NULL, ], ], 'KeyId' => [ 'base' => NULL, 'refs' => [ 'StartStreamEncryptionInput$KeyId' => 'The GUID for the customer-managed Amazon Web Services KMS key to use for encryption. This value can be a globally unique identifier, a fully specified Amazon Resource Name (ARN) to either an alias or a key, or an alias name prefixed by "alias/".You can also use a master key owned by Kinesis Data Streams by specifying the alias aws/kinesis.
Key ARN example: arn:aws:kms:us-east-1:123456789012:key/12345678-1234-1234-1234-123456789012
Alias ARN example: arn:aws:kms:us-east-1:123456789012:alias/MyAliasName
Globally unique key ID example: 12345678-1234-1234-1234-123456789012
Alias name example: alias/MyAliasName
Master key owned by Kinesis Data Streams: alias/aws/kinesis
The GUID for the customer-managed Amazon Web Services KMS key to use for encryption. This value can be a globally unique identifier, a fully specified Amazon Resource Name (ARN) to either an alias or a key, or an alias name prefixed by "alias/".You can also use a master key owned by Kinesis Data Streams by specifying the alias aws/kinesis.
Key ARN example: arn:aws:kms:us-east-1:123456789012:key/12345678-1234-1234-1234-123456789012
Alias ARN example: arn:aws:kms:us-east-1:123456789012:alias/MyAliasName
Globally unique key ID example: 12345678-1234-1234-1234-123456789012
Alias name example: alias/MyAliasName
Master key owned by Kinesis Data Streams: alias/aws/kinesis
The GUID for the customer-managed Amazon Web Services KMS key to use for encryption. This value can be a globally unique identifier, a fully specified ARN to either an alias or a key, or an alias name prefixed by "alias/".You can also use a master key owned by Kinesis Data Streams by specifying the alias aws/kinesis.
Key ARN example: arn:aws:kms:us-east-1:123456789012:key/12345678-1234-1234-1234-123456789012
Alias ARN example: arn:aws:kms:us-east-1:123456789012:alias/MyAliasName
Globally unique key ID example: 12345678-1234-1234-1234-123456789012
Alias name example: alias/MyAliasName
Master key owned by Kinesis Data Streams: alias/aws/kinesis
The GUID for the customer-managed Amazon Web Services KMS key to use for encryption. This value can be a globally unique identifier, a fully specified ARN to either an alias or a key, or an alias name prefixed by "alias/".You can also use a master key owned by Kinesis Data Streams by specifying the alias aws/kinesis.
Key ARN example: arn:aws:kms:us-east-1:123456789012:key/12345678-1234-1234-1234-123456789012
Alias ARN example: arn:aws:kms:us-east-1:123456789012:alias/MyAliasName
Globally unique key ID example: 12345678-1234-1234-1234-123456789012
Alias name example: alias/MyAliasName
Master key owned by Kinesis Data Streams: alias/aws/kinesis
The requested resource exceeds the maximum number allowed, or the number of concurrent stream requests exceeds the maximum number allowed.
', 'refs' => [], ], 'ListShardsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListShardsInputLimit' => [ 'base' => NULL, 'refs' => [ 'ListShardsInput$MaxResults' => 'The maximum number of shards to return in a single call to ListShards. The maximum number of shards to return in a single call. The default value is 1000. If you specify a value greater than 1000, at most 1000 results are returned.
When the number of shards to be listed is greater than the value of MaxResults, the response contains a NextToken value that you can use in a subsequent call to ListShards to list the next set of shards.
The maximum number of consumers that you want a single call of ListStreamConsumers to return. The default value is 100. If you specify a value greater than 100, at most 100 results are returned.
Represents the input for ListStreams.
The maximum number of streams to list. The default value is 100. If you specify a value greater than 100, at most 100 results are returned.
', ], ], 'ListStreamsOutput' => [ 'base' => 'Represents the output for ListStreams.
Represents the input for ListTagsForStream.
The number of tags to return. If this number is less than the total number of tags associated with the stream, HasMoreTags is set to true. To list additional tags, set ExclusiveStartTagKey to the last key in the response.
Represents the output for ListTagsForStream.
Represents the input for MergeShards.
List of shard-level metrics to disable.
The following are the valid shard-level metrics. The value "ALL" disables every metric.
IncomingBytes
IncomingRecords
OutgoingBytes
OutgoingRecords
WriteProvisionedThroughputExceeded
ReadProvisionedThroughputExceeded
IteratorAgeMilliseconds
ALL
For more information, see Monitoring the Amazon Kinesis Data Streams Service with Amazon CloudWatch in the Amazon Kinesis Data Streams Developer Guide.
', 'EnableEnhancedMonitoringInput$ShardLevelMetrics' => 'List of shard-level metrics to enable.
The following are the valid shard-level metrics. The value "ALL" enables every metric.
IncomingBytes
IncomingRecords
OutgoingBytes
OutgoingRecords
WriteProvisionedThroughputExceeded
ReadProvisionedThroughputExceeded
IteratorAgeMilliseconds
ALL
For more information, see Monitoring the Amazon Kinesis Data Streams Service with Amazon CloudWatch in the Amazon Kinesis Data Streams Developer Guide.
', 'EnhancedMetrics$ShardLevelMetrics' => 'List of shard-level metrics.
The following are the valid shard-level metrics. The value "ALL" enhances every metric.
IncomingBytes
IncomingRecords
OutgoingBytes
OutgoingRecords
WriteProvisionedThroughputExceeded
ReadProvisionedThroughputExceeded
IteratorAgeMilliseconds
ALL
For more information, see Monitoring the Amazon Kinesis Data Streams Service with Amazon CloudWatch in the Amazon Kinesis Data Streams Developer Guide.
', 'EnhancedMonitoringOutput$CurrentShardLevelMetrics' => 'Represents the current state of the metrics that are in the enhanced state before the operation.
', 'EnhancedMonitoringOutput$DesiredShardLevelMetrics' => 'Represents the list of all the metrics that would be in the enhanced state after the operation.
', ], ], 'MillisBehindLatest' => [ 'base' => NULL, 'refs' => [ 'GetRecordsOutput$MillisBehindLatest' => 'The number of milliseconds the GetRecords response is from the tip of the stream, indicating how far behind current time the consumer is. A value of zero indicates that record processing is caught up, and there are no new records to process at this moment.
', 'SubscribeToShardEvent$MillisBehindLatest' => 'The number of milliseconds the read records are from the tip of the stream, indicating how far behind current time the consumer is. A value of zero indicates that record processing is caught up, and there are no new records to process at this moment.
', ], ], 'NextToken' => [ 'base' => NULL, 'refs' => [ 'ListShardsInput$NextToken' => 'When the number of shards in the data stream is greater than the default value for the MaxResults parameter, or if you explicitly specify a value for MaxResults that is less than the number of shards in the data stream, the response includes a pagination token named NextToken. You can specify this NextToken value in a subsequent call to ListShards to list the next set of shards.
Don\'t specify StreamName or StreamCreationTimestamp if you specify NextToken because the latter unambiguously identifies the stream.
You can optionally specify a value for the MaxResults parameter when you specify NextToken. If you specify a MaxResults value that is less than the number of shards that the operation returns if you don\'t specify MaxResults, the response will contain a new NextToken value. You can use the new NextToken value in a subsequent call to the ListShards operation.
Tokens expire after 300 seconds. When you obtain a value for NextToken in the response to a call to ListShards, you have 300 seconds to use that value. If you specify an expired token in a call to ListShards, you get ExpiredNextTokenException.
When the number of shards in the data stream is greater than the default value for the MaxResults parameter, or if you explicitly specify a value for MaxResults that is less than the number of shards in the data stream, the response includes a pagination token named NextToken. You can specify this NextToken value in a subsequent call to ListShards to list the next set of shards. For more information about the use of this pagination token when calling the ListShards operation, see ListShardsInput$NextToken.
Tokens expire after 300 seconds. When you obtain a value for NextToken in the response to a call to ListShards, you have 300 seconds to use that value. If you specify an expired token in a call to ListShards, you get ExpiredNextTokenException.
When the number of consumers that are registered with the data stream is greater than the default value for the MaxResults parameter, or if you explicitly specify a value for MaxResults that is less than the number of consumers that are registered with the data stream, the response includes a pagination token named NextToken. You can specify this NextToken value in a subsequent call to ListStreamConsumers to list the next set of registered consumers.
Don\'t specify StreamName or StreamCreationTimestamp if you specify NextToken because the latter unambiguously identifies the stream.
You can optionally specify a value for the MaxResults parameter when you specify NextToken. If you specify a MaxResults value that is less than the number of consumers that the operation returns if you don\'t specify MaxResults, the response will contain a new NextToken value. You can use the new NextToken value in a subsequent call to the ListStreamConsumers operation to list the next set of consumers.
Tokens expire after 300 seconds. When you obtain a value for NextToken in the response to a call to ListStreamConsumers, you have 300 seconds to use that value. If you specify an expired token in a call to ListStreamConsumers, you get ExpiredNextTokenException.
When the number of consumers that are registered with the data stream is greater than the default value for the MaxResults parameter, or if you explicitly specify a value for MaxResults that is less than the number of registered consumers, the response includes a pagination token named NextToken. You can specify this NextToken value in a subsequent call to ListStreamConsumers to list the next set of registered consumers. For more information about the use of this pagination token when calling the ListStreamConsumers operation, see ListStreamConsumersInput$NextToken.
Tokens expire after 300 seconds. When you obtain a value for NextToken in the response to a call to ListStreamConsumers, you have 300 seconds to use that value. If you specify an expired token in a call to ListStreamConsumers, you get ExpiredNextTokenException.
The maximum number of data streams with the on-demand capacity mode.
', ], ], 'OnDemandStreamCountObject' => [ 'base' => NULL, 'refs' => [ 'DescribeLimitsOutput$OnDemandStreamCount' => 'Indicates the number of data streams with the on-demand capacity mode.
', ], ], 'PartitionKey' => [ 'base' => NULL, 'refs' => [ 'PutRecordInput$PartitionKey' => 'Determines which shard in the stream the data record is assigned to. Partition keys are Unicode strings with a maximum length limit of 256 characters for each key. Amazon Kinesis Data Streams uses the partition key as input to a hash function that maps the partition key and associated data to a specific shard. Specifically, an MD5 hash function is used to map partition keys to 128-bit integer values and to map associated data records to shards. As a result of this hashing mechanism, all data records with the same partition key map to the same shard within the stream.
', 'PutRecordsRequestEntry$PartitionKey' => 'Determines which shard in the stream the data record is assigned to. Partition keys are Unicode strings with a maximum length limit of 256 characters for each key. Amazon Kinesis Data Streams uses the partition key as input to a hash function that maps the partition key and associated data to a specific shard. Specifically, an MD5 hash function is used to map partition keys to 128-bit integer values and to map associated data records to shards. As a result of this hashing mechanism, all data records with the same partition key map to the same shard within the stream.
', 'Record$PartitionKey' => 'Identifies which shard in the stream the data record is assigned to.
', ], ], 'Policy' => [ 'base' => NULL, 'refs' => [ 'GetResourcePolicyOutput$Policy' => 'Details of the resource policy. This is formatted as a JSON string.
', 'PutResourcePolicyInput$Policy' => 'Details of the resource policy. It must include the identity of the principal and the actions allowed on this resource. This is formatted as a JSON string.
', ], ], 'PositiveIntegerObject' => [ 'base' => NULL, 'refs' => [ 'CreateStreamInput$ShardCount' => 'The number of shards that the stream will use. The throughput of the stream is a function of the number of shards; more shards are required for greater provisioned throughput.
', 'PutRecordsOutput$FailedRecordCount' => 'The number of unsuccessfully processed records in a PutRecords request.
The new number of shards. This value has the following default limits. By default, you cannot do the following:
Set this value to more than double your current shard count for a stream.
Set this value below half your current shard count for a stream.
Set this value to more than 10000 shards in a stream (the default limit for shard count per stream is 10000 per account per region), unless you request a limit increase.
Scale a stream with more than 10000 shards down unless you set this value to less than 10000 shards.
The current number of shards.
', 'UpdateShardCountOutput$TargetShardCount' => 'The updated number of shards.
', ], ], 'ProvisionedThroughputExceededException' => [ 'base' => 'The request rate for the stream is too high, or the requested data is too large for the available throughput. Reduce the frequency or size of your requests. For more information, see Streams Limits in the Amazon Kinesis Data Streams Developer Guide, and Error Retries and Exponential Backoff in Amazon Web Services in the Amazon Web Services General Reference.
', 'refs' => [], ], 'PutRecordInput' => [ 'base' => 'Represents the input for PutRecord.
Represents the output for PutRecord.
A PutRecords request.
PutRecords results.
Represents the output for PutRecords.
The records associated with the request.
', ], ], 'PutRecordsResultEntry' => [ 'base' => 'Represents the result of an individual record from a PutRecords request. A record that is successfully added to a stream includes SequenceNumber and ShardId in the result. A record that fails to be added to the stream includes ErrorCode and ErrorMessage in the result.
An array of successfully and unsuccessfully processed record results. A record that is successfully added to a stream includes SequenceNumber and ShardId in the result. A record that fails to be added to a stream includes ErrorCode and ErrorMessage in the result.
The unit of data of the Kinesis data stream, which is composed of a sequence number, a partition key, and a data blob.
', 'refs' => [ 'RecordList$member' => NULL, ], ], 'RecordList' => [ 'base' => NULL, 'refs' => [ 'GetRecordsOutput$Records' => 'The data records retrieved from the shard.
', 'SubscribeToShardEvent$Records' => '', ], ], 'RegisterStreamConsumerInput' => [ 'base' => NULL, 'refs' => [], ], 'RegisterStreamConsumerOutput' => [ 'base' => NULL, 'refs' => [], ], 'RemoveTagsFromStreamInput' => [ 'base' => 'Represents the input for RemoveTagsFromStream.
The Amazon Resource Name (ARN) of the data stream or consumer.
', 'GetResourcePolicyInput$ResourceARN' => 'The Amazon Resource Name (ARN) of the data stream or consumer.
', 'PutResourcePolicyInput$ResourceARN' => 'The Amazon Resource Name (ARN) of the data stream or consumer.
', ], ], 'ResourceInUseException' => [ 'base' => 'The resource is not available for this operation. For successful operation, the resource must be in the ACTIVE state.
The requested resource could not be found. The stream might not be specified correctly.
', 'refs' => [ 'SubscribeToShardEventStream$ResourceNotFoundException' => NULL, ], ], 'RetentionPeriodHours' => [ 'base' => NULL, 'refs' => [ 'DecreaseStreamRetentionPeriodInput$RetentionPeriodHours' => 'The new retention period of the stream, in hours. Must be less than the current retention period.
', 'IncreaseStreamRetentionPeriodInput$RetentionPeriodHours' => 'The new retention period of the stream, in hours. Must be more than the current retention period.
', 'StreamDescription$RetentionPeriodHours' => 'The current retention period, in hours. Minimum value of 24. Maximum value of 168.
', 'StreamDescriptionSummary$RetentionPeriodHours' => 'The current retention period, in hours.
', ], ], 'ScalingType' => [ 'base' => NULL, 'refs' => [ 'UpdateShardCountInput$ScalingType' => 'The scaling type. Uniform scaling creates shards of equal size.
', ], ], 'SequenceNumber' => [ 'base' => NULL, 'refs' => [ 'GetShardIteratorInput$StartingSequenceNumber' => 'The sequence number of the data record in the shard from which to start reading. Used with shard iterator type AT_SEQUENCE_NUMBER and AFTER_SEQUENCE_NUMBER.
', 'PutRecordInput$SequenceNumberForOrdering' => 'Guarantees strictly increasing sequence numbers, for puts from the same client and to the same partition key. Usage: set the SequenceNumberForOrdering of record n to the sequence number of record n-1 (as returned in the result when putting record n-1). If this parameter is not set, records are coarsely ordered based on arrival time.
The sequence number identifier that was assigned to the put data record. The sequence number for the record is unique across all records in the stream. A sequence number is the identifier associated with every record put into the stream.
', 'PutRecordsResultEntry$SequenceNumber' => 'The sequence number for an individual record result.
', 'Record$SequenceNumber' => 'The unique identifier of the record within its shard.
', 'SequenceNumberRange$StartingSequenceNumber' => 'The starting sequence number for the range.
', 'SequenceNumberRange$EndingSequenceNumber' => 'The ending sequence number for the range. Shards that are in the OPEN state have an ending sequence number of null.
The sequence number of the data record in the shard from which to start streaming. To specify a sequence number, set StartingPosition to AT_SEQUENCE_NUMBER or AFTER_SEQUENCE_NUMBER.
Use this as SequenceNumber in the next call to SubscribeToShard, with StartingPosition set to AT_SEQUENCE_NUMBER or AFTER_SEQUENCE_NUMBER. Use ContinuationSequenceNumber for checkpointing because it captures your shard progress even when no data is written to the shard.
The range of possible sequence numbers for the shard.
', 'refs' => [ 'Shard$SequenceNumberRange' => 'The range of possible sequence numbers for the shard.
', ], ], 'Shard' => [ 'base' => 'A uniquely identified group of data records in a Kinesis data stream.
', 'refs' => [ 'ShardList$member' => NULL, ], ], 'ShardCountObject' => [ 'base' => NULL, 'refs' => [ 'DescribeLimitsOutput$ShardLimit' => 'The maximum number of shards.
', 'DescribeLimitsOutput$OpenShardCount' => 'The number of open shards.
', 'StreamDescriptionSummary$OpenShardCount' => 'The number of open shards in the stream.
', ], ], 'ShardFilter' => [ 'base' => 'The request parameter used to filter out the response of the ListShards API.
Enables you to filter out the response of the ListShards API. You can only specify one filter at a time.
If you use the ShardFilter parameter when invoking the ListShards API, the Type is the required property and must be specified. If you specify the AT_TRIM_HORIZON, FROM_TRIM_HORIZON, or AT_LATEST types, you do not need to specify either the ShardId or the Timestamp optional properties.
If you specify the AFTER_SHARD_ID type, you must also provide the value for the optional ShardId property. The ShardId property is identical in fuctionality to the ExclusiveStartShardId parameter of the ListShards API. When ShardId property is specified, the response includes the shards starting with the shard whose ID immediately follows the ShardId that you provided.
If you specify the AT_TIMESTAMP or FROM_TIMESTAMP_ID type, you must also provide the value for the optional Timestamp property. If you specify the AT_TIMESTAMP type, then all shards that were open at the provided timestamp are returned. If you specify the FROM_TIMESTAMP type, then all shards starting from the provided timestamp to TIP are returned.
The shard type specified in the ShardFilter parameter. This is a required property of the ShardFilter parameter.
You can specify the following valid values:
AFTER_SHARD_ID - the response includes all the shards, starting with the shard whose ID immediately follows the ShardId that you provided.
AT_TRIM_HORIZON - the response includes all the shards that were open at TRIM_HORIZON.
FROM_TRIM_HORIZON - (default), the response includes all the shards within the retention period of the data stream (trim to tip).
AT_LATEST - the response includes only the currently open shards of the data stream.
AT_TIMESTAMP - the response includes all shards whose start timestamp is less than or equal to the given timestamp and end timestamp is greater than or equal to the given timestamp or still open.
FROM_TIMESTAMP - the response incldues all closed shards whose end timestamp is greater than or equal to the given timestamp and also all open shards. Corrected to TRIM_HORIZON of the data stream if FROM_TIMESTAMP is less than the TRIM_HORIZON value.
The shard ID of the existing child shard of the current shard.
', 'DescribeStreamInput$ExclusiveStartShardId' => 'The shard ID of the shard to start with.
Specify this parameter to indicate that you want to describe the stream starting with the shard whose ID immediately follows ExclusiveStartShardId.
If you don\'t specify this parameter, the default behavior for DescribeStream is to describe the stream starting with the first shard in the stream.
The shard ID of the Kinesis Data Streams shard to get the iterator for.
', 'ListShardsInput$ExclusiveStartShardId' => 'Specify this parameter to indicate that you want to list the shards starting with the shard whose ID immediately follows ExclusiveStartShardId.
If you don\'t specify this parameter, the default behavior is for ListShards to list the shards starting with the first one in the stream.
You cannot specify this parameter if you specify NextToken.
The shard ID of the shard to combine with the adjacent shard for the merge.
', 'MergeShardsInput$AdjacentShardToMerge' => 'The shard ID of the adjacent shard for the merge.
', 'PutRecordOutput$ShardId' => 'The shard ID of the shard where the data record was placed.
', 'PutRecordsResultEntry$ShardId' => 'The shard ID for an individual record result.
', 'Shard$ShardId' => 'The unique identifier of the shard within the stream.
', 'Shard$ParentShardId' => 'The shard ID of the shard\'s parent.
', 'Shard$AdjacentParentShardId' => 'The shard ID of the shard adjacent to the shard\'s parent.
', 'ShardFilter$ShardId' => 'The exclusive start shardID speified in the ShardFilter parameter. This property can only be used if the AFTER_SHARD_ID shard type is specified.
The shard ID of the shard to split.
', 'SubscribeToShardInput$ShardId' => 'The ID of the shard you want to subscribe to. To see a list of all the shards for a given stream, use ListShards.
', ], ], 'ShardIdList' => [ 'base' => NULL, 'refs' => [ 'ChildShard$ParentShards' => 'The current shard that is the parent of the existing child shard.
', ], ], 'ShardIterator' => [ 'base' => NULL, 'refs' => [ 'GetRecordsInput$ShardIterator' => 'The position in the shard from which you want to start sequentially reading data records. A shard iterator specifies this position using the sequence number of a data record in the shard.
', 'GetRecordsOutput$NextShardIterator' => 'The next position in the shard from which to start sequentially reading data records. If set to null, the shard has been closed and the requested iterator does not return any more data.
The position in the shard from which to start reading data records sequentially. A shard iterator specifies this position using the sequence number of a data record in a shard.
', ], ], 'ShardIteratorType' => [ 'base' => NULL, 'refs' => [ 'GetShardIteratorInput$ShardIteratorType' => 'Determines how the shard iterator is used to start reading data records from the shard.
The following are the valid Amazon Kinesis shard iterator types:
AT_SEQUENCE_NUMBER - Start reading from the position denoted by a specific sequence number, provided in the value StartingSequenceNumber.
AFTER_SEQUENCE_NUMBER - Start reading right after the position denoted by a specific sequence number, provided in the value StartingSequenceNumber.
AT_TIMESTAMP - Start reading from the position denoted by a specific time stamp, provided in the value Timestamp.
TRIM_HORIZON - Start reading at the last untrimmed record in the shard in the system, which is the oldest data record in the shard.
LATEST - Start reading just after the most recent record in the shard, so that you always read the most recent data in the shard.
You can set the starting position to one of the following values:
AT_SEQUENCE_NUMBER: Start streaming from the position denoted by the sequence number specified in the SequenceNumber field.
AFTER_SEQUENCE_NUMBER: Start streaming right after the position denoted by the sequence number specified in the SequenceNumber field.
AT_TIMESTAMP: Start streaming from the position denoted by the time stamp specified in the Timestamp field.
TRIM_HORIZON: Start streaming at the last untrimmed record in the shard, which is the oldest data record in the shard.
LATEST: Start streaming just after the most recent record in the shard, so that you always read the most recent data in the shard.
An array of JSON objects. Each object represents one shard and specifies the IDs of the shard, the shard\'s parent, and the shard that\'s adjacent to the shard\'s parent. Each object also contains the starting and ending hash keys and the starting and ending sequence numbers for the shard.
', 'StreamDescription$Shards' => 'The shards that comprise the stream.
', ], ], 'SplitShardInput' => [ 'base' => 'Represents the input for SplitShard.
The starting position in the data stream from which to start streaming.
', 'refs' => [ 'SubscribeToShardInput$StartingPosition' => 'The starting position in the data stream from which to start streaming.
', ], ], 'StopStreamEncryptionInput' => [ 'base' => NULL, 'refs' => [], ], 'StreamARN' => [ 'base' => NULL, 'refs' => [ 'AddTagsToStreamInput$StreamARN' => 'The ARN of the stream.
', 'ConsumerDescription$StreamARN' => 'The ARN of the stream with which you registered the consumer.
', 'DecreaseStreamRetentionPeriodInput$StreamARN' => 'The ARN of the stream.
', 'DeleteStreamInput$StreamARN' => 'The ARN of the stream.
', 'DeregisterStreamConsumerInput$StreamARN' => 'The ARN of the Kinesis data stream that the consumer is registered with. For more information, see Amazon Resource Names (ARNs) and Amazon Web Services Service Namespaces.
', 'DescribeStreamConsumerInput$StreamARN' => 'The ARN of the Kinesis data stream that the consumer is registered with. For more information, see Amazon Resource Names (ARNs) and Amazon Web Services Service Namespaces.
', 'DescribeStreamInput$StreamARN' => 'The ARN of the stream.
', 'DescribeStreamSummaryInput$StreamARN' => 'The ARN of the stream.
', 'DisableEnhancedMonitoringInput$StreamARN' => 'The ARN of the stream.
', 'EnableEnhancedMonitoringInput$StreamARN' => 'The ARN of the stream.
', 'EnhancedMonitoringOutput$StreamARN' => 'The ARN of the stream.
', 'GetRecordsInput$StreamARN' => 'The ARN of the stream.
', 'GetShardIteratorInput$StreamARN' => 'The ARN of the stream.
', 'IncreaseStreamRetentionPeriodInput$StreamARN' => 'The ARN of the stream.
', 'ListShardsInput$StreamARN' => 'The ARN of the stream.
', 'ListStreamConsumersInput$StreamARN' => 'The ARN of the Kinesis data stream for which you want to list the registered consumers. For more information, see Amazon Resource Names (ARNs) and Amazon Web Services Service Namespaces.
', 'ListTagsForStreamInput$StreamARN' => 'The ARN of the stream.
', 'MergeShardsInput$StreamARN' => 'The ARN of the stream.
', 'PutRecordInput$StreamARN' => 'The ARN of the stream.
', 'PutRecordsInput$StreamARN' => 'The ARN of the stream.
', 'RegisterStreamConsumerInput$StreamARN' => 'The ARN of the Kinesis data stream that you want to register the consumer with. For more info, see Amazon Resource Names (ARNs) and Amazon Web Services Service Namespaces.
', 'RemoveTagsFromStreamInput$StreamARN' => 'The ARN of the stream.
', 'SplitShardInput$StreamARN' => 'The ARN of the stream.
', 'StartStreamEncryptionInput$StreamARN' => 'The ARN of the stream.
', 'StopStreamEncryptionInput$StreamARN' => 'The ARN of the stream.
', 'StreamDescription$StreamARN' => 'The Amazon Resource Name (ARN) for the stream being described.
', 'StreamDescriptionSummary$StreamARN' => 'The Amazon Resource Name (ARN) for the stream being described.
', 'StreamSummary$StreamARN' => 'The ARN of the stream.
', 'UpdateShardCountInput$StreamARN' => 'The ARN of the stream.
', 'UpdateShardCountOutput$StreamARN' => 'The ARN of the stream.
', 'UpdateStreamModeInput$StreamARN' => 'Specifies the ARN of the data stream whose capacity mode you want to update.
', ], ], 'StreamDescription' => [ 'base' => 'Represents the output for DescribeStream.
', 'refs' => [ 'DescribeStreamOutput$StreamDescription' => 'The current status of the stream, the stream Amazon Resource Name (ARN), an array of shard objects that comprise the stream, and whether there are more shards available.
', ], ], 'StreamDescriptionSummary' => [ 'base' => 'Represents the output for DescribeStreamSummary
', 'refs' => [ 'DescribeStreamSummaryOutput$StreamDescriptionSummary' => 'A StreamDescriptionSummary containing information about the stream.
', ], ], 'StreamMode' => [ 'base' => NULL, 'refs' => [ 'StreamModeDetails$StreamMode' => 'Specifies the capacity mode to which you want to set your data stream. Currently, in Kinesis Data Streams, you can choose between an on-demand capacity mode and a provisioned capacity mode for your data streams.
', ], ], 'StreamModeDetails' => [ 'base' => 'Specifies the capacity mode to which you want to set your data stream. Currently, in Kinesis Data Streams, you can choose between an on-demand capacity mode and a provisioned capacity mode for your data streams.
', 'refs' => [ 'CreateStreamInput$StreamModeDetails' => 'Indicates the capacity mode of the data stream. Currently, in Kinesis Data Streams, you can choose between an on-demand capacity mode and a provisioned capacity mode for your data streams.
', 'StreamDescription$StreamModeDetails' => 'Specifies the capacity mode to which you want to set your data stream. Currently, in Kinesis Data Streams, you can choose between an on-demand capacity mode and a provisioned capacity mode for your data streams.
', 'StreamDescriptionSummary$StreamModeDetails' => 'Specifies the capacity mode to which you want to set your data stream. Currently, in Kinesis Data Streams, you can choose between an on-demand ycapacity mode and a provisioned capacity mode for your data streams.
', 'StreamSummary$StreamModeDetails' => NULL, 'UpdateStreamModeInput$StreamModeDetails' => 'Specifies the capacity mode to which you want to set your data stream. Currently, in Kinesis Data Streams, you can choose between an on-demand capacity mode and a provisioned capacity mode for your data streams.
', ], ], 'StreamName' => [ 'base' => NULL, 'refs' => [ 'AddTagsToStreamInput$StreamName' => 'The name of the stream.
', 'CreateStreamInput$StreamName' => 'A name to identify the stream. The stream name is scoped to the Amazon Web Services account used by the application that creates the stream. It is also scoped by Amazon Web Services Region. That is, two streams in two different Amazon Web Services accounts can have the same name. Two streams in the same Amazon Web Services account but in two different Regions can also have the same name.
', 'DecreaseStreamRetentionPeriodInput$StreamName' => 'The name of the stream to modify.
', 'DeleteStreamInput$StreamName' => 'The name of the stream to delete.
', 'DescribeStreamInput$StreamName' => 'The name of the stream to describe.
', 'DescribeStreamSummaryInput$StreamName' => 'The name of the stream to describe.
', 'DisableEnhancedMonitoringInput$StreamName' => 'The name of the Kinesis data stream for which to disable enhanced monitoring.
', 'EnableEnhancedMonitoringInput$StreamName' => 'The name of the stream for which to enable enhanced monitoring.
', 'EnhancedMonitoringOutput$StreamName' => 'The name of the Kinesis data stream.
', 'GetShardIteratorInput$StreamName' => 'The name of the Amazon Kinesis data stream.
', 'IncreaseStreamRetentionPeriodInput$StreamName' => 'The name of the stream to modify.
', 'ListShardsInput$StreamName' => 'The name of the data stream whose shards you want to list.
You cannot specify this parameter if you specify the NextToken parameter.
The name of the stream to start the list with.
', 'ListTagsForStreamInput$StreamName' => 'The name of the stream.
', 'MergeShardsInput$StreamName' => 'The name of the stream for the merge.
', 'PutRecordInput$StreamName' => 'The name of the stream to put the data record into.
', 'PutRecordsInput$StreamName' => 'The stream name associated with the request.
', 'RemoveTagsFromStreamInput$StreamName' => 'The name of the stream.
', 'SplitShardInput$StreamName' => 'The name of the stream for the shard split.
', 'StartStreamEncryptionInput$StreamName' => 'The name of the stream for which to start encrypting records.
', 'StopStreamEncryptionInput$StreamName' => 'The name of the stream on which to stop encrypting records.
', 'StreamDescription$StreamName' => 'The name of the stream being described.
', 'StreamDescriptionSummary$StreamName' => 'The name of the stream being described.
', 'StreamNameList$member' => NULL, 'StreamSummary$StreamName' => 'The name of a stream.
', 'UpdateShardCountInput$StreamName' => 'The name of the stream.
', 'UpdateShardCountOutput$StreamName' => 'The name of the stream.
', ], ], 'StreamNameList' => [ 'base' => NULL, 'refs' => [ 'ListStreamsOutput$StreamNames' => 'The names of the streams that are associated with the Amazon Web Services account making the ListStreams request.
The current status of the stream being described. The stream status is one of the following states:
CREATING - The stream is being created. Kinesis Data Streams immediately returns and sets StreamStatus to CREATING.
DELETING - The stream is being deleted. The specified stream is in the DELETING state until Kinesis Data Streams completes the deletion.
ACTIVE - The stream exists and is ready for read and write operations or deletion. You should perform read and write operations only on an ACTIVE stream.
UPDATING - Shards in the stream are being merged or split. Read and write operations continue to work while the stream is in the UPDATING state.
The current status of the stream being described. The stream status is one of the following states:
CREATING - The stream is being created. Kinesis Data Streams immediately returns and sets StreamStatus to CREATING.
DELETING - The stream is being deleted. The specified stream is in the DELETING state until Kinesis Data Streams completes the deletion.
ACTIVE - The stream exists and is ready for read and write operations or deletion. You should perform read and write operations only on an ACTIVE stream.
UPDATING - Shards in the stream are being merged or split. Read and write operations continue to work while the stream is in the UPDATING state.
The status of the stream.
', ], ], 'StreamSummary' => [ 'base' => 'The summary of a stream.
', 'refs' => [ 'StreamSummaryList$member' => NULL, ], ], 'StreamSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListStreamsOutput$StreamSummaries' => '', ], ], 'SubscribeToShardEvent' => [ 'base' => 'After you call SubscribeToShard, Kinesis Data Streams sends events of this type over an HTTP/2 connection to your consumer.
', 'refs' => [ 'SubscribeToShardEventStream$SubscribeToShardEvent' => 'After you call SubscribeToShard, Kinesis Data Streams sends events of this type to your consumer. For an example of how to handle these events, see Enhanced Fan-Out Using the Kinesis Data Streams API.
', ], ], 'SubscribeToShardEventStream' => [ 'base' => 'This is a tagged union for all of the types of events an enhanced fan-out consumer can receive over HTTP/2 after a call to SubscribeToShard.
', 'refs' => [ 'SubscribeToShardOutput$EventStream' => 'The event stream that your consumer can use to read records from the shard.
', ], ], 'SubscribeToShardInput' => [ 'base' => NULL, 'refs' => [], ], 'SubscribeToShardOutput' => [ 'base' => NULL, 'refs' => [], ], 'Tag' => [ 'base' => 'Metadata assigned to the stream, consisting of a key-value pair.
', 'refs' => [ 'TagList$member' => NULL, ], ], 'TagKey' => [ 'base' => NULL, 'refs' => [ 'ListTagsForStreamInput$ExclusiveStartTagKey' => 'The key to use as the starting point for the list of tags. If this parameter is set, ListTagsForStream gets all tags that occur after ExclusiveStartTagKey.
A unique identifier for the tag. Maximum length: 128 characters. Valid characters: Unicode letters, digits, white space, _ . / = + - % @
', 'TagKeyList$member' => NULL, 'TagMap$key' => NULL, ], ], 'TagKeyList' => [ 'base' => NULL, 'refs' => [ 'RemoveTagsFromStreamInput$TagKeys' => 'A list of tag keys. Each corresponding tag is removed from the stream.
', ], ], 'TagList' => [ 'base' => NULL, 'refs' => [ 'ListTagsForStreamOutput$Tags' => 'A list of tags associated with StreamName, starting with the first tag after ExclusiveStartTagKey and up to the specified Limit.
A set of up to 10 key-value pairs to use to create the tags.
', ], ], 'TagValue' => [ 'base' => NULL, 'refs' => [ 'Tag$Value' => 'An optional string, typically used to describe or define the tag. Maximum length: 256 characters. Valid characters: Unicode letters, digits, white space, _ . / = + - % @
', 'TagMap$value' => NULL, ], ], 'Timestamp' => [ 'base' => NULL, 'refs' => [ 'Consumer$ConsumerCreationTimestamp' => '', 'ConsumerDescription$ConsumerCreationTimestamp' => '', 'GetShardIteratorInput$Timestamp' => 'The time stamp of the data record from which to start reading. Used with shard iterator type AT_TIMESTAMP. A time stamp is the Unix epoch date with precision in milliseconds. For example, 2016-04-04T19:58:46.480-00:00 or 1459799926.480. If a record with this exact time stamp does not exist, the iterator returned is for the next (later) record. If the time stamp is older than the current trim horizon, the iterator returned is for the oldest untrimmed data record (TRIM_HORIZON).
Specify this input parameter to distinguish data streams that have the same name. For example, if you create a data stream and then delete it, and you later create another data stream with the same name, you can use this input parameter to specify which of the two streams you want to list the shards for.
You cannot specify this parameter if you specify the NextToken parameter.
Specify this input parameter to distinguish data streams that have the same name. For example, if you create a data stream and then delete it, and you later create another data stream with the same name, you can use this input parameter to specify which of the two streams you want to list the consumers for.
You can\'t specify this parameter if you specify the NextToken parameter.
', 'Record$ApproximateArrivalTimestamp' => 'The approximate time that the record was inserted into the stream.
', 'ShardFilter$Timestamp' => 'The timestamps specified in the ShardFilter parameter. A timestamp is a Unix epoch date with precision in milliseconds. For example, 2016-04-04T19:58:46.480-00:00 or 1459799926.480. This property can only be used if FROM_TIMESTAMP or AT_TIMESTAMP shard types are specified.
The time stamp of the data record from which to start reading. To specify a time stamp, set StartingPosition to Type AT_TIMESTAMP. A time stamp is the Unix epoch date with precision in milliseconds. For example, 2016-04-04T19:58:46.480-00:00 or 1459799926.480. If a record with this exact time stamp does not exist, records will be streamed from the next (later) record. If the time stamp is older than the current trim horizon, records will be streamed from the oldest untrimmed data record (TRIM_HORIZON).
The approximate time that the stream was created.
', 'StreamDescriptionSummary$StreamCreationTimestamp' => 'The approximate time that the stream was created.
', 'StreamSummary$StreamCreationTimestamp' => 'The timestamp at which the stream was created.
', ], ], 'UpdateShardCountInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateShardCountOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateStreamModeInput' => [ 'base' => NULL, 'refs' => [], ], 'ValidationException' => [ 'base' => 'Specifies that you tried to invoke this API for a data stream with the on-demand capacity mode. This API is only supported for data streams with the provisioned capacity mode.
', 'refs' => [], ], ],]; diff --git a/src/data/kinesis/2013-12-02/endpoint-rule-set-1.json b/src/data/kinesis/2013-12-02/endpoint-rule-set-1.json index 6c9d972b60..33343536fd 100644 --- a/src/data/kinesis/2013-12-02/endpoint-rule-set-1.json +++ b/src/data/kinesis/2013-12-02/endpoint-rule-set-1.json @@ -41,6 +41,11 @@ "required": false, "documentation": "The ARN of the Kinesis consumer", "type": "String" + }, + "ResourceARN": { + "required": false, + "documentation": "The ARN of the Kinesis resource", + "type": "String" } }, "rules": [ @@ -50,7 +55,499 @@ "fn": "isSet", "argv": [ { - "ref": "StreamARN" + "ref": "StreamARN" + } + ] + }, + { + "fn": "not", + "argv": [ + { + "fn": "isSet", + "argv": [ + { + "ref": "Endpoint" + } + ] + } + ] + }, + { + "fn": "isSet", + "argv": [ + { + "ref": "Region" + } + ] + }, + { + "fn": "aws.partition", + "argv": [ + { + "ref": "Region" + } + ], + "assign": "PartitionResult" + }, + { + "fn": "not", + "argv": [ + { + "fn": "stringEquals", + "argv": [ + { + "fn": "getAttr", + "argv": [ + { + "ref": "PartitionResult" + }, + "name" + ] + }, + "aws-iso" + ] + } + ] + }, + { + "fn": "not", + "argv": [ + { + "fn": "stringEquals", + "argv": [ + { + "fn": "getAttr", + "argv": [ + { + "ref": "PartitionResult" + }, + "name" + ] + }, + "aws-iso-b" + ] + } + ] + } + ], + "rules": [ + { + "conditions": [ + { + "fn": "aws.parseArn", + "argv": [ + { + "ref": "StreamARN" + } + ], + "assign": "arn" + } + ], + "rules": [ + { + "conditions": [ + { + "fn": "isValidHostLabel", + "argv": [ + { + "fn": "getAttr", + "argv": [ + { + "ref": "arn" + }, + "accountId" + ] + }, + false + ] + } + ], + "rules": [ + { + "conditions": [ + { + "fn": "isValidHostLabel", + "argv": [ + { + "fn": "getAttr", + "argv": [ + { + "ref": "arn" + }, + "region" + ] + }, + false + ] + } + ], + "rules": [ + { + "conditions": [ + { + "fn": "stringEquals", + "argv": [ + { + "fn": "getAttr", + "argv": [ + { + "ref": "arn" + }, + "service" + ] + }, + "kinesis" + ] + } + ], + "rules": [ + { + "conditions": [ + { + "fn": "getAttr", + "argv": [ + { + "ref": "arn" + }, + "resourceId[0]" + ], + "assign": "arnType" + }, + { + "fn": "not", + "argv": [ + { + "fn": "stringEquals", + "argv": [ + { + "ref": "arnType" + }, + "" + ] + } + ] + } + ], + "rules": [ + { + "conditions": [ + { + "fn": "stringEquals", + "argv": [ + { + "ref": "arnType" + }, + "stream" + ] + } + ], + "rules": [ + { + "conditions": [ + { + "fn": "stringEquals", + "argv": [ + { + "fn": "getAttr", + "argv": [ + { + "ref": "PartitionResult" + }, + "name" + ] + }, + "{arn#partition}" + ] + } + ], + "rules": [ + { + "conditions": [ + { + "fn": "isSet", + "argv": [ + { + "ref": "OperationType" + } + ] + } + ], + "rules": [ + { + "conditions": [ + { + "fn": "booleanEquals", + "argv": [ + { + "ref": "UseFIPS" + }, + true + ] + }, + { + "fn": "booleanEquals", + "argv": [ + { + "ref": "UseDualStack" + }, + true + ] + } + ], + "rules": [ + { + "conditions": [ + { + "fn": "booleanEquals", + "argv": [ + { + "fn": "getAttr", + "argv": [ + { + "ref": "PartitionResult" + }, + "supportsFIPS" + ] + }, + true + ] + } + ], + "rules": [ + { + "conditions": [ + { + "fn": "booleanEquals", + "argv": [ + { + "fn": "getAttr", + "argv": [ + { + "ref": "PartitionResult" + }, + "supportsDualStack" + ] + }, + true + ] + } + ], + "rules": [ + { + "conditions": [], + "endpoint": { + "url": "https://{arn#accountId}.{OperationType}-kinesis-fips.{Region}.{PartitionResult#dualStackDnsSuffix}", + "properties": {}, + "headers": {} + }, + "type": "endpoint" + } + ], + "type": "tree" + }, + { + "conditions": [], + "error": "DualStack is enabled, but this partition does not support DualStack.", + "type": "error" + } + ], + "type": "tree" + }, + { + "conditions": [], + "error": "FIPS is enabled, but this partition does not support FIPS.", + "type": "error" + } + ], + "type": "tree" + }, + { + "conditions": [ + { + "fn": "booleanEquals", + "argv": [ + { + "ref": "UseFIPS" + }, + true + ] + } + ], + "rules": [ + { + "conditions": [ + { + "fn": "booleanEquals", + "argv": [ + { + "fn": "getAttr", + "argv": [ + { + "ref": "PartitionResult" + }, + "supportsFIPS" + ] + }, + true + ] + } + ], + "rules": [ + { + "conditions": [], + "endpoint": { + "url": "https://{arn#accountId}.{OperationType}-kinesis-fips.{Region}.{PartitionResult#dnsSuffix}", + "properties": {}, + "headers": {} + }, + "type": "endpoint" + } + ], + "type": "tree" + }, + { + "conditions": [], + "error": "FIPS is enabled but this partition does not support FIPS", + "type": "error" + } + ], + "type": "tree" + }, + { + "conditions": [ + { + "fn": "booleanEquals", + "argv": [ + { + "ref": "UseDualStack" + }, + true + ] + } + ], + "rules": [ + { + "conditions": [ + { + "fn": "booleanEquals", + "argv": [ + { + "fn": "getAttr", + "argv": [ + { + "ref": "PartitionResult" + }, + "supportsDualStack" + ] + }, + true + ] + } + ], + "rules": [ + { + "conditions": [], + "endpoint": { + "url": "https://{arn#accountId}.{OperationType}-kinesis.{Region}.{PartitionResult#dualStackDnsSuffix}", + "properties": {}, + "headers": {} + }, + "type": "endpoint" + } + ], + "type": "tree" + }, + { + "conditions": [], + "error": "DualStack is enabled but this partition does not support DualStack", + "type": "error" + } + ], + "type": "tree" + }, + { + "conditions": [], + "endpoint": { + "url": "https://{arn#accountId}.{OperationType}-kinesis.{Region}.{PartitionResult#dnsSuffix}", + "properties": {}, + "headers": {} + }, + "type": "endpoint" + } + ], + "type": "tree" + }, + { + "conditions": [], + "error": "Operation Type is not set. Please contact service team for resolution.", + "type": "error" + } + ], + "type": "tree" + }, + { + "conditions": [], + "error": "Partition: {arn#partition} from ARN doesn't match with partition name: {PartitionResult#name}.", + "type": "error" + } + ], + "type": "tree" + }, + { + "conditions": [], + "error": "Invalid ARN: Kinesis ARNs don't support `{arnType}` arn types.", + "type": "error" + } + ], + "type": "tree" + }, + { + "conditions": [], + "error": "Invalid ARN: No ARN type specified", + "type": "error" + } + ], + "type": "tree" + }, + { + "conditions": [], + "error": "Invalid ARN: The ARN was not for the Kinesis service, found: {arn#service}.", + "type": "error" + } + ], + "type": "tree" + }, + { + "conditions": [], + "error": "Invalid ARN: Invalid region.", + "type": "error" + } + ], + "type": "tree" + }, + { + "conditions": [], + "error": "Invalid ARN: Invalid account id.", + "type": "error" + } + ], + "type": "tree" + }, + { + "conditions": [], + "error": "Invalid ARN: Failed to parse ARN.", + "type": "error" + } + ], + "type": "tree" + }, + { + "conditions": [ + { + "fn": "isSet", + "argv": [ + { + "ref": "ConsumerARN" } ] }, @@ -125,7 +622,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -133,13 +629,12 @@ "fn": "aws.parseArn", "argv": [ { - "ref": "StreamARN" + "ref": "ConsumerARN" } ], "assign": "arn" } ], - "type": "tree", "rules": [ { "conditions": [ @@ -159,7 +654,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -179,7 +673,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -199,7 +692,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -228,7 +720,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -242,7 +733,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -262,7 +752,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -275,7 +764,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -298,7 +786,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -318,7 +805,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -338,7 +824,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [], @@ -349,21 +834,24 @@ }, "type": "endpoint" } - ] + ], + "type": "tree" }, { "conditions": [], "error": "DualStack is enabled, but this partition does not support DualStack.", "type": "error" } - ] + ], + "type": "tree" }, { "conditions": [], "error": "FIPS is enabled, but this partition does not support FIPS.", "type": "error" } - ] + ], + "type": "tree" }, { "conditions": [ @@ -377,7 +865,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -397,7 +884,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [], @@ -408,14 +894,16 @@ }, "type": "endpoint" } - ] + ], + "type": "tree" }, { "conditions": [], "error": "FIPS is enabled but this partition does not support FIPS", "type": "error" } - ] + ], + "type": "tree" }, { "conditions": [ @@ -429,7 +917,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -449,7 +936,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [], @@ -460,14 +946,16 @@ }, "type": "endpoint" } - ] + ], + "type": "tree" }, { "conditions": [], "error": "DualStack is enabled but this partition does not support DualStack", "type": "error" } - ] + ], + "type": "tree" }, { "conditions": [], @@ -478,63 +966,72 @@ }, "type": "endpoint" } - ] + ], + "type": "tree" }, { "conditions": [], "error": "Operation Type is not set. Please contact service team for resolution.", "type": "error" } - ] + ], + "type": "tree" }, { "conditions": [], "error": "Partition: {arn#partition} from ARN doesn't match with partition name: {PartitionResult#name}.", "type": "error" } - ] + ], + "type": "tree" }, { "conditions": [], "error": "Invalid ARN: Kinesis ARNs don't support `{arnType}` arn types.", "type": "error" } - ] + ], + "type": "tree" }, { "conditions": [], "error": "Invalid ARN: No ARN type specified", "type": "error" } - ] + ], + "type": "tree" }, { "conditions": [], "error": "Invalid ARN: The ARN was not for the Kinesis service, found: {arn#service}.", "type": "error" } - ] + ], + "type": "tree" }, { "conditions": [], "error": "Invalid ARN: Invalid region.", "type": "error" } - ] + ], + "type": "tree" }, { "conditions": [], "error": "Invalid ARN: Invalid account id.", "type": "error" } - ] + ], + "type": "tree" }, { "conditions": [], "error": "Invalid ARN: Failed to parse ARN.", "type": "error" } - ] + ], + "type": "tree" }, { "conditions": [ @@ -542,7 +1039,7 @@ "fn": "isSet", "argv": [ { - "ref": "ConsumerARN" + "ref": "ResourceARN" } ] }, @@ -617,7 +1114,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -625,13 +1121,12 @@ "fn": "aws.parseArn", "argv": [ { - "ref": "ConsumerARN" + "ref": "ResourceARN" } ], "assign": "arn" } ], - "type": "tree", "rules": [ { "conditions": [ @@ -651,7 +1146,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -671,7 +1165,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -691,7 +1184,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -720,7 +1212,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -734,7 +1225,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -754,7 +1244,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -767,7 +1256,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -790,7 +1278,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -810,7 +1297,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -830,7 +1316,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [], @@ -841,21 +1326,24 @@ }, "type": "endpoint" } - ] + ], + "type": "tree" }, { "conditions": [], "error": "DualStack is enabled, but this partition does not support DualStack.", "type": "error" } - ] + ], + "type": "tree" }, { "conditions": [], "error": "FIPS is enabled, but this partition does not support FIPS.", "type": "error" } - ] + ], + "type": "tree" }, { "conditions": [ @@ -869,7 +1357,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -889,7 +1376,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [], @@ -900,14 +1386,16 @@ }, "type": "endpoint" } - ] + ], + "type": "tree" }, { "conditions": [], "error": "FIPS is enabled but this partition does not support FIPS", "type": "error" } - ] + ], + "type": "tree" }, { "conditions": [ @@ -921,7 +1409,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -941,7 +1428,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [], @@ -952,14 +1438,16 @@ }, "type": "endpoint" } - ] + ], + "type": "tree" }, { "conditions": [], "error": "DualStack is enabled but this partition does not support DualStack", "type": "error" } - ] + ], + "type": "tree" }, { "conditions": [], @@ -970,63 +1458,72 @@ }, "type": "endpoint" } - ] + ], + "type": "tree" }, { "conditions": [], "error": "Operation Type is not set. Please contact service team for resolution.", "type": "error" } - ] + ], + "type": "tree" }, { "conditions": [], "error": "Partition: {arn#partition} from ARN doesn't match with partition name: {PartitionResult#name}.", "type": "error" } - ] + ], + "type": "tree" }, { "conditions": [], "error": "Invalid ARN: Kinesis ARNs don't support `{arnType}` arn types.", "type": "error" } - ] + ], + "type": "tree" }, { "conditions": [], "error": "Invalid ARN: No ARN type specified", "type": "error" } - ] + ], + "type": "tree" }, { "conditions": [], "error": "Invalid ARN: The ARN was not for the Kinesis service, found: {arn#service}.", "type": "error" } - ] + ], + "type": "tree" }, { "conditions": [], "error": "Invalid ARN: Invalid region.", "type": "error" } - ] + ], + "type": "tree" }, { "conditions": [], "error": "Invalid ARN: Invalid account id.", "type": "error" } - ] + ], + "type": "tree" }, { "conditions": [], "error": "Invalid ARN: Failed to parse ARN.", "type": "error" } - ] + ], + "type": "tree" }, { "conditions": [ @@ -1039,7 +1536,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -1082,7 +1578,8 @@ }, "type": "endpoint" } - ] + ], + "type": "tree" }, { "conditions": [ @@ -1095,7 +1592,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -1109,7 +1605,6 @@ "assign": "PartitionResult" } ], - "type": "tree", "rules": [ { "conditions": [ @@ -1132,7 +1627,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -1167,7 +1661,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [], @@ -1178,14 +1671,16 @@ }, "type": "endpoint" } - ] + ], + "type": "tree" }, { "conditions": [], "error": "FIPS and DualStack are enabled, but this partition does not support one or both", "type": "error" } - ] + ], + "type": "tree" }, { "conditions": [ @@ -1199,14 +1694,12 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ { "fn": "booleanEquals", "argv": [ - true, { "fn": "getAttr", "argv": [ @@ -1215,18 +1708,17 @@ }, "supportsFIPS" ] - } + }, + true ] } ], - "type": "tree", "rules": [ { "conditions": [ { "fn": "stringEquals", "argv": [ - "aws-us-gov", { "fn": "getAttr", "argv": [ @@ -1235,7 +1727,8 @@ }, "name" ] - } + }, + "aws-us-gov" ] } ], @@ -1255,14 +1748,16 @@ }, "type": "endpoint" } - ] + ], + "type": "tree" }, { "conditions": [], "error": "FIPS is enabled but this partition does not support FIPS", "type": "error" } - ] + ], + "type": "tree" }, { "conditions": [ @@ -1276,7 +1771,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [ @@ -1296,7 +1790,6 @@ ] } ], - "type": "tree", "rules": [ { "conditions": [], @@ -1307,14 +1800,16 @@ }, "type": "endpoint" } - ] + ], + "type": "tree" }, { "conditions": [], "error": "DualStack is enabled but this partition does not support DualStack", "type": "error" } - ] + ], + "type": "tree" }, { "conditions": [], @@ -1325,9 +1820,11 @@ }, "type": "endpoint" } - ] + ], + "type": "tree" } - ] + ], + "type": "tree" }, { "conditions": [], diff --git a/src/data/kinesis/2013-12-02/endpoint-rule-set-1.json.php b/src/data/kinesis/2013-12-02/endpoint-rule-set-1.json.php index 94011de481..bd3c7b6596 100644 --- a/src/data/kinesis/2013-12-02/endpoint-rule-set-1.json.php +++ b/src/data/kinesis/2013-12-02/endpoint-rule-set-1.json.php @@ -1,3 +1,3 @@ '1.0', 'parameters' => [ 'Region' => [ 'builtIn' => 'AWS::Region', 'required' => false, 'documentation' => 'The AWS region used to dispatch the request.', 'type' => 'String', ], 'UseDualStack' => [ 'builtIn' => 'AWS::UseDualStack', 'required' => true, 'default' => false, 'documentation' => 'When true, use the dual-stack endpoint. If the configured endpoint does not support dual-stack, dispatching the request MAY return an error.', 'type' => 'Boolean', ], 'UseFIPS' => [ 'builtIn' => 'AWS::UseFIPS', 'required' => true, 'default' => false, 'documentation' => 'When true, send this request to the FIPS-compliant regional endpoint. If the configured endpoint does not have a FIPS compliant endpoint, dispatching the request will return an error.', 'type' => 'Boolean', ], 'Endpoint' => [ 'builtIn' => 'SDK::Endpoint', 'required' => false, 'documentation' => 'Override the endpoint used to send this request', 'type' => 'String', ], 'StreamARN' => [ 'required' => false, 'documentation' => 'The ARN of the Kinesis stream', 'type' => 'String', ], 'OperationType' => [ 'required' => false, 'documentation' => 'Internal parameter to distinguish between Control/Data plane API and accordingly generate control/data plane endpoint', 'type' => 'String', ], 'ConsumerARN' => [ 'required' => false, 'documentation' => 'The ARN of the Kinesis consumer', 'type' => 'String', ], ], 'rules' => [ [ 'conditions' => [ [ 'fn' => 'isSet', 'argv' => [ [ 'ref' => 'StreamARN', ], ], ], [ 'fn' => 'not', 'argv' => [ [ 'fn' => 'isSet', 'argv' => [ [ 'ref' => 'Endpoint', ], ], ], ], ], [ 'fn' => 'isSet', 'argv' => [ [ 'ref' => 'Region', ], ], ], [ 'fn' => 'aws.partition', 'argv' => [ [ 'ref' => 'Region', ], ], 'assign' => 'PartitionResult', ], [ 'fn' => 'not', 'argv' => [ [ 'fn' => 'stringEquals', 'argv' => [ [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'PartitionResult', ], 'name', ], ], 'aws-iso', ], ], ], ], [ 'fn' => 'not', 'argv' => [ [ 'fn' => 'stringEquals', 'argv' => [ [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'PartitionResult', ], 'name', ], ], 'aws-iso-b', ], ], ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [ [ 'fn' => 'aws.parseArn', 'argv' => [ [ 'ref' => 'StreamARN', ], ], 'assign' => 'arn', ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [ [ 'fn' => 'isValidHostLabel', 'argv' => [ [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'arn', ], 'accountId', ], ], false, ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [ [ 'fn' => 'isValidHostLabel', 'argv' => [ [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'arn', ], 'region', ], ], false, ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [ [ 'fn' => 'stringEquals', 'argv' => [ [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'arn', ], 'service', ], ], 'kinesis', ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [ [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'arn', ], 'resourceId[0]', ], 'assign' => 'arnType', ], [ 'fn' => 'not', 'argv' => [ [ 'fn' => 'stringEquals', 'argv' => [ [ 'ref' => 'arnType', ], '', ], ], ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [ [ 'fn' => 'stringEquals', 'argv' => [ [ 'ref' => 'arnType', ], 'stream', ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [ [ 'fn' => 'stringEquals', 'argv' => [ [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'PartitionResult', ], 'name', ], ], '{arn#partition}', ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [ [ 'fn' => 'isSet', 'argv' => [ [ 'ref' => 'OperationType', ], ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [ [ 'fn' => 'booleanEquals', 'argv' => [ [ 'ref' => 'UseFIPS', ], true, ], ], [ 'fn' => 'booleanEquals', 'argv' => [ [ 'ref' => 'UseDualStack', ], true, ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [ [ 'fn' => 'booleanEquals', 'argv' => [ [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'PartitionResult', ], 'supportsFIPS', ], ], true, ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [ [ 'fn' => 'booleanEquals', 'argv' => [ [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'PartitionResult', ], 'supportsDualStack', ], ], true, ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [], 'endpoint' => [ 'url' => 'https://{arn#accountId}.{OperationType}-kinesis-fips.{Region}.{PartitionResult#dualStackDnsSuffix}', 'properties' => [], 'headers' => [], ], 'type' => 'endpoint', ], ], ], [ 'conditions' => [], 'error' => 'DualStack is enabled, but this partition does not support DualStack.', 'type' => 'error', ], ], ], [ 'conditions' => [], 'error' => 'FIPS is enabled, but this partition does not support FIPS.', 'type' => 'error', ], ], ], [ 'conditions' => [ [ 'fn' => 'booleanEquals', 'argv' => [ [ 'ref' => 'UseFIPS', ], true, ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [ [ 'fn' => 'booleanEquals', 'argv' => [ [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'PartitionResult', ], 'supportsFIPS', ], ], true, ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [], 'endpoint' => [ 'url' => 'https://{arn#accountId}.{OperationType}-kinesis-fips.{Region}.{PartitionResult#dnsSuffix}', 'properties' => [], 'headers' => [], ], 'type' => 'endpoint', ], ], ], [ 'conditions' => [], 'error' => 'FIPS is enabled but this partition does not support FIPS', 'type' => 'error', ], ], ], [ 'conditions' => [ [ 'fn' => 'booleanEquals', 'argv' => [ [ 'ref' => 'UseDualStack', ], true, ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [ [ 'fn' => 'booleanEquals', 'argv' => [ [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'PartitionResult', ], 'supportsDualStack', ], ], true, ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [], 'endpoint' => [ 'url' => 'https://{arn#accountId}.{OperationType}-kinesis.{Region}.{PartitionResult#dualStackDnsSuffix}', 'properties' => [], 'headers' => [], ], 'type' => 'endpoint', ], ], ], [ 'conditions' => [], 'error' => 'DualStack is enabled but this partition does not support DualStack', 'type' => 'error', ], ], ], [ 'conditions' => [], 'endpoint' => [ 'url' => 'https://{arn#accountId}.{OperationType}-kinesis.{Region}.{PartitionResult#dnsSuffix}', 'properties' => [], 'headers' => [], ], 'type' => 'endpoint', ], ], ], [ 'conditions' => [], 'error' => 'Operation Type is not set. Please contact service team for resolution.', 'type' => 'error', ], ], ], [ 'conditions' => [], 'error' => 'Partition: {arn#partition} from ARN doesn\'t match with partition name: {PartitionResult#name}.', 'type' => 'error', ], ], ], [ 'conditions' => [], 'error' => 'Invalid ARN: Kinesis ARNs don\'t support `{arnType}` arn types.', 'type' => 'error', ], ], ], [ 'conditions' => [], 'error' => 'Invalid ARN: No ARN type specified', 'type' => 'error', ], ], ], [ 'conditions' => [], 'error' => 'Invalid ARN: The ARN was not for the Kinesis service, found: {arn#service}.', 'type' => 'error', ], ], ], [ 'conditions' => [], 'error' => 'Invalid ARN: Invalid region.', 'type' => 'error', ], ], ], [ 'conditions' => [], 'error' => 'Invalid ARN: Invalid account id.', 'type' => 'error', ], ], ], [ 'conditions' => [], 'error' => 'Invalid ARN: Failed to parse ARN.', 'type' => 'error', ], ], ], [ 'conditions' => [ [ 'fn' => 'isSet', 'argv' => [ [ 'ref' => 'ConsumerARN', ], ], ], [ 'fn' => 'not', 'argv' => [ [ 'fn' => 'isSet', 'argv' => [ [ 'ref' => 'Endpoint', ], ], ], ], ], [ 'fn' => 'isSet', 'argv' => [ [ 'ref' => 'Region', ], ], ], [ 'fn' => 'aws.partition', 'argv' => [ [ 'ref' => 'Region', ], ], 'assign' => 'PartitionResult', ], [ 'fn' => 'not', 'argv' => [ [ 'fn' => 'stringEquals', 'argv' => [ [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'PartitionResult', ], 'name', ], ], 'aws-iso', ], ], ], ], [ 'fn' => 'not', 'argv' => [ [ 'fn' => 'stringEquals', 'argv' => [ [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'PartitionResult', ], 'name', ], ], 'aws-iso-b', ], ], ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [ [ 'fn' => 'aws.parseArn', 'argv' => [ [ 'ref' => 'ConsumerARN', ], ], 'assign' => 'arn', ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [ [ 'fn' => 'isValidHostLabel', 'argv' => [ [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'arn', ], 'accountId', ], ], false, ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [ [ 'fn' => 'isValidHostLabel', 'argv' => [ [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'arn', ], 'region', ], ], false, ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [ [ 'fn' => 'stringEquals', 'argv' => [ [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'arn', ], 'service', ], ], 'kinesis', ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [ [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'arn', ], 'resourceId[0]', ], 'assign' => 'arnType', ], [ 'fn' => 'not', 'argv' => [ [ 'fn' => 'stringEquals', 'argv' => [ [ 'ref' => 'arnType', ], '', ], ], ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [ [ 'fn' => 'stringEquals', 'argv' => [ [ 'ref' => 'arnType', ], 'stream', ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [ [ 'fn' => 'stringEquals', 'argv' => [ [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'PartitionResult', ], 'name', ], ], '{arn#partition}', ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [ [ 'fn' => 'isSet', 'argv' => [ [ 'ref' => 'OperationType', ], ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [ [ 'fn' => 'booleanEquals', 'argv' => [ [ 'ref' => 'UseFIPS', ], true, ], ], [ 'fn' => 'booleanEquals', 'argv' => [ [ 'ref' => 'UseDualStack', ], true, ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [ [ 'fn' => 'booleanEquals', 'argv' => [ [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'PartitionResult', ], 'supportsFIPS', ], ], true, ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [ [ 'fn' => 'booleanEquals', 'argv' => [ [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'PartitionResult', ], 'supportsDualStack', ], ], true, ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [], 'endpoint' => [ 'url' => 'https://{arn#accountId}.{OperationType}-kinesis-fips.{Region}.{PartitionResult#dualStackDnsSuffix}', 'properties' => [], 'headers' => [], ], 'type' => 'endpoint', ], ], ], [ 'conditions' => [], 'error' => 'DualStack is enabled, but this partition does not support DualStack.', 'type' => 'error', ], ], ], [ 'conditions' => [], 'error' => 'FIPS is enabled, but this partition does not support FIPS.', 'type' => 'error', ], ], ], [ 'conditions' => [ [ 'fn' => 'booleanEquals', 'argv' => [ [ 'ref' => 'UseFIPS', ], true, ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [ [ 'fn' => 'booleanEquals', 'argv' => [ [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'PartitionResult', ], 'supportsFIPS', ], ], true, ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [], 'endpoint' => [ 'url' => 'https://{arn#accountId}.{OperationType}-kinesis-fips.{Region}.{PartitionResult#dnsSuffix}', 'properties' => [], 'headers' => [], ], 'type' => 'endpoint', ], ], ], [ 'conditions' => [], 'error' => 'FIPS is enabled but this partition does not support FIPS', 'type' => 'error', ], ], ], [ 'conditions' => [ [ 'fn' => 'booleanEquals', 'argv' => [ [ 'ref' => 'UseDualStack', ], true, ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [ [ 'fn' => 'booleanEquals', 'argv' => [ [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'PartitionResult', ], 'supportsDualStack', ], ], true, ], ], ], 'type' => 'tree', 'rules' => [ [ 'conditions' => [], 'endpoint' => [ 'url' => 'https://{arn#accountId}.{OperationType}-kinesis.{Region}.{PartitionResult#dualStackDnsSuffix}', 'properties' => [], 'headers' => [], ], 'type' => 'endpoint', ], ], ], [ 'conditions' => [], 'error' => 'DualStack is enabled but this partition does not support DualStack', 'type' => 'error', ], ], ], [ 'conditions' => [], 'endpoint' => [ 'url' => 'https://{arn#accountId}.{OperationType}-kinesis.{Region}.{PartitionResult#dnsSuffix}', 'properties' => [], 'headers' => [], ], 'type' => 'endpoint', ], ], ], [ 'conditions' => [], 'error' => 'Operation Type is not set. 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partition does not support FIPS.', 'type' => 'error', ], ], 'type' => 'tree', ], [ 'conditions' => [ [ 'fn' => 'booleanEquals', 'argv' => [ [ 'ref' => 'UseFIPS', ], true, ], ], ], 'rules' => [ [ 'conditions' => [ [ 'fn' => 'booleanEquals', 'argv' => [ [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'PartitionResult', ], 'supportsFIPS', ], ], true, ], ], ], 'rules' => [ [ 'conditions' => [], 'endpoint' => [ 'url' => 'https://{arn#accountId}.{OperationType}-kinesis-fips.{Region}.{PartitionResult#dnsSuffix}', 'properties' => [], 'headers' => [], ], 'type' => 'endpoint', ], ], 'type' => 'tree', ], [ 'conditions' => [], 'error' => 'FIPS is enabled but this partition does not support FIPS', 'type' => 'error', ], ], 'type' => 'tree', ], [ 'conditions' => [ [ 'fn' => 'booleanEquals', 'argv' => [ [ 'ref' => 'UseDualStack', ], true, ], ], ], 'rules' => [ [ 'conditions' => [ [ 'fn' => 'booleanEquals', 'argv' => [ [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'PartitionResult', ], 'supportsDualStack', ], ], true, ], ], ], 'rules' => [ [ 'conditions' => [], 'endpoint' => [ 'url' => 'https://{arn#accountId}.{OperationType}-kinesis.{Region}.{PartitionResult#dualStackDnsSuffix}', 'properties' => [], 'headers' => [], ], 'type' => 'endpoint', ], ], 'type' => 'tree', ], [ 'conditions' => [], 'error' => 'DualStack is enabled but this partition does not support DualStack', 'type' => 'error', ], ], 'type' => 'tree', ], [ 'conditions' => [], 'endpoint' => [ 'url' => 'https://{arn#accountId}.{OperationType}-kinesis.{Region}.{PartitionResult#dnsSuffix}', 'properties' => [], 'headers' => [], ], 'type' => 'endpoint', ], ], 'type' => 'tree', ], [ 'conditions' => [], 'error' => 'Operation Type is not set. Please contact service team for resolution.', 'type' => 'error', ], ], 'type' => 'tree', ], [ 'conditions' => [], 'error' => 'Partition: {arn#partition} from ARN doesn\'t match with partition name: {PartitionResult#name}.', 'type' => 'error', ], ], 'type' => 'tree', ], [ 'conditions' => [], 'error' => 'Invalid ARN: Kinesis ARNs don\'t support `{arnType}` arn types.', 'type' => 'error', ], ], 'type' => 'tree', ], [ 'conditions' => [], 'error' => 'Invalid ARN: No ARN type specified', 'type' => 'error', ], ], 'type' => 'tree', ], [ 'conditions' => [], 'error' => 'Invalid ARN: The ARN was not for the Kinesis service, found: {arn#service}.', 'type' => 'error', ], ], 'type' => 'tree', ], [ 'conditions' => [], 'error' => 'Invalid ARN: Invalid region.', 'type' => 'error', ], ], 'type' => 'tree', ], [ 'conditions' => [], 'error' => 'Invalid ARN: Invalid account id.', 'type' => 'error', ], ], 'type' => 'tree', ], [ 'conditions' => [], 'error' => 'Invalid ARN: Failed to parse ARN.', 'type' => 'error', ], ], 'type' => 'tree', ], [ 'conditions' => [ [ 'fn' => 'isSet', 'argv' => [ [ 'ref' => 'Endpoint', ], ], ], ], 'rules' => [ [ 'conditions' => [ [ 'fn' => 'booleanEquals', 'argv' => [ [ 'ref' => 'UseFIPS', ], true, ], ], ], 'error' => 'Invalid Configuration: FIPS and custom endpoint are not supported', 'type' => 'error', ], [ 'conditions' => [ [ 'fn' => 'booleanEquals', 'argv' => [ [ 'ref' => 'UseDualStack', ], true, ], ], ], 'error' => 'Invalid Configuration: Dualstack and custom endpoint are not supported', 'type' => 'error', ], [ 'conditions' => [], 'endpoint' => [ 'url' => [ 'ref' => 'Endpoint', ], 'properties' => [], 'headers' => [], ], 'type' => 'endpoint', ], ], 'type' => 'tree', ], [ 'conditions' => [ [ 'fn' => 'isSet', 'argv' => [ [ 'ref' => 'Region', ], ], ], ], 'rules' => [ [ 'conditions' => [ [ 'fn' => 'aws.partition', 'argv' => [ [ 'ref' => 'Region', ], ], 'assign' => 'PartitionResult', ], ], 'rules' => [ [ 'conditions' => [ [ 'fn' => 'booleanEquals', 'argv' => [ [ 'ref' => 'UseFIPS', ], true, ], ], [ 'fn' => 'booleanEquals', 'argv' => [ [ 'ref' => 'UseDualStack', ], true, ], ], ], 'rules' => [ [ 'conditions' => [ [ 'fn' => 'booleanEquals', 'argv' => [ true, [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'PartitionResult', ], 'supportsFIPS', ], ], ], ], [ 'fn' => 'booleanEquals', 'argv' => [ true, [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'PartitionResult', ], 'supportsDualStack', ], ], ], ], ], 'rules' => [ [ 'conditions' => [], 'endpoint' => [ 'url' => 'https://kinesis-fips.{Region}.{PartitionResult#dualStackDnsSuffix}', 'properties' => [], 'headers' => [], ], 'type' => 'endpoint', ], ], 'type' => 'tree', ], [ 'conditions' => [], 'error' => 'FIPS and DualStack are enabled, but this partition does not support one or both', 'type' => 'error', ], ], 'type' => 'tree', ], [ 'conditions' => [ [ 'fn' => 'booleanEquals', 'argv' => [ [ 'ref' => 'UseFIPS', ], true, ], ], ], 'rules' => [ [ 'conditions' => [ [ 'fn' => 'booleanEquals', 'argv' => [ [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'PartitionResult', ], 'supportsFIPS', ], ], true, ], ], ], 'rules' => [ [ 'conditions' => [ [ 'fn' => 'stringEquals', 'argv' => [ [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'PartitionResult', ], 'name', ], ], 'aws-us-gov', ], ], ], 'endpoint' => [ 'url' => 'https://kinesis.{Region}.amazonaws.com', 'properties' => [], 'headers' => [], ], 'type' => 'endpoint', ], [ 'conditions' => [], 'endpoint' => [ 'url' => 'https://kinesis-fips.{Region}.{PartitionResult#dnsSuffix}', 'properties' => [], 'headers' => [], ], 'type' => 'endpoint', ], ], 'type' => 'tree', ], [ 'conditions' => [], 'error' => 'FIPS is enabled but this partition does not support FIPS', 'type' => 'error', ], ], 'type' => 'tree', ], [ 'conditions' => [ [ 'fn' => 'booleanEquals', 'argv' => [ [ 'ref' => 'UseDualStack', ], true, ], ], ], 'rules' => [ [ 'conditions' => [ [ 'fn' => 'booleanEquals', 'argv' => [ true, [ 'fn' => 'getAttr', 'argv' => [ [ 'ref' => 'PartitionResult', ], 'supportsDualStack', ], ], ], ], ], 'rules' => [ [ 'conditions' => [], 'endpoint' => [ 'url' => 'https://kinesis.{Region}.{PartitionResult#dualStackDnsSuffix}', 'properties' => [], 'headers' => [], ], 'type' => 'endpoint', ], ], 'type' => 'tree', ], [ 'conditions' => [], 'error' => 'DualStack is enabled but this partition does not support DualStack', 'type' => 'error', ], ], 'type' => 'tree', ], [ 'conditions' => [], 'endpoint' => [ 'url' => 'https://kinesis.{Region}.{PartitionResult#dnsSuffix}', 'properties' => [], 'headers' => [], ], 'type' => 'endpoint', ], ], 'type' => 'tree', ], ], 'type' => 'tree', ], [ 'conditions' => [], 'error' => 'Invalid Configuration: Missing Region', 'type' => 'error', ], ],]; diff --git a/src/data/kinesis/2013-12-02/endpoint-tests-1.json b/src/data/kinesis/2013-12-02/endpoint-tests-1.json index 03682af4a7..f68c22f6de 100644 --- a/src/data/kinesis/2013-12-02/endpoint-tests-1.json +++ b/src/data/kinesis/2013-12-02/endpoint-tests-1.json @@ -1455,6 +1455,746 @@ "StreamARN": "arn:aws:kinesis:us-east-1:123:stream/foobar", "ConsumerARN": "arn:aws:kinesis:us-east-1:123456789123:stream/foobar/consumer/test-consumer:1525898737" } + }, + { + "documentation": "ResourceARN test: Invalid ARN: Failed to parse ARN.", + "expect": { + "error": "Invalid ARN: Failed to parse ARN." + }, + "params": { + "Region": "us-east-1", + "UseFIPS": false, + "UseDualStack": false, + "ResourceARN": "arn" + } + }, + { + "documentation": "ResourceARN as StreamARN test: Invalid ARN: partition missing from ARN.", + "expect": { + "error": "Invalid ARN: Failed to parse ARN." + }, + "params": { + "Region": "us-east-1", + "UseFIPS": false, + "UseDualStack": false, + "ResourceARN": "arn::kinesis:us-west-2:123456789012:stream/testStream" + } + }, + { + "documentation": "ResourceARN as StreamARN test: Invalid ARN: partitions mismatch.", + "expect": { + "error": "Partition: aws from ARN doesn't match with partition name: aws-us-gov." + }, + "params": { + "Region": "us-gov-west-1", + "UseFIPS": false, + "UseDualStack": false, + "ResourceARN": "arn:aws:kinesis:us-west-2:123456789012:stream/testStream" + } + }, + { + "documentation": "ResourceARN as StreamARN test: Invalid ARN: Not Kinesis", + "expect": { + "error": "Invalid ARN: The ARN was not for the Kinesis service, found: s3." + }, + "params": { + "Region": "us-east-1", + "UseFIPS": false, + "UseDualStack": false, + "ResourceARN": "arn:aws:s3:us-west-2:123456789012:stream/testStream" + } + }, + { + "documentation": "ResourceARN as StreamARN test: Invalid ARN: Region is missing in ARN", + "expect": { + "error": "Invalid ARN: Invalid region." + }, + "params": { + "Region": "us-east-1", + "UseFIPS": false, + "UseDualStack": false, + "ResourceARN": "arn:aws:kinesis::123456789012:stream/testStream" + } + }, + { + "documentation": "ResourceARN as StreamARN test: Invalid ARN: Region is empty string in ARN", + "expect": { + "error": "Invalid ARN: Invalid region." + }, + "params": { + "Region": "us-east-1", + "UseFIPS": false, + "UseDualStack": false, + "ResourceARN": "arn:aws:kinesis: :123456789012:stream/testStream" + } + }, + { + "documentation": "ResourceARN as StreamARN test: Invalid ARN: Invalid account id", + "expect": { + "error": "Invalid ARN: Invalid account id." + }, + "params": { + "Region": "us-east-1", + "UseFIPS": false, + "UseDualStack": false, + "ResourceARN": "arn:aws:kinesis:us-east-1::stream/testStream", + "OperationType": "control" + } + }, + { + "documentation": "ResourceARN as StreamARN test: Invalid ARN: Invalid account id", + "expect": { + "error": "Invalid ARN: Invalid account id." + }, + "params": { + "Region": "us-east-1", + "UseFIPS": false, + "UseDualStack": false, + "ResourceARN": "arn:aws:kinesis:us-east-1: :stream/testStream", + "OperationType": "control" + } + }, + { + "documentation": "ResourceARN as StreamARN test: Invalid ARN: Kinesis ARNs only support stream arn types", + "expect": { + "error": "Invalid ARN: Kinesis ARNs don't support `accesspoint` arn types." + }, + "params": { + "Region": "us-east-1", + "UseFIPS": false, + "UseDualStack": false, + "ResourceARN": "arn:aws:kinesis:us-east-1:123:accesspoint/testStream" + } + }, + { + "documentation": "ResourceARN as StreamARN test: Dual Stack not supported region.", + "expect": { + "error": "FIPS and DualStack are enabled, but this partition does not support one or both" + }, + "params": { + "Region": "us-iso-west-1", + "UseFIPS": true, + "UseDualStack": true, + "ResourceARN": "arn:aws-iso:kinesis:us-iso-west-1:123456789012:stream/testStream", + "OperationType": "control" + } + }, + { + "documentation": "ResourceARN as StreamARN test: OperationType not set", + "expect": { + "error": "Operation Type is not set. Please contact service team for resolution." + }, + "params": { + "Region": "us-east-1", + "UseFIPS": false, + "UseDualStack": false, + "ResourceARN": "arn:aws:kinesis:us-east-1:123456789012:stream/testStream" + } + }, + { + "documentation": "ResourceARN as StreamARN test: Custom Endpoint is specified", + "expect": { + "endpoint": { + "url": "https://example.com" + } + }, + "params": { + "Region": "us-east-1", + "UseFIPS": false, + "UseDualStack": false, + "OperationType": "control", + "ResourceARN": "arn:aws:kinesis:us-east-1:123:stream/test-stream", + "Endpoint": "https://example.com" + } + }, + { + "documentation": "ResourceARN as StreamARN test: Account endpoint targeting control operation type", + "expect": { + "endpoint": { + "url": "https://123.control-kinesis.us-east-1.amazonaws.com" + } + }, + "params": { + "Region": "us-east-1", + "UseFIPS": false, + "UseDualStack": false, + "OperationType": "control", + "ResourceARN": "arn:aws:kinesis:us-east-1:123:stream/test-stream" + } + }, + { + "documentation": "ResourceARN as StreamARN test: Account endpoint targeting data operation type", + "expect": { + "endpoint": { + "url": "https://123.data-kinesis.us-east-1.amazonaws.com" + } + }, + "params": { + "Region": "us-east-1", + "UseFIPS": false, + "UseDualStack": false, + "OperationType": "data", + "ResourceARN": "arn:aws:kinesis:us-east-1:123:stream/test-stream" + } + }, + { + "documentation": "ResourceARN as StreamARN test: Account endpoint with fips targeting data operation type", + "expect": { + "endpoint": { + "url": "https://123.data-kinesis-fips.us-east-1.amazonaws.com" + } + }, + "params": { + "Region": "us-east-1", + "UseFIPS": true, + "UseDualStack": false, + "OperationType": "data", + "ResourceARN": "arn:aws:kinesis:us-east-1:123:stream/test-stream" + } + }, + { + "documentation": "ResourceARN as StreamARN test: Account endpoint with fips targeting control operation type", + "expect": { + "endpoint": { + "url": "https://123.control-kinesis-fips.us-east-1.amazonaws.com" + } + }, + "params": { + "Region": "us-east-1", + "UseFIPS": true, + "UseDualStack": false, + "OperationType": "control", + "ResourceARN": "arn:aws:kinesis:us-east-1:123:stream/test-stream" + } + }, + { + "documentation": "ResourceARN as StreamARN test: Account endpoint with Dual Stack and FIPS enabled", + "expect": { + "endpoint": { + "url": "https://123.control-kinesis-fips.us-east-1.api.aws" + } + }, + "params": { + "Region": "us-east-1", + "UseFIPS": true, + "UseDualStack": true, + "OperationType": "control", + "ResourceARN": "arn:aws:kinesis:us-east-1:123:stream/test-stream" + } + }, + { + "documentation": "ResourceARN as StreamARN test: Account endpoint with Dual Stack enabled", + "expect": { + "endpoint": { + "url": "https://123.data-kinesis.us-west-1.api.aws" + } + }, + "params": { + "Region": "us-west-1", + "UseFIPS": false, + "UseDualStack": true, + "OperationType": "data", + "ResourceARN": "arn:aws:kinesis:us-west-1:123:stream/test-stream" + } + }, + { + "documentation": "ResourceARN as StreamARN test: Account endpoint with FIPS and DualStack disabled", + "expect": { + "endpoint": { + "url": "https://123.control-kinesis.us-west-1.amazonaws.com" + } + }, + "params": { + "Region": "us-west-1", + "UseFIPS": false, + "UseDualStack": false, + "OperationType": "control", + "ResourceARN": "arn:aws:kinesis:us-west-1:123:stream/test-stream" + } + }, + { + "documentation": "ResourceARN as StreamARN test: RegionMismatch: client region should be used for endpoint region", + "expect": { + "endpoint": { + "url": "https://123.data-kinesis.us-east-1.amazonaws.com" + } + }, + "params": { + "Region": "us-east-1", + "UseFIPS": false, + "UseDualStack": false, + "OperationType": "data", + "ResourceARN": "arn:aws:kinesis:us-west-1:123:stream/testStream" + } + }, + { + "documentation": "ResourceARN as StreamARN test: Account endpoint with FIPS enabled", + "expect": { + "endpoint": { + "url": "https://123.data-kinesis-fips.cn-northwest-1.amazonaws.com.cn" + } + }, + "params": { + "Region": "cn-northwest-1", + "UseFIPS": true, + "UseDualStack": false, + "OperationType": "data", + "ResourceARN": "arn:aws-cn:kinesis:cn-northwest-1:123:stream/test-stream" + } + }, + { + "documentation": "ResourceARN as StreamARN test: Account endpoint with FIPS and DualStack enabled for cn regions.", + "expect": { + "endpoint": { + "url": "https://123.data-kinesis-fips.cn-northwest-1.api.amazonwebservices.com.cn" + } + }, + "params": { + "Region": "cn-northwest-1", + "UseFIPS": true, + "UseDualStack": true, + "OperationType": "data", + "ResourceARN": "arn:aws-cn:kinesis:cn-northwest-1:123:stream/test-stream" + } + }, + { + "documentation": "ResourceARN as StreamARN test: Account endpoint targeting control operation type in ADC regions", + "expect": { + "endpoint": { + "url": "https://kinesis.us-iso-east-1.c2s.ic.gov" + } + }, + "params": { + "Region": "us-iso-east-1", + "UseFIPS": false, + "UseDualStack": false, + "OperationType": "control", + "ResourceARN": "arn:aws-iso:kinesis:us-iso-east-1:123:stream/test-stream" + } + }, + { + "documentation": "ResourceARN as StreamARN test: Account endpoint targeting control operation type in ADC regions", + "expect": { + "endpoint": { + "url": "https://kinesis.us-iso-west-1.c2s.ic.gov" + } + }, + "params": { + "Region": "us-iso-west-1", + "UseFIPS": false, + "UseDualStack": false, + "OperationType": "control", + "ResourceARN": "arn:aws-iso:kinesis:us-iso-west-1:123:stream/test-stream" + } + }, + { + "documentation": "ResourceARN as StreamARN test: Account endpoint targeting data operation type in ADC regions", + "expect": { + "endpoint": { + "url": "https://kinesis.us-isob-east-1.sc2s.sgov.gov" + } + }, + "params": { + "Region": "us-isob-east-1", + "UseFIPS": false, + "UseDualStack": false, + "OperationType": "data", + "ResourceARN": "arn:aws-iso-b:kinesis:us-isob-east-1:123:stream/test-stream" + } + }, + { + "documentation": "ResourceARN as StreamARN test: Account endpoint with fips targeting control operation type in ADC regions", + "expect": { + "endpoint": { + "url": "https://kinesis-fips.us-iso-east-1.c2s.ic.gov" + } + }, + "params": { + "Region": "us-iso-east-1", + "UseFIPS": true, + "UseDualStack": false, + "OperationType": "control", + "ResourceARN": "arn:aws-iso:kinesis:us-iso-east-1:123:stream/test-stream" + } + }, + { + "documentation": "ResourceARN as StreamARN test: Account endpoint with fips targeting data operation type in ADC regions", + "expect": { + "endpoint": { + "url": "https://kinesis-fips.us-isob-east-1.sc2s.sgov.gov" + } + }, + "params": { + "Region": "us-isob-east-1", + "UseFIPS": true, + "UseDualStack": false, + "OperationType": "data", + "ResourceARN": "arn:aws-iso-b:kinesis:us-isob-east-1:123:stream/test-stream" + } + }, + { + "documentation": "ResourceARN as ConsumerARN test: Invalid ARN: partition missing from ARN.", + "expect": { + "error": "Invalid ARN: Failed to parse ARN." + }, + "params": { + "Region": "us-east-1", + "UseFIPS": false, + "UseDualStack": false, + "ResourceARN": "arn::kinesis:us-west-2:123456789012:stream/testStream/consumer/test-consumer:1525898737" + } + }, + { + "documentation": "ResourceARN as ConsumerARN test: Invalid ARN: partitions mismatch.", + "expect": { + "error": "Partition: aws from ARN doesn't match with partition name: aws-us-gov." + }, + "params": { + "Region": "us-gov-west-1", + "UseFIPS": false, + "UseDualStack": false, + "ResourceARN": "arn:aws:kinesis:us-west-2:123456789012:stream/testStream/consumer/test-consumer:1525898737" + } + }, + { + "documentation": "ResourceARN as ConsumerARN test: Invalid ARN: Not Kinesis", + "expect": { + "error": "Invalid ARN: The ARN was not for the Kinesis service, found: s3." + }, + "params": { + "Region": "us-east-1", + "UseFIPS": false, + "UseDualStack": false, + "ResourceARN": "arn:aws:s3:us-west-2:123456789012:stream/testStream/consumer/test-consumer:1525898737" + } + }, + { + "documentation": "ResourceARN as ConsumerARN test: Invalid ARN: Region is missing in ARN", + "expect": { + "error": "Invalid ARN: Invalid region." + }, + "params": { + "Region": "us-east-1", + "UseFIPS": false, + "UseDualStack": false, + "ResourceARN": "arn:aws:kinesis::123456789012:stream/testStream/consumer/test-consumer:1525898737" + } + }, + { + "documentation": "ResourceARN as ConsumerARN test: Invalid ARN: Region is empty string in ARN", + "expect": { + "error": "Invalid ARN: Invalid region." + }, + "params": { + "Region": "us-east-1", + "UseFIPS": false, + "UseDualStack": false, + "ResourceARN": "arn:aws:kinesis: :123456789012:stream/testStream/consumer/test-consumer:1525898737" + } + }, + { + "documentation": "ResourceARN as ConsumerARN test: Invalid ARN: Invalid account id", + "expect": { + "error": "Invalid ARN: Invalid account id." + }, + "params": { + "Region": "us-east-1", + "UseFIPS": false, + "UseDualStack": false, + "ResourceARN": "arn:aws:kinesis:us-east-1::stream/testStream/consumer/test-consumer:1525898737", + "OperationType": "control" + } + }, + { + "documentation": "ResourceARN as ConsumerARN test: Invalid ARN: Invalid account id", + "expect": { + "error": "Invalid ARN: Invalid account id." + }, + "params": { + "Region": "us-east-1", + "UseFIPS": false, + "UseDualStack": false, + "ResourceARN": "arn:aws:kinesis:us-east-1: :stream/testStream/consumer/test-consumer:1525898737", + "OperationType": "control" + } + }, + { + "documentation": "ResourceARN as ConsumerARN test: Invalid ARN: Kinesis ARNs only support stream arn/consumer arn types", + "expect": { + "error": "Invalid ARN: Kinesis ARNs don't support `accesspoint` arn types." + }, + "params": { + "Region": "us-east-1", + "UseFIPS": false, + "UseDualStack": false, + "ResourceARN": "arn:aws:kinesis:us-east-1:123:accesspoint/testStream/consumer/test-consumer:1525898737" + } + }, + { + "documentation": "ResourceARN as ConsumerARN test: Dual Stack not supported region.", + "expect": { + "error": "FIPS and DualStack are enabled, but this partition does not support one or both" + }, + "params": { + "Region": "us-iso-west-1", + "UseFIPS": true, + "UseDualStack": true, + "ResourceARN": "arn:aws-iso:kinesis:us-iso-west-1:123456789012:stream/testStream/consumer/test-consumer:1525898737", + "OperationType": "control" + } + }, + { + "documentation": "ResourceARN as ConsumerARN test: OperationType not set", + "expect": { + "error": "Operation Type is not set. Please contact service team for resolution." + }, + "params": { + "Region": "us-east-1", + "UseFIPS": false, + "UseDualStack": false, + "ResourceARN": "arn:aws:kinesis:us-east-1:123456789012:stream/testStream/consumer/test-consumer:1525898737" + } + }, + { + "documentation": "ResourceARN as ConsumerARN test: Custom Endpoint is specified", + "expect": { + "endpoint": { + "url": "https://example.com" + } + }, + "params": { + "Region": "us-east-1", + "UseFIPS": false, + "UseDualStack": false, + "OperationType": "control", + "ResourceARN": "arn:aws:kinesis:us-east-1:123:stream/test-stream/consumer/test-consumer:1525898737", + "Endpoint": "https://example.com" + } + }, + { + "documentation": "ResourceARN as ConsumerARN test: Account endpoint targeting control operation type", + "expect": { + "endpoint": { + "url": "https://123.control-kinesis.us-east-1.amazonaws.com" + } + }, + "params": { + "Region": "us-east-1", + "UseFIPS": false, + "UseDualStack": false, + "OperationType": "control", + "ResourceARN": "arn:aws:kinesis:us-east-1:123:stream/test-stream/consumer/test-consumer:1525898737" + } + }, + { + "documentation": "ResourceARN as ConsumerARN test: Account endpoint targeting data operation type", + "expect": { + "endpoint": { + "url": "https://123.data-kinesis.us-east-1.amazonaws.com" + } + }, + "params": { + "Region": "us-east-1", + "UseFIPS": false, + "UseDualStack": false, + "OperationType": "data", + "ResourceARN": "arn:aws:kinesis:us-east-1:123:stream/test-stream/consumer/test-consumer:1525898737" + } + }, + { + "documentation": "ResourceARN as ConsumerARN test: Account endpoint with fips targeting data operation type", + "expect": { + "endpoint": { + "url": "https://123.data-kinesis-fips.us-east-1.amazonaws.com" + } + }, + "params": { + "Region": "us-east-1", + "UseFIPS": true, + "UseDualStack": false, + "OperationType": "data", + "ResourceARN": "arn:aws:kinesis:us-east-1:123:stream/test-stream/consumer/test-consumer:1525898737" + } + }, + { + "documentation": "ResourceARN as ConsumerARN test: Account endpoint with fips targeting control operation type", + "expect": { + "endpoint": { + "url": "https://123.control-kinesis-fips.us-east-1.amazonaws.com" + } + }, + "params": { + "Region": "us-east-1", + "UseFIPS": true, + "UseDualStack": false, + "OperationType": "control", + "ResourceARN": "arn:aws:kinesis:us-east-1:123:stream/test-stream/consumer/test-consumer:1525898737" + } + }, + { + "documentation": "ResourceARN as ConsumerARN test: Account endpoint with Dual Stack and FIPS enabled", + "expect": { + "endpoint": { + "url": "https://123.control-kinesis-fips.us-east-1.api.aws" + } + }, + "params": { + "Region": "us-east-1", + "UseFIPS": true, + "UseDualStack": true, + "OperationType": "control", + "ResourceARN": "arn:aws:kinesis:us-east-1:123:stream/test-stream/consumer/test-consumer:1525898737" + } + }, + { + "documentation": "ResourceARN as ConsumerARN test: Account endpoint with Dual Stack enabled", + "expect": { + "endpoint": { + "url": "https://123.data-kinesis.us-west-1.api.aws" + } + }, + "params": { + "Region": "us-west-1", + "UseFIPS": false, + "UseDualStack": true, + "OperationType": "data", + "ResourceARN": "arn:aws:kinesis:us-west-1:123:stream/test-stream/consumer/test-consumer:1525898737" + } + }, + { + "documentation": "ResourceARN as ConsumerARN test: Account endpoint with FIPS and DualStack disabled", + "expect": { + "endpoint": { + "url": "https://123.control-kinesis.us-west-1.amazonaws.com" + } + }, + "params": { + "Region": "us-west-1", + "UseFIPS": false, + "UseDualStack": false, + "OperationType": "control", + "ResourceARN": "arn:aws:kinesis:us-west-1:123:stream/test-stream/consumer/test-consumer:1525898737" + } + }, + { + "documentation": "ResourceARN as ConsumerARN test: RegionMismatch: client region should be used for endpoint region", + "expect": { + "endpoint": { + "url": "https://123.data-kinesis.us-east-1.amazonaws.com" + } + }, + "params": { + "Region": "us-east-1", + "UseFIPS": false, + "UseDualStack": false, + "OperationType": "data", + "ResourceARN": "arn:aws:kinesis:us-west-1:123:stream/testStream/consumer/test-consumer:1525898737" + } + }, + { + "documentation": "ResourceARN as ConsumerARN test: Account endpoint with FIPS enabled", + "expect": { + "endpoint": { + "url": "https://123.data-kinesis-fips.cn-northwest-1.amazonaws.com.cn" + } + }, + "params": { + "Region": "cn-northwest-1", + "UseFIPS": true, + "UseDualStack": false, + "OperationType": "data", + "ResourceARN": "arn:aws-cn:kinesis:cn-northwest-1:123:stream/test-stream/consumer/test-consumer:1525898737" + } + }, + { + "documentation": "ResourceARN as ConsumerARN test: Account endpoint with FIPS and DualStack enabled for cn regions.", + "expect": { + "endpoint": { + "url": "https://123.data-kinesis-fips.cn-northwest-1.api.amazonwebservices.com.cn" + } + }, + "params": { + "Region": "cn-northwest-1", + "UseFIPS": true, + "UseDualStack": true, + "OperationType": "data", + "ResourceARN": "arn:aws-cn:kinesis:cn-northwest-1:123:stream/test-stream/consumer/test-consumer:1525898737" + } + }, + { + "documentation": "ResourceARN as ConsumerARN test: Account endpoint targeting control operation type in ADC regions", + "expect": { + "endpoint": { + "url": "https://kinesis.us-iso-east-1.c2s.ic.gov" + } + }, + "params": { + "Region": "us-iso-east-1", + "UseFIPS": false, + "UseDualStack": false, + "OperationType": "control", + "ResourceARN": "arn:aws-iso:kinesis:us-iso-east-1:123:stream/test-stream/consumer/test-consumer:1525898737" + } + }, + { + "documentation": "ResourceARN as ConsumerARN test: Account endpoint targeting control operation type in ADC regions", + "expect": { + "endpoint": { + "url": "https://kinesis.us-iso-west-1.c2s.ic.gov" + } + }, + "params": { + "Region": "us-iso-west-1", + "UseFIPS": false, + "UseDualStack": false, + "OperationType": "control", + "ResourceARN": "arn:aws-iso:kinesis:us-iso-west-1:123:stream/test-stream/consumer/test-consumer:1525898737" + } + }, + { + "documentation": "ResourceARN as ConsumerARN test: Account endpoint targeting data operation type in ADC regions", + "expect": { + "endpoint": { + "url": "https://kinesis.us-isob-east-1.sc2s.sgov.gov" + } + }, + "params": { + "Region": "us-isob-east-1", + "UseFIPS": false, + "UseDualStack": false, + "OperationType": "data", + "ResourceARN": "arn:aws-iso-b:kinesis:us-isob-east-1:123:stream/test-stream/consumer/test-consumer:1525898737" + } + }, + { + "documentation": "ResourceARN as ConsumerARN test: Account endpoint with fips targeting control operation type in ADC regions", + "expect": { + "endpoint": { + "url": "https://kinesis-fips.us-iso-east-1.c2s.ic.gov" + } + }, + "params": { + "Region": "us-iso-east-1", + "UseFIPS": true, + "UseDualStack": false, + "OperationType": "control", + "ResourceARN": "arn:aws-iso:kinesis:us-iso-east-1:123:stream/test-stream/consumer/test-consumer:1525898737" + } + }, + { + "documentation": "ResourceARN as ConsumerARN test: Account endpoint with fips targeting data operation type in ADC regions", + "expect": { + "endpoint": { + "url": "https://kinesis-fips.us-isob-east-1.sc2s.sgov.gov" + } + }, + "params": { + "Region": "us-isob-east-1", + "UseFIPS": true, + "UseDualStack": false, + "OperationType": "data", + "ResourceARN": "arn:aws-iso-b:kinesis:us-isob-east-1:123:stream/test-stream/consumer/test-consumer:1525898737" + } } ], "version": "1.0" diff --git a/src/data/kinesis/2013-12-02/endpoint-tests-1.json.php b/src/data/kinesis/2013-12-02/endpoint-tests-1.json.php index f7cd009add..6c5b0f7200 100644 --- a/src/data/kinesis/2013-12-02/endpoint-tests-1.json.php +++ b/src/data/kinesis/2013-12-02/endpoint-tests-1.json.php @@ -1,3 +1,3 @@ [ [ 'documentation' => 'For region af-south-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.af-south-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'af-south-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region ap-east-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.ap-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'ap-east-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region ap-northeast-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.ap-northeast-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'ap-northeast-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region ap-northeast-2 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.ap-northeast-2.amazonaws.com', ], ], 'params' => [ 'Region' => 'ap-northeast-2', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region ap-northeast-3 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.ap-northeast-3.amazonaws.com', ], ], 'params' => [ 'Region' => 'ap-northeast-3', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region ap-south-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.ap-south-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'ap-south-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region ap-southeast-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.ap-southeast-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'ap-southeast-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region ap-southeast-2 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.ap-southeast-2.amazonaws.com', ], ], 'params' => [ 'Region' => 'ap-southeast-2', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region ap-southeast-3 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.ap-southeast-3.amazonaws.com', ], ], 'params' => [ 'Region' => 'ap-southeast-3', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region ca-central-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.ca-central-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'ca-central-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region eu-central-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.eu-central-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'eu-central-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region eu-north-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.eu-north-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'eu-north-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region eu-south-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.eu-south-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'eu-south-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region eu-west-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.eu-west-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'eu-west-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region eu-west-2 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.eu-west-2.amazonaws.com', ], ], 'params' => [ 'Region' => 'eu-west-2', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region eu-west-3 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.eu-west-3.amazonaws.com', ], ], 'params' => [ 'Region' => 'eu-west-3', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region me-south-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.me-south-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'me-south-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region sa-east-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.sa-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'sa-east-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-east-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-east-1 with FIPS enabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => true, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-east-2 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-east-2.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-2', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-east-2 with FIPS enabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-east-2.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-2', 'UseFIPS' => true, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-west-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-west-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-west-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-west-1 with FIPS enabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-west-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-west-1', 'UseFIPS' => true, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-west-2 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-west-2.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-west-2', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-west-2 with FIPS enabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-west-2.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-west-2', 'UseFIPS' => true, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-east-1 with FIPS enabled and DualStack enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-east-1.api.aws', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => true, 'UseDualStack' => true, ], ], [ 'documentation' => 'For region us-east-1 with FIPS disabled and DualStack enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-east-1.api.aws', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => true, ], ], [ 'documentation' => 'For region cn-north-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.cn-north-1.amazonaws.com.cn', ], ], 'params' => [ 'Region' => 'cn-north-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region cn-northwest-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.cn-northwest-1.amazonaws.com.cn', ], ], 'params' => [ 'Region' => 'cn-northwest-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region cn-north-1 with FIPS enabled and DualStack enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.cn-north-1.api.amazonwebservices.com.cn', ], ], 'params' => [ 'Region' => 'cn-north-1', 'UseFIPS' => true, 'UseDualStack' => true, ], ], [ 'documentation' => 'For region cn-north-1 with FIPS enabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.cn-north-1.amazonaws.com.cn', ], ], 'params' => [ 'Region' => 'cn-north-1', 'UseFIPS' => true, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region cn-north-1 with FIPS disabled and DualStack enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.cn-north-1.api.amazonwebservices.com.cn', ], ], 'params' => [ 'Region' => 'cn-north-1', 'UseFIPS' => false, 'UseDualStack' => true, ], ], [ 'documentation' => 'For region us-gov-east-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-gov-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-gov-east-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-gov-east-1 with FIPS enabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-gov-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-gov-east-1', 'UseFIPS' => true, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-gov-west-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-gov-west-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-gov-west-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-gov-west-1 with FIPS enabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-gov-west-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-gov-west-1', 'UseFIPS' => true, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-gov-east-1 with FIPS enabled and DualStack enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-gov-east-1.api.aws', ], ], 'params' => [ 'Region' => 'us-gov-east-1', 'UseFIPS' => true, 'UseDualStack' => true, ], ], [ 'documentation' => 'For region us-gov-east-1 with FIPS disabled and DualStack enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-gov-east-1.api.aws', ], ], 'params' => [ 'Region' => 'us-gov-east-1', 'UseFIPS' => false, 'UseDualStack' => true, ], ], [ 'documentation' => 'For region us-iso-east-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-iso-east-1.c2s.ic.gov', ], ], 'params' => [ 'Region' => 'us-iso-east-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-iso-west-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-iso-west-1.c2s.ic.gov', ], ], 'params' => [ 'Region' => 'us-iso-west-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-iso-east-1 with FIPS enabled and DualStack enabled', 'expect' => [ 'error' => 'FIPS and DualStack are enabled, but this partition does not support one or both', ], 'params' => [ 'Region' => 'us-iso-east-1', 'UseFIPS' => true, 'UseDualStack' => true, ], ], [ 'documentation' => 'For region us-iso-east-1 with FIPS enabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-iso-east-1.c2s.ic.gov', ], ], 'params' => [ 'Region' => 'us-iso-east-1', 'UseFIPS' => true, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-iso-east-1 with FIPS disabled and DualStack enabled', 'expect' => [ 'error' => 'DualStack is enabled but this partition does not support DualStack', ], 'params' => [ 'Region' => 'us-iso-east-1', 'UseFIPS' => false, 'UseDualStack' => true, ], ], [ 'documentation' => 'For region us-isob-east-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-isob-east-1.sc2s.sgov.gov', ], ], 'params' => [ 'Region' => 'us-isob-east-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-isob-east-1 with FIPS enabled and DualStack enabled', 'expect' => [ 'error' => 'FIPS and DualStack are enabled, but this partition does not support one or both', ], 'params' => [ 'Region' => 'us-isob-east-1', 'UseFIPS' => true, 'UseDualStack' => true, ], ], [ 'documentation' => 'For region us-isob-east-1 with FIPS enabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-isob-east-1.sc2s.sgov.gov', ], ], 'params' => [ 'Region' => 'us-isob-east-1', 'UseFIPS' => true, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-isob-east-1 with FIPS disabled and DualStack enabled', 'expect' => [ 'error' => 'DualStack is enabled but this partition does not support DualStack', ], 'params' => [ 'Region' => 'us-isob-east-1', 'UseFIPS' => false, 'UseDualStack' => true, ], ], [ 'documentation' => 'For custom endpoint with region set and fips disabled and dualstack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://example.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'Endpoint' => 'https://example.com', ], ], [ 'documentation' => 'For custom endpoint with region not set and fips disabled and dualstack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://example.com', ], ], 'params' => [ 'UseFIPS' => false, 'UseDualStack' => false, 'Endpoint' => 'https://example.com', ], ], [ 'documentation' => 'For custom endpoint with fips enabled and dualstack disabled', 'expect' => [ 'error' => 'Invalid Configuration: FIPS and custom endpoint are not supported', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => true, 'UseDualStack' => false, 'Endpoint' => 'https://example.com', ], ], [ 'documentation' => 'For custom endpoint with fips disabled and dualstack enabled', 'expect' => [ 'error' => 'Invalid Configuration: Dualstack and custom endpoint are not supported', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => true, 'Endpoint' => 'https://example.com', ], ], [ 'documentation' => 'Missing region', 'expect' => [ 'error' => 'Invalid Configuration: Missing Region', ], ], [ 'documentation' => 'Invalid ARN: Failed to parse ARN.', 'expect' => [ 'error' => 'Invalid ARN: Failed to parse ARN.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'StreamARN' => 'arn', ], ], [ 'documentation' => 'Invalid ARN: partition missing from ARN.', 'expect' => [ 'error' => 'Invalid ARN: Failed to parse ARN.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'StreamARN' => 'arn::kinesis:us-west-2:123456789012:stream/testStream', ], ], [ 'documentation' => 'Invalid ARN: partitions mismatch.', 'expect' => [ 'error' => 'Partition: aws from ARN doesn\'t match with partition name: aws-us-gov.', ], 'params' => [ 'Region' => 'us-gov-west-1', 'UseFIPS' => false, 'UseDualStack' => false, 'StreamARN' => 'arn:aws:kinesis:us-west-2:123456789012:stream/testStream', ], ], [ 'documentation' => 'Invalid ARN: Not Kinesis', 'expect' => [ 'error' => 'Invalid ARN: The ARN was not for the Kinesis service, found: s3.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'StreamARN' => 'arn:aws:s3:us-west-2:123456789012:stream/testStream', ], ], [ 'documentation' => 'Invalid ARN: Region is missing in ARN', 'expect' => [ 'error' => 'Invalid ARN: Invalid region.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'StreamARN' => 'arn:aws:kinesis::123456789012:stream/testStream', ], ], [ 'documentation' => 'Invalid ARN: Region is empty string in ARN', 'expect' => [ 'error' => 'Invalid ARN: Invalid region.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'StreamARN' => 'arn:aws:kinesis: :123456789012:stream/testStream', ], ], [ 'documentation' => 'Invalid ARN: Invalid account id', 'expect' => [ 'error' => 'Invalid ARN: Invalid account id.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'StreamARN' => 'arn:aws:kinesis:us-east-1::stream/testStream', 'OperationType' => 'control', ], ], [ 'documentation' => 'Invalid ARN: Invalid account id', 'expect' => [ 'error' => 'Invalid ARN: Invalid account id.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'StreamARN' => 'arn:aws:kinesis:us-east-1: :stream/testStream', 'OperationType' => 'control', ], ], [ 'documentation' => 'Invalid ARN: Kinesis ARNs only support stream arn types', 'expect' => [ 'error' => 'Invalid ARN: Kinesis ARNs don\'t support `accesspoint` arn types.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'StreamARN' => 'arn:aws:kinesis:us-east-1:123:accesspoint/testStream', ], ], [ 'documentation' => 'Dual Stack not supported region.', 'expect' => [ 'error' => 'FIPS and DualStack are enabled, but this partition does not support one or both', ], 'params' => [ 'Region' => 'us-iso-west-1', 'UseFIPS' => true, 'UseDualStack' => true, 'StreamARN' => 'arn:aws-iso:kinesis:us-iso-west-1:123456789012:stream/testStream', 'OperationType' => 'control', ], ], [ 'documentation' => 'OperationType not set', 'expect' => [ 'error' => 'Operation Type is not set. Please contact service team for resolution.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'StreamARN' => 'arn:aws:kinesis:us-east-1:123456789012:stream/testStream', ], ], [ 'documentation' => 'Custom Endpoint is specified', 'expect' => [ 'endpoint' => [ 'url' => 'https://example.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'StreamARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream', 'Endpoint' => 'https://example.com', ], ], [ 'documentation' => 'Account endpoint targeting control operation type', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.control-kinesis.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'StreamARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream', ], ], [ 'documentation' => 'Account endpoint targeting data operation type', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'data', 'StreamARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream', ], ], [ 'documentation' => 'Account endpoint with fips targeting data operation type', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis-fips.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'data', 'StreamARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream', ], ], [ 'documentation' => 'Account endpoint with fips targeting control operation type', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.control-kinesis-fips.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'control', 'StreamARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream', ], ], [ 'documentation' => 'Account endpoint with Dual Stack and FIPS enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.control-kinesis-fips.us-east-1.api.aws', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => true, 'UseDualStack' => true, 'OperationType' => 'control', 'StreamARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream', ], ], [ 'documentation' => 'Account endpoint with Dual Stack enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis.us-west-1.api.aws', ], ], 'params' => [ 'Region' => 'us-west-1', 'UseFIPS' => false, 'UseDualStack' => true, 'OperationType' => 'data', 'StreamARN' => 'arn:aws:kinesis:us-west-1:123:stream/test-stream', ], ], [ 'documentation' => 'Account endpoint with FIPS and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.control-kinesis.us-west-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-west-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'StreamARN' => 'arn:aws:kinesis:us-west-1:123:stream/test-stream', ], ], [ 'documentation' => 'RegionMismatch: client region should be used for endpoint region', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'data', 'StreamARN' => 'arn:aws:kinesis:us-west-1:123:stream/testStream', ], ], [ 'documentation' => 'Account endpoint with FIPS enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis-fips.cn-northwest-1.amazonaws.com.cn', ], ], 'params' => [ 'Region' => 'cn-northwest-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'data', 'StreamARN' => 'arn:aws-cn:kinesis:cn-northwest-1:123:stream/test-stream', ], ], [ 'documentation' => 'Account endpoint with FIPS and DualStack enabled for cn regions.', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis-fips.cn-northwest-1.api.amazonwebservices.com.cn', ], ], 'params' => [ 'Region' => 'cn-northwest-1', 'UseFIPS' => true, 'UseDualStack' => true, 'OperationType' => 'data', 'StreamARN' => 'arn:aws-cn:kinesis:cn-northwest-1:123:stream/test-stream', ], ], [ 'documentation' => 'Account endpoint targeting control operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-iso-east-1.c2s.ic.gov', ], ], 'params' => [ 'Region' => 'us-iso-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'StreamARN' => 'arn:aws-iso:kinesis:us-iso-east-1:123:stream/test-stream', ], ], [ 'documentation' => 'Account endpoint targeting control operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-iso-west-1.c2s.ic.gov', ], ], 'params' => [ 'Region' => 'us-iso-west-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'StreamARN' => 'arn:aws-iso:kinesis:us-iso-west-1:123:stream/test-stream', ], ], [ 'documentation' => 'Account endpoint targeting data operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-isob-east-1.sc2s.sgov.gov', ], ], 'params' => [ 'Region' => 'us-isob-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'data', 'StreamARN' => 'arn:aws-iso-b:kinesis:us-isob-east-1:123:stream/test-stream', ], ], [ 'documentation' => 'Account endpoint with fips targeting control operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-iso-east-1.c2s.ic.gov', ], ], 'params' => [ 'Region' => 'us-iso-east-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'control', 'StreamARN' => 'arn:aws-iso:kinesis:us-iso-east-1:123:stream/test-stream', ], ], [ 'documentation' => 'Account endpoint with fips targeting data operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-isob-east-1.sc2s.sgov.gov', ], ], 'params' => [ 'Region' => 'us-isob-east-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'data', 'StreamARN' => 'arn:aws-iso-b:kinesis:us-isob-east-1:123:stream/test-stream', ], ], [ 'documentation' => 'Invalid ConsumerARN: Failed to parse ARN.', 'expect' => [ 'error' => 'Invalid ARN: Failed to parse ARN.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ConsumerARN' => 'arn', ], ], [ 'documentation' => 'Invalid ConsumerARN: partition missing from ARN.', 'expect' => [ 'error' => 'Invalid ARN: Failed to parse ARN.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ConsumerARN' => 'arn::kinesis:us-west-2:123456789012:stream/testStream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Invalid ARN: partitions mismatch.', 'expect' => [ 'error' => 'Partition: aws from ARN doesn\'t match with partition name: aws-us-gov.', ], 'params' => [ 'Region' => 'us-gov-west-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ConsumerARN' => 'arn:aws:kinesis:us-west-2:123456789012:stream/testStream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Invalid ARN: Not Kinesis', 'expect' => [ 'error' => 'Invalid ARN: The ARN was not for the Kinesis service, found: s3.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ConsumerARN' => 'arn:aws:s3:us-west-2:123456789012:stream/testStream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Invalid ARN: Region is missing in ARN', 'expect' => [ 'error' => 'Invalid ARN: Invalid region.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ConsumerARN' => 'arn:aws:kinesis::123456789012:stream/testStream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Invalid ARN: Region is empty string in ARN', 'expect' => [ 'error' => 'Invalid ARN: Invalid region.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ConsumerARN' => 'arn:aws:kinesis: :123456789012:stream/testStream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Invalid ARN: Invalid account id', 'expect' => [ 'error' => 'Invalid ARN: Invalid account id.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ConsumerARN' => 'arn:aws:kinesis:us-east-1::stream/testStream/consumer/test-consumer:1525898737', 'OperationType' => 'control', ], ], [ 'documentation' => 'Invalid ARN: Invalid account id', 'expect' => [ 'error' => 'Invalid ARN: Invalid account id.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ConsumerARN' => 'arn:aws:kinesis:us-east-1: :stream/testStream/consumer/test-consumer:1525898737', 'OperationType' => 'control', ], ], [ 'documentation' => 'Invalid ARN: Kinesis ARNs only support stream arn/consumer arn types', 'expect' => [ 'error' => 'Invalid ARN: Kinesis ARNs don\'t support `accesspoint` arn types.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ConsumerARN' => 'arn:aws:kinesis:us-east-1:123:accesspoint/testStream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Dual Stack not supported region.', 'expect' => [ 'error' => 'FIPS and DualStack are enabled, but this partition does not support one or both', ], 'params' => [ 'Region' => 'us-iso-west-1', 'UseFIPS' => true, 'UseDualStack' => true, 'ConsumerARN' => 'arn:aws-iso:kinesis:us-iso-west-1:123456789012:stream/testStream/consumer/test-consumer:1525898737', 'OperationType' => 'control', ], ], [ 'documentation' => 'OperationType not set', 'expect' => [ 'error' => 'Operation Type is not set. Please contact service team for resolution.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ConsumerARN' => 'arn:aws:kinesis:us-east-1:123456789012:stream/testStream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Custom Endpoint is specified', 'expect' => [ 'endpoint' => [ 'url' => 'https://example.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'ConsumerARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', 'Endpoint' => 'https://example.com', ], ], [ 'documentation' => 'Account endpoint targeting control operation type', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.control-kinesis.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'ConsumerARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Account endpoint targeting data operation type', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'data', 'ConsumerARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Account endpoint with fips targeting data operation type', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis-fips.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'data', 'ConsumerARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Account endpoint with fips targeting control operation type', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.control-kinesis-fips.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'control', 'ConsumerARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Account endpoint with Dual Stack and FIPS enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.control-kinesis-fips.us-east-1.api.aws', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => true, 'UseDualStack' => true, 'OperationType' => 'control', 'ConsumerARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Account endpoint with Dual Stack enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis.us-west-1.api.aws', ], ], 'params' => [ 'Region' => 'us-west-1', 'UseFIPS' => false, 'UseDualStack' => true, 'OperationType' => 'data', 'ConsumerARN' => 'arn:aws:kinesis:us-west-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Account endpoint with FIPS and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.control-kinesis.us-west-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-west-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'ConsumerARN' => 'arn:aws:kinesis:us-west-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'RegionMismatch: client region should be used for endpoint region', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'data', 'ConsumerARN' => 'arn:aws:kinesis:us-west-1:123:stream/testStream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Account endpoint with FIPS enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis-fips.cn-northwest-1.amazonaws.com.cn', ], ], 'params' => [ 'Region' => 'cn-northwest-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'data', 'ConsumerARN' => 'arn:aws-cn:kinesis:cn-northwest-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Account endpoint with FIPS and DualStack enabled for cn regions.', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis-fips.cn-northwest-1.api.amazonwebservices.com.cn', ], ], 'params' => [ 'Region' => 'cn-northwest-1', 'UseFIPS' => true, 'UseDualStack' => true, 'OperationType' => 'data', 'ConsumerARN' => 'arn:aws-cn:kinesis:cn-northwest-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Account endpoint targeting control operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-iso-east-1.c2s.ic.gov', ], ], 'params' => [ 'Region' => 'us-iso-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'ConsumerARN' => 'arn:aws-iso:kinesis:us-iso-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Account endpoint targeting control operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-iso-west-1.c2s.ic.gov', ], ], 'params' => [ 'Region' => 'us-iso-west-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'ConsumerARN' => 'arn:aws-iso:kinesis:us-iso-west-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Account endpoint targeting data operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-isob-east-1.sc2s.sgov.gov', ], ], 'params' => [ 'Region' => 'us-isob-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'data', 'ConsumerARN' => 'arn:aws-iso-b:kinesis:us-isob-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Account endpoint with fips targeting control operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-iso-east-1.c2s.ic.gov', ], ], 'params' => [ 'Region' => 'us-iso-east-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'control', 'ConsumerARN' => 'arn:aws-iso:kinesis:us-iso-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Account endpoint with fips targeting data operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-isob-east-1.sc2s.sgov.gov', ], ], 'params' => [ 'Region' => 'us-isob-east-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'data', 'ConsumerARN' => 'arn:aws-iso-b:kinesis:us-isob-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'ConsumerARN targeting US-EAST-1', 'expect' => [ 'endpoint' => [ 'url' => 'https://123456789123.data-kinesis.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'data', 'ConsumerARN' => 'arn:aws:kinesis:us-east-1:123456789123:stream/foobar/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Both StreamARN and ConsumerARN specified. StreamARN should take precedence', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'data', 'StreamARN' => 'arn:aws:kinesis:us-east-1:123:stream/foobar', 'ConsumerARN' => 'arn:aws:kinesis:us-east-1:123456789123:stream/foobar/consumer/test-consumer:1525898737', ], ], ], 'version' => '1.0',]; +return [ 'testCases' => [ [ 'documentation' => 'For region af-south-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.af-south-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'af-south-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region ap-east-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.ap-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'ap-east-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region ap-northeast-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.ap-northeast-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'ap-northeast-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region ap-northeast-2 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.ap-northeast-2.amazonaws.com', ], ], 'params' => [ 'Region' => 'ap-northeast-2', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region ap-northeast-3 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.ap-northeast-3.amazonaws.com', ], ], 'params' => [ 'Region' => 'ap-northeast-3', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region ap-south-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.ap-south-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'ap-south-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region ap-southeast-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.ap-southeast-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'ap-southeast-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region ap-southeast-2 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.ap-southeast-2.amazonaws.com', ], ], 'params' => [ 'Region' => 'ap-southeast-2', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region ap-southeast-3 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.ap-southeast-3.amazonaws.com', ], ], 'params' => [ 'Region' => 'ap-southeast-3', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region ca-central-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.ca-central-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'ca-central-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region eu-central-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.eu-central-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'eu-central-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region eu-north-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.eu-north-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'eu-north-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region eu-south-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.eu-south-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'eu-south-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region eu-west-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.eu-west-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'eu-west-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region eu-west-2 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.eu-west-2.amazonaws.com', ], ], 'params' => [ 'Region' => 'eu-west-2', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region eu-west-3 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.eu-west-3.amazonaws.com', ], ], 'params' => [ 'Region' => 'eu-west-3', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region me-south-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.me-south-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'me-south-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region sa-east-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.sa-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'sa-east-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-east-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-east-1 with FIPS enabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => true, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-east-2 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-east-2.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-2', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-east-2 with FIPS enabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-east-2.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-2', 'UseFIPS' => true, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-west-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-west-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-west-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-west-1 with FIPS enabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-west-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-west-1', 'UseFIPS' => true, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-west-2 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-west-2.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-west-2', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-west-2 with FIPS enabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-west-2.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-west-2', 'UseFIPS' => true, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-east-1 with FIPS enabled and DualStack enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-east-1.api.aws', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => true, 'UseDualStack' => true, ], ], [ 'documentation' => 'For region us-east-1 with FIPS disabled and DualStack enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-east-1.api.aws', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => true, ], ], [ 'documentation' => 'For region cn-north-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.cn-north-1.amazonaws.com.cn', ], ], 'params' => [ 'Region' => 'cn-north-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region cn-northwest-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.cn-northwest-1.amazonaws.com.cn', ], ], 'params' => [ 'Region' => 'cn-northwest-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region cn-north-1 with FIPS enabled and DualStack enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.cn-north-1.api.amazonwebservices.com.cn', ], ], 'params' => [ 'Region' => 'cn-north-1', 'UseFIPS' => true, 'UseDualStack' => true, ], ], [ 'documentation' => 'For region cn-north-1 with FIPS enabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.cn-north-1.amazonaws.com.cn', ], ], 'params' => [ 'Region' => 'cn-north-1', 'UseFIPS' => true, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region cn-north-1 with FIPS disabled and DualStack enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.cn-north-1.api.amazonwebservices.com.cn', ], ], 'params' => [ 'Region' => 'cn-north-1', 'UseFIPS' => false, 'UseDualStack' => true, ], ], [ 'documentation' => 'For region us-gov-east-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-gov-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-gov-east-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-gov-east-1 with FIPS enabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-gov-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-gov-east-1', 'UseFIPS' => true, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-gov-west-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-gov-west-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-gov-west-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-gov-west-1 with FIPS enabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-gov-west-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-gov-west-1', 'UseFIPS' => true, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-gov-east-1 with FIPS enabled and DualStack enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-gov-east-1.api.aws', ], ], 'params' => [ 'Region' => 'us-gov-east-1', 'UseFIPS' => true, 'UseDualStack' => true, ], ], [ 'documentation' => 'For region us-gov-east-1 with FIPS disabled and DualStack enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-gov-east-1.api.aws', ], ], 'params' => [ 'Region' => 'us-gov-east-1', 'UseFIPS' => false, 'UseDualStack' => true, ], ], [ 'documentation' => 'For region us-iso-east-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-iso-east-1.c2s.ic.gov', ], ], 'params' => [ 'Region' => 'us-iso-east-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-iso-west-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-iso-west-1.c2s.ic.gov', ], ], 'params' => [ 'Region' => 'us-iso-west-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-iso-east-1 with FIPS enabled and DualStack enabled', 'expect' => [ 'error' => 'FIPS and DualStack are enabled, but this partition does not support one or both', ], 'params' => [ 'Region' => 'us-iso-east-1', 'UseFIPS' => true, 'UseDualStack' => true, ], ], [ 'documentation' => 'For region us-iso-east-1 with FIPS enabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-iso-east-1.c2s.ic.gov', ], ], 'params' => [ 'Region' => 'us-iso-east-1', 'UseFIPS' => true, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-iso-east-1 with FIPS disabled and DualStack enabled', 'expect' => [ 'error' => 'DualStack is enabled but this partition does not support DualStack', ], 'params' => [ 'Region' => 'us-iso-east-1', 'UseFIPS' => false, 'UseDualStack' => true, ], ], [ 'documentation' => 'For region us-isob-east-1 with FIPS disabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-isob-east-1.sc2s.sgov.gov', ], ], 'params' => [ 'Region' => 'us-isob-east-1', 'UseFIPS' => false, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-isob-east-1 with FIPS enabled and DualStack enabled', 'expect' => [ 'error' => 'FIPS and DualStack are enabled, but this partition does not support one or both', ], 'params' => [ 'Region' => 'us-isob-east-1', 'UseFIPS' => true, 'UseDualStack' => true, ], ], [ 'documentation' => 'For region us-isob-east-1 with FIPS enabled and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-isob-east-1.sc2s.sgov.gov', ], ], 'params' => [ 'Region' => 'us-isob-east-1', 'UseFIPS' => true, 'UseDualStack' => false, ], ], [ 'documentation' => 'For region us-isob-east-1 with FIPS disabled and DualStack enabled', 'expect' => [ 'error' => 'DualStack is enabled but this partition does not support DualStack', ], 'params' => [ 'Region' => 'us-isob-east-1', 'UseFIPS' => false, 'UseDualStack' => true, ], ], [ 'documentation' => 'For custom endpoint with region set and fips disabled and dualstack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://example.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'Endpoint' => 'https://example.com', ], ], [ 'documentation' => 'For custom endpoint with region not set and fips disabled and dualstack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://example.com', ], ], 'params' => [ 'UseFIPS' => false, 'UseDualStack' => false, 'Endpoint' => 'https://example.com', ], ], [ 'documentation' => 'For custom endpoint with fips enabled and dualstack disabled', 'expect' => [ 'error' => 'Invalid Configuration: FIPS and custom endpoint are not supported', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => true, 'UseDualStack' => false, 'Endpoint' => 'https://example.com', ], ], [ 'documentation' => 'For custom endpoint with fips disabled and dualstack enabled', 'expect' => [ 'error' => 'Invalid Configuration: Dualstack and custom endpoint are not supported', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => true, 'Endpoint' => 'https://example.com', ], ], [ 'documentation' => 'Missing region', 'expect' => [ 'error' => 'Invalid Configuration: Missing Region', ], ], [ 'documentation' => 'Invalid ARN: Failed to parse ARN.', 'expect' => [ 'error' => 'Invalid ARN: Failed to parse ARN.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'StreamARN' => 'arn', ], ], [ 'documentation' => 'Invalid ARN: partition missing from ARN.', 'expect' => [ 'error' => 'Invalid ARN: Failed to parse ARN.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'StreamARN' => 'arn::kinesis:us-west-2:123456789012:stream/testStream', ], ], [ 'documentation' => 'Invalid ARN: partitions mismatch.', 'expect' => [ 'error' => 'Partition: aws from ARN doesn\'t match with partition name: aws-us-gov.', ], 'params' => [ 'Region' => 'us-gov-west-1', 'UseFIPS' => false, 'UseDualStack' => false, 'StreamARN' => 'arn:aws:kinesis:us-west-2:123456789012:stream/testStream', ], ], [ 'documentation' => 'Invalid ARN: Not Kinesis', 'expect' => [ 'error' => 'Invalid ARN: The ARN was not for the Kinesis service, found: s3.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'StreamARN' => 'arn:aws:s3:us-west-2:123456789012:stream/testStream', ], ], [ 'documentation' => 'Invalid ARN: Region is missing in ARN', 'expect' => [ 'error' => 'Invalid ARN: Invalid region.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'StreamARN' => 'arn:aws:kinesis::123456789012:stream/testStream', ], ], [ 'documentation' => 'Invalid ARN: Region is empty string in ARN', 'expect' => [ 'error' => 'Invalid ARN: Invalid region.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'StreamARN' => 'arn:aws:kinesis: :123456789012:stream/testStream', ], ], [ 'documentation' => 'Invalid ARN: Invalid account id', 'expect' => [ 'error' => 'Invalid ARN: Invalid account id.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'StreamARN' => 'arn:aws:kinesis:us-east-1::stream/testStream', 'OperationType' => 'control', ], ], [ 'documentation' => 'Invalid ARN: Invalid account id', 'expect' => [ 'error' => 'Invalid ARN: Invalid account id.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'StreamARN' => 'arn:aws:kinesis:us-east-1: :stream/testStream', 'OperationType' => 'control', ], ], [ 'documentation' => 'Invalid ARN: Kinesis ARNs only support stream arn types', 'expect' => [ 'error' => 'Invalid ARN: Kinesis ARNs don\'t support `accesspoint` arn types.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'StreamARN' => 'arn:aws:kinesis:us-east-1:123:accesspoint/testStream', ], ], [ 'documentation' => 'Dual Stack not supported region.', 'expect' => [ 'error' => 'FIPS and DualStack are enabled, but this partition does not support one or both', ], 'params' => [ 'Region' => 'us-iso-west-1', 'UseFIPS' => true, 'UseDualStack' => true, 'StreamARN' => 'arn:aws-iso:kinesis:us-iso-west-1:123456789012:stream/testStream', 'OperationType' => 'control', ], ], [ 'documentation' => 'OperationType not set', 'expect' => [ 'error' => 'Operation Type is not set. Please contact service team for resolution.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'StreamARN' => 'arn:aws:kinesis:us-east-1:123456789012:stream/testStream', ], ], [ 'documentation' => 'Custom Endpoint is specified', 'expect' => [ 'endpoint' => [ 'url' => 'https://example.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'StreamARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream', 'Endpoint' => 'https://example.com', ], ], [ 'documentation' => 'Account endpoint targeting control operation type', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.control-kinesis.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'StreamARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream', ], ], [ 'documentation' => 'Account endpoint targeting data operation type', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'data', 'StreamARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream', ], ], [ 'documentation' => 'Account endpoint with fips targeting data operation type', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis-fips.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'data', 'StreamARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream', ], ], [ 'documentation' => 'Account endpoint with fips targeting control operation type', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.control-kinesis-fips.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'control', 'StreamARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream', ], ], [ 'documentation' => 'Account endpoint with Dual Stack and FIPS enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.control-kinesis-fips.us-east-1.api.aws', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => true, 'UseDualStack' => true, 'OperationType' => 'control', 'StreamARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream', ], ], [ 'documentation' => 'Account endpoint with Dual Stack enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis.us-west-1.api.aws', ], ], 'params' => [ 'Region' => 'us-west-1', 'UseFIPS' => false, 'UseDualStack' => true, 'OperationType' => 'data', 'StreamARN' => 'arn:aws:kinesis:us-west-1:123:stream/test-stream', ], ], [ 'documentation' => 'Account endpoint with FIPS and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.control-kinesis.us-west-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-west-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'StreamARN' => 'arn:aws:kinesis:us-west-1:123:stream/test-stream', ], ], [ 'documentation' => 'RegionMismatch: client region should be used for endpoint region', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'data', 'StreamARN' => 'arn:aws:kinesis:us-west-1:123:stream/testStream', ], ], [ 'documentation' => 'Account endpoint with FIPS enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis-fips.cn-northwest-1.amazonaws.com.cn', ], ], 'params' => [ 'Region' => 'cn-northwest-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'data', 'StreamARN' => 'arn:aws-cn:kinesis:cn-northwest-1:123:stream/test-stream', ], ], [ 'documentation' => 'Account endpoint with FIPS and DualStack enabled for cn regions.', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis-fips.cn-northwest-1.api.amazonwebservices.com.cn', ], ], 'params' => [ 'Region' => 'cn-northwest-1', 'UseFIPS' => true, 'UseDualStack' => true, 'OperationType' => 'data', 'StreamARN' => 'arn:aws-cn:kinesis:cn-northwest-1:123:stream/test-stream', ], ], [ 'documentation' => 'Account endpoint targeting control operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-iso-east-1.c2s.ic.gov', ], ], 'params' => [ 'Region' => 'us-iso-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'StreamARN' => 'arn:aws-iso:kinesis:us-iso-east-1:123:stream/test-stream', ], ], [ 'documentation' => 'Account endpoint targeting control operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-iso-west-1.c2s.ic.gov', ], ], 'params' => [ 'Region' => 'us-iso-west-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'StreamARN' => 'arn:aws-iso:kinesis:us-iso-west-1:123:stream/test-stream', ], ], [ 'documentation' => 'Account endpoint targeting data operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-isob-east-1.sc2s.sgov.gov', ], ], 'params' => [ 'Region' => 'us-isob-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'data', 'StreamARN' => 'arn:aws-iso-b:kinesis:us-isob-east-1:123:stream/test-stream', ], ], [ 'documentation' => 'Account endpoint with fips targeting control operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-iso-east-1.c2s.ic.gov', ], ], 'params' => [ 'Region' => 'us-iso-east-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'control', 'StreamARN' => 'arn:aws-iso:kinesis:us-iso-east-1:123:stream/test-stream', ], ], [ 'documentation' => 'Account endpoint with fips targeting data operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-isob-east-1.sc2s.sgov.gov', ], ], 'params' => [ 'Region' => 'us-isob-east-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'data', 'StreamARN' => 'arn:aws-iso-b:kinesis:us-isob-east-1:123:stream/test-stream', ], ], [ 'documentation' => 'Invalid ConsumerARN: Failed to parse ARN.', 'expect' => [ 'error' => 'Invalid ARN: Failed to parse ARN.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ConsumerARN' => 'arn', ], ], [ 'documentation' => 'Invalid ConsumerARN: partition missing from ARN.', 'expect' => [ 'error' => 'Invalid ARN: Failed to parse ARN.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ConsumerARN' => 'arn::kinesis:us-west-2:123456789012:stream/testStream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Invalid ARN: partitions mismatch.', 'expect' => [ 'error' => 'Partition: aws from ARN doesn\'t match with partition name: aws-us-gov.', ], 'params' => [ 'Region' => 'us-gov-west-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ConsumerARN' => 'arn:aws:kinesis:us-west-2:123456789012:stream/testStream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Invalid ARN: Not Kinesis', 'expect' => [ 'error' => 'Invalid ARN: The ARN was not for the Kinesis service, found: s3.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ConsumerARN' => 'arn:aws:s3:us-west-2:123456789012:stream/testStream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Invalid ARN: Region is missing in ARN', 'expect' => [ 'error' => 'Invalid ARN: Invalid region.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ConsumerARN' => 'arn:aws:kinesis::123456789012:stream/testStream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Invalid ARN: Region is empty string in ARN', 'expect' => [ 'error' => 'Invalid ARN: Invalid region.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ConsumerARN' => 'arn:aws:kinesis: :123456789012:stream/testStream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Invalid ARN: Invalid account id', 'expect' => [ 'error' => 'Invalid ARN: Invalid account id.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ConsumerARN' => 'arn:aws:kinesis:us-east-1::stream/testStream/consumer/test-consumer:1525898737', 'OperationType' => 'control', ], ], [ 'documentation' => 'Invalid ARN: Invalid account id', 'expect' => [ 'error' => 'Invalid ARN: Invalid account id.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ConsumerARN' => 'arn:aws:kinesis:us-east-1: :stream/testStream/consumer/test-consumer:1525898737', 'OperationType' => 'control', ], ], [ 'documentation' => 'Invalid ARN: Kinesis ARNs only support stream arn/consumer arn types', 'expect' => [ 'error' => 'Invalid ARN: Kinesis ARNs don\'t support `accesspoint` arn types.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ConsumerARN' => 'arn:aws:kinesis:us-east-1:123:accesspoint/testStream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Dual Stack not supported region.', 'expect' => [ 'error' => 'FIPS and DualStack are enabled, but this partition does not support one or both', ], 'params' => [ 'Region' => 'us-iso-west-1', 'UseFIPS' => true, 'UseDualStack' => true, 'ConsumerARN' => 'arn:aws-iso:kinesis:us-iso-west-1:123456789012:stream/testStream/consumer/test-consumer:1525898737', 'OperationType' => 'control', ], ], [ 'documentation' => 'OperationType not set', 'expect' => [ 'error' => 'Operation Type is not set. Please contact service team for resolution.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ConsumerARN' => 'arn:aws:kinesis:us-east-1:123456789012:stream/testStream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Custom Endpoint is specified', 'expect' => [ 'endpoint' => [ 'url' => 'https://example.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'ConsumerARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', 'Endpoint' => 'https://example.com', ], ], [ 'documentation' => 'Account endpoint targeting control operation type', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.control-kinesis.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'ConsumerARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Account endpoint targeting data operation type', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'data', 'ConsumerARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Account endpoint with fips targeting data operation type', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis-fips.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'data', 'ConsumerARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Account endpoint with fips targeting control operation type', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.control-kinesis-fips.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'control', 'ConsumerARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Account endpoint with Dual Stack and FIPS enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.control-kinesis-fips.us-east-1.api.aws', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => true, 'UseDualStack' => true, 'OperationType' => 'control', 'ConsumerARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Account endpoint with Dual Stack enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis.us-west-1.api.aws', ], ], 'params' => [ 'Region' => 'us-west-1', 'UseFIPS' => false, 'UseDualStack' => true, 'OperationType' => 'data', 'ConsumerARN' => 'arn:aws:kinesis:us-west-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Account endpoint with FIPS and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.control-kinesis.us-west-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-west-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'ConsumerARN' => 'arn:aws:kinesis:us-west-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'RegionMismatch: client region should be used for endpoint region', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'data', 'ConsumerARN' => 'arn:aws:kinesis:us-west-1:123:stream/testStream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Account endpoint with FIPS enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis-fips.cn-northwest-1.amazonaws.com.cn', ], ], 'params' => [ 'Region' => 'cn-northwest-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'data', 'ConsumerARN' => 'arn:aws-cn:kinesis:cn-northwest-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Account endpoint with FIPS and DualStack enabled for cn regions.', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis-fips.cn-northwest-1.api.amazonwebservices.com.cn', ], ], 'params' => [ 'Region' => 'cn-northwest-1', 'UseFIPS' => true, 'UseDualStack' => true, 'OperationType' => 'data', 'ConsumerARN' => 'arn:aws-cn:kinesis:cn-northwest-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Account endpoint targeting control operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-iso-east-1.c2s.ic.gov', ], ], 'params' => [ 'Region' => 'us-iso-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'ConsumerARN' => 'arn:aws-iso:kinesis:us-iso-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Account endpoint targeting control operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-iso-west-1.c2s.ic.gov', ], ], 'params' => [ 'Region' => 'us-iso-west-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'ConsumerARN' => 'arn:aws-iso:kinesis:us-iso-west-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Account endpoint targeting data operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-isob-east-1.sc2s.sgov.gov', ], ], 'params' => [ 'Region' => 'us-isob-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'data', 'ConsumerARN' => 'arn:aws-iso-b:kinesis:us-isob-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Account endpoint with fips targeting control operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-iso-east-1.c2s.ic.gov', ], ], 'params' => [ 'Region' => 'us-iso-east-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'control', 'ConsumerARN' => 'arn:aws-iso:kinesis:us-iso-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Account endpoint with fips targeting data operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-isob-east-1.sc2s.sgov.gov', ], ], 'params' => [ 'Region' => 'us-isob-east-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'data', 'ConsumerARN' => 'arn:aws-iso-b:kinesis:us-isob-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'ConsumerARN targeting US-EAST-1', 'expect' => [ 'endpoint' => [ 'url' => 'https://123456789123.data-kinesis.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'data', 'ConsumerARN' => 'arn:aws:kinesis:us-east-1:123456789123:stream/foobar/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'Both StreamARN and ConsumerARN specified. StreamARN should take precedence', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'data', 'StreamARN' => 'arn:aws:kinesis:us-east-1:123:stream/foobar', 'ConsumerARN' => 'arn:aws:kinesis:us-east-1:123456789123:stream/foobar/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'ResourceARN test: Invalid ARN: Failed to parse ARN.', 'expect' => [ 'error' => 'Invalid ARN: Failed to parse ARN.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ResourceARN' => 'arn', ], ], [ 'documentation' => 'ResourceARN as StreamARN test: Invalid ARN: partition missing from ARN.', 'expect' => [ 'error' => 'Invalid ARN: Failed to parse ARN.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ResourceARN' => 'arn::kinesis:us-west-2:123456789012:stream/testStream', ], ], [ 'documentation' => 'ResourceARN as StreamARN test: Invalid ARN: partitions mismatch.', 'expect' => [ 'error' => 'Partition: aws from ARN doesn\'t match with partition name: aws-us-gov.', ], 'params' => [ 'Region' => 'us-gov-west-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ResourceARN' => 'arn:aws:kinesis:us-west-2:123456789012:stream/testStream', ], ], [ 'documentation' => 'ResourceARN as StreamARN test: Invalid ARN: Not Kinesis', 'expect' => [ 'error' => 'Invalid ARN: The ARN was not for the Kinesis service, found: s3.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ResourceARN' => 'arn:aws:s3:us-west-2:123456789012:stream/testStream', ], ], [ 'documentation' => 'ResourceARN as StreamARN test: Invalid ARN: Region is missing in ARN', 'expect' => [ 'error' => 'Invalid ARN: Invalid region.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ResourceARN' => 'arn:aws:kinesis::123456789012:stream/testStream', ], ], [ 'documentation' => 'ResourceARN as StreamARN test: Invalid ARN: Region is empty string in ARN', 'expect' => [ 'error' => 'Invalid ARN: Invalid region.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ResourceARN' => 'arn:aws:kinesis: :123456789012:stream/testStream', ], ], [ 'documentation' => 'ResourceARN as StreamARN test: Invalid ARN: Invalid account id', 'expect' => [ 'error' => 'Invalid ARN: Invalid account id.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ResourceARN' => 'arn:aws:kinesis:us-east-1::stream/testStream', 'OperationType' => 'control', ], ], [ 'documentation' => 'ResourceARN as StreamARN test: Invalid ARN: Invalid account id', 'expect' => [ 'error' => 'Invalid ARN: Invalid account id.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ResourceARN' => 'arn:aws:kinesis:us-east-1: :stream/testStream', 'OperationType' => 'control', ], ], [ 'documentation' => 'ResourceARN as StreamARN test: Invalid ARN: Kinesis ARNs only support stream arn types', 'expect' => [ 'error' => 'Invalid ARN: Kinesis ARNs don\'t support `accesspoint` arn types.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ResourceARN' => 'arn:aws:kinesis:us-east-1:123:accesspoint/testStream', ], ], [ 'documentation' => 'ResourceARN as StreamARN test: Dual Stack not supported region.', 'expect' => [ 'error' => 'FIPS and DualStack are enabled, but this partition does not support one or both', ], 'params' => [ 'Region' => 'us-iso-west-1', 'UseFIPS' => true, 'UseDualStack' => true, 'ResourceARN' => 'arn:aws-iso:kinesis:us-iso-west-1:123456789012:stream/testStream', 'OperationType' => 'control', ], ], [ 'documentation' => 'ResourceARN as StreamARN test: OperationType not set', 'expect' => [ 'error' => 'Operation Type is not set. Please contact service team for resolution.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ResourceARN' => 'arn:aws:kinesis:us-east-1:123456789012:stream/testStream', ], ], [ 'documentation' => 'ResourceARN as StreamARN test: Custom Endpoint is specified', 'expect' => [ 'endpoint' => [ 'url' => 'https://example.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'ResourceARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream', 'Endpoint' => 'https://example.com', ], ], [ 'documentation' => 'ResourceARN as StreamARN test: Account endpoint targeting control operation type', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.control-kinesis.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'ResourceARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream', ], ], [ 'documentation' => 'ResourceARN as StreamARN test: Account endpoint targeting data operation type', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'data', 'ResourceARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream', ], ], [ 'documentation' => 'ResourceARN as StreamARN test: Account endpoint with fips targeting data operation type', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis-fips.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'data', 'ResourceARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream', ], ], [ 'documentation' => 'ResourceARN as StreamARN test: Account endpoint with fips targeting control operation type', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.control-kinesis-fips.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'control', 'ResourceARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream', ], ], [ 'documentation' => 'ResourceARN as StreamARN test: Account endpoint with Dual Stack and FIPS enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.control-kinesis-fips.us-east-1.api.aws', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => true, 'UseDualStack' => true, 'OperationType' => 'control', 'ResourceARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream', ], ], [ 'documentation' => 'ResourceARN as StreamARN test: Account endpoint with Dual Stack enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis.us-west-1.api.aws', ], ], 'params' => [ 'Region' => 'us-west-1', 'UseFIPS' => false, 'UseDualStack' => true, 'OperationType' => 'data', 'ResourceARN' => 'arn:aws:kinesis:us-west-1:123:stream/test-stream', ], ], [ 'documentation' => 'ResourceARN as StreamARN test: Account endpoint with FIPS and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.control-kinesis.us-west-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-west-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'ResourceARN' => 'arn:aws:kinesis:us-west-1:123:stream/test-stream', ], ], [ 'documentation' => 'ResourceARN as StreamARN test: RegionMismatch: client region should be used for endpoint region', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'data', 'ResourceARN' => 'arn:aws:kinesis:us-west-1:123:stream/testStream', ], ], [ 'documentation' => 'ResourceARN as StreamARN test: Account endpoint with FIPS enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis-fips.cn-northwest-1.amazonaws.com.cn', ], ], 'params' => [ 'Region' => 'cn-northwest-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'data', 'ResourceARN' => 'arn:aws-cn:kinesis:cn-northwest-1:123:stream/test-stream', ], ], [ 'documentation' => 'ResourceARN as StreamARN test: Account endpoint with FIPS and DualStack enabled for cn regions.', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis-fips.cn-northwest-1.api.amazonwebservices.com.cn', ], ], 'params' => [ 'Region' => 'cn-northwest-1', 'UseFIPS' => true, 'UseDualStack' => true, 'OperationType' => 'data', 'ResourceARN' => 'arn:aws-cn:kinesis:cn-northwest-1:123:stream/test-stream', ], ], [ 'documentation' => 'ResourceARN as StreamARN test: Account endpoint targeting control operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-iso-east-1.c2s.ic.gov', ], ], 'params' => [ 'Region' => 'us-iso-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'ResourceARN' => 'arn:aws-iso:kinesis:us-iso-east-1:123:stream/test-stream', ], ], [ 'documentation' => 'ResourceARN as StreamARN test: Account endpoint targeting control operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-iso-west-1.c2s.ic.gov', ], ], 'params' => [ 'Region' => 'us-iso-west-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'ResourceARN' => 'arn:aws-iso:kinesis:us-iso-west-1:123:stream/test-stream', ], ], [ 'documentation' => 'ResourceARN as StreamARN test: Account endpoint targeting data operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-isob-east-1.sc2s.sgov.gov', ], ], 'params' => [ 'Region' => 'us-isob-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'data', 'ResourceARN' => 'arn:aws-iso-b:kinesis:us-isob-east-1:123:stream/test-stream', ], ], [ 'documentation' => 'ResourceARN as StreamARN test: Account endpoint with fips targeting control operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-iso-east-1.c2s.ic.gov', ], ], 'params' => [ 'Region' => 'us-iso-east-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'control', 'ResourceARN' => 'arn:aws-iso:kinesis:us-iso-east-1:123:stream/test-stream', ], ], [ 'documentation' => 'ResourceARN as StreamARN test: Account endpoint with fips targeting data operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-isob-east-1.sc2s.sgov.gov', ], ], 'params' => [ 'Region' => 'us-isob-east-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'data', 'ResourceARN' => 'arn:aws-iso-b:kinesis:us-isob-east-1:123:stream/test-stream', ], ], [ 'documentation' => 'ResourceARN as ConsumerARN test: Invalid ARN: partition missing from ARN.', 'expect' => [ 'error' => 'Invalid ARN: Failed to parse ARN.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ResourceARN' => 'arn::kinesis:us-west-2:123456789012:stream/testStream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'ResourceARN as ConsumerARN test: Invalid ARN: partitions mismatch.', 'expect' => [ 'error' => 'Partition: aws from ARN doesn\'t match with partition name: aws-us-gov.', ], 'params' => [ 'Region' => 'us-gov-west-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ResourceARN' => 'arn:aws:kinesis:us-west-2:123456789012:stream/testStream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'ResourceARN as ConsumerARN test: Invalid ARN: Not Kinesis', 'expect' => [ 'error' => 'Invalid ARN: The ARN was not for the Kinesis service, found: s3.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ResourceARN' => 'arn:aws:s3:us-west-2:123456789012:stream/testStream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'ResourceARN as ConsumerARN test: Invalid ARN: Region is missing in ARN', 'expect' => [ 'error' => 'Invalid ARN: Invalid region.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ResourceARN' => 'arn:aws:kinesis::123456789012:stream/testStream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'ResourceARN as ConsumerARN test: Invalid ARN: Region is empty string in ARN', 'expect' => [ 'error' => 'Invalid ARN: Invalid region.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ResourceARN' => 'arn:aws:kinesis: :123456789012:stream/testStream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'ResourceARN as ConsumerARN test: Invalid ARN: Invalid account id', 'expect' => [ 'error' => 'Invalid ARN: Invalid account id.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ResourceARN' => 'arn:aws:kinesis:us-east-1::stream/testStream/consumer/test-consumer:1525898737', 'OperationType' => 'control', ], ], [ 'documentation' => 'ResourceARN as ConsumerARN test: Invalid ARN: Invalid account id', 'expect' => [ 'error' => 'Invalid ARN: Invalid account id.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ResourceARN' => 'arn:aws:kinesis:us-east-1: :stream/testStream/consumer/test-consumer:1525898737', 'OperationType' => 'control', ], ], [ 'documentation' => 'ResourceARN as ConsumerARN test: Invalid ARN: Kinesis ARNs only support stream arn/consumer arn types', 'expect' => [ 'error' => 'Invalid ARN: Kinesis ARNs don\'t support `accesspoint` arn types.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ResourceARN' => 'arn:aws:kinesis:us-east-1:123:accesspoint/testStream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'ResourceARN as ConsumerARN test: Dual Stack not supported region.', 'expect' => [ 'error' => 'FIPS and DualStack are enabled, but this partition does not support one or both', ], 'params' => [ 'Region' => 'us-iso-west-1', 'UseFIPS' => true, 'UseDualStack' => true, 'ResourceARN' => 'arn:aws-iso:kinesis:us-iso-west-1:123456789012:stream/testStream/consumer/test-consumer:1525898737', 'OperationType' => 'control', ], ], [ 'documentation' => 'ResourceARN as ConsumerARN test: OperationType not set', 'expect' => [ 'error' => 'Operation Type is not set. Please contact service team for resolution.', ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'ResourceARN' => 'arn:aws:kinesis:us-east-1:123456789012:stream/testStream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'ResourceARN as ConsumerARN test: Custom Endpoint is specified', 'expect' => [ 'endpoint' => [ 'url' => 'https://example.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'ResourceARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', 'Endpoint' => 'https://example.com', ], ], [ 'documentation' => 'ResourceARN as ConsumerARN test: Account endpoint targeting control operation type', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.control-kinesis.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'ResourceARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'ResourceARN as ConsumerARN test: Account endpoint targeting data operation type', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'data', 'ResourceARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'ResourceARN as ConsumerARN test: Account endpoint with fips targeting data operation type', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis-fips.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'data', 'ResourceARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'ResourceARN as ConsumerARN test: Account endpoint with fips targeting control operation type', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.control-kinesis-fips.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'control', 'ResourceARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'ResourceARN as ConsumerARN test: Account endpoint with Dual Stack and FIPS enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.control-kinesis-fips.us-east-1.api.aws', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => true, 'UseDualStack' => true, 'OperationType' => 'control', 'ResourceARN' => 'arn:aws:kinesis:us-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'ResourceARN as ConsumerARN test: Account endpoint with Dual Stack enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis.us-west-1.api.aws', ], ], 'params' => [ 'Region' => 'us-west-1', 'UseFIPS' => false, 'UseDualStack' => true, 'OperationType' => 'data', 'ResourceARN' => 'arn:aws:kinesis:us-west-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'ResourceARN as ConsumerARN test: Account endpoint with FIPS and DualStack disabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.control-kinesis.us-west-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-west-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'ResourceARN' => 'arn:aws:kinesis:us-west-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'ResourceARN as ConsumerARN test: RegionMismatch: client region should be used for endpoint region', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis.us-east-1.amazonaws.com', ], ], 'params' => [ 'Region' => 'us-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'data', 'ResourceARN' => 'arn:aws:kinesis:us-west-1:123:stream/testStream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'ResourceARN as ConsumerARN test: Account endpoint with FIPS enabled', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis-fips.cn-northwest-1.amazonaws.com.cn', ], ], 'params' => [ 'Region' => 'cn-northwest-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'data', 'ResourceARN' => 'arn:aws-cn:kinesis:cn-northwest-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'ResourceARN as ConsumerARN test: Account endpoint with FIPS and DualStack enabled for cn regions.', 'expect' => [ 'endpoint' => [ 'url' => 'https://123.data-kinesis-fips.cn-northwest-1.api.amazonwebservices.com.cn', ], ], 'params' => [ 'Region' => 'cn-northwest-1', 'UseFIPS' => true, 'UseDualStack' => true, 'OperationType' => 'data', 'ResourceARN' => 'arn:aws-cn:kinesis:cn-northwest-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'ResourceARN as ConsumerARN test: Account endpoint targeting control operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-iso-east-1.c2s.ic.gov', ], ], 'params' => [ 'Region' => 'us-iso-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'ResourceARN' => 'arn:aws-iso:kinesis:us-iso-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'ResourceARN as ConsumerARN test: Account endpoint targeting control operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-iso-west-1.c2s.ic.gov', ], ], 'params' => [ 'Region' => 'us-iso-west-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'control', 'ResourceARN' => 'arn:aws-iso:kinesis:us-iso-west-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'ResourceARN as ConsumerARN test: Account endpoint targeting data operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis.us-isob-east-1.sc2s.sgov.gov', ], ], 'params' => [ 'Region' => 'us-isob-east-1', 'UseFIPS' => false, 'UseDualStack' => false, 'OperationType' => 'data', 'ResourceARN' => 'arn:aws-iso-b:kinesis:us-isob-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'ResourceARN as ConsumerARN test: Account endpoint with fips targeting control operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-iso-east-1.c2s.ic.gov', ], ], 'params' => [ 'Region' => 'us-iso-east-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'control', 'ResourceARN' => 'arn:aws-iso:kinesis:us-iso-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], [ 'documentation' => 'ResourceARN as ConsumerARN test: Account endpoint with fips targeting data operation type in ADC regions', 'expect' => [ 'endpoint' => [ 'url' => 'https://kinesis-fips.us-isob-east-1.sc2s.sgov.gov', ], ], 'params' => [ 'Region' => 'us-isob-east-1', 'UseFIPS' => true, 'UseDualStack' => false, 'OperationType' => 'data', 'ResourceARN' => 'arn:aws-iso-b:kinesis:us-isob-east-1:123:stream/test-stream/consumer/test-consumer:1525898737', ], ], ], 'version' => '1.0',]; diff --git a/src/data/s3control/2018-08-20/api-2.json b/src/data/s3control/2018-08-20/api-2.json index 39416114df..77d98a599e 100644 --- a/src/data/s3control/2018-08-20/api-2.json +++ b/src/data/s3control/2018-08-20/api-2.json @@ -3033,7 +3033,17 @@ }, "CreatedAfter":{"shape":"ObjectCreationTime"}, "CreatedBefore":{"shape":"ObjectCreationTime"}, - "ObjectReplicationStatuses":{"shape":"ReplicationStatusFilterList"} + "ObjectReplicationStatuses":{"shape":"ReplicationStatusFilterList"}, + "KeyNameConstraint":{"shape":"KeyNameConstraint"}, + "ObjectSizeGreaterThanBytes":{ + "shape":"ObjectSizeGreaterThanBytes", + "box":true + }, + "ObjectSizeLessThanBytes":{ + "shape":"ObjectSizeLessThanBytes", + "box":true + }, + "MatchAnyStorageClass":{"shape":"StorageClassList"} } }, "JobManifestLocation":{ @@ -3220,6 +3230,14 @@ "type":"long", "min":0 }, + "KeyNameConstraint":{ + "type":"structure", + "members":{ + "MatchAnyPrefix":{"shape":"NonEmptyMaxLength1024StringList"}, + "MatchAnySuffix":{"shape":"NonEmptyMaxLength1024StringList"}, + "MatchAnySubstring":{"shape":"NonEmptyMaxLength1024StringList"} + } + }, "KmsKeyArnString":{ "type":"string", "max":2000, @@ -3761,6 +3779,10 @@ "max":1024, "min":1 }, + "NonEmptyMaxLength1024StringList":{ + "type":"list", + "member":{"shape":"NonEmptyMaxLength1024String"} + }, "NonEmptyMaxLength2048String":{ "type":"string", "max":2048, @@ -5030,6 +5052,10 @@ "Disabled" ] }, + "StorageClassList":{ + "type":"list", + "member":{"shape":"S3StorageClass"} + }, "StorageLensArn":{ "type":"string", "max":1024, diff --git a/src/data/s3control/2018-08-20/api-2.json.php b/src/data/s3control/2018-08-20/api-2.json.php index 337efa3a53..aa74542ac5 100644 --- a/src/data/s3control/2018-08-20/api-2.json.php +++ b/src/data/s3control/2018-08-20/api-2.json.php @@ -1,3 +1,3 @@ '2.0', 'metadata' => [ 'apiVersion' => '2018-08-20', 'endpointPrefix' => 's3-control', 'protocol' => 'rest-xml', 'serviceFullName' => 'AWS S3 Control', 'serviceId' => 'S3 Control', 'signatureVersion' => 's3v4', 'signingName' => 's3', 'uid' => 's3control-2018-08-20', ], 'operations' => [ 'CreateAccessPoint' => [ 'name' => 'CreateAccessPoint', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/accesspoint/{name}', ], 'input' => [ 'shape' => 'CreateAccessPointRequest', 'locationName' => 'CreateAccessPointRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'output' => [ 'shape' => 'CreateAccessPointResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'CreateAccessPointForObjectLambda' => [ 'name' => 'CreateAccessPointForObjectLambda', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/accesspointforobjectlambda/{name}', ], 'input' => [ 'shape' => 'CreateAccessPointForObjectLambdaRequest', 'locationName' => 'CreateAccessPointForObjectLambdaRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'output' => [ 'shape' => 'CreateAccessPointForObjectLambdaResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'CreateBucket' => [ 'name' => 'CreateBucket', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/bucket/{name}', ], 'input' => [ 'shape' => 'CreateBucketRequest', ], 'output' => [ 'shape' => 'CreateBucketResult', ], 'errors' => [ [ 'shape' => 'BucketAlreadyExists', ], [ 'shape' => 'BucketAlreadyOwnedByYou', ], ], 'httpChecksumRequired' => true, ], 'CreateJob' => [ 'name' => 'CreateJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/v20180820/jobs', ], 'input' => [ 'shape' => 'CreateJobRequest', 'locationName' => 'CreateJobRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'output' => [ 'shape' => 'CreateJobResult', ], 'errors' => [ [ 'shape' => 'TooManyRequestsException', ], [ 'shape' => 'BadRequestException', ], [ 'shape' => 'IdempotencyException', ], [ 'shape' => 'InternalServiceException', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'CreateMultiRegionAccessPoint' => [ 'name' => 'CreateMultiRegionAccessPoint', 'http' => [ 'method' => 'POST', 'requestUri' => '/v20180820/async-requests/mrap/create', ], 'input' => [ 'shape' => 'CreateMultiRegionAccessPointRequest', 'locationName' => 'CreateMultiRegionAccessPointRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'output' => [ 'shape' => 'CreateMultiRegionAccessPointResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'CreateStorageLensGroup' => [ 'name' => 'CreateStorageLensGroup', 'http' => [ 'method' => 'POST', 'requestUri' => '/v20180820/storagelensgroup', 'responseCode' => 204, ], 'input' => [ 'shape' => 'CreateStorageLensGroupRequest', 'locationName' => 'CreateStorageLensGroupRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteAccessPoint' => [ 'name' => 'DeleteAccessPoint', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/accesspoint/{name}', ], 'input' => [ 'shape' => 'DeleteAccessPointRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteAccessPointForObjectLambda' => [ 'name' => 'DeleteAccessPointForObjectLambda', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/accesspointforobjectlambda/{name}', ], 'input' => [ 'shape' => 'DeleteAccessPointForObjectLambdaRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteAccessPointPolicy' => [ 'name' => 'DeleteAccessPointPolicy', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/accesspoint/{name}/policy', ], 'input' => [ 'shape' => 'DeleteAccessPointPolicyRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteAccessPointPolicyForObjectLambda' => [ 'name' => 'DeleteAccessPointPolicyForObjectLambda', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/accesspointforobjectlambda/{name}/policy', ], 'input' => [ 'shape' => 'DeleteAccessPointPolicyForObjectLambdaRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteBucket' => [ 'name' => 'DeleteBucket', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/bucket/{name}', ], 'input' => [ 'shape' => 'DeleteBucketRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteBucketLifecycleConfiguration' => [ 'name' => 'DeleteBucketLifecycleConfiguration', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/bucket/{name}/lifecycleconfiguration', ], 'input' => [ 'shape' => 'DeleteBucketLifecycleConfigurationRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteBucketPolicy' => [ 'name' => 'DeleteBucketPolicy', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/bucket/{name}/policy', ], 'input' => [ 'shape' => 'DeleteBucketPolicyRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteBucketReplication' => [ 'name' => 'DeleteBucketReplication', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/bucket/{name}/replication', ], 'input' => [ 'shape' => 'DeleteBucketReplicationRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteBucketTagging' => [ 'name' => 'DeleteBucketTagging', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/bucket/{name}/tagging', 'responseCode' => 204, ], 'input' => [ 'shape' => 'DeleteBucketTaggingRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteJobTagging' => [ 'name' => 'DeleteJobTagging', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/jobs/{id}/tagging', ], 'input' => [ 'shape' => 'DeleteJobTaggingRequest', ], 'output' => [ 'shape' => 'DeleteJobTaggingResult', ], 'errors' => [ [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'TooManyRequestsException', ], [ 'shape' => 'NotFoundException', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteMultiRegionAccessPoint' => [ 'name' => 'DeleteMultiRegionAccessPoint', 'http' => [ 'method' => 'POST', 'requestUri' => '/v20180820/async-requests/mrap/delete', ], 'input' => [ 'shape' => 'DeleteMultiRegionAccessPointRequest', 'locationName' => 'DeleteMultiRegionAccessPointRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'output' => [ 'shape' => 'DeleteMultiRegionAccessPointResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeletePublicAccessBlock' => [ 'name' => 'DeletePublicAccessBlock', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/configuration/publicAccessBlock', ], 'input' => [ 'shape' => 'DeletePublicAccessBlockRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteStorageLensConfiguration' => [ 'name' => 'DeleteStorageLensConfiguration', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/storagelens/{storagelensid}', ], 'input' => [ 'shape' => 'DeleteStorageLensConfigurationRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteStorageLensConfigurationTagging' => [ 'name' => 'DeleteStorageLensConfigurationTagging', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/storagelens/{storagelensid}/tagging', ], 'input' => [ 'shape' => 'DeleteStorageLensConfigurationTaggingRequest', ], 'output' => [ 'shape' => 'DeleteStorageLensConfigurationTaggingResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteStorageLensGroup' => [ 'name' => 'DeleteStorageLensGroup', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/storagelensgroup/{name}', 'responseCode' => 204, ], 'input' => [ 'shape' => 'DeleteStorageLensGroupRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DescribeJob' => [ 'name' => 'DescribeJob', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/jobs/{id}', ], 'input' => [ 'shape' => 'DescribeJobRequest', ], 'output' => [ 'shape' => 'DescribeJobResult', ], 'errors' => [ [ 'shape' => 'BadRequestException', ], [ 'shape' => 'TooManyRequestsException', ], [ 'shape' => 'NotFoundException', ], [ 'shape' => 'InternalServiceException', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DescribeMultiRegionAccessPointOperation' => [ 'name' => 'DescribeMultiRegionAccessPointOperation', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/async-requests/mrap/{request_token+}', ], 'input' => [ 'shape' => 'DescribeMultiRegionAccessPointOperationRequest', ], 'output' => [ 'shape' => 'DescribeMultiRegionAccessPointOperationResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetAccessPoint' => [ 'name' => 'GetAccessPoint', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/accesspoint/{name}', ], 'input' => [ 'shape' => 'GetAccessPointRequest', ], 'output' => [ 'shape' => 'GetAccessPointResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetAccessPointConfigurationForObjectLambda' => [ 'name' => 'GetAccessPointConfigurationForObjectLambda', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/accesspointforobjectlambda/{name}/configuration', ], 'input' => [ 'shape' => 'GetAccessPointConfigurationForObjectLambdaRequest', ], 'output' => [ 'shape' => 'GetAccessPointConfigurationForObjectLambdaResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetAccessPointForObjectLambda' => [ 'name' => 'GetAccessPointForObjectLambda', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/accesspointforobjectlambda/{name}', ], 'input' => [ 'shape' => 'GetAccessPointForObjectLambdaRequest', ], 'output' => [ 'shape' => 'GetAccessPointForObjectLambdaResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetAccessPointPolicy' => [ 'name' => 'GetAccessPointPolicy', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/accesspoint/{name}/policy', ], 'input' => [ 'shape' => 'GetAccessPointPolicyRequest', ], 'output' => [ 'shape' => 'GetAccessPointPolicyResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetAccessPointPolicyForObjectLambda' => [ 'name' => 'GetAccessPointPolicyForObjectLambda', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/accesspointforobjectlambda/{name}/policy', ], 'input' => [ 'shape' => 'GetAccessPointPolicyForObjectLambdaRequest', ], 'output' => [ 'shape' => 'GetAccessPointPolicyForObjectLambdaResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetAccessPointPolicyStatus' => [ 'name' => 'GetAccessPointPolicyStatus', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/accesspoint/{name}/policyStatus', ], 'input' => [ 'shape' => 'GetAccessPointPolicyStatusRequest', ], 'output' => [ 'shape' => 'GetAccessPointPolicyStatusResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetAccessPointPolicyStatusForObjectLambda' => [ 'name' => 'GetAccessPointPolicyStatusForObjectLambda', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/accesspointforobjectlambda/{name}/policyStatus', ], 'input' => [ 'shape' => 'GetAccessPointPolicyStatusForObjectLambdaRequest', ], 'output' => [ 'shape' => 'GetAccessPointPolicyStatusForObjectLambdaResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetBucket' => [ 'name' => 'GetBucket', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/bucket/{name}', ], 'input' => [ 'shape' => 'GetBucketRequest', ], 'output' => [ 'shape' => 'GetBucketResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetBucketLifecycleConfiguration' => [ 'name' => 'GetBucketLifecycleConfiguration', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/bucket/{name}/lifecycleconfiguration', ], 'input' => [ 'shape' => 'GetBucketLifecycleConfigurationRequest', ], 'output' => [ 'shape' => 'GetBucketLifecycleConfigurationResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetBucketPolicy' => [ 'name' => 'GetBucketPolicy', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/bucket/{name}/policy', ], 'input' => [ 'shape' => 'GetBucketPolicyRequest', ], 'output' => [ 'shape' => 'GetBucketPolicyResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetBucketReplication' => [ 'name' => 'GetBucketReplication', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/bucket/{name}/replication', ], 'input' => [ 'shape' => 'GetBucketReplicationRequest', ], 'output' => [ 'shape' => 'GetBucketReplicationResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetBucketTagging' => [ 'name' => 'GetBucketTagging', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/bucket/{name}/tagging', ], 'input' => [ 'shape' => 'GetBucketTaggingRequest', ], 'output' => [ 'shape' => 'GetBucketTaggingResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetBucketVersioning' => [ 'name' => 'GetBucketVersioning', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/bucket/{name}/versioning', ], 'input' => [ 'shape' => 'GetBucketVersioningRequest', ], 'output' => [ 'shape' => 'GetBucketVersioningResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetJobTagging' => [ 'name' => 'GetJobTagging', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/jobs/{id}/tagging', ], 'input' => [ 'shape' => 'GetJobTaggingRequest', ], 'output' => [ 'shape' => 'GetJobTaggingResult', ], 'errors' => [ [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'TooManyRequestsException', ], [ 'shape' => 'NotFoundException', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetMultiRegionAccessPoint' => [ 'name' => 'GetMultiRegionAccessPoint', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/mrap/instances/{name+}', ], 'input' => [ 'shape' => 'GetMultiRegionAccessPointRequest', ], 'output' => [ 'shape' => 'GetMultiRegionAccessPointResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetMultiRegionAccessPointPolicy' => [ 'name' => 'GetMultiRegionAccessPointPolicy', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/mrap/instances/{name+}/policy', ], 'input' => [ 'shape' => 'GetMultiRegionAccessPointPolicyRequest', ], 'output' => [ 'shape' => 'GetMultiRegionAccessPointPolicyResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetMultiRegionAccessPointPolicyStatus' => [ 'name' => 'GetMultiRegionAccessPointPolicyStatus', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/mrap/instances/{name+}/policystatus', ], 'input' => [ 'shape' => 'GetMultiRegionAccessPointPolicyStatusRequest', ], 'output' => [ 'shape' => 'GetMultiRegionAccessPointPolicyStatusResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetMultiRegionAccessPointRoutes' => [ 'name' => 'GetMultiRegionAccessPointRoutes', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/mrap/instances/{mrap+}/routes', ], 'input' => [ 'shape' => 'GetMultiRegionAccessPointRoutesRequest', ], 'output' => [ 'shape' => 'GetMultiRegionAccessPointRoutesResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetPublicAccessBlock' => [ 'name' => 'GetPublicAccessBlock', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/configuration/publicAccessBlock', ], 'input' => [ 'shape' => 'GetPublicAccessBlockRequest', ], 'output' => [ 'shape' => 'GetPublicAccessBlockOutput', ], 'errors' => [ [ 'shape' => 'NoSuchPublicAccessBlockConfiguration', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetStorageLensConfiguration' => [ 'name' => 'GetStorageLensConfiguration', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/storagelens/{storagelensid}', ], 'input' => [ 'shape' => 'GetStorageLensConfigurationRequest', ], 'output' => [ 'shape' => 'GetStorageLensConfigurationResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetStorageLensConfigurationTagging' => [ 'name' => 'GetStorageLensConfigurationTagging', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/storagelens/{storagelensid}/tagging', ], 'input' => [ 'shape' => 'GetStorageLensConfigurationTaggingRequest', ], 'output' => [ 'shape' => 'GetStorageLensConfigurationTaggingResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetStorageLensGroup' => [ 'name' => 'GetStorageLensGroup', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/storagelensgroup/{name}', ], 'input' => [ 'shape' => 'GetStorageLensGroupRequest', ], 'output' => [ 'shape' => 'GetStorageLensGroupResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'ListAccessPoints' => [ 'name' => 'ListAccessPoints', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/accesspoint', ], 'input' => [ 'shape' => 'ListAccessPointsRequest', ], 'output' => [ 'shape' => 'ListAccessPointsResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'ListAccessPointsForObjectLambda' => [ 'name' => 'ListAccessPointsForObjectLambda', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/accesspointforobjectlambda', ], 'input' => [ 'shape' => 'ListAccessPointsForObjectLambdaRequest', ], 'output' => [ 'shape' => 'ListAccessPointsForObjectLambdaResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'ListJobs' => [ 'name' => 'ListJobs', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/jobs', ], 'input' => [ 'shape' => 'ListJobsRequest', ], 'output' => [ 'shape' => 'ListJobsResult', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidNextTokenException', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'ListMultiRegionAccessPoints' => [ 'name' => 'ListMultiRegionAccessPoints', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/mrap/instances', ], 'input' => [ 'shape' => 'ListMultiRegionAccessPointsRequest', ], 'output' => [ 'shape' => 'ListMultiRegionAccessPointsResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'ListRegionalBuckets' => [ 'name' => 'ListRegionalBuckets', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/bucket', ], 'input' => [ 'shape' => 'ListRegionalBucketsRequest', ], 'output' => [ 'shape' => 'ListRegionalBucketsResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'ListStorageLensConfigurations' => [ 'name' => 'ListStorageLensConfigurations', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/storagelens', ], 'input' => [ 'shape' => 'ListStorageLensConfigurationsRequest', ], 'output' => [ 'shape' => 'ListStorageLensConfigurationsResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'ListStorageLensGroups' => [ 'name' => 'ListStorageLensGroups', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/storagelensgroup', ], 'input' => [ 'shape' => 'ListStorageLensGroupsRequest', ], 'output' => [ 'shape' => 'ListStorageLensGroupsResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'ListTagsForResource' => [ 'name' => 'ListTagsForResource', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/tags/{resourceArn+}', ], 'input' => [ 'shape' => 'ListTagsForResourceRequest', ], 'output' => [ 'shape' => 'ListTagsForResourceResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'PutAccessPointConfigurationForObjectLambda' => [ 'name' => 'PutAccessPointConfigurationForObjectLambda', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/accesspointforobjectlambda/{name}/configuration', ], 'input' => [ 'shape' => 'PutAccessPointConfigurationForObjectLambdaRequest', 'locationName' => 'PutAccessPointConfigurationForObjectLambdaRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'PutAccessPointPolicy' => [ 'name' => 'PutAccessPointPolicy', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/accesspoint/{name}/policy', ], 'input' => [ 'shape' => 'PutAccessPointPolicyRequest', 'locationName' => 'PutAccessPointPolicyRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'PutAccessPointPolicyForObjectLambda' => [ 'name' => 'PutAccessPointPolicyForObjectLambda', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/accesspointforobjectlambda/{name}/policy', ], 'input' => [ 'shape' => 'PutAccessPointPolicyForObjectLambdaRequest', 'locationName' => 'PutAccessPointPolicyForObjectLambdaRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'PutBucketLifecycleConfiguration' => [ 'name' => 'PutBucketLifecycleConfiguration', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/bucket/{name}/lifecycleconfiguration', ], 'input' => [ 'shape' => 'PutBucketLifecycleConfigurationRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'PutBucketPolicy' => [ 'name' => 'PutBucketPolicy', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/bucket/{name}/policy', ], 'input' => [ 'shape' => 'PutBucketPolicyRequest', 'locationName' => 'PutBucketPolicyRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'PutBucketReplication' => [ 'name' => 'PutBucketReplication', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/bucket/{name}/replication', ], 'input' => [ 'shape' => 'PutBucketReplicationRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'PutBucketTagging' => [ 'name' => 'PutBucketTagging', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/bucket/{name}/tagging', ], 'input' => [ 'shape' => 'PutBucketTaggingRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'PutBucketVersioning' => [ 'name' => 'PutBucketVersioning', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/bucket/{name}/versioning', ], 'input' => [ 'shape' => 'PutBucketVersioningRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'PutJobTagging' => [ 'name' => 'PutJobTagging', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/jobs/{id}/tagging', ], 'input' => [ 'shape' => 'PutJobTaggingRequest', 'locationName' => 'PutJobTaggingRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'output' => [ 'shape' => 'PutJobTaggingResult', ], 'errors' => [ [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'TooManyRequestsException', ], [ 'shape' => 'NotFoundException', ], [ 'shape' => 'TooManyTagsException', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'PutMultiRegionAccessPointPolicy' => [ 'name' => 'PutMultiRegionAccessPointPolicy', 'http' => [ 'method' => 'POST', 'requestUri' => '/v20180820/async-requests/mrap/put-policy', ], 'input' => [ 'shape' => 'PutMultiRegionAccessPointPolicyRequest', 'locationName' => 'PutMultiRegionAccessPointPolicyRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'output' => [ 'shape' => 'PutMultiRegionAccessPointPolicyResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'PutPublicAccessBlock' => [ 'name' => 'PutPublicAccessBlock', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/configuration/publicAccessBlock', ], 'input' => [ 'shape' => 'PutPublicAccessBlockRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'PutStorageLensConfiguration' => [ 'name' => 'PutStorageLensConfiguration', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/storagelens/{storagelensid}', ], 'input' => [ 'shape' => 'PutStorageLensConfigurationRequest', 'locationName' => 'PutStorageLensConfigurationRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'PutStorageLensConfigurationTagging' => [ 'name' => 'PutStorageLensConfigurationTagging', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/storagelens/{storagelensid}/tagging', ], 'input' => [ 'shape' => 'PutStorageLensConfigurationTaggingRequest', 'locationName' => 'PutStorageLensConfigurationTaggingRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'output' => [ 'shape' => 'PutStorageLensConfigurationTaggingResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'SubmitMultiRegionAccessPointRoutes' => [ 'name' => 'SubmitMultiRegionAccessPointRoutes', 'http' => [ 'method' => 'PATCH', 'requestUri' => '/v20180820/mrap/instances/{mrap+}/routes', ], 'input' => [ 'shape' => 'SubmitMultiRegionAccessPointRoutesRequest', 'locationName' => 'SubmitMultiRegionAccessPointRoutesRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'output' => [ 'shape' => 'SubmitMultiRegionAccessPointRoutesResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'TagResource' => [ 'name' => 'TagResource', 'http' => [ 'method' => 'POST', 'requestUri' => '/v20180820/tags/{resourceArn+}', 'responseCode' => 204, ], 'input' => [ 'shape' => 'TagResourceRequest', 'locationName' => 'TagResourceRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'output' => [ 'shape' => 'TagResourceResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'UntagResource' => [ 'name' => 'UntagResource', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/tags/{resourceArn+}', 'responseCode' => 204, ], 'input' => [ 'shape' => 'UntagResourceRequest', ], 'output' => [ 'shape' => 'UntagResourceResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'UpdateJobPriority' => [ 'name' => 'UpdateJobPriority', 'http' => [ 'method' => 'POST', 'requestUri' => '/v20180820/jobs/{id}/priority', ], 'input' => [ 'shape' => 'UpdateJobPriorityRequest', ], 'output' => [ 'shape' => 'UpdateJobPriorityResult', ], 'errors' => [ [ 'shape' => 'BadRequestException', ], [ 'shape' => 'TooManyRequestsException', ], [ 'shape' => 'NotFoundException', ], [ 'shape' => 'InternalServiceException', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'UpdateJobStatus' => [ 'name' => 'UpdateJobStatus', 'http' => [ 'method' => 'POST', 'requestUri' => '/v20180820/jobs/{id}/status', ], 'input' => [ 'shape' => 'UpdateJobStatusRequest', ], 'output' => [ 'shape' => 'UpdateJobStatusResult', ], 'errors' => [ [ 'shape' => 'BadRequestException', ], [ 'shape' => 'TooManyRequestsException', ], [ 'shape' => 'NotFoundException', ], [ 'shape' => 'JobStatusException', ], [ 'shape' => 'InternalServiceException', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'UpdateStorageLensGroup' => [ 'name' => 'UpdateStorageLensGroup', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/storagelensgroup/{name}', 'responseCode' => 204, ], 'input' => [ 'shape' => 'UpdateStorageLensGroupRequest', 'locationName' => 'UpdateStorageLensGroupRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], ], 'shapes' => [ 'AbortIncompleteMultipartUpload' => [ 'type' => 'structure', 'members' => [ 'DaysAfterInitiation' => [ 'shape' => 'DaysAfterInitiation', ], ], ], 'AccessControlTranslation' => [ 'type' => 'structure', 'required' => [ 'Owner', ], 'members' => [ 'Owner' => [ 'shape' => 'OwnerOverride', ], ], ], 'AccessPoint' => [ 'type' => 'structure', 'required' => [ 'Name', 'NetworkOrigin', 'Bucket', ], 'members' => [ 'Name' => [ 'shape' => 'AccessPointName', ], 'NetworkOrigin' => [ 'shape' => 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'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'StorageLensGroup' => [ 'shape' => 'StorageLensGroup', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreationDate' => [ 'type' => 'timestamp', ], 'CreationTimestamp' => [ 'type' => 'timestamp', ], 'Date' => [ 'type' => 'timestamp', ], 'Days' => [ 'type' => 'integer', ], 'DaysAfterInitiation' => [ 'type' => 'integer', ], 'DeleteAccessPointForObjectLambdaRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'ObjectLambdaAccessPointName', 'location' => 'uri', 'locationName' => 'name', ], ], ], 'DeleteAccessPointPolicyForObjectLambdaRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'ObjectLambdaAccessPointName', 'location' => 'uri', 'locationName' => 'name', ], ], ], 'DeleteAccessPointPolicyRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'AccessPointName', 'contextParam' => [ 'name' => 'AccessPointName', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'DeleteAccessPointRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'AccessPointName', 'contextParam' => [ 'name' => 'AccessPointName', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'DeleteBucketLifecycleConfigurationRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'DeleteBucketPolicyRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'DeleteBucketReplicationRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'DeleteBucketRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'DeleteBucketTaggingRequest' => [ 'type' => 'structure', 'required' => [ 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'type' => 'string', 'enum' => [ 'Enabled', 'Disabled', ], ], 'DeleteMultiRegionAccessPointInput' => [ 'type' => 'structure', 'required' => [ 'Name', ], 'members' => [ 'Name' => [ 'shape' => 'MultiRegionAccessPointName', ], ], ], 'DeleteMultiRegionAccessPointRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'ClientToken', 'Details', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'ClientToken' => [ 'shape' => 'MultiRegionAccessPointClientToken', 'idempotencyToken' => true, ], 'Details' => [ 'shape' => 'DeleteMultiRegionAccessPointInput', ], ], ], 'DeleteMultiRegionAccessPointResult' => [ 'type' => 'structure', 'members' => [ 'RequestTokenARN' => [ 'shape' => 'AsyncRequestTokenARN', ], ], ], 'DeletePublicAccessBlockRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], ], ], 'DeleteStorageLensConfigurationRequest' => [ 'type' => 'structure', 'required' => [ 'ConfigId', 'AccountId', ], 'members' => [ 'ConfigId' => [ 'shape' => 'ConfigId', 'location' => 'uri', 'locationName' => 'storagelensid', ], 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], ], ], 'DeleteStorageLensConfigurationTaggingRequest' => [ 'type' => 'structure', 'required' => [ 'ConfigId', 'AccountId', ], 'members' => [ 'ConfigId' => [ 'shape' => 'ConfigId', 'location' => 'uri', 'locationName' => 'storagelensid', ], 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], ], ], 'DeleteStorageLensConfigurationTaggingResult' => [ 'type' => 'structure', 'members' => [], ], 'DeleteStorageLensGroupRequest' => [ 'type' => 'structure', 'required' => [ 'Name', 'AccountId', ], 'members' => [ 'Name' => [ 'shape' => 'StorageLensGroupName', 'location' => 'uri', 'locationName' => 'name', ], 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], ], ], 'DescribeJobRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'JobId', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'JobId' => [ 'shape' => 'JobId', 'location' => 'uri', 'locationName' => 'id', ], ], ], 'DescribeJobResult' => [ 'type' => 'structure', 'members' => [ 'Job' => [ 'shape' => 'JobDescriptor', ], ], ], 'DescribeMultiRegionAccessPointOperationRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'RequestTokenARN', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'RequestTokenARN' => [ 'shape' => 'AsyncRequestTokenARN', 'location' => 'uri', 'locationName' => 'request_token', ], ], ], 'DescribeMultiRegionAccessPointOperationResult' => [ 'type' => 'structure', 'members' => [ 'AsyncOperation' => [ 'shape' => 'AsyncOperation', ], ], ], 'Destination' => [ 'type' => 'structure', 'required' => [ 'Bucket', ], 'members' => [ 'Account' => [ 'shape' => 'AccountId', ], 'Bucket' => [ 'shape' => 'BucketIdentifierString', ], 'ReplicationTime' => [ 'shape' => 'ReplicationTime', ], 'AccessControlTranslation' => [ 'shape' => 'AccessControlTranslation', ], 'EncryptionConfiguration' => [ 'shape' => 'EncryptionConfiguration', ], 'Metrics' => [ 'shape' => 'Metrics', ], 'StorageClass' => [ 'shape' => 'ReplicationStorageClass', ], ], ], 'DetailedStatusCodesMetrics' => [ 'type' => 'structure', 'members' => [ 'IsEnabled' => [ 'shape' => 'IsEnabled', ], ], ], 'EncryptionConfiguration' => [ 'type' => 'structure', 'members' => [ 'ReplicaKmsKeyID' => [ 'shape' => 'ReplicaKmsKeyID', 'box' => true, ], ], ], 'Endpoints' => [ 'type' => 'map', 'key' => [ 'shape' => 'NonEmptyMaxLength64String', ], 'value' => [ 'shape' => 'NonEmptyMaxLength1024String', ], ], 'EstablishedMultiRegionAccessPointPolicy' => [ 'type' => 'structure', 'members' => [ 'Policy' => [ 'shape' => 'Policy', ], ], ], 'ExceptionMessage' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, ], 'Exclude' => [ 'type' => 'structure', 'members' => [ 'Buckets' => [ 'shape' => 'Buckets', ], 'Regions' => [ 'shape' => 'Regions', ], ], ], 'ExistingObjectReplication' => [ 'type' => 'structure', 'required' => [ 'Status', ], 'members' => [ 'Status' => [ 'shape' => 'ExistingObjectReplicationStatus', ], ], ], 'ExistingObjectReplicationStatus' => [ 'type' => 'string', 'enum' => [ 'Enabled', 'Disabled', ], ], 'ExpirationStatus' => [ 'type' => 'string', 'enum' => [ 'Enabled', 'Disabled', ], ], 'ExpiredObjectDeleteMarker' => [ 'type' => 'boolean', ], 'Format' => [ 'type' => 'string', 'enum' => [ 'CSV', 'Parquet', ], ], 'FunctionArnString' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, 'pattern' => '(arn:(aws[a-zA-Z-]*)?:lambda:)?([a-z]{2}((-gov)|(-iso(b?)))?-[a-z]+-\\d{1}:)?(\\d{12}:)?(function:)?([a-zA-Z0-9-_]+)(:(\\$LATEST|[a-zA-Z0-9-_]+))?', ], 'GeneratedManifestEncryption' => [ 'type' => 'structure', 'members' => [ 'SSES3' => [ 'shape' => 'SSES3Encryption', 'locationName' => 'SSE-S3', ], 'SSEKMS' => [ 'shape' => 'SSEKMSEncryption', 'locationName' => 'SSE-KMS', ], ], ], 'GeneratedManifestFormat' => [ 'type' => 'string', 'enum' => [ 'S3InventoryReport_CSV_20211130', ], ], 'GetAccessPointConfigurationForObjectLambdaRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'ObjectLambdaAccessPointName', 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetAccessPointConfigurationForObjectLambdaResult' => [ 'type' => 'structure', 'members' => [ 'Configuration' => [ 'shape' => 'ObjectLambdaConfiguration', ], ], ], 'GetAccessPointForObjectLambdaRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'ObjectLambdaAccessPointName', 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetAccessPointForObjectLambdaResult' => [ 'type' => 'structure', 'members' => [ 'Name' => [ 'shape' => 'ObjectLambdaAccessPointName', ], 'PublicAccessBlockConfiguration' => [ 'shape' => 'PublicAccessBlockConfiguration', ], 'CreationDate' => [ 'shape' => 'CreationDate', ], 'Alias' => [ 'shape' => 'ObjectLambdaAccessPointAlias', ], ], ], 'GetAccessPointPolicyForObjectLambdaRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'ObjectLambdaAccessPointName', 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetAccessPointPolicyForObjectLambdaResult' => [ 'type' => 'structure', 'members' => [ 'Policy' => [ 'shape' => 'ObjectLambdaPolicy', ], ], ], 'GetAccessPointPolicyRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'AccessPointName', 'contextParam' => [ 'name' => 'AccessPointName', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetAccessPointPolicyResult' => [ 'type' => 'structure', 'members' => [ 'Policy' => [ 'shape' => 'Policy', ], ], ], 'GetAccessPointPolicyStatusForObjectLambdaRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'ObjectLambdaAccessPointName', 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetAccessPointPolicyStatusForObjectLambdaResult' => [ 'type' => 'structure', 'members' => [ 'PolicyStatus' => [ 'shape' => 'PolicyStatus', ], ], ], 'GetAccessPointPolicyStatusRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'AccessPointName', 'contextParam' => [ 'name' => 'AccessPointName', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetAccessPointPolicyStatusResult' => [ 'type' => 'structure', 'members' => [ 'PolicyStatus' => [ 'shape' => 'PolicyStatus', ], ], ], 'GetAccessPointRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'AccessPointName', 'contextParam' => [ 'name' => 'AccessPointName', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetAccessPointResult' => [ 'type' => 'structure', 'members' => [ 'Name' => [ 'shape' => 'AccessPointName', ], 'Bucket' => [ 'shape' => 'BucketName', ], 'NetworkOrigin' => [ 'shape' => 'NetworkOrigin', ], 'VpcConfiguration' => [ 'shape' => 'VpcConfiguration', ], 'PublicAccessBlockConfiguration' => [ 'shape' => 'PublicAccessBlockConfiguration', ], 'CreationDate' => [ 'shape' => 'CreationDate', ], 'Alias' => [ 'shape' => 'Alias', ], 'AccessPointArn' => [ 'shape' => 'S3AccessPointArn', ], 'Endpoints' => [ 'shape' => 'Endpoints', ], 'BucketAccountId' => [ 'shape' => 'AccountId', ], ], ], 'GetBucketLifecycleConfigurationRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetBucketLifecycleConfigurationResult' => [ 'type' => 'structure', 'members' => [ 'Rules' => [ 'shape' => 'LifecycleRules', ], ], ], 'GetBucketPolicyRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetBucketPolicyResult' => [ 'type' => 'structure', 'members' => [ 'Policy' => [ 'shape' => 'Policy', ], ], ], 'GetBucketReplicationRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetBucketReplicationResult' => [ 'type' => 'structure', 'members' => [ 'ReplicationConfiguration' => [ 'shape' => 'ReplicationConfiguration', ], ], ], 'GetBucketRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetBucketResult' => [ 'type' => 'structure', 'members' => [ 'Bucket' => [ 'shape' => 'BucketName', ], 'PublicAccessBlockEnabled' => [ 'shape' => 'PublicAccessBlockEnabled', ], 'CreationDate' => [ 'shape' => 'CreationDate', ], ], ], 'GetBucketTaggingRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetBucketTaggingResult' => [ 'type' => 'structure', 'required' => [ 'TagSet', ], 'members' => [ 'TagSet' => [ 'shape' => 'S3TagSet', ], ], ], 'GetBucketVersioningRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetBucketVersioningResult' => [ 'type' => 'structure', 'members' => [ 'Status' => [ 'shape' => 'BucketVersioningStatus', ], 'MFADelete' => [ 'shape' => 'MFADeleteStatus', 'locationName' => 'MfaDelete', ], ], ], 'GetJobTaggingRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'JobId', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'JobId' => [ 'shape' => 'JobId', 'location' => 'uri', 'locationName' => 'id', ], ], ], 'GetJobTaggingResult' => [ 'type' => 'structure', 'members' => [ 'Tags' => [ 'shape' => 'S3TagSet', ], ], ], 'GetMultiRegionAccessPointPolicyRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'MultiRegionAccessPointName', 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetMultiRegionAccessPointPolicyResult' => [ 'type' => 'structure', 'members' => [ 'Policy' => [ 'shape' => 'MultiRegionAccessPointPolicyDocument', ], ], ], 'GetMultiRegionAccessPointPolicyStatusRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'MultiRegionAccessPointName', 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetMultiRegionAccessPointPolicyStatusResult' => [ 'type' => 'structure', 'members' => [ 'Established' => [ 'shape' => 'PolicyStatus', ], ], ], 'GetMultiRegionAccessPointRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'MultiRegionAccessPointName', 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetMultiRegionAccessPointResult' => [ 'type' => 'structure', 'members' => [ 'AccessPoint' => [ 'shape' => 'MultiRegionAccessPointReport', ], ], ], 'GetMultiRegionAccessPointRoutesRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Mrap', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Mrap' => [ 'shape' => 'MultiRegionAccessPointId', 'location' => 'uri', 'locationName' => 'mrap', ], ], ], 'GetMultiRegionAccessPointRoutesResult' => [ 'type' => 'structure', 'members' => [ 'Mrap' => [ 'shape' => 'MultiRegionAccessPointId', ], 'Routes' => [ 'shape' => 'RouteList', ], ], ], 'GetPublicAccessBlockOutput' => [ 'type' => 'structure', 'members' => [ 'PublicAccessBlockConfiguration' => [ 'shape' => 'PublicAccessBlockConfiguration', ], ], 'payload' => 'PublicAccessBlockConfiguration', ], 'GetPublicAccessBlockRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], ], ], 'GetStorageLensConfigurationRequest' => [ 'type' => 'structure', 'required' => [ 'ConfigId', 'AccountId', ], 'members' => [ 'ConfigId' => [ 'shape' => 'ConfigId', 'location' => 'uri', 'locationName' => 'storagelensid', ], 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], ], ], 'GetStorageLensConfigurationResult' => [ 'type' => 'structure', 'members' => [ 'StorageLensConfiguration' => [ 'shape' => 'StorageLensConfiguration', ], ], 'payload' => 'StorageLensConfiguration', ], 'GetStorageLensConfigurationTaggingRequest' => [ 'type' => 'structure', 'required' => [ 'ConfigId', 'AccountId', ], 'members' => [ 'ConfigId' => [ 'shape' => 'ConfigId', 'location' => 'uri', 'locationName' => 'storagelensid', ], 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], ], ], 'GetStorageLensConfigurationTaggingResult' => [ 'type' => 'structure', 'members' => [ 'Tags' => [ 'shape' => 'StorageLensTags', ], ], ], 'GetStorageLensGroupRequest' => [ 'type' => 'structure', 'required' => [ 'Name', 'AccountId', ], 'members' => [ 'Name' => [ 'shape' => 'StorageLensGroupName', 'location' => 'uri', 'locationName' => 'name', ], 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], ], ], 'GetStorageLensGroupResult' => [ 'type' => 'structure', 'members' => [ 'StorageLensGroup' => [ 'shape' => 'StorageLensGroup', ], ], 'payload' => 'StorageLensGroup', ], 'GrantFullControl' => [ 'type' => 'string', ], 'GrantRead' => [ 'type' => 'string', ], 'GrantReadACP' => [ 'type' => 'string', ], 'GrantWrite' => [ 'type' => 'string', ], 'GrantWriteACP' => [ 'type' => 'string', ], 'IAMRoleArn' => [ 'type' => 'string', 'max' => 2048, 'min' => 1, 'pattern' => 'arn:[^:]+:iam::\\d{12}:role/.*', ], 'ID' => [ 'type' => 'string', ], 'IdempotencyException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'ExceptionMessage', ], ], 'exception' => true, ], 'Include' => [ 'type' => 'structure', 'members' => [ 'Buckets' => [ 'shape' => 'Buckets', ], 'Regions' => [ 'shape' => 'Regions', ], ], ], 'InternalServiceException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'ExceptionMessage', ], ], 'exception' => true, 'fault' => true, ], 'InvalidNextTokenException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'ExceptionMessage', ], ], 'exception' => true, ], 'InvalidRequestException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'ExceptionMessage', ], ], 'exception' => true, ], 'IsEnabled' => [ 'type' => 'boolean', ], 'IsPublic' => [ 'type' => 'boolean', ], 'JobArn' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, 'pattern' => 'arn:[^:]+:s3:[a-zA-Z0-9\\-]+:\\d{12}:job\\/.*', ], 'JobCreationTime' => [ 'type' => 'timestamp', ], 'JobDescriptor' => [ 'type' => 'structure', 'members' => [ 'JobId' => [ 'shape' => 'JobId', ], 'ConfirmationRequired' => [ 'shape' => 'ConfirmationRequired', 'box' => true, ], 'Description' => [ 'shape' => 'NonEmptyMaxLength256String', 'box' => true, ], 'JobArn' => [ 'shape' => 'JobArn', 'box' => true, ], 'Status' => [ 'shape' => 'JobStatus', ], 'Manifest' => [ 'shape' => 'JobManifest', 'box' => true, ], 'Operation' => [ 'shape' => 'JobOperation', 'box' => true, ], 'Priority' => [ 'shape' => 'JobPriority', ], 'ProgressSummary' => [ 'shape' => 'JobProgressSummary', 'box' => true, ], 'StatusUpdateReason' => [ 'shape' => 'JobStatusUpdateReason', 'box' => true, ], 'FailureReasons' => [ 'shape' => 'JobFailureList', 'box' => true, ], 'Report' => [ 'shape' => 'JobReport', 'box' => true, ], 'CreationTime' => [ 'shape' => 'JobCreationTime', ], 'TerminationDate' => [ 'shape' => 'JobTerminationDate', 'box' => true, ], 'RoleArn' => [ 'shape' => 'IAMRoleArn', 'box' => true, ], 'SuspendedDate' => [ 'shape' => 'SuspendedDate', 'box' => true, ], 'SuspendedCause' => [ 'shape' => 'SuspendedCause', 'box' => true, ], 'ManifestGenerator' => [ 'shape' => 'JobManifestGenerator', ], 'GeneratedManifestDescriptor' => [ 'shape' => 'S3GeneratedManifestDescriptor', ], ], ], 'JobFailure' => [ 'type' => 'structure', 'members' => [ 'FailureCode' => [ 'shape' => 'JobFailureCode', ], 'FailureReason' => [ 'shape' => 'JobFailureReason', ], ], ], 'JobFailureCode' => [ 'type' => 'string', 'max' => 64, 'min' => 1, ], 'JobFailureList' => [ 'type' => 'list', 'member' => [ 'shape' => 'JobFailure', ], ], 'JobFailureReason' => [ 'type' => 'string', 'max' => 256, 'min' => 1, ], 'JobId' => [ 'type' => 'string', 'max' => 36, 'min' => 5, 'pattern' => '[a-zA-Z0-9\\-\\_]+', ], 'JobListDescriptor' => [ 'type' => 'structure', 'members' => [ 'JobId' => [ 'shape' => 'JobId', ], 'Description' => [ 'shape' => 'NonEmptyMaxLength256String', ], 'Operation' => [ 'shape' => 'OperationName', ], 'Priority' => [ 'shape' => 'JobPriority', ], 'Status' => [ 'shape' => 'JobStatus', ], 'CreationTime' => [ 'shape' => 'JobCreationTime', ], 'TerminationDate' => [ 'shape' => 'JobTerminationDate', ], 'ProgressSummary' => [ 'shape' => 'JobProgressSummary', ], ], ], 'JobListDescriptorList' => [ 'type' => 'list', 'member' => [ 'shape' => 'JobListDescriptor', ], ], 'JobManifest' => [ 'type' => 'structure', 'required' => [ 'Spec', 'Location', ], 'members' => [ 'Spec' => [ 'shape' => 'JobManifestSpec', ], 'Location' => [ 'shape' => 'JobManifestLocation', ], ], ], 'JobManifestFieldList' => [ 'type' => 'list', 'member' => [ 'shape' => 'JobManifestFieldName', ], ], 'JobManifestFieldName' => [ 'type' => 'string', 'enum' => [ 'Ignore', 'Bucket', 'Key', 'VersionId', ], ], 'JobManifestFormat' => [ 'type' => 'string', 'enum' => [ 'S3BatchOperations_CSV_20180820', 'S3InventoryReport_CSV_20161130', ], ], 'JobManifestGenerator' => [ 'type' => 'structure', 'members' => [ 'S3JobManifestGenerator' => [ 'shape' => 'S3JobManifestGenerator', ], ], 'union' => true, ], 'JobManifestGeneratorFilter' => [ 'type' => 'structure', 'members' => [ 'EligibleForReplication' => [ 'shape' => 'Boolean', 'box' => true, ], 'CreatedAfter' => [ 'shape' => 'ObjectCreationTime', ], 'CreatedBefore' => [ 'shape' => 'ObjectCreationTime', ], 'ObjectReplicationStatuses' => [ 'shape' => 'ReplicationStatusFilterList', ], ], ], 'JobManifestLocation' => [ 'type' => 'structure', 'required' => [ 'ObjectArn', 'ETag', ], 'members' => [ 'ObjectArn' => [ 'shape' => 'S3KeyArnString', ], 'ObjectVersionId' => [ 'shape' => 'S3ObjectVersionId', 'box' => true, ], 'ETag' => [ 'shape' => 'NonEmptyMaxLength1024String', ], ], ], 'JobManifestSpec' => [ 'type' => 'structure', 'required' => [ 'Format', ], 'members' => [ 'Format' => [ 'shape' => 'JobManifestFormat', ], 'Fields' => [ 'shape' => 'JobManifestFieldList', 'box' => true, ], ], ], 'JobNumberOfTasksFailed' => [ 'type' => 'long', 'min' => 0, ], 'JobNumberOfTasksSucceeded' => [ 'type' => 'long', 'min' => 0, ], 'JobOperation' => [ 'type' => 'structure', 'members' => [ 'LambdaInvoke' => [ 'shape' => 'LambdaInvokeOperation', 'box' => true, ], 'S3PutObjectCopy' => [ 'shape' => 'S3CopyObjectOperation', 'box' => true, ], 'S3PutObjectAcl' => [ 'shape' => 'S3SetObjectAclOperation', 'box' => true, ], 'S3PutObjectTagging' => [ 'shape' => 'S3SetObjectTaggingOperation', 'box' => true, ], 'S3DeleteObjectTagging' => [ 'shape' => 'S3DeleteObjectTaggingOperation', 'box' => true, ], 'S3InitiateRestoreObject' => [ 'shape' => 'S3InitiateRestoreObjectOperation', 'box' => true, ], 'S3PutObjectLegalHold' => [ 'shape' => 'S3SetObjectLegalHoldOperation', 'box' => true, ], 'S3PutObjectRetention' => [ 'shape' => 'S3SetObjectRetentionOperation', 'box' => true, ], 'S3ReplicateObject' => [ 'shape' => 'S3ReplicateObjectOperation', 'box' => true, ], ], ], 'JobPriority' => [ 'type' => 'integer', 'max' => 2147483647, 'min' => 0, ], 'JobProgressSummary' => [ 'type' => 'structure', 'members' => [ 'TotalNumberOfTasks' => [ 'shape' => 'JobTotalNumberOfTasks', 'box' => true, ], 'NumberOfTasksSucceeded' => [ 'shape' => 'JobNumberOfTasksSucceeded', 'box' => true, ], 'NumberOfTasksFailed' => [ 'shape' => 'JobNumberOfTasksFailed', 'box' => true, ], 'Timers' => [ 'shape' => 'JobTimers', ], ], ], 'JobReport' => [ 'type' => 'structure', 'required' => [ 'Enabled', ], 'members' => [ 'Bucket' => [ 'shape' => 'S3BucketArnString', 'box' => true, ], 'Format' => [ 'shape' => 'JobReportFormat', 'box' => true, ], 'Enabled' => [ 'shape' => 'Boolean', ], 'Prefix' => [ 'shape' => 'ReportPrefixString', 'box' => true, ], 'ReportScope' => [ 'shape' => 'JobReportScope', 'box' => true, ], ], ], 'JobReportFormat' => [ 'type' => 'string', 'enum' => [ 'Report_CSV_20180820', ], ], 'JobReportScope' => [ 'type' => 'string', 'enum' => [ 'AllTasks', 'FailedTasksOnly', ], ], 'JobStatus' => [ 'type' => 'string', 'enum' => [ 'Active', 'Cancelled', 'Cancelling', 'Complete', 'Completing', 'Failed', 'Failing', 'New', 'Paused', 'Pausing', 'Preparing', 'Ready', 'Suspended', ], ], 'JobStatusException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'ExceptionMessage', ], ], 'exception' => true, ], 'JobStatusList' => [ 'type' => 'list', 'member' => [ 'shape' => 'JobStatus', ], ], 'JobStatusUpdateReason' => [ 'type' => 'string', 'max' => 256, 'min' => 1, ], 'JobTerminationDate' => [ 'type' => 'timestamp', ], 'JobTimeInStateSeconds' => [ 'type' => 'long', 'min' => 0, ], 'JobTimers' => [ 'type' => 'structure', 'members' => [ 'ElapsedTimeInActiveSeconds' => [ 'shape' => 'JobTimeInStateSeconds', 'box' => true, ], ], ], 'JobTotalNumberOfTasks' => [ 'type' => 'long', 'min' => 0, ], 'KmsKeyArnString' => [ 'type' => 'string', 'max' => 2000, 'min' => 1, ], 'LambdaInvokeOperation' => [ 'type' => 'structure', 'members' => [ 'FunctionArn' => [ 'shape' => 'FunctionArnString', ], ], ], 'LifecycleConfiguration' => [ 'type' => 'structure', 'members' => [ 'Rules' => [ 'shape' => 'LifecycleRules', ], ], ], 'LifecycleExpiration' => [ 'type' => 'structure', 'members' => [ 'Date' => [ 'shape' => 'Date', ], 'Days' => [ 'shape' => 'Days', ], 'ExpiredObjectDeleteMarker' => [ 'shape' => 'ExpiredObjectDeleteMarker', ], ], ], 'LifecycleRule' => [ 'type' => 'structure', 'required' => [ 'Status', ], 'members' => [ 'Expiration' => [ 'shape' => 'LifecycleExpiration', ], 'ID' => [ 'shape' => 'ID', ], 'Filter' => [ 'shape' => 'LifecycleRuleFilter', ], 'Status' => [ 'shape' => 'ExpirationStatus', ], 'Transitions' => [ 'shape' => 'TransitionList', ], 'NoncurrentVersionTransitions' => [ 'shape' => 'NoncurrentVersionTransitionList', ], 'NoncurrentVersionExpiration' => [ 'shape' => 'NoncurrentVersionExpiration', ], 'AbortIncompleteMultipartUpload' => [ 'shape' => 'AbortIncompleteMultipartUpload', ], ], ], 'LifecycleRuleAndOperator' => [ 'type' => 'structure', 'members' => [ 'Prefix' => [ 'shape' => 'Prefix', ], 'Tags' => [ 'shape' => 'S3TagSet', ], 'ObjectSizeGreaterThan' => [ 'shape' => 'ObjectSizeGreaterThanBytes', 'box' => true, ], 'ObjectSizeLessThan' => [ 'shape' => 'ObjectSizeLessThanBytes', 'box' => true, ], ], ], 'LifecycleRuleFilter' => [ 'type' => 'structure', 'members' => [ 'Prefix' => [ 'shape' => 'Prefix', ], 'Tag' => [ 'shape' => 'S3Tag', ], 'And' => [ 'shape' => 'LifecycleRuleAndOperator', ], 'ObjectSizeGreaterThan' => [ 'shape' => 'ObjectSizeGreaterThanBytes', 'box' => true, ], 'ObjectSizeLessThan' => [ 'shape' => 'ObjectSizeLessThanBytes', 'box' => true, ], ], ], 'LifecycleRules' => [ 'type' => 'list', 'member' => [ 'shape' => 'LifecycleRule', 'locationName' => 'Rule', ], ], 'ListAccessPointsForObjectLambdaRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'NextToken' => [ 'shape' => 'NonEmptyMaxLength1024String', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResults', 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListAccessPointsForObjectLambdaResult' => [ 'type' => 'structure', 'members' => [ 'ObjectLambdaAccessPointList' => [ 'shape' => 'ObjectLambdaAccessPointList', ], 'NextToken' => [ 'shape' => 'NonEmptyMaxLength1024String', ], ], ], 'ListAccessPointsRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'querystring', 'locationName' => 'bucket', ], 'NextToken' => [ 'shape' => 'NonEmptyMaxLength1024String', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResults', 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListAccessPointsResult' => [ 'type' => 'structure', 'members' => [ 'AccessPointList' => [ 'shape' => 'AccessPointList', ], 'NextToken' => [ 'shape' => 'NonEmptyMaxLength1024String', ], ], ], 'ListJobsRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'JobStatuses' => [ 'shape' => 'JobStatusList', 'location' => 'querystring', 'locationName' => 'jobStatuses', ], 'NextToken' => [ 'shape' => 'StringForNextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResults', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListJobsResult' => [ 'type' => 'structure', 'members' => [ 'NextToken' => [ 'shape' => 'StringForNextToken', ], 'Jobs' => [ 'shape' => 'JobListDescriptorList', ], ], ], 'ListMultiRegionAccessPointsRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'NextToken' => [ 'shape' => 'NonEmptyMaxLength1024String', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResults', 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListMultiRegionAccessPointsResult' => [ 'type' => 'structure', 'members' => [ 'AccessPoints' => [ 'shape' => 'MultiRegionAccessPointReportList', ], 'NextToken' => [ 'shape' => 'NonEmptyMaxLength1024String', ], ], ], 'ListRegionalBucketsRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'NextToken' => [ 'shape' => 'NonEmptyMaxLength1024String', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResults', 'location' => 'querystring', 'locationName' => 'maxResults', ], 'OutpostId' => [ 'shape' => 'NonEmptyMaxLength64String', 'contextParam' => [ 'name' => 'OutpostId', ], 'location' => 'header', 'locationName' => 'x-amz-outpost-id', ], ], ], 'ListRegionalBucketsResult' => [ 'type' => 'structure', 'members' => [ 'RegionalBucketList' => [ 'shape' => 'RegionalBucketList', ], 'NextToken' => [ 'shape' => 'NonEmptyMaxLength1024String', ], ], ], 'ListStorageLensConfigurationEntry' => [ 'type' => 'structure', 'required' => [ 'Id', 'StorageLensArn', 'HomeRegion', ], 'members' => [ 'Id' => [ 'shape' => 'ConfigId', ], 'StorageLensArn' => [ 'shape' => 'StorageLensArn', ], 'HomeRegion' => [ 'shape' => 'S3AWSRegion', ], 'IsEnabled' => [ 'shape' => 'IsEnabled', ], ], ], 'ListStorageLensConfigurationsRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'NextToken' => [ 'shape' => 'ContinuationToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], ], ], 'ListStorageLensConfigurationsResult' => [ 'type' => 'structure', 'members' => [ 'NextToken' => [ 'shape' => 'ContinuationToken', ], 'StorageLensConfigurationList' => [ 'shape' => 'StorageLensConfigurationList', ], ], ], 'ListStorageLensGroupEntry' => [ 'type' => 'structure', 'required' => [ 'Name', 'StorageLensGroupArn', 'HomeRegion', ], 'members' => [ 'Name' => [ 'shape' => 'StorageLensGroupName', ], 'StorageLensGroupArn' => [ 'shape' => 'StorageLensGroupArn', ], 'HomeRegion' => [ 'shape' => 'S3AWSRegion', ], ], ], 'ListStorageLensGroupsRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'NextToken' => [ 'shape' => 'ContinuationToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], ], ], 'ListStorageLensGroupsResult' => [ 'type' => 'structure', 'members' => [ 'NextToken' => [ 'shape' => 'ContinuationToken', ], 'StorageLensGroupList' => [ 'shape' => 'StorageLensGroupList', ], ], ], 'ListTagsForResourceRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'ResourceArn', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'ResourceArn' => [ 'shape' => 'S3ResourceArn', 'location' => 'uri', 'locationName' => 'resourceArn', ], ], ], 'ListTagsForResourceResult' => [ 'type' => 'structure', 'members' => [ 'Tags' => [ 'shape' => 'TagList', ], ], ], 'Location' => [ 'type' => 'string', ], 'MFA' => [ 'type' => 'string', ], 'MFADelete' => [ 'type' => 'string', 'enum' => [ 'Enabled', 'Disabled', ], ], 'MFADeleteStatus' => [ 'type' => 'string', 'enum' => [ 'Enabled', 'Disabled', ], ], 'ManifestPrefixString' => [ 'type' => 'string', 'max' => 512, 'min' => 1, ], 'MatchAnyPrefix' => [ 'type' => 'list', 'member' => [ 'shape' => 'Prefix', 'locationName' => 'Prefix', ], ], 'MatchAnySuffix' => [ 'type' => 'list', 'member' => [ 'shape' => 'Suffix', 'locationName' => 'Suffix', ], ], 'MatchAnyTag' => [ 'type' => 'list', 'member' => [ 'shape' => 'S3Tag', 'locationName' => 'Tag', ], ], 'MatchObjectAge' => [ 'type' => 'structure', 'members' => [ 'DaysGreaterThan' => [ 'shape' => 'ObjectAgeValue', ], 'DaysLessThan' => [ 'shape' => 'ObjectAgeValue', ], ], ], 'MatchObjectSize' => [ 'type' => 'structure', 'members' => [ 'BytesGreaterThan' => [ 'shape' => 'ObjectSizeValue', ], 'BytesLessThan' => [ 'shape' => 'ObjectSizeValue', ], ], ], 'MaxLength1024String' => [ 'type' => 'string', 'max' => 1024, ], 'MaxResults' => [ 'type' => 'integer', 'max' => 1000, 'min' => 0, ], 'Metrics' => [ 'type' => 'structure', 'required' => [ 'Status', ], 'members' => [ 'Status' => [ 'shape' => 'MetricsStatus', ], 'EventThreshold' => [ 'shape' => 'ReplicationTimeValue', ], ], ], 'MetricsStatus' => [ 'type' => 'string', 'enum' => [ 'Enabled', 'Disabled', ], ], 'MinStorageBytesPercentage' => [ 'type' => 'double', 'max' => 100, 'min' => 0.1, ], 'Minutes' => [ 'type' => 'integer', ], 'MultiRegionAccessPointAlias' => [ 'type' => 'string', 'max' => 63, 'pattern' => '^[a-z][a-z0-9]*[.]mrap$', ], 'MultiRegionAccessPointClientToken' => [ 'type' => 'string', 'max' => 64, 'pattern' => '\\S+', ], 'MultiRegionAccessPointId' => [ 'type' => 'string', 'max' => 200, 'pattern' => '^[a-zA-Z0-9\\:.-]{3,200}$', ], 'MultiRegionAccessPointName' => [ 'type' => 'string', 'max' => 50, 'pattern' => '^[a-z0-9][-a-z0-9]{1,48}[a-z0-9]$', ], 'MultiRegionAccessPointPolicyDocument' => [ 'type' => 'structure', 'members' => [ 'Established' => [ 'shape' => 'EstablishedMultiRegionAccessPointPolicy', ], 'Proposed' => [ 'shape' => 'ProposedMultiRegionAccessPointPolicy', ], ], ], 'MultiRegionAccessPointRegionalResponse' => [ 'type' => 'structure', 'members' => [ 'Name' => [ 'shape' => 'RegionName', ], 'RequestStatus' => [ 'shape' => 'AsyncRequestStatus', ], ], ], 'MultiRegionAccessPointRegionalResponseList' => [ 'type' => 'list', 'member' => [ 'shape' => 'MultiRegionAccessPointRegionalResponse', 'locationName' => 'Region', ], ], 'MultiRegionAccessPointReport' => [ 'type' => 'structure', 'members' => [ 'Name' => [ 'shape' => 'MultiRegionAccessPointName', ], 'Alias' => [ 'shape' => 'MultiRegionAccessPointAlias', ], 'CreatedAt' => [ 'shape' => 'CreationTimestamp', ], 'PublicAccessBlock' => [ 'shape' => 'PublicAccessBlockConfiguration', ], 'Status' => [ 'shape' => 'MultiRegionAccessPointStatus', ], 'Regions' => [ 'shape' => 'RegionReportList', ], ], ], 'MultiRegionAccessPointReportList' => [ 'type' => 'list', 'member' => [ 'shape' => 'MultiRegionAccessPointReport', 'locationName' => 'AccessPoint', ], ], 'MultiRegionAccessPointRoute' => [ 'type' => 'structure', 'required' => [ 'TrafficDialPercentage', ], 'members' => [ 'Bucket' => [ 'shape' => 'BucketName', ], 'Region' => [ 'shape' => 'RegionName', ], 'TrafficDialPercentage' => [ 'shape' => 'TrafficDialPercentage', ], ], ], 'MultiRegionAccessPointStatus' => [ 'type' => 'string', 'enum' => [ 'READY', 'INCONSISTENT_ACROSS_REGIONS', 'CREATING', 'PARTIALLY_CREATED', 'PARTIALLY_DELETED', 'DELETING', ], ], 'MultiRegionAccessPointsAsyncResponse' => [ 'type' => 'structure', 'members' => [ 'Regions' => [ 'shape' => 'MultiRegionAccessPointRegionalResponseList', ], ], ], 'NetworkOrigin' => [ 'type' => 'string', 'enum' => [ 'Internet', 'VPC', ], ], 'NoSuchPublicAccessBlockConfiguration' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'NoSuchPublicAccessBlockConfigurationMessage', ], ], 'error' => [ 'httpStatusCode' => 404, ], 'exception' => true, ], 'NoSuchPublicAccessBlockConfigurationMessage' => [ 'type' => 'string', ], 'NonEmptyMaxLength1024String' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, ], 'NonEmptyMaxLength2048String' => [ 'type' => 'string', 'max' => 2048, 'min' => 1, ], 'NonEmptyMaxLength256String' => [ 'type' => 'string', 'max' => 256, 'min' => 1, ], 'NonEmptyMaxLength64String' => [ 'type' => 'string', 'max' => 64, 'min' => 1, ], 'NoncurrentVersionCount' => [ 'type' => 'integer', ], 'NoncurrentVersionExpiration' => [ 'type' => 'structure', 'members' => [ 'NoncurrentDays' => [ 'shape' => 'Days', ], 'NewerNoncurrentVersions' => [ 'shape' => 'NoncurrentVersionCount', 'box' => true, ], ], ], 'NoncurrentVersionTransition' => [ 'type' => 'structure', 'members' => [ 'NoncurrentDays' => [ 'shape' => 'Days', ], 'StorageClass' => [ 'shape' => 'TransitionStorageClass', ], ], ], 'NoncurrentVersionTransitionList' => [ 'type' => 'list', 'member' => [ 'shape' => 'NoncurrentVersionTransition', 'locationName' => 'NoncurrentVersionTransition', ], ], 'NotFoundException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'ExceptionMessage', ], ], 'exception' => true, ], 'ObjectAgeValue' => [ 'type' => 'integer', ], 'ObjectCreationTime' => [ 'type' => 'timestamp', ], 'ObjectLambdaAccessPoint' => [ 'type' => 'structure', 'required' => [ 'Name', ], 'members' => [ 'Name' => [ 'shape' => 'ObjectLambdaAccessPointName', ], 'ObjectLambdaAccessPointArn' => [ 'shape' => 'ObjectLambdaAccessPointArn', ], 'Alias' => [ 'shape' => 'ObjectLambdaAccessPointAlias', ], ], ], 'ObjectLambdaAccessPointAlias' => [ 'type' => 'structure', 'members' => [ 'Value' => [ 'shape' => 'ObjectLambdaAccessPointAliasValue', ], 'Status' => [ 'shape' => 'ObjectLambdaAccessPointAliasStatus', ], ], ], 'ObjectLambdaAccessPointAliasStatus' => [ 'type' => 'string', 'enum' => [ 'PROVISIONING', 'READY', ], 'max' => 16, 'min' => 2, ], 'ObjectLambdaAccessPointAliasValue' => [ 'type' => 'string', 'max' => 63, 'min' => 3, 'pattern' => '^[0-9a-z\\\\-]{3,63}', ], 'ObjectLambdaAccessPointArn' => [ 'type' => 'string', 'max' => 2048, 'min' => 1, 'pattern' => 'arn:[^:]+:s3-object-lambda:[^:]*:\\d{12}:accesspoint/.*', ], 'ObjectLambdaAccessPointList' => [ 'type' => 'list', 'member' => [ 'shape' => 'ObjectLambdaAccessPoint', 'locationName' => 'ObjectLambdaAccessPoint', ], ], 'ObjectLambdaAccessPointName' => [ 'type' => 'string', 'max' => 45, 'min' => 3, 'pattern' => '^[a-z0-9]([a-z0-9\\-]*[a-z0-9])?$', ], 'ObjectLambdaAllowedFeature' => [ 'type' => 'string', 'enum' => [ 'GetObject-Range', 'GetObject-PartNumber', 'HeadObject-Range', 'HeadObject-PartNumber', ], ], 'ObjectLambdaAllowedFeaturesList' => [ 'type' => 'list', 'member' => [ 'shape' => 'ObjectLambdaAllowedFeature', 'locationName' => 'AllowedFeature', ], ], 'ObjectLambdaConfiguration' => [ 'type' => 'structure', 'required' => [ 'SupportingAccessPoint', 'TransformationConfigurations', ], 'members' => [ 'SupportingAccessPoint' => [ 'shape' => 'ObjectLambdaSupportingAccessPointArn', ], 'CloudWatchMetricsEnabled' => [ 'shape' => 'Boolean', ], 'AllowedFeatures' => [ 'shape' => 'ObjectLambdaAllowedFeaturesList', ], 'TransformationConfigurations' => [ 'shape' => 'ObjectLambdaTransformationConfigurationsList', ], ], ], 'ObjectLambdaContentTransformation' => [ 'type' => 'structure', 'members' => [ 'AwsLambda' => [ 'shape' => 'AwsLambdaTransformation', ], ], 'union' => true, ], 'ObjectLambdaPolicy' => [ 'type' => 'string', ], 'ObjectLambdaSupportingAccessPointArn' => [ 'type' => 'string', 'max' => 2048, 'min' => 1, 'pattern' => 'arn:[^:]+:s3:[^:]*:\\d{12}:accesspoint/.*', ], 'ObjectLambdaTransformationConfiguration' => [ 'type' => 'structure', 'required' => [ 'Actions', 'ContentTransformation', ], 'members' => [ 'Actions' => [ 'shape' => 'ObjectLambdaTransformationConfigurationActionsList', ], 'ContentTransformation' => [ 'shape' => 'ObjectLambdaContentTransformation', ], ], ], 'ObjectLambdaTransformationConfigurationAction' => [ 'type' => 'string', 'enum' => [ 'GetObject', 'HeadObject', 'ListObjects', 'ListObjectsV2', ], ], 'ObjectLambdaTransformationConfigurationActionsList' => [ 'type' => 'list', 'member' => [ 'shape' => 'ObjectLambdaTransformationConfigurationAction', 'locationName' => 'Action', ], ], 'ObjectLambdaTransformationConfigurationsList' => [ 'type' => 'list', 'member' => [ 'shape' => 'ObjectLambdaTransformationConfiguration', 'locationName' => 'TransformationConfiguration', ], ], 'ObjectLockEnabledForBucket' => [ 'type' => 'boolean', ], 'ObjectSizeGreaterThanBytes' => [ 'type' => 'long', ], 'ObjectSizeLessThanBytes' => [ 'type' => 'long', ], 'ObjectSizeValue' => [ 'type' => 'long', ], 'OperationName' => [ 'type' => 'string', 'enum' => [ 'LambdaInvoke', 'S3PutObjectCopy', 'S3PutObjectAcl', 'S3PutObjectTagging', 'S3DeleteObjectTagging', 'S3InitiateRestoreObject', 'S3PutObjectLegalHold', 'S3PutObjectRetention', 'S3ReplicateObject', ], ], 'OutputSchemaVersion' => [ 'type' => 'string', 'enum' => [ 'V_1', ], ], 'OwnerOverride' => [ 'type' => 'string', 'enum' => [ 'Destination', ], ], 'Policy' => [ 'type' => 'string', ], 'PolicyStatus' => [ 'type' => 'structure', 'members' => [ 'IsPublic' => [ 'shape' => 'IsPublic', 'locationName' => 'IsPublic', ], ], ], 'Prefix' => [ 'type' => 'string', ], 'PrefixLevel' => [ 'type' => 'structure', 'required' => [ 'StorageMetrics', ], 'members' => [ 'StorageMetrics' => [ 'shape' => 'PrefixLevelStorageMetrics', ], ], ], 'PrefixLevelStorageMetrics' => [ 'type' => 'structure', 'members' => [ 'IsEnabled' => [ 'shape' => 'IsEnabled', ], 'SelectionCriteria' => [ 'shape' => 'SelectionCriteria', ], ], ], 'Priority' => [ 'type' => 'integer', ], 'ProposedMultiRegionAccessPointPolicy' => [ 'type' => 'structure', 'members' => [ 'Policy' => [ 'shape' => 'Policy', ], ], ], 'PublicAccessBlockConfiguration' => [ 'type' => 'structure', 'members' => [ 'BlockPublicAcls' => [ 'shape' => 'Setting', 'locationName' => 'BlockPublicAcls', ], 'IgnorePublicAcls' => [ 'shape' => 'Setting', 'locationName' => 'IgnorePublicAcls', ], 'BlockPublicPolicy' => [ 'shape' => 'Setting', 'locationName' => 'BlockPublicPolicy', ], 'RestrictPublicBuckets' => [ 'shape' => 'Setting', 'locationName' => 'RestrictPublicBuckets', ], ], ], 'PublicAccessBlockEnabled' => [ 'type' => 'boolean', ], 'PutAccessPointConfigurationForObjectLambdaRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', 'Configuration', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'ObjectLambdaAccessPointName', 'location' => 'uri', 'locationName' => 'name', ], 'Configuration' => [ 'shape' => 'ObjectLambdaConfiguration', ], ], ], 'PutAccessPointPolicyForObjectLambdaRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', 'Policy', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'ObjectLambdaAccessPointName', 'location' => 'uri', 'locationName' => 'name', ], 'Policy' => [ 'shape' => 'ObjectLambdaPolicy', ], ], ], 'PutAccessPointPolicyRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', 'Policy', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'AccessPointName', 'contextParam' => [ 'name' => 'AccessPointName', ], 'location' => 'uri', 'locationName' => 'name', ], 'Policy' => [ 'shape' => 'Policy', ], ], ], 'PutBucketLifecycleConfigurationRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], 'LifecycleConfiguration' => [ 'shape' => 'LifecycleConfiguration', 'locationName' => 'LifecycleConfiguration', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], ], 'payload' => 'LifecycleConfiguration', ], 'PutBucketPolicyRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', 'Policy', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], 'ConfirmRemoveSelfBucketAccess' => [ 'shape' => 'ConfirmRemoveSelfBucketAccess', 'location' => 'header', 'locationName' => 'x-amz-confirm-remove-self-bucket-access', ], 'Policy' => [ 'shape' => 'Policy', ], ], ], 'PutBucketReplicationRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', 'ReplicationConfiguration', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], 'ReplicationConfiguration' => [ 'shape' => 'ReplicationConfiguration', 'locationName' => 'ReplicationConfiguration', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], ], 'payload' => 'ReplicationConfiguration', ], 'PutBucketTaggingRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', 'Tagging', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], 'Tagging' => [ 'shape' => 'Tagging', 'locationName' => 'Tagging', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], ], 'payload' => 'Tagging', ], 'PutBucketVersioningRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', 'VersioningConfiguration', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], 'MFA' => [ 'shape' => 'MFA', 'location' => 'header', 'locationName' => 'x-amz-mfa', ], 'VersioningConfiguration' => [ 'shape' => 'VersioningConfiguration', 'locationName' => 'VersioningConfiguration', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], ], 'payload' => 'VersioningConfiguration', ], 'PutJobTaggingRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'JobId', 'Tags', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'JobId' => [ 'shape' => 'JobId', 'location' => 'uri', 'locationName' => 'id', ], 'Tags' => [ 'shape' => 'S3TagSet', ], ], ], 'PutJobTaggingResult' => [ 'type' => 'structure', 'members' => [], ], 'PutMultiRegionAccessPointPolicyInput' => [ 'type' => 'structure', 'required' => [ 'Name', 'Policy', ], 'members' => [ 'Name' => [ 'shape' => 'MultiRegionAccessPointName', ], 'Policy' => [ 'shape' => 'Policy', ], ], ], 'PutMultiRegionAccessPointPolicyRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'ClientToken', 'Details', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'ClientToken' => [ 'shape' => 'MultiRegionAccessPointClientToken', 'idempotencyToken' => true, ], 'Details' => [ 'shape' => 'PutMultiRegionAccessPointPolicyInput', ], ], ], 'PutMultiRegionAccessPointPolicyResult' => [ 'type' => 'structure', 'members' => [ 'RequestTokenARN' => [ 'shape' => 'AsyncRequestTokenARN', ], ], ], 'PutPublicAccessBlockRequest' => [ 'type' => 'structure', 'required' => [ 'PublicAccessBlockConfiguration', 'AccountId', ], 'members' => [ 'PublicAccessBlockConfiguration' => [ 'shape' => 'PublicAccessBlockConfiguration', 'locationName' => 'PublicAccessBlockConfiguration', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], ], 'payload' => 'PublicAccessBlockConfiguration', ], 'PutStorageLensConfigurationRequest' => [ 'type' => 'structure', 'required' => [ 'ConfigId', 'AccountId', 'StorageLensConfiguration', ], 'members' => [ 'ConfigId' => [ 'shape' => 'ConfigId', 'location' => 'uri', 'locationName' => 'storagelensid', ], 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'StorageLensConfiguration' => [ 'shape' => 'StorageLensConfiguration', ], 'Tags' => [ 'shape' => 'StorageLensTags', ], ], ], 'PutStorageLensConfigurationTaggingRequest' => [ 'type' => 'structure', 'required' => [ 'ConfigId', 'AccountId', 'Tags', ], 'members' => [ 'ConfigId' => [ 'shape' => 'ConfigId', 'location' => 'uri', 'locationName' => 'storagelensid', ], 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Tags' => [ 'shape' => 'StorageLensTags', ], ], ], 'PutStorageLensConfigurationTaggingResult' => [ 'type' => 'structure', 'members' => [], ], 'Region' => [ 'type' => 'structure', 'required' => [ 'Bucket', ], 'members' => [ 'Bucket' => [ 'shape' => 'BucketName', ], 'BucketAccountId' => [ 'shape' => 'AccountId', ], ], ], 'RegionCreationList' => [ 'type' => 'list', 'member' => [ 'shape' => 'Region', 'locationName' => 'Region', ], ], 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'type' => 'list', 'member' => [ 'shape' => 'ReplicationStatus', ], ], 'ReplicationStorageClass' => [ 'type' => 'string', 'enum' => [ 'STANDARD', 'REDUCED_REDUNDANCY', 'STANDARD_IA', 'ONEZONE_IA', 'INTELLIGENT_TIERING', 'GLACIER', 'DEEP_ARCHIVE', 'OUTPOSTS', 'GLACIER_IR', ], ], 'ReplicationTime' => [ 'type' => 'structure', 'required' => [ 'Status', 'Time', ], 'members' => [ 'Status' => [ 'shape' => 'ReplicationTimeStatus', ], 'Time' => [ 'shape' => 'ReplicationTimeValue', ], ], ], 'ReplicationTimeStatus' => [ 'type' => 'string', 'enum' => [ 'Enabled', 'Disabled', ], ], 'ReplicationTimeValue' => [ 'type' => 'structure', 'members' => [ 'Minutes' => [ 'shape' => 'Minutes', 'box' => true, ], ], ], 'ReportPrefixString' => [ 'type' => 'string', 'max' => 512, 'min' => 1, ], 'RequestedJobStatus' => [ 'type' => 'string', 'enum' => [ 'Cancelled', 'Ready', ], ], 'Role' => [ 'type' => 'string', ], 'RouteList' => [ 'type' => 'list', 'member' => [ 'shape' => 'MultiRegionAccessPointRoute', 'locationName' => 'Route', ], ], 'S3AWSRegion' => [ 'type' => 'string', 'max' => 30, 'min' => 5, 'pattern' => '[a-z0-9\\-]+', ], 'S3AccessControlList' => [ 'type' => 'structure', 'required' => [ 'Owner', ], 'members' => [ 'Owner' => [ 'shape' => 'S3ObjectOwner', ], 'Grants' => [ 'shape' => 'S3GrantList', ], ], ], 'S3AccessControlPolicy' => [ 'type' => 'structure', 'members' => [ 'AccessControlList' => [ 'shape' => 'S3AccessControlList', 'box' => true, ], 'CannedAccessControlList' => [ 'shape' => 'S3CannedAccessControlList', 'box' => true, ], ], ], 'S3AccessPointArn' => [ 'type' => 'string', 'max' => 128, 'min' => 4, ], 'S3BucketArnString' => [ 'type' => 'string', 'max' => 128, 'min' => 1, 'pattern' => 'arn:[^:]+:s3:.*', ], 'S3BucketDestination' => [ 'type' => 'structure', 'required' => [ 'Format', 'OutputSchemaVersion', 'AccountId', 'Arn', ], 'members' => [ 'Format' => [ 'shape' => 'Format', ], 'OutputSchemaVersion' => [ 'shape' => 'OutputSchemaVersion', ], 'AccountId' => [ 'shape' => 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'HttpExpiresDate' => [ 'shape' => 'TimeStamp', ], 'RequesterCharged' => [ 'shape' => 'Boolean', ], 'SSEAlgorithm' => [ 'shape' => 'S3SSEAlgorithm', ], ], ], 'S3ObjectOwner' => [ 'type' => 'structure', 'members' => [ 'ID' => [ 'shape' => 'NonEmptyMaxLength1024String', ], 'DisplayName' => [ 'shape' => 'NonEmptyMaxLength1024String', ], ], ], 'S3ObjectVersionId' => [ 'type' => 'string', 'max' => 2000, 'min' => 1, ], 'S3Permission' => [ 'type' => 'string', 'enum' => [ 'FULL_CONTROL', 'READ', 'WRITE', 'READ_ACP', 'WRITE_ACP', ], ], 'S3RegionalBucketArn' => [ 'type' => 'string', 'max' => 128, 'min' => 4, ], 'S3ReplicateObjectOperation' => [ 'type' => 'structure', 'members' => [], ], 'S3ResourceArn' => [ 'type' => 'string', 'max' => 1011, 'pattern' => 'arn:[^:]+:s3:[^:].*', ], 'S3Retention' => [ 'type' => 'structure', 'members' => [ 'RetainUntilDate' => [ 'shape' => 'TimeStamp', ], 'Mode' => [ 'shape' => 'S3ObjectLockRetentionMode', ], ], ], 'S3SSEAlgorithm' => [ 'type' => 'string', 'enum' => [ 'AES256', 'KMS', ], ], 'S3SetObjectAclOperation' => [ 'type' => 'structure', 'members' => [ 'AccessControlPolicy' => [ 'shape' => 'S3AccessControlPolicy', ], ], ], 'S3SetObjectLegalHoldOperation' => [ 'type' => 'structure', 'required' => [ 'LegalHold', ], 'members' => [ 'LegalHold' => [ 'shape' => 'S3ObjectLockLegalHold', ], ], ], 'S3SetObjectRetentionOperation' => [ 'type' => 'structure', 'required' => [ 'Retention', ], 'members' => [ 'BypassGovernanceRetention' => [ 'shape' => 'Boolean', 'box' => true, ], 'Retention' => [ 'shape' => 'S3Retention', ], ], ], 'S3SetObjectTaggingOperation' => [ 'type' => 'structure', 'members' => [ 'TagSet' => [ 'shape' => 'S3TagSet', ], ], ], 'S3StorageClass' => [ 'type' => 'string', 'enum' => [ 'STANDARD', 'STANDARD_IA', 'ONEZONE_IA', 'GLACIER', 'INTELLIGENT_TIERING', 'DEEP_ARCHIVE', 'GLACIER_IR', ], ], 'S3Tag' => [ 'type' => 'structure', 'required' => [ 'Key', 'Value', ], 'members' => [ 'Key' => [ 'shape' => 'TagKeyString', ], 'Value' => [ 'shape' => 'TagValueString', ], ], ], 'S3TagSet' => [ 'type' => 'list', 'member' => [ 'shape' => 'S3Tag', ], ], 'S3UserMetadata' => [ 'type' => 'map', 'key' => [ 'shape' => 'NonEmptyMaxLength1024String', ], 'value' => [ 'shape' => 'MaxLength1024String', ], 'max' => 8192, ], 'SSEKMS' => [ 'type' => 'structure', 'required' => [ 'KeyId', ], 'members' => [ 'KeyId' => [ 'shape' => 'SSEKMSKeyId', ], ], 'locationName' => 'SSE-KMS', ], 'SSEKMSEncryption' => [ 'type' => 'structure', 'required' => [ 'KeyId', ], 'members' => [ 'KeyId' => [ 'shape' => 'KmsKeyArnString', ], ], 'locationName' => 'SSE-KMS', ], 'SSEKMSKeyId' => [ 'type' => 'string', ], 'SSES3' => [ 'type' => 'structure', 'members' => [], 'locationName' => 'SSE-S3', ], 'SSES3Encryption' => [ 'type' => 'structure', 'members' => [], 'locationName' => 'SSE-S3', ], 'SelectionCriteria' => [ 'type' => 'structure', 'members' => [ 'Delimiter' => [ 'shape' => 'StorageLensPrefixLevelDelimiter', ], 'MaxDepth' => [ 'shape' => 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'IsEnabled', ], 'members' => [ 'Id' => [ 'shape' => 'ConfigId', ], 'AccountLevel' => [ 'shape' => 'AccountLevel', ], 'Include' => [ 'shape' => 'Include', ], 'Exclude' => [ 'shape' => 'Exclude', ], 'DataExport' => [ 'shape' => 'StorageLensDataExport', ], 'IsEnabled' => [ 'shape' => 'IsEnabled', ], 'AwsOrg' => [ 'shape' => 'StorageLensAwsOrg', ], 'StorageLensArn' => [ 'shape' => 'StorageLensArn', ], ], ], 'StorageLensConfigurationList' => [ 'type' => 'list', 'member' => [ 'shape' => 'ListStorageLensConfigurationEntry', 'locationName' => 'StorageLensConfiguration', ], 'flattened' => true, ], 'StorageLensDataExport' => [ 'type' => 'structure', 'members' => [ 'S3BucketDestination' => [ 'shape' => 'S3BucketDestination', ], 'CloudWatchMetrics' => [ 'shape' => 'CloudWatchMetrics', ], ], ], 'StorageLensDataExportEncryption' => [ 'type' => 'structure', 'members' => [ 'SSES3' => [ 'shape' => 'SSES3', 'locationName' => 'SSE-S3', ], 'SSEKMS' => [ 'shape' => 'SSEKMS', 'locationName' => 'SSE-KMS', ], ], ], 'StorageLensGroup' => [ 'type' => 'structure', 'required' => [ 'Name', 'Filter', ], 'members' => [ 'Name' => [ 'shape' => 'StorageLensGroupName', ], 'Filter' => [ 'shape' => 'StorageLensGroupFilter', ], 'StorageLensGroupArn' => [ 'shape' => 'StorageLensGroupArn', ], ], ], 'StorageLensGroupAndOperator' => [ 'type' => 'structure', 'members' => [ 'MatchAnyPrefix' => [ 'shape' => 'MatchAnyPrefix', ], 'MatchAnySuffix' => [ 'shape' => 'MatchAnySuffix', ], 'MatchAnyTag' => [ 'shape' => 'MatchAnyTag', ], 'MatchObjectAge' => [ 'shape' => 'MatchObjectAge', ], 'MatchObjectSize' => [ 'shape' => 'MatchObjectSize', ], ], ], 'StorageLensGroupArn' => [ 'type' => 'string', 'max' => 1024, 'min' => 4, 'pattern' => 'arn:[a-z\\-]+:s3:[a-z0-9\\-]+:\\d{12}:storage\\-lens\\-group\\/.*', ], 'StorageLensGroupFilter' => [ 'type' => 'structure', 'members' => [ 'MatchAnyPrefix' => [ 'shape' => 'MatchAnyPrefix', ], 'MatchAnySuffix' => [ 'shape' => 'MatchAnySuffix', ], 'MatchAnyTag' => [ 'shape' => 'MatchAnyTag', ], 'MatchObjectAge' => [ 'shape' => 'MatchObjectAge', ], 'MatchObjectSize' => [ 'shape' => 'MatchObjectSize', ], 'And' => [ 'shape' => 'StorageLensGroupAndOperator', ], 'Or' => [ 'shape' => 'StorageLensGroupOrOperator', ], ], ], 'StorageLensGroupLevel' => [ 'type' => 'structure', 'members' => [ 'SelectionCriteria' => [ 'shape' => 'StorageLensGroupLevelSelectionCriteria', ], ], ], 'StorageLensGroupLevelExclude' => [ 'type' => 'list', 'member' => [ 'shape' => 'StorageLensGroupArn', 'locationName' => 'Arn', ], ], 'StorageLensGroupLevelInclude' => [ 'type' => 'list', 'member' => [ 'shape' => 'StorageLensGroupArn', 'locationName' => 'Arn', ], ], 'StorageLensGroupLevelSelectionCriteria' => [ 'type' => 'structure', 'members' => [ 'Include' => [ 'shape' => 'StorageLensGroupLevelInclude', ], 'Exclude' => [ 'shape' => 'StorageLensGroupLevelExclude', ], ], ], 'StorageLensGroupList' => [ 'type' => 'list', 'member' => [ 'shape' => 'ListStorageLensGroupEntry', 'locationName' => 'StorageLensGroup', ], 'flattened' => true, ], 'StorageLensGroupName' => [ 'type' => 'string', 'max' => 64, 'min' => 1, 'pattern' => '[a-zA-Z0-9\\-\\_]+', ], 'StorageLensGroupOrOperator' => [ 'type' => 'structure', 'members' => [ 'MatchAnyPrefix' => [ 'shape' => 'MatchAnyPrefix', ], 'MatchAnySuffix' => [ 'shape' => 'MatchAnySuffix', ], 'MatchAnyTag' => [ 'shape' => 'MatchAnyTag', ], 'MatchObjectAge' => [ 'shape' => 'MatchObjectAge', ], 'MatchObjectSize' => [ 'shape' => 'MatchObjectSize', ], ], ], 'StorageLensPrefixLevelDelimiter' => [ 'type' => 'string', 'max' => 1, ], 'StorageLensPrefixLevelMaxDepth' => [ 'type' => 'integer', 'max' => 10, 'min' => 1, ], 'StorageLensTag' => [ 'type' => 'structure', 'required' => [ 'Key', 'Value', ], 'members' => [ 'Key' => [ 'shape' => 'TagKeyString', ], 'Value' => [ 'shape' => 'TagValueString', ], ], ], 'StorageLensTags' => [ 'type' => 'list', 'member' => [ 'shape' => 'StorageLensTag', 'locationName' => 'Tag', ], ], 'StringForNextToken' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, 'pattern' => '^[A-Za-z0-9\\+\\:\\/\\=\\?\\#-_]+$', ], 'SubmitMultiRegionAccessPointRoutesRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Mrap', 'RouteUpdates', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Mrap' => [ 'shape' => 'MultiRegionAccessPointId', 'location' => 'uri', 'locationName' => 'mrap', ], 'RouteUpdates' => [ 'shape' => 'RouteList', ], ], ], 'SubmitMultiRegionAccessPointRoutesResult' => [ 'type' => 'structure', 'members' => [], ], 'Suffix' => [ 'type' => 'string', ], 'SuspendedCause' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, ], 'SuspendedDate' => [ 'type' => 'timestamp', ], 'Tag' => [ 'type' => 'structure', 'required' => [ 'Key', 'Value', ], 'members' => [ 'Key' => [ 'shape' => 'TagKeyString', ], 'Value' => [ 'shape' => 'TagValueString', ], ], ], 'TagKeyList' => [ 'type' => 'list', 'member' => [ 'shape' => 'TagKeyString', ], 'max' => 50, 'min' => 0, ], 'TagKeyString' => [ 'type' => 'string', 'max' => 128, 'min' => 1, 'pattern' => '^([\\p{L}\\p{Z}\\p{N}_.:/=+\\-@]*)$', ], 'TagList' => [ 'type' => 'list', 'member' => [ 'shape' => 'Tag', 'locationName' => 'Tag', ], 'max' => 50, 'min' => 0, ], 'TagResourceRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'ResourceArn', 'Tags', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'ResourceArn' => [ 'shape' => 'S3ResourceArn', 'location' => 'uri', 'locationName' => 'resourceArn', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'TagResourceResult' => [ 'type' => 'structure', 'members' => [], ], 'TagValueString' => [ 'type' => 'string', 'max' => 256, 'min' => 0, 'pattern' => '^([\\p{L}\\p{Z}\\p{N}_.:/=+\\-@]*)$', ], 'Tagging' => [ 'type' => 'structure', 'required' => [ 'TagSet', ], 'members' => [ 'TagSet' => [ 'shape' => 'S3TagSet', ], ], ], 'TimeStamp' => [ 'type' => 'timestamp', ], 'TooManyRequestsException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'ExceptionMessage', ], ], 'exception' => true, ], 'TooManyTagsException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'ExceptionMessage', ], ], 'exception' => true, ], 'TrafficDialPercentage' => [ 'type' => 'integer', 'max' => 100, 'min' => 0, ], 'Transition' => [ 'type' => 'structure', 'members' => [ 'Date' => [ 'shape' => 'Date', ], 'Days' => [ 'shape' => 'Days', ], 'StorageClass' => [ 'shape' => 'TransitionStorageClass', ], ], ], 'TransitionList' => [ 'type' => 'list', 'member' => [ 'shape' => 'Transition', 'locationName' => 'Transition', ], ], 'TransitionStorageClass' => [ 'type' => 'string', 'enum' => [ 'GLACIER', 'STANDARD_IA', 'ONEZONE_IA', 'INTELLIGENT_TIERING', 'DEEP_ARCHIVE', ], ], 'UntagResourceRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'ResourceArn', 'TagKeys', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'ResourceArn' => [ 'shape' => 'S3ResourceArn', 'location' => 'uri', 'locationName' => 'resourceArn', ], 'TagKeys' => [ 'shape' => 'TagKeyList', 'location' => 'querystring', 'locationName' => 'tagKeys', ], ], ], 'UntagResourceResult' => [ 'type' => 'structure', 'members' => [], ], 'UpdateJobPriorityRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'JobId', 'Priority', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'JobId' => [ 'shape' => 'JobId', 'location' => 'uri', 'locationName' => 'id', ], 'Priority' => [ 'shape' => 'JobPriority', 'location' => 'querystring', 'locationName' => 'priority', ], ], ], 'UpdateJobPriorityResult' => [ 'type' => 'structure', 'required' => [ 'JobId', 'Priority', ], 'members' => [ 'JobId' => [ 'shape' => 'JobId', ], 'Priority' => [ 'shape' => 'JobPriority', ], ], ], 'UpdateJobStatusRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'JobId', 'RequestedJobStatus', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'JobId' => [ 'shape' => 'JobId', 'location' => 'uri', 'locationName' => 'id', ], 'RequestedJobStatus' => [ 'shape' => 'RequestedJobStatus', 'location' => 'querystring', 'locationName' => 'requestedJobStatus', ], 'StatusUpdateReason' => [ 'shape' => 'JobStatusUpdateReason', 'location' => 'querystring', 'locationName' => 'statusUpdateReason', ], ], ], 'UpdateJobStatusResult' => [ 'type' => 'structure', 'members' => [ 'JobId' => [ 'shape' => 'JobId', ], 'Status' => [ 'shape' => 'JobStatus', ], 'StatusUpdateReason' => [ 'shape' => 'JobStatusUpdateReason', ], ], ], 'UpdateStorageLensGroupRequest' => [ 'type' => 'structure', 'required' => [ 'Name', 'AccountId', 'StorageLensGroup', ], 'members' => [ 'Name' => [ 'shape' => 'StorageLensGroupName', 'location' => 'uri', 'locationName' => 'name', ], 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'StorageLensGroup' => [ 'shape' => 'StorageLensGroup', ], ], ], 'VersioningConfiguration' => [ 'type' => 'structure', 'members' => [ 'MFADelete' => [ 'shape' => 'MFADelete', 'locationName' => 'MfaDelete', ], 'Status' => [ 'shape' => 'BucketVersioningStatus', ], ], ], 'VpcConfiguration' => [ 'type' => 'structure', 'required' => [ 'VpcId', ], 'members' => [ 'VpcId' => [ 'shape' => 'VpcId', ], ], ], 'VpcId' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, ], ], 'clientContextParams' => [ 'UseArnRegion' => [ 'documentation' => 'Enables this client to use an ARN\'s region when constructing an endpoint instead of the client\'s configured region.', 'type' => 'boolean', ], ],]; +return [ 'version' => '2.0', 'metadata' => [ 'apiVersion' => '2018-08-20', 'endpointPrefix' => 's3-control', 'protocol' => 'rest-xml', 'serviceFullName' => 'AWS S3 Control', 'serviceId' => 'S3 Control', 'signatureVersion' => 's3v4', 'signingName' => 's3', 'uid' => 's3control-2018-08-20', ], 'operations' => [ 'CreateAccessPoint' => [ 'name' => 'CreateAccessPoint', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/accesspoint/{name}', ], 'input' => [ 'shape' => 'CreateAccessPointRequest', 'locationName' => 'CreateAccessPointRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'output' => [ 'shape' => 'CreateAccessPointResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'CreateAccessPointForObjectLambda' => [ 'name' => 'CreateAccessPointForObjectLambda', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/accesspointforobjectlambda/{name}', ], 'input' => [ 'shape' => 'CreateAccessPointForObjectLambdaRequest', 'locationName' => 'CreateAccessPointForObjectLambdaRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'output' => [ 'shape' => 'CreateAccessPointForObjectLambdaResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'CreateBucket' => [ 'name' => 'CreateBucket', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/bucket/{name}', ], 'input' => [ 'shape' => 'CreateBucketRequest', ], 'output' => [ 'shape' => 'CreateBucketResult', ], 'errors' => [ [ 'shape' => 'BucketAlreadyExists', ], [ 'shape' => 'BucketAlreadyOwnedByYou', ], ], 'httpChecksumRequired' => true, ], 'CreateJob' => [ 'name' => 'CreateJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/v20180820/jobs', ], 'input' => [ 'shape' => 'CreateJobRequest', 'locationName' => 'CreateJobRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'output' => [ 'shape' => 'CreateJobResult', ], 'errors' => [ [ 'shape' => 'TooManyRequestsException', ], [ 'shape' => 'BadRequestException', ], [ 'shape' => 'IdempotencyException', ], [ 'shape' => 'InternalServiceException', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'CreateMultiRegionAccessPoint' => [ 'name' => 'CreateMultiRegionAccessPoint', 'http' => [ 'method' => 'POST', 'requestUri' => '/v20180820/async-requests/mrap/create', ], 'input' => [ 'shape' => 'CreateMultiRegionAccessPointRequest', 'locationName' => 'CreateMultiRegionAccessPointRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'output' => [ 'shape' => 'CreateMultiRegionAccessPointResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'CreateStorageLensGroup' => [ 'name' => 'CreateStorageLensGroup', 'http' => [ 'method' => 'POST', 'requestUri' => '/v20180820/storagelensgroup', 'responseCode' => 204, ], 'input' => [ 'shape' => 'CreateStorageLensGroupRequest', 'locationName' => 'CreateStorageLensGroupRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteAccessPoint' => [ 'name' => 'DeleteAccessPoint', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/accesspoint/{name}', ], 'input' => [ 'shape' => 'DeleteAccessPointRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteAccessPointForObjectLambda' => [ 'name' => 'DeleteAccessPointForObjectLambda', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/accesspointforobjectlambda/{name}', ], 'input' => [ 'shape' => 'DeleteAccessPointForObjectLambdaRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteAccessPointPolicy' => [ 'name' => 'DeleteAccessPointPolicy', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/accesspoint/{name}/policy', ], 'input' => [ 'shape' => 'DeleteAccessPointPolicyRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteAccessPointPolicyForObjectLambda' => [ 'name' => 'DeleteAccessPointPolicyForObjectLambda', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/accesspointforobjectlambda/{name}/policy', ], 'input' => [ 'shape' => 'DeleteAccessPointPolicyForObjectLambdaRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteBucket' => [ 'name' => 'DeleteBucket', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/bucket/{name}', ], 'input' => [ 'shape' => 'DeleteBucketRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteBucketLifecycleConfiguration' => [ 'name' => 'DeleteBucketLifecycleConfiguration', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/bucket/{name}/lifecycleconfiguration', ], 'input' => [ 'shape' => 'DeleteBucketLifecycleConfigurationRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteBucketPolicy' => [ 'name' => 'DeleteBucketPolicy', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/bucket/{name}/policy', ], 'input' => [ 'shape' => 'DeleteBucketPolicyRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteBucketReplication' => [ 'name' => 'DeleteBucketReplication', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/bucket/{name}/replication', ], 'input' => [ 'shape' => 'DeleteBucketReplicationRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteBucketTagging' => [ 'name' => 'DeleteBucketTagging', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/bucket/{name}/tagging', 'responseCode' => 204, ], 'input' => [ 'shape' => 'DeleteBucketTaggingRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteJobTagging' => [ 'name' => 'DeleteJobTagging', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/jobs/{id}/tagging', ], 'input' => [ 'shape' => 'DeleteJobTaggingRequest', ], 'output' => [ 'shape' => 'DeleteJobTaggingResult', ], 'errors' => [ [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'TooManyRequestsException', ], [ 'shape' => 'NotFoundException', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteMultiRegionAccessPoint' => [ 'name' => 'DeleteMultiRegionAccessPoint', 'http' => [ 'method' => 'POST', 'requestUri' => '/v20180820/async-requests/mrap/delete', ], 'input' => [ 'shape' => 'DeleteMultiRegionAccessPointRequest', 'locationName' => 'DeleteMultiRegionAccessPointRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'output' => [ 'shape' => 'DeleteMultiRegionAccessPointResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeletePublicAccessBlock' => [ 'name' => 'DeletePublicAccessBlock', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/configuration/publicAccessBlock', ], 'input' => [ 'shape' => 'DeletePublicAccessBlockRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteStorageLensConfiguration' => [ 'name' => 'DeleteStorageLensConfiguration', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/storagelens/{storagelensid}', ], 'input' => [ 'shape' => 'DeleteStorageLensConfigurationRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteStorageLensConfigurationTagging' => [ 'name' => 'DeleteStorageLensConfigurationTagging', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/storagelens/{storagelensid}/tagging', ], 'input' => [ 'shape' => 'DeleteStorageLensConfigurationTaggingRequest', ], 'output' => [ 'shape' => 'DeleteStorageLensConfigurationTaggingResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DeleteStorageLensGroup' => [ 'name' => 'DeleteStorageLensGroup', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/storagelensgroup/{name}', 'responseCode' => 204, ], 'input' => [ 'shape' => 'DeleteStorageLensGroupRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DescribeJob' => [ 'name' => 'DescribeJob', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/jobs/{id}', ], 'input' => [ 'shape' => 'DescribeJobRequest', ], 'output' => [ 'shape' => 'DescribeJobResult', ], 'errors' => [ [ 'shape' => 'BadRequestException', ], [ 'shape' => 'TooManyRequestsException', ], [ 'shape' => 'NotFoundException', ], [ 'shape' => 'InternalServiceException', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'DescribeMultiRegionAccessPointOperation' => [ 'name' => 'DescribeMultiRegionAccessPointOperation', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/async-requests/mrap/{request_token+}', ], 'input' => [ 'shape' => 'DescribeMultiRegionAccessPointOperationRequest', ], 'output' => [ 'shape' => 'DescribeMultiRegionAccessPointOperationResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetAccessPoint' => [ 'name' => 'GetAccessPoint', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/accesspoint/{name}', ], 'input' => [ 'shape' => 'GetAccessPointRequest', ], 'output' => [ 'shape' => 'GetAccessPointResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetAccessPointConfigurationForObjectLambda' => [ 'name' => 'GetAccessPointConfigurationForObjectLambda', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/accesspointforobjectlambda/{name}/configuration', ], 'input' => [ 'shape' => 'GetAccessPointConfigurationForObjectLambdaRequest', ], 'output' => [ 'shape' => 'GetAccessPointConfigurationForObjectLambdaResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetAccessPointForObjectLambda' => [ 'name' => 'GetAccessPointForObjectLambda', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/accesspointforobjectlambda/{name}', ], 'input' => [ 'shape' => 'GetAccessPointForObjectLambdaRequest', ], 'output' => [ 'shape' => 'GetAccessPointForObjectLambdaResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetAccessPointPolicy' => [ 'name' => 'GetAccessPointPolicy', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/accesspoint/{name}/policy', ], 'input' => [ 'shape' => 'GetAccessPointPolicyRequest', ], 'output' => [ 'shape' => 'GetAccessPointPolicyResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetAccessPointPolicyForObjectLambda' => [ 'name' => 'GetAccessPointPolicyForObjectLambda', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/accesspointforobjectlambda/{name}/policy', ], 'input' => [ 'shape' => 'GetAccessPointPolicyForObjectLambdaRequest', ], 'output' => [ 'shape' => 'GetAccessPointPolicyForObjectLambdaResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetAccessPointPolicyStatus' => [ 'name' => 'GetAccessPointPolicyStatus', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/accesspoint/{name}/policyStatus', ], 'input' => [ 'shape' => 'GetAccessPointPolicyStatusRequest', ], 'output' => [ 'shape' => 'GetAccessPointPolicyStatusResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetAccessPointPolicyStatusForObjectLambda' => [ 'name' => 'GetAccessPointPolicyStatusForObjectLambda', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/accesspointforobjectlambda/{name}/policyStatus', ], 'input' => [ 'shape' => 'GetAccessPointPolicyStatusForObjectLambdaRequest', ], 'output' => [ 'shape' => 'GetAccessPointPolicyStatusForObjectLambdaResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetBucket' => [ 'name' => 'GetBucket', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/bucket/{name}', ], 'input' => [ 'shape' => 'GetBucketRequest', ], 'output' => [ 'shape' => 'GetBucketResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetBucketLifecycleConfiguration' => [ 'name' => 'GetBucketLifecycleConfiguration', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/bucket/{name}/lifecycleconfiguration', ], 'input' => [ 'shape' => 'GetBucketLifecycleConfigurationRequest', ], 'output' => [ 'shape' => 'GetBucketLifecycleConfigurationResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetBucketPolicy' => [ 'name' => 'GetBucketPolicy', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/bucket/{name}/policy', ], 'input' => [ 'shape' => 'GetBucketPolicyRequest', ], 'output' => [ 'shape' => 'GetBucketPolicyResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetBucketReplication' => [ 'name' => 'GetBucketReplication', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/bucket/{name}/replication', ], 'input' => [ 'shape' => 'GetBucketReplicationRequest', ], 'output' => [ 'shape' => 'GetBucketReplicationResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetBucketTagging' => [ 'name' => 'GetBucketTagging', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/bucket/{name}/tagging', ], 'input' => [ 'shape' => 'GetBucketTaggingRequest', ], 'output' => [ 'shape' => 'GetBucketTaggingResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetBucketVersioning' => [ 'name' => 'GetBucketVersioning', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/bucket/{name}/versioning', ], 'input' => [ 'shape' => 'GetBucketVersioningRequest', ], 'output' => [ 'shape' => 'GetBucketVersioningResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetJobTagging' => [ 'name' => 'GetJobTagging', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/jobs/{id}/tagging', ], 'input' => [ 'shape' => 'GetJobTaggingRequest', ], 'output' => [ 'shape' => 'GetJobTaggingResult', ], 'errors' => [ [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'TooManyRequestsException', ], [ 'shape' => 'NotFoundException', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetMultiRegionAccessPoint' => [ 'name' => 'GetMultiRegionAccessPoint', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/mrap/instances/{name+}', ], 'input' => [ 'shape' => 'GetMultiRegionAccessPointRequest', ], 'output' => [ 'shape' => 'GetMultiRegionAccessPointResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetMultiRegionAccessPointPolicy' => [ 'name' => 'GetMultiRegionAccessPointPolicy', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/mrap/instances/{name+}/policy', ], 'input' => [ 'shape' => 'GetMultiRegionAccessPointPolicyRequest', ], 'output' => [ 'shape' => 'GetMultiRegionAccessPointPolicyResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetMultiRegionAccessPointPolicyStatus' => [ 'name' => 'GetMultiRegionAccessPointPolicyStatus', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/mrap/instances/{name+}/policystatus', ], 'input' => [ 'shape' => 'GetMultiRegionAccessPointPolicyStatusRequest', ], 'output' => [ 'shape' => 'GetMultiRegionAccessPointPolicyStatusResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetMultiRegionAccessPointRoutes' => [ 'name' => 'GetMultiRegionAccessPointRoutes', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/mrap/instances/{mrap+}/routes', ], 'input' => [ 'shape' => 'GetMultiRegionAccessPointRoutesRequest', ], 'output' => [ 'shape' => 'GetMultiRegionAccessPointRoutesResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetPublicAccessBlock' => [ 'name' => 'GetPublicAccessBlock', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/configuration/publicAccessBlock', ], 'input' => [ 'shape' => 'GetPublicAccessBlockRequest', ], 'output' => [ 'shape' => 'GetPublicAccessBlockOutput', ], 'errors' => [ [ 'shape' => 'NoSuchPublicAccessBlockConfiguration', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetStorageLensConfiguration' => [ 'name' => 'GetStorageLensConfiguration', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/storagelens/{storagelensid}', ], 'input' => [ 'shape' => 'GetStorageLensConfigurationRequest', ], 'output' => [ 'shape' => 'GetStorageLensConfigurationResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetStorageLensConfigurationTagging' => [ 'name' => 'GetStorageLensConfigurationTagging', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/storagelens/{storagelensid}/tagging', ], 'input' => [ 'shape' => 'GetStorageLensConfigurationTaggingRequest', ], 'output' => [ 'shape' => 'GetStorageLensConfigurationTaggingResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'GetStorageLensGroup' => [ 'name' => 'GetStorageLensGroup', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/storagelensgroup/{name}', ], 'input' => [ 'shape' => 'GetStorageLensGroupRequest', ], 'output' => [ 'shape' => 'GetStorageLensGroupResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'ListAccessPoints' => [ 'name' => 'ListAccessPoints', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/accesspoint', ], 'input' => [ 'shape' => 'ListAccessPointsRequest', ], 'output' => [ 'shape' => 'ListAccessPointsResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'ListAccessPointsForObjectLambda' => [ 'name' => 'ListAccessPointsForObjectLambda', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/accesspointforobjectlambda', ], 'input' => [ 'shape' => 'ListAccessPointsForObjectLambdaRequest', ], 'output' => [ 'shape' => 'ListAccessPointsForObjectLambdaResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'ListJobs' => [ 'name' => 'ListJobs', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/jobs', ], 'input' => [ 'shape' => 'ListJobsRequest', ], 'output' => [ 'shape' => 'ListJobsResult', ], 'errors' => [ [ 'shape' => 'InvalidRequestException', ], [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'InvalidNextTokenException', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'ListMultiRegionAccessPoints' => [ 'name' => 'ListMultiRegionAccessPoints', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/mrap/instances', ], 'input' => [ 'shape' => 'ListMultiRegionAccessPointsRequest', ], 'output' => [ 'shape' => 'ListMultiRegionAccessPointsResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'ListRegionalBuckets' => [ 'name' => 'ListRegionalBuckets', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/bucket', ], 'input' => [ 'shape' => 'ListRegionalBucketsRequest', ], 'output' => [ 'shape' => 'ListRegionalBucketsResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'ListStorageLensConfigurations' => [ 'name' => 'ListStorageLensConfigurations', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/storagelens', ], 'input' => [ 'shape' => 'ListStorageLensConfigurationsRequest', ], 'output' => [ 'shape' => 'ListStorageLensConfigurationsResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'ListStorageLensGroups' => [ 'name' => 'ListStorageLensGroups', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/storagelensgroup', ], 'input' => [ 'shape' => 'ListStorageLensGroupsRequest', ], 'output' => [ 'shape' => 'ListStorageLensGroupsResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'ListTagsForResource' => [ 'name' => 'ListTagsForResource', 'http' => [ 'method' => 'GET', 'requestUri' => '/v20180820/tags/{resourceArn+}', ], 'input' => [ 'shape' => 'ListTagsForResourceRequest', ], 'output' => [ 'shape' => 'ListTagsForResourceResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'PutAccessPointConfigurationForObjectLambda' => [ 'name' => 'PutAccessPointConfigurationForObjectLambda', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/accesspointforobjectlambda/{name}/configuration', ], 'input' => [ 'shape' => 'PutAccessPointConfigurationForObjectLambdaRequest', 'locationName' => 'PutAccessPointConfigurationForObjectLambdaRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'PutAccessPointPolicy' => [ 'name' => 'PutAccessPointPolicy', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/accesspoint/{name}/policy', ], 'input' => [ 'shape' => 'PutAccessPointPolicyRequest', 'locationName' => 'PutAccessPointPolicyRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'PutAccessPointPolicyForObjectLambda' => [ 'name' => 'PutAccessPointPolicyForObjectLambda', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/accesspointforobjectlambda/{name}/policy', ], 'input' => [ 'shape' => 'PutAccessPointPolicyForObjectLambdaRequest', 'locationName' => 'PutAccessPointPolicyForObjectLambdaRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'PutBucketLifecycleConfiguration' => [ 'name' => 'PutBucketLifecycleConfiguration', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/bucket/{name}/lifecycleconfiguration', ], 'input' => [ 'shape' => 'PutBucketLifecycleConfigurationRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'PutBucketPolicy' => [ 'name' => 'PutBucketPolicy', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/bucket/{name}/policy', ], 'input' => [ 'shape' => 'PutBucketPolicyRequest', 'locationName' => 'PutBucketPolicyRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'PutBucketReplication' => [ 'name' => 'PutBucketReplication', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/bucket/{name}/replication', ], 'input' => [ 'shape' => 'PutBucketReplicationRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'PutBucketTagging' => [ 'name' => 'PutBucketTagging', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/bucket/{name}/tagging', ], 'input' => [ 'shape' => 'PutBucketTaggingRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'PutBucketVersioning' => [ 'name' => 'PutBucketVersioning', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/bucket/{name}/versioning', ], 'input' => [ 'shape' => 'PutBucketVersioningRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'PutJobTagging' => [ 'name' => 'PutJobTagging', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/jobs/{id}/tagging', ], 'input' => [ 'shape' => 'PutJobTaggingRequest', 'locationName' => 'PutJobTaggingRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'output' => [ 'shape' => 'PutJobTaggingResult', ], 'errors' => [ [ 'shape' => 'InternalServiceException', ], [ 'shape' => 'TooManyRequestsException', ], [ 'shape' => 'NotFoundException', ], [ 'shape' => 'TooManyTagsException', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'PutMultiRegionAccessPointPolicy' => [ 'name' => 'PutMultiRegionAccessPointPolicy', 'http' => [ 'method' => 'POST', 'requestUri' => '/v20180820/async-requests/mrap/put-policy', ], 'input' => [ 'shape' => 'PutMultiRegionAccessPointPolicyRequest', 'locationName' => 'PutMultiRegionAccessPointPolicyRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'output' => [ 'shape' => 'PutMultiRegionAccessPointPolicyResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'PutPublicAccessBlock' => [ 'name' => 'PutPublicAccessBlock', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/configuration/publicAccessBlock', ], 'input' => [ 'shape' => 'PutPublicAccessBlockRequest', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'PutStorageLensConfiguration' => [ 'name' => 'PutStorageLensConfiguration', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/storagelens/{storagelensid}', ], 'input' => [ 'shape' => 'PutStorageLensConfigurationRequest', 'locationName' => 'PutStorageLensConfigurationRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'PutStorageLensConfigurationTagging' => [ 'name' => 'PutStorageLensConfigurationTagging', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/storagelens/{storagelensid}/tagging', ], 'input' => [ 'shape' => 'PutStorageLensConfigurationTaggingRequest', 'locationName' => 'PutStorageLensConfigurationTaggingRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'output' => [ 'shape' => 'PutStorageLensConfigurationTaggingResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'SubmitMultiRegionAccessPointRoutes' => [ 'name' => 'SubmitMultiRegionAccessPointRoutes', 'http' => [ 'method' => 'PATCH', 'requestUri' => '/v20180820/mrap/instances/{mrap+}/routes', ], 'input' => [ 'shape' => 'SubmitMultiRegionAccessPointRoutesRequest', 'locationName' => 'SubmitMultiRegionAccessPointRoutesRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'output' => [ 'shape' => 'SubmitMultiRegionAccessPointRoutesResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'httpChecksumRequired' => true, 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'TagResource' => [ 'name' => 'TagResource', 'http' => [ 'method' => 'POST', 'requestUri' => '/v20180820/tags/{resourceArn+}', 'responseCode' => 204, ], 'input' => [ 'shape' => 'TagResourceRequest', 'locationName' => 'TagResourceRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'output' => [ 'shape' => 'TagResourceResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'UntagResource' => [ 'name' => 'UntagResource', 'http' => [ 'method' => 'DELETE', 'requestUri' => '/v20180820/tags/{resourceArn+}', 'responseCode' => 204, ], 'input' => [ 'shape' => 'UntagResourceRequest', ], 'output' => [ 'shape' => 'UntagResourceResult', ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'UpdateJobPriority' => [ 'name' => 'UpdateJobPriority', 'http' => [ 'method' => 'POST', 'requestUri' => '/v20180820/jobs/{id}/priority', ], 'input' => [ 'shape' => 'UpdateJobPriorityRequest', ], 'output' => [ 'shape' => 'UpdateJobPriorityResult', ], 'errors' => [ [ 'shape' => 'BadRequestException', ], [ 'shape' => 'TooManyRequestsException', ], [ 'shape' => 'NotFoundException', ], [ 'shape' => 'InternalServiceException', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'UpdateJobStatus' => [ 'name' => 'UpdateJobStatus', 'http' => [ 'method' => 'POST', 'requestUri' => '/v20180820/jobs/{id}/status', ], 'input' => [ 'shape' => 'UpdateJobStatusRequest', ], 'output' => [ 'shape' => 'UpdateJobStatusResult', ], 'errors' => [ [ 'shape' => 'BadRequestException', ], [ 'shape' => 'TooManyRequestsException', ], [ 'shape' => 'NotFoundException', ], [ 'shape' => 'JobStatusException', ], [ 'shape' => 'InternalServiceException', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], 'UpdateStorageLensGroup' => [ 'name' => 'UpdateStorageLensGroup', 'http' => [ 'method' => 'PUT', 'requestUri' => '/v20180820/storagelensgroup/{name}', 'responseCode' => 204, ], 'input' => [ 'shape' => 'UpdateStorageLensGroupRequest', 'locationName' => 'UpdateStorageLensGroupRequest', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'endpoint' => [ 'hostPrefix' => '{AccountId}.', ], 'staticContextParams' => [ 'RequiresAccountId' => [ 'value' => true, ], ], ], ], 'shapes' => [ 'AbortIncompleteMultipartUpload' => [ 'type' => 'structure', 'members' => [ 'DaysAfterInitiation' => [ 'shape' => 'DaysAfterInitiation', ], ], ], 'AccessControlTranslation' => [ 'type' => 'structure', 'required' => [ 'Owner', ], 'members' => [ 'Owner' => [ 'shape' => 'OwnerOverride', ], ], ], 'AccessPoint' => [ 'type' => 'structure', 'required' => [ 'Name', 'NetworkOrigin', 'Bucket', ], 'members' => [ 'Name' => [ 'shape' => 'AccessPointName', ], 'NetworkOrigin' => [ 'shape' => 'NetworkOrigin', ], 'VpcConfiguration' => [ 'shape' => 'VpcConfiguration', ], 'Bucket' => [ 'shape' => 'BucketName', ], 'AccessPointArn' => [ 'shape' => 'S3AccessPointArn', ], 'Alias' => [ 'shape' => 'Alias', ], 'BucketAccountId' => [ 'shape' => 'AccountId', ], ], ], 'AccessPointList' => [ 'type' => 'list', 'member' => [ 'shape' => 'AccessPoint', 'locationName' => 'AccessPoint', ], ], 'AccessPointName' => [ 'type' => 'string', 'max' => 255, 'min' => 3, ], 'AccountId' => [ 'type' => 'string', 'max' => 64, 'pattern' => '^\\d{12}$', ], 'AccountLevel' => [ 'type' => 'structure', 'required' => [ 'BucketLevel', ], 'members' => [ 'ActivityMetrics' => [ 'shape' => 'ActivityMetrics', ], 'BucketLevel' => [ 'shape' => 'BucketLevel', ], 'AdvancedCostOptimizationMetrics' => [ 'shape' => 'AdvancedCostOptimizationMetrics', ], 'AdvancedDataProtectionMetrics' => [ 'shape' => 'AdvancedDataProtectionMetrics', ], 'DetailedStatusCodesMetrics' => [ 'shape' => 'DetailedStatusCodesMetrics', ], 'StorageLensGroupLevel' => [ 'shape' => 'StorageLensGroupLevel', ], ], ], 'ActivityMetrics' => [ 'type' => 'structure', 'members' => [ 'IsEnabled' => [ 'shape' => 'IsEnabled', ], ], ], 'AdvancedCostOptimizationMetrics' => [ 'type' => 'structure', 'members' => [ 'IsEnabled' => [ 'shape' => 'IsEnabled', ], ], ], 'AdvancedDataProtectionMetrics' => [ 'type' => 'structure', 'members' => [ 'IsEnabled' => [ 'shape' => 'IsEnabled', ], ], ], 'Alias' => [ 'type' => 'string', 'max' => 63, 'pattern' => '^[0-9a-z\\\\-]{63}', ], 'AsyncCreationTimestamp' => [ 'type' => 'timestamp', ], 'AsyncErrorDetails' => [ 'type' => 'structure', 'members' => [ 'Code' => [ 'shape' => 'MaxLength1024String', ], 'Message' => [ 'shape' => 'MaxLength1024String', ], 'Resource' => [ 'shape' => 'MaxLength1024String', ], 'RequestId' => [ 'shape' => 'MaxLength1024String', ], ], ], 'AsyncOperation' => [ 'type' => 'structure', 'members' => [ 'CreationTime' => [ 'shape' => 'AsyncCreationTimestamp', ], 'Operation' => [ 'shape' => 'AsyncOperationName', ], 'RequestTokenARN' => [ 'shape' => 'AsyncRequestTokenARN', ], 'RequestParameters' => [ 'shape' => 'AsyncRequestParameters', ], 'RequestStatus' => [ 'shape' => 'AsyncRequestStatus', ], 'ResponseDetails' => [ 'shape' => 'AsyncResponseDetails', ], ], ], 'AsyncOperationName' => [ 'type' => 'string', 'enum' => [ 'CreateMultiRegionAccessPoint', 'DeleteMultiRegionAccessPoint', 'PutMultiRegionAccessPointPolicy', ], ], 'AsyncRequestParameters' => [ 'type' => 'structure', 'members' => [ 'CreateMultiRegionAccessPointRequest' => [ 'shape' => 'CreateMultiRegionAccessPointInput', ], 'DeleteMultiRegionAccessPointRequest' => [ 'shape' => 'DeleteMultiRegionAccessPointInput', ], 'PutMultiRegionAccessPointPolicyRequest' => [ 'shape' => 'PutMultiRegionAccessPointPolicyInput', ], ], ], 'AsyncRequestStatus' => [ 'type' => 'string', ], 'AsyncRequestTokenARN' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, 'pattern' => 'arn:.+', ], 'AsyncResponseDetails' => [ 'type' => 'structure', 'members' => [ 'MultiRegionAccessPointDetails' => [ 'shape' => 'MultiRegionAccessPointsAsyncResponse', ], 'ErrorDetails' => [ 'shape' => 'AsyncErrorDetails', ], ], ], 'AwsLambdaTransformation' => [ 'type' => 'structure', 'required' => [ 'FunctionArn', ], 'members' => [ 'FunctionArn' => [ 'shape' => 'FunctionArnString', ], 'FunctionPayload' => [ 'shape' => 'AwsLambdaTransformationPayload', ], ], ], 'AwsLambdaTransformationPayload' => [ 'type' => 'string', ], 'AwsOrgArn' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, 'pattern' => 'arn:[a-z\\-]+:organizations::\\d{12}:organization\\/o-[a-z0-9]{10,32}', ], 'BadRequestException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'ExceptionMessage', ], ], 'exception' => true, ], 'Boolean' => [ 'type' => 'boolean', ], 'BucketAlreadyExists' => [ 'type' => 'structure', 'members' => [], 'exception' => true, ], 'BucketAlreadyOwnedByYou' => [ 'type' => 'structure', 'members' => [], 'exception' => true, ], 'BucketCannedACL' => [ 'type' => 'string', 'enum' => [ 'private', 'public-read', 'public-read-write', 'authenticated-read', ], ], 'BucketIdentifierString' => [ 'type' => 'string', ], 'BucketLevel' => [ 'type' => 'structure', 'members' => [ 'ActivityMetrics' => [ 'shape' => 'ActivityMetrics', ], 'PrefixLevel' => [ 'shape' => 'PrefixLevel', ], 'AdvancedCostOptimizationMetrics' => [ 'shape' => 'AdvancedCostOptimizationMetrics', ], 'AdvancedDataProtectionMetrics' => [ 'shape' => 'AdvancedDataProtectionMetrics', ], 'DetailedStatusCodesMetrics' => [ 'shape' => 'DetailedStatusCodesMetrics', ], ], ], 'BucketLocationConstraint' => [ 'type' => 'string', 'enum' => [ 'EU', 'eu-west-1', 'us-west-1', 'us-west-2', 'ap-south-1', 'ap-southeast-1', 'ap-southeast-2', 'ap-northeast-1', 'sa-east-1', 'cn-north-1', 'eu-central-1', ], ], 'BucketName' => [ 'type' => 'string', 'max' => 255, 'min' => 3, ], 'BucketVersioningStatus' => [ 'type' => 'string', 'enum' => [ 'Enabled', 'Suspended', ], ], 'Buckets' => [ 'type' => 'list', 'member' => [ 'shape' => 'S3BucketArnString', 'locationName' => 'Arn', ], ], 'CloudWatchMetrics' => [ 'type' => 'structure', 'required' => [ 'IsEnabled', ], 'members' => [ 'IsEnabled' => [ 'shape' => 'IsEnabled', ], ], ], 'ConfigId' => [ 'type' => 'string', 'max' => 64, 'min' => 1, 'pattern' => '[a-zA-Z0-9\\-\\_\\.]+', ], 'ConfirmRemoveSelfBucketAccess' => [ 'type' => 'boolean', ], 'ConfirmationRequired' => [ 'type' => 'boolean', ], 'ContinuationToken' => [ 'type' => 'string', ], 'CreateAccessPointForObjectLambdaRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', 'Configuration', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'ObjectLambdaAccessPointName', 'location' => 'uri', 'locationName' => 'name', ], 'Configuration' => [ 'shape' => 'ObjectLambdaConfiguration', ], ], ], 'CreateAccessPointForObjectLambdaResult' => [ 'type' => 'structure', 'members' => [ 'ObjectLambdaAccessPointArn' => [ 'shape' => 'ObjectLambdaAccessPointArn', ], 'Alias' => [ 'shape' => 'ObjectLambdaAccessPointAlias', ], ], ], 'CreateAccessPointRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', 'Bucket', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'AccessPointName', 'location' => 'uri', 'locationName' => 'name', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], ], 'VpcConfiguration' => [ 'shape' => 'VpcConfiguration', ], 'PublicAccessBlockConfiguration' => [ 'shape' => 'PublicAccessBlockConfiguration', ], 'BucketAccountId' => [ 'shape' => 'AccountId', ], ], ], 'CreateAccessPointResult' => [ 'type' => 'structure', 'members' => [ 'AccessPointArn' => [ 'shape' => 'S3AccessPointArn', ], 'Alias' => [ 'shape' => 'Alias', ], ], ], 'CreateBucketConfiguration' => [ 'type' => 'structure', 'members' => [ 'LocationConstraint' => [ 'shape' => 'BucketLocationConstraint', ], ], ], 'CreateBucketRequest' => [ 'type' => 'structure', 'required' => [ 'Bucket', ], 'members' => [ 'ACL' => [ 'shape' => 'BucketCannedACL', 'location' => 'header', 'locationName' => 'x-amz-acl', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], 'CreateBucketConfiguration' => [ 'shape' => 'CreateBucketConfiguration', 'locationName' => 'CreateBucketConfiguration', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'GrantFullControl' => [ 'shape' => 'GrantFullControl', 'location' => 'header', 'locationName' => 'x-amz-grant-full-control', ], 'GrantRead' => [ 'shape' => 'GrantRead', 'location' => 'header', 'locationName' => 'x-amz-grant-read', ], 'GrantReadACP' => [ 'shape' => 'GrantReadACP', 'location' => 'header', 'locationName' => 'x-amz-grant-read-acp', ], 'GrantWrite' => [ 'shape' => 'GrantWrite', 'location' => 'header', 'locationName' => 'x-amz-grant-write', ], 'GrantWriteACP' => [ 'shape' => 'GrantWriteACP', 'location' => 'header', 'locationName' => 'x-amz-grant-write-acp', ], 'ObjectLockEnabledForBucket' => [ 'shape' => 'ObjectLockEnabledForBucket', 'location' => 'header', 'locationName' => 'x-amz-bucket-object-lock-enabled', ], 'OutpostId' => [ 'shape' => 'NonEmptyMaxLength64String', 'contextParam' => [ 'name' => 'OutpostId', ], 'location' => 'header', 'locationName' => 'x-amz-outpost-id', ], ], 'payload' => 'CreateBucketConfiguration', ], 'CreateBucketResult' => [ 'type' => 'structure', 'members' => [ 'Location' => [ 'shape' => 'Location', 'location' => 'header', 'locationName' => 'Location', ], 'BucketArn' => [ 'shape' => 'S3RegionalBucketArn', ], ], ], 'CreateJobRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Operation', 'Report', 'ClientRequestToken', 'Priority', 'RoleArn', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'ConfirmationRequired' => [ 'shape' => 'ConfirmationRequired', 'box' => true, ], 'Operation' => [ 'shape' => 'JobOperation', ], 'Report' => [ 'shape' => 'JobReport', ], 'ClientRequestToken' => [ 'shape' => 'NonEmptyMaxLength64String', 'idempotencyToken' => true, ], 'Manifest' => [ 'shape' => 'JobManifest', ], 'Description' => [ 'shape' => 'NonEmptyMaxLength256String', ], 'Priority' => [ 'shape' => 'JobPriority', 'box' => true, ], 'RoleArn' => [ 'shape' => 'IAMRoleArn', ], 'Tags' => [ 'shape' => 'S3TagSet', ], 'ManifestGenerator' => [ 'shape' => 'JobManifestGenerator', ], ], ], 'CreateJobResult' => [ 'type' => 'structure', 'members' => [ 'JobId' => [ 'shape' => 'JobId', ], ], ], 'CreateMultiRegionAccessPointInput' => [ 'type' => 'structure', 'required' => [ 'Name', 'Regions', ], 'members' => [ 'Name' => [ 'shape' => 'MultiRegionAccessPointName', ], 'PublicAccessBlock' => [ 'shape' => 'PublicAccessBlockConfiguration', ], 'Regions' => [ 'shape' => 'RegionCreationList', ], ], ], 'CreateMultiRegionAccessPointRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'ClientToken', 'Details', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'ClientToken' => [ 'shape' => 'MultiRegionAccessPointClientToken', 'idempotencyToken' => true, ], 'Details' => [ 'shape' => 'CreateMultiRegionAccessPointInput', ], ], ], 'CreateMultiRegionAccessPointResult' => [ 'type' => 'structure', 'members' => [ 'RequestTokenARN' => [ 'shape' => 'AsyncRequestTokenARN', ], ], ], 'CreateStorageLensGroupRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'StorageLensGroup', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'StorageLensGroup' => [ 'shape' => 'StorageLensGroup', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreationDate' => [ 'type' => 'timestamp', ], 'CreationTimestamp' => [ 'type' => 'timestamp', ], 'Date' => [ 'type' => 'timestamp', ], 'Days' => [ 'type' => 'integer', ], 'DaysAfterInitiation' => [ 'type' => 'integer', ], 'DeleteAccessPointForObjectLambdaRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'ObjectLambdaAccessPointName', 'location' => 'uri', 'locationName' => 'name', ], ], ], 'DeleteAccessPointPolicyForObjectLambdaRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'ObjectLambdaAccessPointName', 'location' => 'uri', 'locationName' => 'name', ], ], ], 'DeleteAccessPointPolicyRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'AccessPointName', 'contextParam' => [ 'name' => 'AccessPointName', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'DeleteAccessPointRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'AccessPointName', 'contextParam' => [ 'name' => 'AccessPointName', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'DeleteBucketLifecycleConfigurationRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'DeleteBucketPolicyRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'DeleteBucketReplicationRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'DeleteBucketRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'DeleteBucketTaggingRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'DeleteJobTaggingRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'JobId', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'JobId' => [ 'shape' => 'JobId', 'location' => 'uri', 'locationName' => 'id', ], ], ], 'DeleteJobTaggingResult' => [ 'type' => 'structure', 'members' => [], ], 'DeleteMarkerReplication' => [ 'type' => 'structure', 'required' => [ 'Status', ], 'members' => [ 'Status' => [ 'shape' => 'DeleteMarkerReplicationStatus', ], ], ], 'DeleteMarkerReplicationStatus' => [ 'type' => 'string', 'enum' => [ 'Enabled', 'Disabled', ], ], 'DeleteMultiRegionAccessPointInput' => [ 'type' => 'structure', 'required' => [ 'Name', ], 'members' => [ 'Name' => [ 'shape' => 'MultiRegionAccessPointName', ], ], ], 'DeleteMultiRegionAccessPointRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'ClientToken', 'Details', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'ClientToken' => [ 'shape' => 'MultiRegionAccessPointClientToken', 'idempotencyToken' => true, ], 'Details' => [ 'shape' => 'DeleteMultiRegionAccessPointInput', ], ], ], 'DeleteMultiRegionAccessPointResult' => [ 'type' => 'structure', 'members' => [ 'RequestTokenARN' => [ 'shape' => 'AsyncRequestTokenARN', ], ], ], 'DeletePublicAccessBlockRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], ], ], 'DeleteStorageLensConfigurationRequest' => [ 'type' => 'structure', 'required' => [ 'ConfigId', 'AccountId', ], 'members' => [ 'ConfigId' => [ 'shape' => 'ConfigId', 'location' => 'uri', 'locationName' => 'storagelensid', ], 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], ], ], 'DeleteStorageLensConfigurationTaggingRequest' => [ 'type' => 'structure', 'required' => [ 'ConfigId', 'AccountId', ], 'members' => [ 'ConfigId' => [ 'shape' => 'ConfigId', 'location' => 'uri', 'locationName' => 'storagelensid', ], 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], ], ], 'DeleteStorageLensConfigurationTaggingResult' => [ 'type' => 'structure', 'members' => [], ], 'DeleteStorageLensGroupRequest' => [ 'type' => 'structure', 'required' => [ 'Name', 'AccountId', ], 'members' => [ 'Name' => [ 'shape' => 'StorageLensGroupName', 'location' => 'uri', 'locationName' => 'name', ], 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], ], ], 'DescribeJobRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'JobId', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'JobId' => [ 'shape' => 'JobId', 'location' => 'uri', 'locationName' => 'id', ], ], ], 'DescribeJobResult' => [ 'type' => 'structure', 'members' => [ 'Job' => [ 'shape' => 'JobDescriptor', ], ], ], 'DescribeMultiRegionAccessPointOperationRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'RequestTokenARN', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'RequestTokenARN' => [ 'shape' => 'AsyncRequestTokenARN', 'location' => 'uri', 'locationName' => 'request_token', ], ], ], 'DescribeMultiRegionAccessPointOperationResult' => [ 'type' => 'structure', 'members' => [ 'AsyncOperation' => [ 'shape' => 'AsyncOperation', ], ], ], 'Destination' => [ 'type' => 'structure', 'required' => [ 'Bucket', ], 'members' => [ 'Account' => [ 'shape' => 'AccountId', ], 'Bucket' => [ 'shape' => 'BucketIdentifierString', ], 'ReplicationTime' => [ 'shape' => 'ReplicationTime', ], 'AccessControlTranslation' => [ 'shape' => 'AccessControlTranslation', ], 'EncryptionConfiguration' => [ 'shape' => 'EncryptionConfiguration', ], 'Metrics' => [ 'shape' => 'Metrics', ], 'StorageClass' => [ 'shape' => 'ReplicationStorageClass', ], ], ], 'DetailedStatusCodesMetrics' => [ 'type' => 'structure', 'members' => [ 'IsEnabled' => [ 'shape' => 'IsEnabled', ], ], ], 'EncryptionConfiguration' => [ 'type' => 'structure', 'members' => [ 'ReplicaKmsKeyID' => [ 'shape' => 'ReplicaKmsKeyID', 'box' => true, ], ], ], 'Endpoints' => [ 'type' => 'map', 'key' => [ 'shape' => 'NonEmptyMaxLength64String', ], 'value' => [ 'shape' => 'NonEmptyMaxLength1024String', ], ], 'EstablishedMultiRegionAccessPointPolicy' => [ 'type' => 'structure', 'members' => [ 'Policy' => [ 'shape' => 'Policy', ], ], ], 'ExceptionMessage' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, ], 'Exclude' => [ 'type' => 'structure', 'members' => [ 'Buckets' => [ 'shape' => 'Buckets', ], 'Regions' => [ 'shape' => 'Regions', ], ], ], 'ExistingObjectReplication' => [ 'type' => 'structure', 'required' => [ 'Status', ], 'members' => [ 'Status' => [ 'shape' => 'ExistingObjectReplicationStatus', ], ], ], 'ExistingObjectReplicationStatus' => [ 'type' => 'string', 'enum' => [ 'Enabled', 'Disabled', ], ], 'ExpirationStatus' => [ 'type' => 'string', 'enum' => [ 'Enabled', 'Disabled', ], ], 'ExpiredObjectDeleteMarker' => [ 'type' => 'boolean', ], 'Format' => [ 'type' => 'string', 'enum' => [ 'CSV', 'Parquet', ], ], 'FunctionArnString' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, 'pattern' => '(arn:(aws[a-zA-Z-]*)?:lambda:)?([a-z]{2}((-gov)|(-iso(b?)))?-[a-z]+-\\d{1}:)?(\\d{12}:)?(function:)?([a-zA-Z0-9-_]+)(:(\\$LATEST|[a-zA-Z0-9-_]+))?', ], 'GeneratedManifestEncryption' => [ 'type' => 'structure', 'members' => [ 'SSES3' => [ 'shape' => 'SSES3Encryption', 'locationName' => 'SSE-S3', ], 'SSEKMS' => [ 'shape' => 'SSEKMSEncryption', 'locationName' => 'SSE-KMS', ], ], ], 'GeneratedManifestFormat' => [ 'type' => 'string', 'enum' => [ 'S3InventoryReport_CSV_20211130', ], ], 'GetAccessPointConfigurationForObjectLambdaRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'ObjectLambdaAccessPointName', 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetAccessPointConfigurationForObjectLambdaResult' => [ 'type' => 'structure', 'members' => [ 'Configuration' => [ 'shape' => 'ObjectLambdaConfiguration', ], ], ], 'GetAccessPointForObjectLambdaRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'ObjectLambdaAccessPointName', 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetAccessPointForObjectLambdaResult' => [ 'type' => 'structure', 'members' => [ 'Name' => [ 'shape' => 'ObjectLambdaAccessPointName', ], 'PublicAccessBlockConfiguration' => [ 'shape' => 'PublicAccessBlockConfiguration', ], 'CreationDate' => [ 'shape' => 'CreationDate', ], 'Alias' => [ 'shape' => 'ObjectLambdaAccessPointAlias', ], ], ], 'GetAccessPointPolicyForObjectLambdaRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'ObjectLambdaAccessPointName', 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetAccessPointPolicyForObjectLambdaResult' => [ 'type' => 'structure', 'members' => [ 'Policy' => [ 'shape' => 'ObjectLambdaPolicy', ], ], ], 'GetAccessPointPolicyRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'AccessPointName', 'contextParam' => [ 'name' => 'AccessPointName', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetAccessPointPolicyResult' => [ 'type' => 'structure', 'members' => [ 'Policy' => [ 'shape' => 'Policy', ], ], ], 'GetAccessPointPolicyStatusForObjectLambdaRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'ObjectLambdaAccessPointName', 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetAccessPointPolicyStatusForObjectLambdaResult' => [ 'type' => 'structure', 'members' => [ 'PolicyStatus' => [ 'shape' => 'PolicyStatus', ], ], ], 'GetAccessPointPolicyStatusRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'AccessPointName', 'contextParam' => [ 'name' => 'AccessPointName', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetAccessPointPolicyStatusResult' => [ 'type' => 'structure', 'members' => [ 'PolicyStatus' => [ 'shape' => 'PolicyStatus', ], ], ], 'GetAccessPointRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'AccessPointName', 'contextParam' => [ 'name' => 'AccessPointName', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetAccessPointResult' => [ 'type' => 'structure', 'members' => [ 'Name' => [ 'shape' => 'AccessPointName', ], 'Bucket' => [ 'shape' => 'BucketName', ], 'NetworkOrigin' => [ 'shape' => 'NetworkOrigin', ], 'VpcConfiguration' => [ 'shape' => 'VpcConfiguration', ], 'PublicAccessBlockConfiguration' => [ 'shape' => 'PublicAccessBlockConfiguration', ], 'CreationDate' => [ 'shape' => 'CreationDate', ], 'Alias' => [ 'shape' => 'Alias', ], 'AccessPointArn' => [ 'shape' => 'S3AccessPointArn', ], 'Endpoints' => [ 'shape' => 'Endpoints', ], 'BucketAccountId' => [ 'shape' => 'AccountId', ], ], ], 'GetBucketLifecycleConfigurationRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetBucketLifecycleConfigurationResult' => [ 'type' => 'structure', 'members' => [ 'Rules' => [ 'shape' => 'LifecycleRules', ], ], ], 'GetBucketPolicyRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetBucketPolicyResult' => [ 'type' => 'structure', 'members' => [ 'Policy' => [ 'shape' => 'Policy', ], ], ], 'GetBucketReplicationRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetBucketReplicationResult' => [ 'type' => 'structure', 'members' => [ 'ReplicationConfiguration' => [ 'shape' => 'ReplicationConfiguration', ], ], ], 'GetBucketRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetBucketResult' => [ 'type' => 'structure', 'members' => [ 'Bucket' => [ 'shape' => 'BucketName', ], 'PublicAccessBlockEnabled' => [ 'shape' => 'PublicAccessBlockEnabled', ], 'CreationDate' => [ 'shape' => 'CreationDate', ], ], ], 'GetBucketTaggingRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetBucketTaggingResult' => [ 'type' => 'structure', 'required' => [ 'TagSet', ], 'members' => [ 'TagSet' => [ 'shape' => 'S3TagSet', ], ], ], 'GetBucketVersioningRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetBucketVersioningResult' => [ 'type' => 'structure', 'members' => [ 'Status' => [ 'shape' => 'BucketVersioningStatus', ], 'MFADelete' => [ 'shape' => 'MFADeleteStatus', 'locationName' => 'MfaDelete', ], ], ], 'GetJobTaggingRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'JobId', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'JobId' => [ 'shape' => 'JobId', 'location' => 'uri', 'locationName' => 'id', ], ], ], 'GetJobTaggingResult' => [ 'type' => 'structure', 'members' => [ 'Tags' => [ 'shape' => 'S3TagSet', ], ], ], 'GetMultiRegionAccessPointPolicyRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'MultiRegionAccessPointName', 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetMultiRegionAccessPointPolicyResult' => [ 'type' => 'structure', 'members' => [ 'Policy' => [ 'shape' => 'MultiRegionAccessPointPolicyDocument', ], ], ], 'GetMultiRegionAccessPointPolicyStatusRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'MultiRegionAccessPointName', 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetMultiRegionAccessPointPolicyStatusResult' => [ 'type' => 'structure', 'members' => [ 'Established' => [ 'shape' => 'PolicyStatus', ], ], ], 'GetMultiRegionAccessPointRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'MultiRegionAccessPointName', 'location' => 'uri', 'locationName' => 'name', ], ], ], 'GetMultiRegionAccessPointResult' => [ 'type' => 'structure', 'members' => [ 'AccessPoint' => [ 'shape' => 'MultiRegionAccessPointReport', ], ], ], 'GetMultiRegionAccessPointRoutesRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Mrap', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Mrap' => [ 'shape' => 'MultiRegionAccessPointId', 'location' => 'uri', 'locationName' => 'mrap', ], ], ], 'GetMultiRegionAccessPointRoutesResult' => [ 'type' => 'structure', 'members' => [ 'Mrap' => [ 'shape' => 'MultiRegionAccessPointId', ], 'Routes' => [ 'shape' => 'RouteList', ], ], ], 'GetPublicAccessBlockOutput' => [ 'type' => 'structure', 'members' => [ 'PublicAccessBlockConfiguration' => [ 'shape' => 'PublicAccessBlockConfiguration', ], ], 'payload' => 'PublicAccessBlockConfiguration', ], 'GetPublicAccessBlockRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], ], ], 'GetStorageLensConfigurationRequest' => [ 'type' => 'structure', 'required' => [ 'ConfigId', 'AccountId', ], 'members' => [ 'ConfigId' => [ 'shape' => 'ConfigId', 'location' => 'uri', 'locationName' => 'storagelensid', ], 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], ], ], 'GetStorageLensConfigurationResult' => [ 'type' => 'structure', 'members' => [ 'StorageLensConfiguration' => [ 'shape' => 'StorageLensConfiguration', ], ], 'payload' => 'StorageLensConfiguration', ], 'GetStorageLensConfigurationTaggingRequest' => [ 'type' => 'structure', 'required' => [ 'ConfigId', 'AccountId', ], 'members' => [ 'ConfigId' => [ 'shape' => 'ConfigId', 'location' => 'uri', 'locationName' => 'storagelensid', ], 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], ], ], 'GetStorageLensConfigurationTaggingResult' => [ 'type' => 'structure', 'members' => [ 'Tags' => [ 'shape' => 'StorageLensTags', ], ], ], 'GetStorageLensGroupRequest' => [ 'type' => 'structure', 'required' => [ 'Name', 'AccountId', ], 'members' => [ 'Name' => [ 'shape' => 'StorageLensGroupName', 'location' => 'uri', 'locationName' => 'name', ], 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], ], ], 'GetStorageLensGroupResult' => [ 'type' => 'structure', 'members' => [ 'StorageLensGroup' => [ 'shape' => 'StorageLensGroup', ], ], 'payload' => 'StorageLensGroup', ], 'GrantFullControl' => [ 'type' => 'string', ], 'GrantRead' => [ 'type' => 'string', ], 'GrantReadACP' => [ 'type' => 'string', ], 'GrantWrite' => [ 'type' => 'string', ], 'GrantWriteACP' => [ 'type' => 'string', ], 'IAMRoleArn' => [ 'type' => 'string', 'max' => 2048, 'min' => 1, 'pattern' => 'arn:[^:]+:iam::\\d{12}:role/.*', ], 'ID' => [ 'type' => 'string', ], 'IdempotencyException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'ExceptionMessage', ], ], 'exception' => true, ], 'Include' => [ 'type' => 'structure', 'members' => [ 'Buckets' => [ 'shape' => 'Buckets', ], 'Regions' => [ 'shape' => 'Regions', ], ], ], 'InternalServiceException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'ExceptionMessage', ], ], 'exception' => true, 'fault' => true, ], 'InvalidNextTokenException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'ExceptionMessage', ], ], 'exception' => true, ], 'InvalidRequestException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'ExceptionMessage', ], ], 'exception' => true, ], 'IsEnabled' => [ 'type' => 'boolean', ], 'IsPublic' => [ 'type' => 'boolean', ], 'JobArn' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, 'pattern' => 'arn:[^:]+:s3:[a-zA-Z0-9\\-]+:\\d{12}:job\\/.*', ], 'JobCreationTime' => [ 'type' => 'timestamp', ], 'JobDescriptor' => [ 'type' => 'structure', 'members' => [ 'JobId' => [ 'shape' => 'JobId', ], 'ConfirmationRequired' => [ 'shape' => 'ConfirmationRequired', 'box' => true, ], 'Description' => [ 'shape' => 'NonEmptyMaxLength256String', 'box' => true, ], 'JobArn' => [ 'shape' => 'JobArn', 'box' => true, ], 'Status' => [ 'shape' => 'JobStatus', ], 'Manifest' => [ 'shape' => 'JobManifest', 'box' => true, ], 'Operation' => [ 'shape' => 'JobOperation', 'box' => true, ], 'Priority' => [ 'shape' => 'JobPriority', ], 'ProgressSummary' => [ 'shape' => 'JobProgressSummary', 'box' => true, ], 'StatusUpdateReason' => [ 'shape' => 'JobStatusUpdateReason', 'box' => true, ], 'FailureReasons' => [ 'shape' => 'JobFailureList', 'box' => true, ], 'Report' => [ 'shape' => 'JobReport', 'box' => true, ], 'CreationTime' => [ 'shape' => 'JobCreationTime', ], 'TerminationDate' => [ 'shape' => 'JobTerminationDate', 'box' => true, ], 'RoleArn' => [ 'shape' => 'IAMRoleArn', 'box' => true, ], 'SuspendedDate' => [ 'shape' => 'SuspendedDate', 'box' => true, ], 'SuspendedCause' => [ 'shape' => 'SuspendedCause', 'box' => true, ], 'ManifestGenerator' => [ 'shape' => 'JobManifestGenerator', ], 'GeneratedManifestDescriptor' => [ 'shape' => 'S3GeneratedManifestDescriptor', ], ], ], 'JobFailure' => [ 'type' => 'structure', 'members' => [ 'FailureCode' => [ 'shape' => 'JobFailureCode', ], 'FailureReason' => [ 'shape' => 'JobFailureReason', ], ], ], 'JobFailureCode' => [ 'type' => 'string', 'max' => 64, 'min' => 1, ], 'JobFailureList' => [ 'type' => 'list', 'member' => [ 'shape' => 'JobFailure', ], ], 'JobFailureReason' => [ 'type' => 'string', 'max' => 256, 'min' => 1, ], 'JobId' => [ 'type' => 'string', 'max' => 36, 'min' => 5, 'pattern' => '[a-zA-Z0-9\\-\\_]+', ], 'JobListDescriptor' => [ 'type' => 'structure', 'members' => [ 'JobId' => [ 'shape' => 'JobId', ], 'Description' => [ 'shape' => 'NonEmptyMaxLength256String', ], 'Operation' => [ 'shape' => 'OperationName', ], 'Priority' => [ 'shape' => 'JobPriority', ], 'Status' => [ 'shape' => 'JobStatus', ], 'CreationTime' => [ 'shape' => 'JobCreationTime', ], 'TerminationDate' => [ 'shape' => 'JobTerminationDate', ], 'ProgressSummary' => [ 'shape' => 'JobProgressSummary', ], ], ], 'JobListDescriptorList' => [ 'type' => 'list', 'member' => [ 'shape' => 'JobListDescriptor', ], ], 'JobManifest' => [ 'type' => 'structure', 'required' => [ 'Spec', 'Location', ], 'members' => [ 'Spec' => [ 'shape' => 'JobManifestSpec', ], 'Location' => [ 'shape' => 'JobManifestLocation', ], ], ], 'JobManifestFieldList' => [ 'type' => 'list', 'member' => [ 'shape' => 'JobManifestFieldName', ], ], 'JobManifestFieldName' => [ 'type' => 'string', 'enum' => [ 'Ignore', 'Bucket', 'Key', 'VersionId', ], ], 'JobManifestFormat' => [ 'type' => 'string', 'enum' => [ 'S3BatchOperations_CSV_20180820', 'S3InventoryReport_CSV_20161130', ], ], 'JobManifestGenerator' => [ 'type' => 'structure', 'members' => [ 'S3JobManifestGenerator' => [ 'shape' => 'S3JobManifestGenerator', ], ], 'union' => true, ], 'JobManifestGeneratorFilter' => [ 'type' => 'structure', 'members' => [ 'EligibleForReplication' => [ 'shape' => 'Boolean', 'box' => true, ], 'CreatedAfter' => [ 'shape' => 'ObjectCreationTime', ], 'CreatedBefore' => [ 'shape' => 'ObjectCreationTime', ], 'ObjectReplicationStatuses' => [ 'shape' => 'ReplicationStatusFilterList', ], 'KeyNameConstraint' => [ 'shape' => 'KeyNameConstraint', ], 'ObjectSizeGreaterThanBytes' => [ 'shape' => 'ObjectSizeGreaterThanBytes', 'box' => true, ], 'ObjectSizeLessThanBytes' => [ 'shape' => 'ObjectSizeLessThanBytes', 'box' => true, ], 'MatchAnyStorageClass' => [ 'shape' => 'StorageClassList', ], ], ], 'JobManifestLocation' => [ 'type' => 'structure', 'required' => [ 'ObjectArn', 'ETag', ], 'members' => [ 'ObjectArn' => [ 'shape' => 'S3KeyArnString', ], 'ObjectVersionId' => [ 'shape' => 'S3ObjectVersionId', 'box' => true, ], 'ETag' => [ 'shape' => 'NonEmptyMaxLength1024String', ], ], ], 'JobManifestSpec' => [ 'type' => 'structure', 'required' => [ 'Format', ], 'members' => [ 'Format' => [ 'shape' => 'JobManifestFormat', ], 'Fields' => [ 'shape' => 'JobManifestFieldList', 'box' => true, ], ], ], 'JobNumberOfTasksFailed' => [ 'type' => 'long', 'min' => 0, ], 'JobNumberOfTasksSucceeded' => [ 'type' => 'long', 'min' => 0, ], 'JobOperation' => [ 'type' => 'structure', 'members' => [ 'LambdaInvoke' => [ 'shape' => 'LambdaInvokeOperation', 'box' => true, ], 'S3PutObjectCopy' => [ 'shape' => 'S3CopyObjectOperation', 'box' => true, ], 'S3PutObjectAcl' => [ 'shape' => 'S3SetObjectAclOperation', 'box' => true, ], 'S3PutObjectTagging' => [ 'shape' => 'S3SetObjectTaggingOperation', 'box' => true, ], 'S3DeleteObjectTagging' => [ 'shape' => 'S3DeleteObjectTaggingOperation', 'box' => true, ], 'S3InitiateRestoreObject' => [ 'shape' => 'S3InitiateRestoreObjectOperation', 'box' => true, ], 'S3PutObjectLegalHold' => [ 'shape' => 'S3SetObjectLegalHoldOperation', 'box' => true, ], 'S3PutObjectRetention' => [ 'shape' => 'S3SetObjectRetentionOperation', 'box' => true, ], 'S3ReplicateObject' => [ 'shape' => 'S3ReplicateObjectOperation', 'box' => true, ], ], ], 'JobPriority' => [ 'type' => 'integer', 'max' => 2147483647, 'min' => 0, ], 'JobProgressSummary' => [ 'type' => 'structure', 'members' => [ 'TotalNumberOfTasks' => [ 'shape' => 'JobTotalNumberOfTasks', 'box' => true, ], 'NumberOfTasksSucceeded' => [ 'shape' => 'JobNumberOfTasksSucceeded', 'box' => true, ], 'NumberOfTasksFailed' => [ 'shape' => 'JobNumberOfTasksFailed', 'box' => true, ], 'Timers' => [ 'shape' => 'JobTimers', ], ], ], 'JobReport' => [ 'type' => 'structure', 'required' => [ 'Enabled', ], 'members' => [ 'Bucket' => [ 'shape' => 'S3BucketArnString', 'box' => true, ], 'Format' => [ 'shape' => 'JobReportFormat', 'box' => true, ], 'Enabled' => [ 'shape' => 'Boolean', ], 'Prefix' => [ 'shape' => 'ReportPrefixString', 'box' => true, ], 'ReportScope' => [ 'shape' => 'JobReportScope', 'box' => true, ], ], ], 'JobReportFormat' => [ 'type' => 'string', 'enum' => [ 'Report_CSV_20180820', ], ], 'JobReportScope' => [ 'type' => 'string', 'enum' => [ 'AllTasks', 'FailedTasksOnly', ], ], 'JobStatus' => [ 'type' => 'string', 'enum' => [ 'Active', 'Cancelled', 'Cancelling', 'Complete', 'Completing', 'Failed', 'Failing', 'New', 'Paused', 'Pausing', 'Preparing', 'Ready', 'Suspended', ], ], 'JobStatusException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'ExceptionMessage', ], ], 'exception' => true, ], 'JobStatusList' => [ 'type' => 'list', 'member' => [ 'shape' => 'JobStatus', ], ], 'JobStatusUpdateReason' => [ 'type' => 'string', 'max' => 256, 'min' => 1, ], 'JobTerminationDate' => [ 'type' => 'timestamp', ], 'JobTimeInStateSeconds' => [ 'type' => 'long', 'min' => 0, ], 'JobTimers' => [ 'type' => 'structure', 'members' => [ 'ElapsedTimeInActiveSeconds' => [ 'shape' => 'JobTimeInStateSeconds', 'box' => true, ], ], ], 'JobTotalNumberOfTasks' => [ 'type' => 'long', 'min' => 0, ], 'KeyNameConstraint' => [ 'type' => 'structure', 'members' => [ 'MatchAnyPrefix' => [ 'shape' => 'NonEmptyMaxLength1024StringList', ], 'MatchAnySuffix' => [ 'shape' => 'NonEmptyMaxLength1024StringList', ], 'MatchAnySubstring' => [ 'shape' => 'NonEmptyMaxLength1024StringList', ], ], ], 'KmsKeyArnString' => [ 'type' => 'string', 'max' => 2000, 'min' => 1, ], 'LambdaInvokeOperation' => [ 'type' => 'structure', 'members' => [ 'FunctionArn' => [ 'shape' => 'FunctionArnString', ], ], ], 'LifecycleConfiguration' => [ 'type' => 'structure', 'members' => [ 'Rules' => [ 'shape' => 'LifecycleRules', ], ], ], 'LifecycleExpiration' => [ 'type' => 'structure', 'members' => [ 'Date' => [ 'shape' => 'Date', ], 'Days' => [ 'shape' => 'Days', ], 'ExpiredObjectDeleteMarker' => [ 'shape' => 'ExpiredObjectDeleteMarker', ], ], ], 'LifecycleRule' => [ 'type' => 'structure', 'required' => [ 'Status', ], 'members' => [ 'Expiration' => [ 'shape' => 'LifecycleExpiration', ], 'ID' => [ 'shape' => 'ID', ], 'Filter' => [ 'shape' => 'LifecycleRuleFilter', ], 'Status' => [ 'shape' => 'ExpirationStatus', ], 'Transitions' => [ 'shape' => 'TransitionList', ], 'NoncurrentVersionTransitions' => [ 'shape' => 'NoncurrentVersionTransitionList', ], 'NoncurrentVersionExpiration' => [ 'shape' => 'NoncurrentVersionExpiration', ], 'AbortIncompleteMultipartUpload' => [ 'shape' => 'AbortIncompleteMultipartUpload', ], ], ], 'LifecycleRuleAndOperator' => [ 'type' => 'structure', 'members' => [ 'Prefix' => [ 'shape' => 'Prefix', ], 'Tags' => [ 'shape' => 'S3TagSet', ], 'ObjectSizeGreaterThan' => [ 'shape' => 'ObjectSizeGreaterThanBytes', 'box' => true, ], 'ObjectSizeLessThan' => [ 'shape' => 'ObjectSizeLessThanBytes', 'box' => true, ], ], ], 'LifecycleRuleFilter' => [ 'type' => 'structure', 'members' => [ 'Prefix' => [ 'shape' => 'Prefix', ], 'Tag' => [ 'shape' => 'S3Tag', ], 'And' => [ 'shape' => 'LifecycleRuleAndOperator', ], 'ObjectSizeGreaterThan' => [ 'shape' => 'ObjectSizeGreaterThanBytes', 'box' => true, ], 'ObjectSizeLessThan' => [ 'shape' => 'ObjectSizeLessThanBytes', 'box' => true, ], ], ], 'LifecycleRules' => [ 'type' => 'list', 'member' => [ 'shape' => 'LifecycleRule', 'locationName' => 'Rule', ], ], 'ListAccessPointsForObjectLambdaRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'NextToken' => [ 'shape' => 'NonEmptyMaxLength1024String', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResults', 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListAccessPointsForObjectLambdaResult' => [ 'type' => 'structure', 'members' => [ 'ObjectLambdaAccessPointList' => [ 'shape' => 'ObjectLambdaAccessPointList', ], 'NextToken' => [ 'shape' => 'NonEmptyMaxLength1024String', ], ], ], 'ListAccessPointsRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'querystring', 'locationName' => 'bucket', ], 'NextToken' => [ 'shape' => 'NonEmptyMaxLength1024String', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResults', 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListAccessPointsResult' => [ 'type' => 'structure', 'members' => [ 'AccessPointList' => [ 'shape' => 'AccessPointList', ], 'NextToken' => [ 'shape' => 'NonEmptyMaxLength1024String', ], ], ], 'ListJobsRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'JobStatuses' => [ 'shape' => 'JobStatusList', 'location' => 'querystring', 'locationName' => 'jobStatuses', ], 'NextToken' => [ 'shape' => 'StringForNextToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResults', 'box' => true, 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListJobsResult' => [ 'type' => 'structure', 'members' => [ 'NextToken' => [ 'shape' => 'StringForNextToken', ], 'Jobs' => [ 'shape' => 'JobListDescriptorList', ], ], ], 'ListMultiRegionAccessPointsRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'NextToken' => [ 'shape' => 'NonEmptyMaxLength1024String', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResults', 'location' => 'querystring', 'locationName' => 'maxResults', ], ], ], 'ListMultiRegionAccessPointsResult' => [ 'type' => 'structure', 'members' => [ 'AccessPoints' => [ 'shape' => 'MultiRegionAccessPointReportList', ], 'NextToken' => [ 'shape' => 'NonEmptyMaxLength1024String', ], ], ], 'ListRegionalBucketsRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'NextToken' => [ 'shape' => 'NonEmptyMaxLength1024String', 'location' => 'querystring', 'locationName' => 'nextToken', ], 'MaxResults' => [ 'shape' => 'MaxResults', 'location' => 'querystring', 'locationName' => 'maxResults', ], 'OutpostId' => [ 'shape' => 'NonEmptyMaxLength64String', 'contextParam' => [ 'name' => 'OutpostId', ], 'location' => 'header', 'locationName' => 'x-amz-outpost-id', ], ], ], 'ListRegionalBucketsResult' => [ 'type' => 'structure', 'members' => [ 'RegionalBucketList' => [ 'shape' => 'RegionalBucketList', ], 'NextToken' => [ 'shape' => 'NonEmptyMaxLength1024String', ], ], ], 'ListStorageLensConfigurationEntry' => [ 'type' => 'structure', 'required' => [ 'Id', 'StorageLensArn', 'HomeRegion', ], 'members' => [ 'Id' => [ 'shape' => 'ConfigId', ], 'StorageLensArn' => [ 'shape' => 'StorageLensArn', ], 'HomeRegion' => [ 'shape' => 'S3AWSRegion', ], 'IsEnabled' => [ 'shape' => 'IsEnabled', ], ], ], 'ListStorageLensConfigurationsRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'NextToken' => [ 'shape' => 'ContinuationToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], ], ], 'ListStorageLensConfigurationsResult' => [ 'type' => 'structure', 'members' => [ 'NextToken' => [ 'shape' => 'ContinuationToken', ], 'StorageLensConfigurationList' => [ 'shape' => 'StorageLensConfigurationList', ], ], ], 'ListStorageLensGroupEntry' => [ 'type' => 'structure', 'required' => [ 'Name', 'StorageLensGroupArn', 'HomeRegion', ], 'members' => [ 'Name' => [ 'shape' => 'StorageLensGroupName', ], 'StorageLensGroupArn' => [ 'shape' => 'StorageLensGroupArn', ], 'HomeRegion' => [ 'shape' => 'S3AWSRegion', ], ], ], 'ListStorageLensGroupsRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'NextToken' => [ 'shape' => 'ContinuationToken', 'location' => 'querystring', 'locationName' => 'nextToken', ], ], ], 'ListStorageLensGroupsResult' => [ 'type' => 'structure', 'members' => [ 'NextToken' => [ 'shape' => 'ContinuationToken', ], 'StorageLensGroupList' => [ 'shape' => 'StorageLensGroupList', ], ], ], 'ListTagsForResourceRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'ResourceArn', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'ResourceArn' => [ 'shape' => 'S3ResourceArn', 'location' => 'uri', 'locationName' => 'resourceArn', ], ], ], 'ListTagsForResourceResult' => [ 'type' => 'structure', 'members' => [ 'Tags' => [ 'shape' => 'TagList', ], ], ], 'Location' => [ 'type' => 'string', ], 'MFA' => [ 'type' => 'string', ], 'MFADelete' => [ 'type' => 'string', 'enum' => [ 'Enabled', 'Disabled', ], ], 'MFADeleteStatus' => [ 'type' => 'string', 'enum' => [ 'Enabled', 'Disabled', ], ], 'ManifestPrefixString' => [ 'type' => 'string', 'max' => 512, 'min' => 1, ], 'MatchAnyPrefix' => [ 'type' => 'list', 'member' => [ 'shape' => 'Prefix', 'locationName' => 'Prefix', ], ], 'MatchAnySuffix' => [ 'type' => 'list', 'member' => [ 'shape' => 'Suffix', 'locationName' => 'Suffix', ], ], 'MatchAnyTag' => [ 'type' => 'list', 'member' => [ 'shape' => 'S3Tag', 'locationName' => 'Tag', ], ], 'MatchObjectAge' => [ 'type' => 'structure', 'members' => [ 'DaysGreaterThan' => [ 'shape' => 'ObjectAgeValue', ], 'DaysLessThan' => [ 'shape' => 'ObjectAgeValue', ], ], ], 'MatchObjectSize' => [ 'type' => 'structure', 'members' => [ 'BytesGreaterThan' => [ 'shape' => 'ObjectSizeValue', ], 'BytesLessThan' => [ 'shape' => 'ObjectSizeValue', ], ], ], 'MaxLength1024String' => [ 'type' => 'string', 'max' => 1024, ], 'MaxResults' => [ 'type' => 'integer', 'max' => 1000, 'min' => 0, ], 'Metrics' => [ 'type' => 'structure', 'required' => [ 'Status', ], 'members' => [ 'Status' => [ 'shape' => 'MetricsStatus', ], 'EventThreshold' => [ 'shape' => 'ReplicationTimeValue', ], ], ], 'MetricsStatus' => [ 'type' => 'string', 'enum' => [ 'Enabled', 'Disabled', ], ], 'MinStorageBytesPercentage' => [ 'type' => 'double', 'max' => 100, 'min' => 0.1, ], 'Minutes' => [ 'type' => 'integer', ], 'MultiRegionAccessPointAlias' => [ 'type' => 'string', 'max' => 63, 'pattern' => '^[a-z][a-z0-9]*[.]mrap$', ], 'MultiRegionAccessPointClientToken' => [ 'type' => 'string', 'max' => 64, 'pattern' => '\\S+', ], 'MultiRegionAccessPointId' => [ 'type' => 'string', 'max' => 200, 'pattern' => '^[a-zA-Z0-9\\:.-]{3,200}$', ], 'MultiRegionAccessPointName' => [ 'type' => 'string', 'max' => 50, 'pattern' => '^[a-z0-9][-a-z0-9]{1,48}[a-z0-9]$', ], 'MultiRegionAccessPointPolicyDocument' => [ 'type' => 'structure', 'members' => [ 'Established' => [ 'shape' => 'EstablishedMultiRegionAccessPointPolicy', ], 'Proposed' => [ 'shape' => 'ProposedMultiRegionAccessPointPolicy', ], ], ], 'MultiRegionAccessPointRegionalResponse' => [ 'type' => 'structure', 'members' => [ 'Name' => [ 'shape' => 'RegionName', ], 'RequestStatus' => [ 'shape' => 'AsyncRequestStatus', ], ], ], 'MultiRegionAccessPointRegionalResponseList' => [ 'type' => 'list', 'member' => [ 'shape' => 'MultiRegionAccessPointRegionalResponse', 'locationName' => 'Region', ], ], 'MultiRegionAccessPointReport' => [ 'type' => 'structure', 'members' => [ 'Name' => [ 'shape' => 'MultiRegionAccessPointName', ], 'Alias' => [ 'shape' => 'MultiRegionAccessPointAlias', ], 'CreatedAt' => [ 'shape' => 'CreationTimestamp', ], 'PublicAccessBlock' => [ 'shape' => 'PublicAccessBlockConfiguration', ], 'Status' => [ 'shape' => 'MultiRegionAccessPointStatus', ], 'Regions' => [ 'shape' => 'RegionReportList', ], ], ], 'MultiRegionAccessPointReportList' => [ 'type' => 'list', 'member' => [ 'shape' => 'MultiRegionAccessPointReport', 'locationName' => 'AccessPoint', ], ], 'MultiRegionAccessPointRoute' => [ 'type' => 'structure', 'required' => [ 'TrafficDialPercentage', ], 'members' => [ 'Bucket' => [ 'shape' => 'BucketName', ], 'Region' => [ 'shape' => 'RegionName', ], 'TrafficDialPercentage' => [ 'shape' => 'TrafficDialPercentage', ], ], ], 'MultiRegionAccessPointStatus' => [ 'type' => 'string', 'enum' => [ 'READY', 'INCONSISTENT_ACROSS_REGIONS', 'CREATING', 'PARTIALLY_CREATED', 'PARTIALLY_DELETED', 'DELETING', ], ], 'MultiRegionAccessPointsAsyncResponse' => [ 'type' => 'structure', 'members' => [ 'Regions' => [ 'shape' => 'MultiRegionAccessPointRegionalResponseList', ], ], ], 'NetworkOrigin' => [ 'type' => 'string', 'enum' => [ 'Internet', 'VPC', ], ], 'NoSuchPublicAccessBlockConfiguration' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'NoSuchPublicAccessBlockConfigurationMessage', ], ], 'error' => [ 'httpStatusCode' => 404, ], 'exception' => true, ], 'NoSuchPublicAccessBlockConfigurationMessage' => [ 'type' => 'string', ], 'NonEmptyMaxLength1024String' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, ], 'NonEmptyMaxLength1024StringList' => [ 'type' => 'list', 'member' => [ 'shape' => 'NonEmptyMaxLength1024String', ], ], 'NonEmptyMaxLength2048String' => [ 'type' => 'string', 'max' => 2048, 'min' => 1, ], 'NonEmptyMaxLength256String' => [ 'type' => 'string', 'max' => 256, 'min' => 1, ], 'NonEmptyMaxLength64String' => [ 'type' => 'string', 'max' => 64, 'min' => 1, ], 'NoncurrentVersionCount' => [ 'type' => 'integer', ], 'NoncurrentVersionExpiration' => [ 'type' => 'structure', 'members' => [ 'NoncurrentDays' => [ 'shape' => 'Days', ], 'NewerNoncurrentVersions' => [ 'shape' => 'NoncurrentVersionCount', 'box' => true, ], ], ], 'NoncurrentVersionTransition' => [ 'type' => 'structure', 'members' => [ 'NoncurrentDays' => [ 'shape' => 'Days', ], 'StorageClass' => [ 'shape' => 'TransitionStorageClass', ], ], ], 'NoncurrentVersionTransitionList' => [ 'type' => 'list', 'member' => [ 'shape' => 'NoncurrentVersionTransition', 'locationName' => 'NoncurrentVersionTransition', ], ], 'NotFoundException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'ExceptionMessage', ], ], 'exception' => true, ], 'ObjectAgeValue' => [ 'type' => 'integer', ], 'ObjectCreationTime' => [ 'type' => 'timestamp', ], 'ObjectLambdaAccessPoint' => [ 'type' => 'structure', 'required' => [ 'Name', ], 'members' => [ 'Name' => [ 'shape' => 'ObjectLambdaAccessPointName', ], 'ObjectLambdaAccessPointArn' => [ 'shape' => 'ObjectLambdaAccessPointArn', ], 'Alias' => [ 'shape' => 'ObjectLambdaAccessPointAlias', ], ], ], 'ObjectLambdaAccessPointAlias' => [ 'type' => 'structure', 'members' => [ 'Value' => [ 'shape' => 'ObjectLambdaAccessPointAliasValue', ], 'Status' => [ 'shape' => 'ObjectLambdaAccessPointAliasStatus', ], ], ], 'ObjectLambdaAccessPointAliasStatus' => [ 'type' => 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'S3PutObjectTagging', 'S3DeleteObjectTagging', 'S3InitiateRestoreObject', 'S3PutObjectLegalHold', 'S3PutObjectRetention', 'S3ReplicateObject', ], ], 'OutputSchemaVersion' => [ 'type' => 'string', 'enum' => [ 'V_1', ], ], 'OwnerOverride' => [ 'type' => 'string', 'enum' => [ 'Destination', ], ], 'Policy' => [ 'type' => 'string', ], 'PolicyStatus' => [ 'type' => 'structure', 'members' => [ 'IsPublic' => [ 'shape' => 'IsPublic', 'locationName' => 'IsPublic', ], ], ], 'Prefix' => [ 'type' => 'string', ], 'PrefixLevel' => [ 'type' => 'structure', 'required' => [ 'StorageMetrics', ], 'members' => [ 'StorageMetrics' => [ 'shape' => 'PrefixLevelStorageMetrics', ], ], ], 'PrefixLevelStorageMetrics' => [ 'type' => 'structure', 'members' => [ 'IsEnabled' => [ 'shape' => 'IsEnabled', ], 'SelectionCriteria' => [ 'shape' => 'SelectionCriteria', ], ], ], 'Priority' => [ 'type' => 'integer', ], 'ProposedMultiRegionAccessPointPolicy' => [ 'type' => 'structure', 'members' => [ 'Policy' => [ 'shape' => 'Policy', ], ], ], 'PublicAccessBlockConfiguration' => [ 'type' => 'structure', 'members' => [ 'BlockPublicAcls' => [ 'shape' => 'Setting', 'locationName' => 'BlockPublicAcls', ], 'IgnorePublicAcls' => [ 'shape' => 'Setting', 'locationName' => 'IgnorePublicAcls', ], 'BlockPublicPolicy' => [ 'shape' => 'Setting', 'locationName' => 'BlockPublicPolicy', ], 'RestrictPublicBuckets' => [ 'shape' => 'Setting', 'locationName' => 'RestrictPublicBuckets', ], ], ], 'PublicAccessBlockEnabled' => [ 'type' => 'boolean', ], 'PutAccessPointConfigurationForObjectLambdaRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', 'Configuration', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'ObjectLambdaAccessPointName', 'location' => 'uri', 'locationName' => 'name', ], 'Configuration' => [ 'shape' => 'ObjectLambdaConfiguration', ], ], ], 'PutAccessPointPolicyForObjectLambdaRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', 'Policy', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'ObjectLambdaAccessPointName', 'location' => 'uri', 'locationName' => 'name', ], 'Policy' => [ 'shape' => 'ObjectLambdaPolicy', ], ], ], 'PutAccessPointPolicyRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Name', 'Policy', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Name' => [ 'shape' => 'AccessPointName', 'contextParam' => [ 'name' => 'AccessPointName', ], 'location' => 'uri', 'locationName' => 'name', ], 'Policy' => [ 'shape' => 'Policy', ], ], ], 'PutBucketLifecycleConfigurationRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], 'LifecycleConfiguration' => [ 'shape' => 'LifecycleConfiguration', 'locationName' => 'LifecycleConfiguration', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], ], 'payload' => 'LifecycleConfiguration', ], 'PutBucketPolicyRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', 'Policy', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 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'ReplicationConfiguration', ], 'PutBucketTaggingRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', 'Tagging', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], 'Tagging' => [ 'shape' => 'Tagging', 'locationName' => 'Tagging', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], ], 'payload' => 'Tagging', ], 'PutBucketVersioningRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Bucket', 'VersioningConfiguration', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Bucket' => [ 'shape' => 'BucketName', 'contextParam' => [ 'name' => 'Bucket', ], 'location' => 'uri', 'locationName' => 'name', ], 'MFA' => [ 'shape' => 'MFA', 'location' => 'header', 'locationName' => 'x-amz-mfa', ], 'VersioningConfiguration' => [ 'shape' => 'VersioningConfiguration', 'locationName' => 'VersioningConfiguration', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], ], 'payload' => 'VersioningConfiguration', ], 'PutJobTaggingRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'JobId', 'Tags', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'JobId' => [ 'shape' => 'JobId', 'location' => 'uri', 'locationName' => 'id', ], 'Tags' => [ 'shape' => 'S3TagSet', ], ], ], 'PutJobTaggingResult' => [ 'type' => 'structure', 'members' => [], ], 'PutMultiRegionAccessPointPolicyInput' => [ 'type' => 'structure', 'required' => [ 'Name', 'Policy', ], 'members' => [ 'Name' => [ 'shape' => 'MultiRegionAccessPointName', ], 'Policy' => [ 'shape' => 'Policy', ], ], ], 'PutMultiRegionAccessPointPolicyRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'ClientToken', 'Details', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'ClientToken' => [ 'shape' => 'MultiRegionAccessPointClientToken', 'idempotencyToken' => true, ], 'Details' => [ 'shape' => 'PutMultiRegionAccessPointPolicyInput', ], ], ], 'PutMultiRegionAccessPointPolicyResult' => [ 'type' => 'structure', 'members' => [ 'RequestTokenARN' => [ 'shape' => 'AsyncRequestTokenARN', ], ], ], 'PutPublicAccessBlockRequest' => [ 'type' => 'structure', 'required' => [ 'PublicAccessBlockConfiguration', 'AccountId', ], 'members' => [ 'PublicAccessBlockConfiguration' => [ 'shape' => 'PublicAccessBlockConfiguration', 'locationName' => 'PublicAccessBlockConfiguration', 'xmlNamespace' => [ 'uri' => 'http://awss3control.amazonaws.com/doc/2018-08-20/', ], ], 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], ], 'payload' => 'PublicAccessBlockConfiguration', ], 'PutStorageLensConfigurationRequest' => [ 'type' => 'structure', 'required' => [ 'ConfigId', 'AccountId', 'StorageLensConfiguration', ], 'members' => [ 'ConfigId' => [ 'shape' => 'ConfigId', 'location' => 'uri', 'locationName' => 'storagelensid', ], 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'StorageLensConfiguration' => [ 'shape' => 'StorageLensConfiguration', ], 'Tags' => [ 'shape' => 'StorageLensTags', ], ], ], 'PutStorageLensConfigurationTaggingRequest' => [ 'type' => 'structure', 'required' => [ 'ConfigId', 'AccountId', 'Tags', ], 'members' => [ 'ConfigId' => [ 'shape' => 'ConfigId', 'location' => 'uri', 'locationName' => 'storagelensid', ], 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Tags' => [ 'shape' => 'StorageLensTags', ], ], ], 'PutStorageLensConfigurationTaggingResult' => [ 'type' => 'structure', 'members' => [], ], 'Region' => [ 'type' => 'structure', 'required' => [ 'Bucket', ], 'members' => [ 'Bucket' => [ 'shape' => 'BucketName', ], 'BucketAccountId' => [ 'shape' => 'AccountId', ], ], ], 'RegionCreationList' => [ 'type' => 'list', 'member' => [ 'shape' => 'Region', 'locationName' => 'Region', ], ], 'RegionName' => [ 'type' => 'string', 'max' => 64, 'min' => 1, ], 'RegionReport' => [ 'type' => 'structure', 'members' => [ 'Bucket' => [ 'shape' => 'BucketName', ], 'Region' => [ 'shape' => 'RegionName', ], 'BucketAccountId' => [ 'shape' => 'AccountId', ], ], ], 'RegionReportList' => [ 'type' => 'list', 'member' => [ 'shape' => 'RegionReport', 'locationName' => 'Region', ], ], 'RegionalBucket' => [ 'type' => 'structure', 'required' => [ 'Bucket', 'PublicAccessBlockEnabled', 'CreationDate', ], 'members' => [ 'Bucket' => [ 'shape' => 'BucketName', ], 'BucketArn' => [ 'shape' => 'S3RegionalBucketArn', ], 'PublicAccessBlockEnabled' => [ 'shape' => 'PublicAccessBlockEnabled', ], 'CreationDate' => [ 'shape' => 'CreationDate', ], 'OutpostId' => [ 'shape' => 'NonEmptyMaxLength64String', ], ], ], 'RegionalBucketList' => [ 'type' => 'list', 'member' => [ 'shape' => 'RegionalBucket', 'locationName' => 'RegionalBucket', ], ], 'Regions' => [ 'type' => 'list', 'member' => [ 'shape' => 'S3AWSRegion', 'locationName' => 'Region', ], ], 'ReplicaKmsKeyID' => [ 'type' => 'string', ], 'ReplicaModifications' => [ 'type' => 'structure', 'required' => [ 'Status', ], 'members' => [ 'Status' => [ 'shape' => 'ReplicaModificationsStatus', ], ], ], 'ReplicaModificationsStatus' => [ 'type' => 'string', 'enum' => [ 'Enabled', 'Disabled', ], ], 'ReplicationConfiguration' => [ 'type' => 'structure', 'required' => [ 'Role', 'Rules', ], 'members' => [ 'Role' => [ 'shape' => 'Role', ], 'Rules' => [ 'shape' => 'ReplicationRules', ], ], ], 'ReplicationRule' => [ 'type' => 'structure', 'required' => [ 'Status', 'Destination', 'Bucket', ], 'members' => [ 'ID' => [ 'shape' => 'ID', ], 'Priority' => [ 'shape' => 'Priority', 'box' => true, ], 'Prefix' => [ 'shape' => 'Prefix', 'deprecated' => true, 'deprecatedMessage' => 'Prefix has been deprecated', ], 'Filter' => [ 'shape' => 'ReplicationRuleFilter', ], 'Status' => [ 'shape' => 'ReplicationRuleStatus', ], 'SourceSelectionCriteria' => [ 'shape' => 'SourceSelectionCriteria', ], 'ExistingObjectReplication' => [ 'shape' => 'ExistingObjectReplication', ], 'Destination' => [ 'shape' => 'Destination', ], 'DeleteMarkerReplication' => [ 'shape' => 'DeleteMarkerReplication', ], 'Bucket' => [ 'shape' => 'BucketIdentifierString', ], ], ], 'ReplicationRuleAndOperator' => [ 'type' => 'structure', 'members' => [ 'Prefix' => [ 'shape' => 'Prefix', ], 'Tags' => [ 'shape' => 'S3TagSet', ], ], ], 'ReplicationRuleFilter' => [ 'type' => 'structure', 'members' => [ 'Prefix' => [ 'shape' => 'Prefix', ], 'Tag' => [ 'shape' => 'S3Tag', ], 'And' => [ 'shape' => 'ReplicationRuleAndOperator', ], ], ], 'ReplicationRuleStatus' => [ 'type' => 'string', 'enum' => [ 'Enabled', 'Disabled', ], ], 'ReplicationRules' => [ 'type' => 'list', 'member' => [ 'shape' => 'ReplicationRule', 'locationName' => 'Rule', ], ], 'ReplicationStatus' => [ 'type' => 'string', 'enum' => [ 'COMPLETED', 'FAILED', 'REPLICA', 'NONE', ], ], 'ReplicationStatusFilterList' => [ 'type' => 'list', 'member' => [ 'shape' => 'ReplicationStatus', ], ], 'ReplicationStorageClass' => [ 'type' => 'string', 'enum' => [ 'STANDARD', 'REDUCED_REDUNDANCY', 'STANDARD_IA', 'ONEZONE_IA', 'INTELLIGENT_TIERING', 'GLACIER', 'DEEP_ARCHIVE', 'OUTPOSTS', 'GLACIER_IR', ], ], 'ReplicationTime' => [ 'type' => 'structure', 'required' => [ 'Status', 'Time', ], 'members' => [ 'Status' => [ 'shape' => 'ReplicationTimeStatus', ], 'Time' => [ 'shape' => 'ReplicationTimeValue', ], ], ], 'ReplicationTimeStatus' => [ 'type' => 'string', 'enum' => [ 'Enabled', 'Disabled', ], ], 'ReplicationTimeValue' => [ 'type' => 'structure', 'members' => [ 'Minutes' => [ 'shape' => 'Minutes', 'box' => true, ], ], ], 'ReportPrefixString' => [ 'type' => 'string', 'max' => 512, 'min' => 1, ], 'RequestedJobStatus' => [ 'type' => 'string', 'enum' => [ 'Cancelled', 'Ready', ], ], 'Role' => [ 'type' => 'string', ], 'RouteList' => [ 'type' => 'list', 'member' => [ 'shape' => 'MultiRegionAccessPointRoute', 'locationName' => 'Route', ], ], 'S3AWSRegion' => [ 'type' => 'string', 'max' => 30, 'min' => 5, 'pattern' => '[a-z0-9\\-]+', ], 'S3AccessControlList' => [ 'type' => 'structure', 'required' => [ 'Owner', ], 'members' => [ 'Owner' => [ 'shape' => 'S3ObjectOwner', ], 'Grants' => [ 'shape' => 'S3GrantList', ], ], ], 'S3AccessControlPolicy' => [ 'type' => 'structure', 'members' => [ 'AccessControlList' => [ 'shape' => 'S3AccessControlList', 'box' => true, ], 'CannedAccessControlList' => [ 'shape' => 'S3CannedAccessControlList', 'box' => true, ], ], ], 'S3AccessPointArn' => [ 'type' => 'string', 'max' => 128, 'min' => 4, ], 'S3BucketArnString' => [ 'type' => 'string', 'max' => 128, 'min' => 1, 'pattern' => 'arn:[^:]+:s3:.*', ], 'S3BucketDestination' => [ 'type' => 'structure', 'required' => [ 'Format', 'OutputSchemaVersion', 'AccountId', 'Arn', ], 'members' => [ 'Format' => [ 'shape' => 'Format', ], 'OutputSchemaVersion' => [ 'shape' => 'OutputSchemaVersion', ], 'AccountId' => [ 'shape' => 'AccountId', ], 'Arn' => [ 'shape' => 'S3BucketArnString', ], 'Prefix' => [ 'shape' => 'Prefix', ], 'Encryption' => [ 'shape' => 'StorageLensDataExportEncryption', ], ], ], 'S3CannedAccessControlList' => [ 'type' => 'string', 'enum' => [ 'private', 'public-read', 'public-read-write', 'aws-exec-read', 'authenticated-read', 'bucket-owner-read', 'bucket-owner-full-control', ], ], 'S3ChecksumAlgorithm' => [ 'type' => 'string', 'enum' => [ 'CRC32', 'CRC32C', 'SHA1', 'SHA256', ], ], 'S3ContentLength' => [ 'type' => 'long', 'min' => 0, ], 'S3CopyObjectOperation' => [ 'type' => 'structure', 'members' => [ 'TargetResource' => [ 'shape' => 'S3BucketArnString', ], 'CannedAccessControlList' => [ 'shape' => 'S3CannedAccessControlList', 'box' => true, ], 'AccessControlGrants' => [ 'shape' => 'S3GrantList', 'box' => true, ], 'MetadataDirective' => [ 'shape' => 'S3MetadataDirective', ], 'ModifiedSinceConstraint' => [ 'shape' => 'TimeStamp', ], 'NewObjectMetadata' => [ 'shape' => 'S3ObjectMetadata', ], 'NewObjectTagging' => [ 'shape' => 'S3TagSet', ], 'RedirectLocation' => [ 'shape' => 'NonEmptyMaxLength2048String', ], 'RequesterPays' => [ 'shape' => 'Boolean', ], 'StorageClass' => [ 'shape' => 'S3StorageClass', ], 'UnModifiedSinceConstraint' => [ 'shape' => 'TimeStamp', ], 'SSEAwsKmsKeyId' => [ 'shape' => 'KmsKeyArnString', ], 'TargetKeyPrefix' => [ 'shape' => 'NonEmptyMaxLength1024String', ], 'ObjectLockLegalHoldStatus' => [ 'shape' => 'S3ObjectLockLegalHoldStatus', ], 'ObjectLockMode' => [ 'shape' => 'S3ObjectLockMode', ], 'ObjectLockRetainUntilDate' => [ 'shape' => 'TimeStamp', ], 'BucketKeyEnabled' => [ 'shape' => 'Boolean', ], 'ChecksumAlgorithm' => [ 'shape' => 'S3ChecksumAlgorithm', ], ], ], 'S3DeleteObjectTaggingOperation' => [ 'type' => 'structure', 'members' => [], ], 'S3ExpirationInDays' => [ 'type' => 'integer', 'min' => 0, ], 'S3GeneratedManifestDescriptor' => [ 'type' => 'structure', 'members' => [ 'Format' => [ 'shape' => 'GeneratedManifestFormat', ], 'Location' => [ 'shape' => 'JobManifestLocation', ], ], ], 'S3GlacierJobTier' => [ 'type' => 'string', 'enum' => [ 'BULK', 'STANDARD', ], ], 'S3Grant' => [ 'type' => 'structure', 'members' => [ 'Grantee' => [ 'shape' => 'S3Grantee', ], 'Permission' => [ 'shape' => 'S3Permission', ], ], ], 'S3GrantList' => [ 'type' => 'list', 'member' => [ 'shape' => 'S3Grant', ], ], 'S3Grantee' => [ 'type' => 'structure', 'members' => [ 'TypeIdentifier' => [ 'shape' => 'S3GranteeTypeIdentifier', ], 'Identifier' => [ 'shape' => 'NonEmptyMaxLength1024String', 'box' => true, ], 'DisplayName' => [ 'shape' => 'NonEmptyMaxLength1024String', ], ], ], 'S3GranteeTypeIdentifier' => [ 'type' => 'string', 'enum' => [ 'id', 'emailAddress', 'uri', ], ], 'S3InitiateRestoreObjectOperation' => [ 'type' => 'structure', 'members' => [ 'ExpirationInDays' => [ 'shape' => 'S3ExpirationInDays', 'box' => true, ], 'GlacierJobTier' => [ 'shape' => 'S3GlacierJobTier', ], ], ], 'S3JobManifestGenerator' => [ 'type' => 'structure', 'required' => [ 'SourceBucket', 'EnableManifestOutput', ], 'members' => [ 'ExpectedBucketOwner' => [ 'shape' => 'AccountId', ], 'SourceBucket' => [ 'shape' => 'S3BucketArnString', ], 'ManifestOutputLocation' => [ 'shape' => 'S3ManifestOutputLocation', ], 'Filter' => [ 'shape' => 'JobManifestGeneratorFilter', ], 'EnableManifestOutput' => [ 'shape' => 'Boolean', ], ], ], 'S3KeyArnString' => [ 'type' => 'string', 'max' => 2000, 'min' => 1, 'pattern' => 'arn:[^:]+:s3:.*', ], 'S3ManifestOutputLocation' => [ 'type' => 'structure', 'required' => [ 'Bucket', 'ManifestFormat', ], 'members' => [ 'ExpectedManifestBucketOwner' => [ 'shape' => 'AccountId', ], 'Bucket' => [ 'shape' => 'S3BucketArnString', ], 'ManifestPrefix' => [ 'shape' => 'ManifestPrefixString', ], 'ManifestEncryption' => [ 'shape' => 'GeneratedManifestEncryption', ], 'ManifestFormat' => [ 'shape' => 'GeneratedManifestFormat', ], ], ], 'S3MetadataDirective' => [ 'type' => 'string', 'enum' => [ 'COPY', 'REPLACE', ], ], 'S3ObjectLockLegalHold' => [ 'type' => 'structure', 'required' => [ 'Status', ], 'members' => [ 'Status' => [ 'shape' => 'S3ObjectLockLegalHoldStatus', ], ], ], 'S3ObjectLockLegalHoldStatus' => [ 'type' => 'string', 'enum' => [ 'OFF', 'ON', ], ], 'S3ObjectLockMode' => [ 'type' => 'string', 'enum' => [ 'COMPLIANCE', 'GOVERNANCE', ], ], 'S3ObjectLockRetentionMode' => [ 'type' => 'string', 'enum' => [ 'COMPLIANCE', 'GOVERNANCE', ], ], 'S3ObjectMetadata' => [ 'type' => 'structure', 'members' => [ 'CacheControl' => [ 'shape' => 'NonEmptyMaxLength1024String', ], 'ContentDisposition' => [ 'shape' => 'NonEmptyMaxLength1024String', ], 'ContentEncoding' => [ 'shape' => 'NonEmptyMaxLength1024String', ], 'ContentLanguage' => [ 'shape' => 'NonEmptyMaxLength1024String', ], 'UserMetadata' => [ 'shape' => 'S3UserMetadata', ], 'ContentLength' => [ 'shape' => 'S3ContentLength', 'box' => true, ], 'ContentMD5' => [ 'shape' => 'NonEmptyMaxLength1024String', ], 'ContentType' => [ 'shape' => 'NonEmptyMaxLength1024String', ], 'HttpExpiresDate' => [ 'shape' => 'TimeStamp', ], 'RequesterCharged' => [ 'shape' => 'Boolean', ], 'SSEAlgorithm' => [ 'shape' => 'S3SSEAlgorithm', ], ], ], 'S3ObjectOwner' => [ 'type' => 'structure', 'members' => [ 'ID' => [ 'shape' => 'NonEmptyMaxLength1024String', ], 'DisplayName' => [ 'shape' => 'NonEmptyMaxLength1024String', ], ], ], 'S3ObjectVersionId' => [ 'type' => 'string', 'max' => 2000, 'min' => 1, ], 'S3Permission' => [ 'type' => 'string', 'enum' => [ 'FULL_CONTROL', 'READ', 'WRITE', 'READ_ACP', 'WRITE_ACP', ], ], 'S3RegionalBucketArn' => [ 'type' => 'string', 'max' => 128, 'min' => 4, ], 'S3ReplicateObjectOperation' => [ 'type' => 'structure', 'members' => [], ], 'S3ResourceArn' => [ 'type' => 'string', 'max' => 1011, 'pattern' => 'arn:[^:]+:s3:[^:].*', ], 'S3Retention' => [ 'type' => 'structure', 'members' => [ 'RetainUntilDate' => [ 'shape' => 'TimeStamp', ], 'Mode' => [ 'shape' => 'S3ObjectLockRetentionMode', ], ], ], 'S3SSEAlgorithm' => [ 'type' => 'string', 'enum' => [ 'AES256', 'KMS', ], ], 'S3SetObjectAclOperation' => [ 'type' => 'structure', 'members' => [ 'AccessControlPolicy' => [ 'shape' => 'S3AccessControlPolicy', ], ], ], 'S3SetObjectLegalHoldOperation' => [ 'type' => 'structure', 'required' => [ 'LegalHold', ], 'members' => [ 'LegalHold' => [ 'shape' => 'S3ObjectLockLegalHold', ], ], ], 'S3SetObjectRetentionOperation' => [ 'type' => 'structure', 'required' => [ 'Retention', ], 'members' => [ 'BypassGovernanceRetention' => [ 'shape' => 'Boolean', 'box' => true, ], 'Retention' => [ 'shape' => 'S3Retention', ], ], ], 'S3SetObjectTaggingOperation' => [ 'type' => 'structure', 'members' => [ 'TagSet' => [ 'shape' => 'S3TagSet', ], ], ], 'S3StorageClass' => [ 'type' => 'string', 'enum' => [ 'STANDARD', 'STANDARD_IA', 'ONEZONE_IA', 'GLACIER', 'INTELLIGENT_TIERING', 'DEEP_ARCHIVE', 'GLACIER_IR', ], ], 'S3Tag' => [ 'type' => 'structure', 'required' => [ 'Key', 'Value', ], 'members' => [ 'Key' => [ 'shape' => 'TagKeyString', ], 'Value' => [ 'shape' => 'TagValueString', ], ], ], 'S3TagSet' => [ 'type' => 'list', 'member' => [ 'shape' => 'S3Tag', ], ], 'S3UserMetadata' => [ 'type' => 'map', 'key' => [ 'shape' => 'NonEmptyMaxLength1024String', ], 'value' => [ 'shape' => 'MaxLength1024String', ], 'max' => 8192, ], 'SSEKMS' => [ 'type' => 'structure', 'required' => [ 'KeyId', ], 'members' => [ 'KeyId' => [ 'shape' => 'SSEKMSKeyId', ], ], 'locationName' => 'SSE-KMS', ], 'SSEKMSEncryption' => [ 'type' => 'structure', 'required' => [ 'KeyId', ], 'members' => [ 'KeyId' => [ 'shape' => 'KmsKeyArnString', ], ], 'locationName' => 'SSE-KMS', ], 'SSEKMSKeyId' => [ 'type' => 'string', ], 'SSES3' => [ 'type' => 'structure', 'members' => [], 'locationName' => 'SSE-S3', ], 'SSES3Encryption' => [ 'type' => 'structure', 'members' => [], 'locationName' => 'SSE-S3', ], 'SelectionCriteria' => [ 'type' => 'structure', 'members' => [ 'Delimiter' => [ 'shape' => 'StorageLensPrefixLevelDelimiter', ], 'MaxDepth' => [ 'shape' => 'StorageLensPrefixLevelMaxDepth', ], 'MinStorageBytesPercentage' => [ 'shape' => 'MinStorageBytesPercentage', ], ], ], 'Setting' => [ 'type' => 'boolean', ], 'SourceSelectionCriteria' => [ 'type' => 'structure', 'members' => [ 'SseKmsEncryptedObjects' => [ 'shape' => 'SseKmsEncryptedObjects', ], 'ReplicaModifications' => [ 'shape' => 'ReplicaModifications', ], ], ], 'SseKmsEncryptedObjects' => [ 'type' => 'structure', 'required' => [ 'Status', ], 'members' => [ 'Status' => [ 'shape' => 'SseKmsEncryptedObjectsStatus', ], ], ], 'SseKmsEncryptedObjectsStatus' => [ 'type' => 'string', 'enum' => [ 'Enabled', 'Disabled', ], ], 'StorageClassList' => [ 'type' => 'list', 'member' => [ 'shape' => 'S3StorageClass', ], ], 'StorageLensArn' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, 'pattern' => 'arn:[a-z\\-]+:s3:[a-z0-9\\-]+:\\d{12}:storage\\-lens\\/.*', ], 'StorageLensAwsOrg' => [ 'type' => 'structure', 'required' => [ 'Arn', ], 'members' => [ 'Arn' => [ 'shape' => 'AwsOrgArn', ], ], ], 'StorageLensConfiguration' => [ 'type' => 'structure', 'required' => [ 'Id', 'AccountLevel', 'IsEnabled', ], 'members' => [ 'Id' => [ 'shape' => 'ConfigId', ], 'AccountLevel' => [ 'shape' => 'AccountLevel', ], 'Include' => [ 'shape' => 'Include', ], 'Exclude' => [ 'shape' => 'Exclude', ], 'DataExport' => [ 'shape' => 'StorageLensDataExport', ], 'IsEnabled' => [ 'shape' => 'IsEnabled', ], 'AwsOrg' => [ 'shape' => 'StorageLensAwsOrg', ], 'StorageLensArn' => [ 'shape' => 'StorageLensArn', ], ], ], 'StorageLensConfigurationList' => [ 'type' => 'list', 'member' => [ 'shape' => 'ListStorageLensConfigurationEntry', 'locationName' => 'StorageLensConfiguration', ], 'flattened' => true, ], 'StorageLensDataExport' => [ 'type' => 'structure', 'members' => [ 'S3BucketDestination' => [ 'shape' => 'S3BucketDestination', ], 'CloudWatchMetrics' => [ 'shape' => 'CloudWatchMetrics', ], ], ], 'StorageLensDataExportEncryption' => [ 'type' => 'structure', 'members' => [ 'SSES3' => [ 'shape' => 'SSES3', 'locationName' => 'SSE-S3', ], 'SSEKMS' => [ 'shape' => 'SSEKMS', 'locationName' => 'SSE-KMS', ], ], ], 'StorageLensGroup' => [ 'type' => 'structure', 'required' => [ 'Name', 'Filter', ], 'members' => [ 'Name' => [ 'shape' => 'StorageLensGroupName', ], 'Filter' => [ 'shape' => 'StorageLensGroupFilter', ], 'StorageLensGroupArn' => [ 'shape' => 'StorageLensGroupArn', ], ], ], 'StorageLensGroupAndOperator' => [ 'type' => 'structure', 'members' => [ 'MatchAnyPrefix' => [ 'shape' => 'MatchAnyPrefix', ], 'MatchAnySuffix' => [ 'shape' => 'MatchAnySuffix', ], 'MatchAnyTag' => [ 'shape' => 'MatchAnyTag', ], 'MatchObjectAge' => [ 'shape' => 'MatchObjectAge', ], 'MatchObjectSize' => [ 'shape' => 'MatchObjectSize', ], ], ], 'StorageLensGroupArn' => [ 'type' => 'string', 'max' => 1024, 'min' => 4, 'pattern' => 'arn:[a-z\\-]+:s3:[a-z0-9\\-]+:\\d{12}:storage\\-lens\\-group\\/.*', ], 'StorageLensGroupFilter' => [ 'type' => 'structure', 'members' => [ 'MatchAnyPrefix' => [ 'shape' => 'MatchAnyPrefix', ], 'MatchAnySuffix' => [ 'shape' => 'MatchAnySuffix', ], 'MatchAnyTag' => [ 'shape' => 'MatchAnyTag', ], 'MatchObjectAge' => [ 'shape' => 'MatchObjectAge', ], 'MatchObjectSize' => [ 'shape' => 'MatchObjectSize', ], 'And' => [ 'shape' => 'StorageLensGroupAndOperator', ], 'Or' => [ 'shape' => 'StorageLensGroupOrOperator', ], ], ], 'StorageLensGroupLevel' => [ 'type' => 'structure', 'members' => [ 'SelectionCriteria' => [ 'shape' => 'StorageLensGroupLevelSelectionCriteria', ], ], ], 'StorageLensGroupLevelExclude' => [ 'type' => 'list', 'member' => [ 'shape' => 'StorageLensGroupArn', 'locationName' => 'Arn', ], ], 'StorageLensGroupLevelInclude' => [ 'type' => 'list', 'member' => [ 'shape' => 'StorageLensGroupArn', 'locationName' => 'Arn', ], ], 'StorageLensGroupLevelSelectionCriteria' => [ 'type' => 'structure', 'members' => [ 'Include' => [ 'shape' => 'StorageLensGroupLevelInclude', ], 'Exclude' => [ 'shape' => 'StorageLensGroupLevelExclude', ], ], ], 'StorageLensGroupList' => [ 'type' => 'list', 'member' => [ 'shape' => 'ListStorageLensGroupEntry', 'locationName' => 'StorageLensGroup', ], 'flattened' => true, ], 'StorageLensGroupName' => [ 'type' => 'string', 'max' => 64, 'min' => 1, 'pattern' => '[a-zA-Z0-9\\-\\_]+', ], 'StorageLensGroupOrOperator' => [ 'type' => 'structure', 'members' => [ 'MatchAnyPrefix' => [ 'shape' => 'MatchAnyPrefix', ], 'MatchAnySuffix' => [ 'shape' => 'MatchAnySuffix', ], 'MatchAnyTag' => [ 'shape' => 'MatchAnyTag', ], 'MatchObjectAge' => [ 'shape' => 'MatchObjectAge', ], 'MatchObjectSize' => [ 'shape' => 'MatchObjectSize', ], ], ], 'StorageLensPrefixLevelDelimiter' => [ 'type' => 'string', 'max' => 1, ], 'StorageLensPrefixLevelMaxDepth' => [ 'type' => 'integer', 'max' => 10, 'min' => 1, ], 'StorageLensTag' => [ 'type' => 'structure', 'required' => [ 'Key', 'Value', ], 'members' => [ 'Key' => [ 'shape' => 'TagKeyString', ], 'Value' => [ 'shape' => 'TagValueString', ], ], ], 'StorageLensTags' => [ 'type' => 'list', 'member' => [ 'shape' => 'StorageLensTag', 'locationName' => 'Tag', ], ], 'StringForNextToken' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, 'pattern' => '^[A-Za-z0-9\\+\\:\\/\\=\\?\\#-_]+$', ], 'SubmitMultiRegionAccessPointRoutesRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'Mrap', 'RouteUpdates', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'Mrap' => [ 'shape' => 'MultiRegionAccessPointId', 'location' => 'uri', 'locationName' => 'mrap', ], 'RouteUpdates' => [ 'shape' => 'RouteList', ], ], ], 'SubmitMultiRegionAccessPointRoutesResult' => [ 'type' => 'structure', 'members' => [], ], 'Suffix' => [ 'type' => 'string', ], 'SuspendedCause' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, ], 'SuspendedDate' => [ 'type' => 'timestamp', ], 'Tag' => [ 'type' => 'structure', 'required' => [ 'Key', 'Value', ], 'members' => [ 'Key' => [ 'shape' => 'TagKeyString', ], 'Value' => [ 'shape' => 'TagValueString', ], ], ], 'TagKeyList' => [ 'type' => 'list', 'member' => [ 'shape' => 'TagKeyString', ], 'max' => 50, 'min' => 0, ], 'TagKeyString' => [ 'type' => 'string', 'max' => 128, 'min' => 1, 'pattern' => '^([\\p{L}\\p{Z}\\p{N}_.:/=+\\-@]*)$', ], 'TagList' => [ 'type' => 'list', 'member' => [ 'shape' => 'Tag', 'locationName' => 'Tag', ], 'max' => 50, 'min' => 0, ], 'TagResourceRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'ResourceArn', 'Tags', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'ResourceArn' => [ 'shape' => 'S3ResourceArn', 'location' => 'uri', 'locationName' => 'resourceArn', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'TagResourceResult' => [ 'type' => 'structure', 'members' => [], ], 'TagValueString' => [ 'type' => 'string', 'max' => 256, 'min' => 0, 'pattern' => '^([\\p{L}\\p{Z}\\p{N}_.:/=+\\-@]*)$', ], 'Tagging' => [ 'type' => 'structure', 'required' => [ 'TagSet', ], 'members' => [ 'TagSet' => [ 'shape' => 'S3TagSet', ], ], ], 'TimeStamp' => [ 'type' => 'timestamp', ], 'TooManyRequestsException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'ExceptionMessage', ], ], 'exception' => true, ], 'TooManyTagsException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'ExceptionMessage', ], ], 'exception' => true, ], 'TrafficDialPercentage' => [ 'type' => 'integer', 'max' => 100, 'min' => 0, ], 'Transition' => [ 'type' => 'structure', 'members' => [ 'Date' => [ 'shape' => 'Date', ], 'Days' => [ 'shape' => 'Days', ], 'StorageClass' => [ 'shape' => 'TransitionStorageClass', ], ], ], 'TransitionList' => [ 'type' => 'list', 'member' => [ 'shape' => 'Transition', 'locationName' => 'Transition', ], ], 'TransitionStorageClass' => [ 'type' => 'string', 'enum' => [ 'GLACIER', 'STANDARD_IA', 'ONEZONE_IA', 'INTELLIGENT_TIERING', 'DEEP_ARCHIVE', ], ], 'UntagResourceRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'ResourceArn', 'TagKeys', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'ResourceArn' => [ 'shape' => 'S3ResourceArn', 'location' => 'uri', 'locationName' => 'resourceArn', ], 'TagKeys' => [ 'shape' => 'TagKeyList', 'location' => 'querystring', 'locationName' => 'tagKeys', ], ], ], 'UntagResourceResult' => [ 'type' => 'structure', 'members' => [], ], 'UpdateJobPriorityRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'JobId', 'Priority', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'JobId' => [ 'shape' => 'JobId', 'location' => 'uri', 'locationName' => 'id', ], 'Priority' => [ 'shape' => 'JobPriority', 'location' => 'querystring', 'locationName' => 'priority', ], ], ], 'UpdateJobPriorityResult' => [ 'type' => 'structure', 'required' => [ 'JobId', 'Priority', ], 'members' => [ 'JobId' => [ 'shape' => 'JobId', ], 'Priority' => [ 'shape' => 'JobPriority', ], ], ], 'UpdateJobStatusRequest' => [ 'type' => 'structure', 'required' => [ 'AccountId', 'JobId', 'RequestedJobStatus', ], 'members' => [ 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'JobId' => [ 'shape' => 'JobId', 'location' => 'uri', 'locationName' => 'id', ], 'RequestedJobStatus' => [ 'shape' => 'RequestedJobStatus', 'location' => 'querystring', 'locationName' => 'requestedJobStatus', ], 'StatusUpdateReason' => [ 'shape' => 'JobStatusUpdateReason', 'location' => 'querystring', 'locationName' => 'statusUpdateReason', ], ], ], 'UpdateJobStatusResult' => [ 'type' => 'structure', 'members' => [ 'JobId' => [ 'shape' => 'JobId', ], 'Status' => [ 'shape' => 'JobStatus', ], 'StatusUpdateReason' => [ 'shape' => 'JobStatusUpdateReason', ], ], ], 'UpdateStorageLensGroupRequest' => [ 'type' => 'structure', 'required' => [ 'Name', 'AccountId', 'StorageLensGroup', ], 'members' => [ 'Name' => [ 'shape' => 'StorageLensGroupName', 'location' => 'uri', 'locationName' => 'name', ], 'AccountId' => [ 'shape' => 'AccountId', 'contextParam' => [ 'name' => 'AccountId', ], 'hostLabel' => true, 'location' => 'header', 'locationName' => 'x-amz-account-id', ], 'StorageLensGroup' => [ 'shape' => 'StorageLensGroup', ], ], ], 'VersioningConfiguration' => [ 'type' => 'structure', 'members' => [ 'MFADelete' => [ 'shape' => 'MFADelete', 'locationName' => 'MfaDelete', ], 'Status' => [ 'shape' => 'BucketVersioningStatus', ], ], ], 'VpcConfiguration' => [ 'type' => 'structure', 'required' => [ 'VpcId', ], 'members' => [ 'VpcId' => [ 'shape' => 'VpcId', ], ], ], 'VpcId' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, ], ], 'clientContextParams' => [ 'UseArnRegion' => [ 'documentation' => 'Enables this client to use an ARN\'s region when constructing an endpoint instead of the client\'s configured region.', 'type' => 'boolean', ], ],]; diff --git a/src/data/s3control/2018-08-20/docs-2.json b/src/data/s3control/2018-08-20/docs-2.json index 892dcece41..e6b51f7e9e 100644 --- a/src/data/s3control/2018-08-20/docs-2.json +++ b/src/data/s3control/2018-08-20/docs-2.json @@ -1318,6 +1318,12 @@ "JobProgressSummary$TotalNumberOfTasks": "" } }, + "KeyNameConstraint": { + "base": "If provided, the generated manifest includes only source bucket objects whose object keys match the string constraints specified for MatchAnyPrefix, MatchAnySuffix, and MatchAnySubstring.
If provided, the generated manifest includes only source bucket objects whose object keys match the string constraints specified for MatchAnyPrefix, MatchAnySuffix, and MatchAnySubstring.
If the specified bucket has more Multi-Region Access Points than can be returned in one call to this action, this field contains a continuation token. You can use this token tin subsequent calls to this action to retrieve additional Multi-Region Access Points.
", "ListRegionalBucketsRequest$NextToken": "", "ListRegionalBucketsResult$NextToken": " NextToken is sent when isTruncated is true, which means there are more buckets that can be listed. The next list requests to Amazon S3 can be continued with this NextToken. NextToken is obfuscated and is not a real key.
Specifies the folder prefix that you want the objects to be copied into. For example, to copy objects into a folder named Folder1 in the destination bucket, set the TargetKeyPrefix property to Folder1.
If provided, the generated manifest includes objects where the specified string appears at the start of the object key string.
", + "KeyNameConstraint$MatchAnySuffix": "If provided, the generated manifest includes objects where the specified string appears at the end of the object key string.
", + "KeyNameConstraint$MatchAnySubstring": "If provided, the generated manifest includes objects where the specified string appears anywhere within the object key string.
" + } + }, "NonEmptyMaxLength2048String": { "base": null, "refs": { @@ -1765,8 +1780,8 @@ "ObjectCreationTime": { "base": null, "refs": { - "JobManifestGeneratorFilter$CreatedAfter": "If provided, the generated manifest should include only source bucket objects that were created after this time.
", - "JobManifestGeneratorFilter$CreatedBefore": "If provided, the generated manifest should include only source bucket objects that were created before this time.
" + "JobManifestGeneratorFilter$CreatedAfter": "If provided, the generated manifest includes only source bucket objects that were created after this time.
", + "JobManifestGeneratorFilter$CreatedBefore": "If provided, the generated manifest includes only source bucket objects that were created before this time.
" } }, "ObjectLambdaAccessPoint": { @@ -1896,6 +1911,7 @@ "ObjectSizeGreaterThanBytes": { "base": null, "refs": { + "JobManifestGeneratorFilter$ObjectSizeGreaterThanBytes": "If provided, the generated manifest includes only source bucket objects whose file size is greater than the specified number of bytes.
", "LifecycleRuleAndOperator$ObjectSizeGreaterThan": "Minimum object size to which the rule applies.
", "LifecycleRuleFilter$ObjectSizeGreaterThan": "Minimum object size to which the rule applies.
" } @@ -1903,6 +1919,7 @@ "ObjectSizeLessThanBytes": { "base": null, "refs": { + "JobManifestGeneratorFilter$ObjectSizeLessThanBytes": "If provided, the generated manifest includes only source bucket objects whose file size is less than the specified number of bytes.
", "LifecycleRuleAndOperator$ObjectSizeLessThan": "Maximum object size to which the rule applies.
", "LifecycleRuleFilter$ObjectSizeLessThan": "Maximum object size to which the rule applies.
" } @@ -2209,7 +2226,7 @@ "ReplicationStatusFilterList": { "base": null, "refs": { - "JobManifestGeneratorFilter$ObjectReplicationStatuses": "If provided, the generated manifest should include only source bucket objects that have one of the specified Replication statuses.
" + "JobManifestGeneratorFilter$ObjectReplicationStatuses": "If provided, the generated manifest includes only source bucket objects that have one of the specified Replication statuses.
" } }, "ReplicationStorageClass": { @@ -2520,7 +2537,8 @@ "S3StorageClass": { "base": null, "refs": { - "S3CopyObjectOperation$StorageClass": "" + "S3CopyObjectOperation$StorageClass": "", + "StorageClassList$member": null } }, "S3Tag": { @@ -2615,6 +2633,12 @@ "SseKmsEncryptedObjects$Status": "Specifies whether Amazon S3 replicates objects that are created with server-side encryption by using an KMS key stored in Key Management Service.
" } }, + "StorageClassList": { + "base": null, + "refs": { + "JobManifestGeneratorFilter$MatchAnyStorageClass": "If provided, the generated manifest includes only source bucket objects that are stored with the specified storage class.
" + } + }, "StorageLensArn": { "base": null, "refs": { diff --git a/src/data/s3control/2018-08-20/docs-2.json.php b/src/data/s3control/2018-08-20/docs-2.json.php index 83c1c55ff6..157ca5151f 100644 --- a/src/data/s3control/2018-08-20/docs-2.json.php +++ b/src/data/s3control/2018-08-20/docs-2.json.php @@ -1,3 +1,3 @@ '2.0', 'service' => 'Amazon Web Services S3 Control provides access to Amazon S3 control plane actions.
', 'operations' => [ 'CreateAccessPoint' => 'Creates an access point and associates it with the specified bucket. For more information, see Managing Data Access with Amazon S3 Access Points in the Amazon S3 User Guide.
S3 on Outposts only supports VPC-style access points.
For more information, see Accessing Amazon S3 on Outposts using virtual private cloud (VPC) only access points in the Amazon S3 User Guide.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following actions are related to CreateAccessPoint:
Creates an Object Lambda Access Point. For more information, see Transforming objects with Object Lambda Access Points in the Amazon S3 User Guide.
The following actions are related to CreateAccessPointForObjectLambda:
This action creates an Amazon S3 on Outposts bucket. To create an S3 bucket, see Create Bucket in the Amazon S3 API Reference.
Creates a new Outposts bucket. By creating the bucket, you become the bucket owner. To create an Outposts bucket, you must have S3 on Outposts. For more information, see Using Amazon S3 on Outposts in Amazon S3 User Guide.
Not every string is an acceptable bucket name. For information on bucket naming restrictions, see Working with Amazon S3 Buckets.
S3 on Outposts buckets support:
Tags
LifecycleConfigurations for deleting expired objects
For a complete list of restrictions and Amazon S3 feature limitations on S3 on Outposts, see Amazon S3 on Outposts Restrictions and Limitations.
For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and x-amz-outpost-id in your API request, see the Examples section.
The following actions are related to CreateBucket for Amazon S3 on Outposts:
You can use S3 Batch Operations to perform large-scale batch actions on Amazon S3 objects. Batch Operations can run a single action on lists of Amazon S3 objects that you specify. For more information, see S3 Batch Operations in the Amazon S3 User Guide.
This action creates a S3 Batch Operations job.
Related actions include:
', 'CreateMultiRegionAccessPoint' => 'Creates a Multi-Region Access Point and associates it with the specified buckets. For more information about creating Multi-Region Access Points, see Creating Multi-Region Access Points in the Amazon S3 User Guide.
This action will always be routed to the US West (Oregon) Region. For more information about the restrictions around managing Multi-Region Access Points, see Managing Multi-Region Access Points in the Amazon S3 User Guide.
This request is asynchronous, meaning that you might receive a response before the command has completed. When this request provides a response, it provides a token that you can use to monitor the status of the request with DescribeMultiRegionAccessPointOperation.
The following actions are related to CreateMultiRegionAccessPoint:
Creates a new S3 Storage Lens group and associates it with the specified Amazon Web Services account ID. An S3 Storage Lens group is a custom grouping of objects based on prefix, suffix, object tags, object size, object age, or a combination of these filters. For each Storage Lens group that you’ve created, you can also optionally add Amazon Web Services resource tags. For more information about S3 Storage Lens groups, see Working with S3 Storage Lens groups.
To use this operation, you must have the permission to perform the s3:CreateStorageLensGroup action. If you’re trying to create a Storage Lens group with Amazon Web Services resource tags, you must also have permission to perform the s3:TagResource action. For more information about the required Storage Lens Groups permissions, see Setting account permissions to use S3 Storage Lens groups.
For information about Storage Lens groups errors, see List of Amazon S3 Storage Lens error codes.
', 'DeleteAccessPoint' => 'Deletes the specified access point.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following actions are related to DeleteAccessPoint:
Deletes the specified Object Lambda Access Point.
The following actions are related to DeleteAccessPointForObjectLambda:
Deletes the access point policy for the specified access point.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following actions are related to DeleteAccessPointPolicy:
Removes the resource policy for an Object Lambda Access Point.
The following actions are related to DeleteAccessPointPolicyForObjectLambda:
This action deletes an Amazon S3 on Outposts bucket. To delete an S3 bucket, see DeleteBucket in the Amazon S3 API Reference.
Deletes the Amazon S3 on Outposts bucket. All objects (including all object versions and delete markers) in the bucket must be deleted before the bucket itself can be deleted. For more information, see Using Amazon S3 on Outposts in Amazon S3 User Guide.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
Related Resources
', 'DeleteBucketLifecycleConfiguration' => 'This action deletes an Amazon S3 on Outposts bucket\'s lifecycle configuration. To delete an S3 bucket\'s lifecycle configuration, see DeleteBucketLifecycle in the Amazon S3 API Reference.
Deletes the lifecycle configuration from the specified Outposts bucket. Amazon S3 on Outposts removes all the lifecycle configuration rules in the lifecycle subresource associated with the bucket. Your objects never expire, and Amazon S3 on Outposts no longer automatically deletes any objects on the basis of rules contained in the deleted lifecycle configuration. For more information, see Using Amazon S3 on Outposts in Amazon S3 User Guide.
To use this operation, you must have permission to perform the s3-outposts:PutLifecycleConfiguration action. By default, the bucket owner has this permission and the Outposts bucket owner can grant this permission to others.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
For more information about object expiration, see Elements to Describe Lifecycle Actions.
Related actions include:
', 'DeleteBucketPolicy' => 'This action deletes an Amazon S3 on Outposts bucket policy. To delete an S3 bucket policy, see DeleteBucketPolicy in the Amazon S3 API Reference.
This implementation of the DELETE action uses the policy subresource to delete the policy of a specified Amazon S3 on Outposts bucket. If you are using an identity other than the root user of the Amazon Web Services account that owns the bucket, the calling identity must have the s3-outposts:DeleteBucketPolicy permissions on the specified Outposts bucket and belong to the bucket owner\'s account to use this action. For more information, see Using Amazon S3 on Outposts in Amazon S3 User Guide.
If you don\'t have DeleteBucketPolicy permissions, Amazon S3 returns a 403 Access Denied error. If you have the correct permissions, but you\'re not using an identity that belongs to the bucket owner\'s account, Amazon S3 returns a 405 Method Not Allowed error.
As a security precaution, the root user of the Amazon Web Services account that owns a bucket can always use this action, even if the policy explicitly denies the root user the ability to perform this action.
For more information about bucket policies, see Using Bucket Policies and User Policies.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following actions are related to DeleteBucketPolicy:
This operation deletes an Amazon S3 on Outposts bucket\'s replication configuration. To delete an S3 bucket\'s replication configuration, see DeleteBucketReplication in the Amazon S3 API Reference.
Deletes the replication configuration from the specified S3 on Outposts bucket.
To use this operation, you must have permissions to perform the s3-outposts:PutReplicationConfiguration action. The Outposts bucket owner has this permission by default and can grant it to others. For more information about permissions, see Setting up IAM with S3 on Outposts and Managing access to S3 on Outposts buckets in the Amazon S3 User Guide.
It can take a while to propagate PUT or DELETE requests for a replication configuration to all S3 on Outposts systems. Therefore, the replication configuration that\'s returned by a GET request soon after a PUT or DELETE request might return a more recent result than what\'s on the Outpost. If an Outpost is offline, the delay in updating the replication configuration on that Outpost can be significant.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
For information about S3 replication on Outposts configuration, see Replicating objects for S3 on Outposts in the Amazon S3 User Guide.
The following operations are related to DeleteBucketReplication:
This action deletes an Amazon S3 on Outposts bucket\'s tags. To delete an S3 bucket tags, see DeleteBucketTagging in the Amazon S3 API Reference.
Deletes the tags from the Outposts bucket. For more information, see Using Amazon S3 on Outposts in Amazon S3 User Guide.
To use this action, you must have permission to perform the PutBucketTagging action. By default, the bucket owner has this permission and can grant this permission to others.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following actions are related to DeleteBucketTagging:
Removes the entire tag set from the specified S3 Batch Operations job. To use the DeleteJobTagging operation, you must have permission to perform the s3:DeleteJobTagging action. For more information, see Controlling access and labeling jobs using tags in the Amazon S3 User Guide.
Related actions include:
', 'DeleteMultiRegionAccessPoint' => 'Deletes a Multi-Region Access Point. This action does not delete the buckets associated with the Multi-Region Access Point, only the Multi-Region Access Point itself.
This action will always be routed to the US West (Oregon) Region. For more information about the restrictions around managing Multi-Region Access Points, see Managing Multi-Region Access Points in the Amazon S3 User Guide.
This request is asynchronous, meaning that you might receive a response before the command has completed. When this request provides a response, it provides a token that you can use to monitor the status of the request with DescribeMultiRegionAccessPointOperation.
The following actions are related to DeleteMultiRegionAccessPoint:
Removes the PublicAccessBlock configuration for an Amazon Web Services account. For more information, see Using Amazon S3 block public access.
Related actions include:
', 'DeleteStorageLensConfiguration' => 'Deletes the Amazon S3 Storage Lens configuration. For more information about S3 Storage Lens, see Assessing your storage activity and usage with Amazon S3 Storage Lens in the Amazon S3 User Guide.
To use this action, you must have permission to perform the s3:DeleteStorageLensConfiguration action. For more information, see Setting permissions to use Amazon S3 Storage Lens in the Amazon S3 User Guide.
Deletes the Amazon S3 Storage Lens configuration tags. For more information about S3 Storage Lens, see Assessing your storage activity and usage with Amazon S3 Storage Lens in the Amazon S3 User Guide.
To use this action, you must have permission to perform the s3:DeleteStorageLensConfigurationTagging action. For more information, see Setting permissions to use Amazon S3 Storage Lens in the Amazon S3 User Guide.
Deletes an existing S3 Storage Lens group.
To use this operation, you must have the permission to perform the s3:DeleteStorageLensGroup action. For more information about the required Storage Lens Groups permissions, see Setting account permissions to use S3 Storage Lens groups.
For information about Storage Lens groups errors, see List of Amazon S3 Storage Lens error codes.
', 'DescribeJob' => 'Retrieves the configuration parameters and status for a Batch Operations job. For more information, see S3 Batch Operations in the Amazon S3 User Guide.
Related actions include:
', 'DescribeMultiRegionAccessPointOperation' => 'Retrieves the status of an asynchronous request to manage a Multi-Region Access Point. For more information about managing Multi-Region Access Points and how asynchronous requests work, see Managing Multi-Region Access Points in the Amazon S3 User Guide.
The following actions are related to GetMultiRegionAccessPoint:
Returns configuration information about the specified access point.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following actions are related to GetAccessPoint:
Returns configuration for an Object Lambda Access Point.
The following actions are related to GetAccessPointConfigurationForObjectLambda:
Returns configuration information about the specified Object Lambda Access Point
The following actions are related to GetAccessPointForObjectLambda:
Returns the access point policy associated with the specified access point.
The following actions are related to GetAccessPointPolicy:
Returns the resource policy for an Object Lambda Access Point.
The following actions are related to GetAccessPointPolicyForObjectLambda:
Indicates whether the specified access point currently has a policy that allows public access. For more information about public access through access points, see Managing Data Access with Amazon S3 access points in the Amazon S3 User Guide.
', 'GetAccessPointPolicyStatusForObjectLambda' => 'Returns the status of the resource policy associated with an Object Lambda Access Point.
', 'GetBucket' => 'Gets an Amazon S3 on Outposts bucket. For more information, see Using Amazon S3 on Outposts in the Amazon S3 User Guide.
If you are using an identity other than the root user of the Amazon Web Services account that owns the Outposts bucket, the calling identity must have the s3-outposts:GetBucket permissions on the specified Outposts bucket and belong to the Outposts bucket owner\'s account in order to use this action. Only users from Outposts bucket owner account with the right permissions can perform actions on an Outposts bucket.
If you don\'t have s3-outposts:GetBucket permissions or you\'re not using an identity that belongs to the bucket owner\'s account, Amazon S3 returns a 403 Access Denied error.
The following actions are related to GetBucket for Amazon S3 on Outposts:
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
This action gets an Amazon S3 on Outposts bucket\'s lifecycle configuration. To get an S3 bucket\'s lifecycle configuration, see GetBucketLifecycleConfiguration in the Amazon S3 API Reference.
Returns the lifecycle configuration information set on the Outposts bucket. For more information, see Using Amazon S3 on Outposts and for information about lifecycle configuration, see Object Lifecycle Management in Amazon S3 User Guide.
To use this action, you must have permission to perform the s3-outposts:GetLifecycleConfiguration action. The Outposts bucket owner has this permission, by default. The bucket owner can grant this permission to others. For more information about permissions, see Permissions Related to Bucket Subresource Operations and Managing Access Permissions to Your Amazon S3 Resources.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
GetBucketLifecycleConfiguration has the following special error:
Error code: NoSuchLifecycleConfiguration
Description: The lifecycle configuration does not exist.
HTTP Status Code: 404 Not Found
SOAP Fault Code Prefix: Client
The following actions are related to GetBucketLifecycleConfiguration:
This action gets a bucket policy for an Amazon S3 on Outposts bucket. To get a policy for an S3 bucket, see GetBucketPolicy in the Amazon S3 API Reference.
Returns the policy of a specified Outposts bucket. For more information, see Using Amazon S3 on Outposts in the Amazon S3 User Guide.
If you are using an identity other than the root user of the Amazon Web Services account that owns the bucket, the calling identity must have the GetBucketPolicy permissions on the specified bucket and belong to the bucket owner\'s account in order to use this action.
Only users from Outposts bucket owner account with the right permissions can perform actions on an Outposts bucket. If you don\'t have s3-outposts:GetBucketPolicy permissions or you\'re not using an identity that belongs to the bucket owner\'s account, Amazon S3 returns a 403 Access Denied error.
As a security precaution, the root user of the Amazon Web Services account that owns a bucket can always use this action, even if the policy explicitly denies the root user the ability to perform this action.
For more information about bucket policies, see Using Bucket Policies and User Policies.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following actions are related to GetBucketPolicy:
This operation gets an Amazon S3 on Outposts bucket\'s replication configuration. To get an S3 bucket\'s replication configuration, see GetBucketReplication in the Amazon S3 API Reference.
Returns the replication configuration of an S3 on Outposts bucket. For more information about S3 on Outposts, see Using Amazon S3 on Outposts in the Amazon S3 User Guide. For information about S3 replication on Outposts configuration, see Replicating objects for S3 on Outposts in the Amazon S3 User Guide.
It can take a while to propagate PUT or DELETE requests for a replication configuration to all S3 on Outposts systems. Therefore, the replication configuration that\'s returned by a GET request soon after a PUT or DELETE request might return a more recent result than what\'s on the Outpost. If an Outpost is offline, the delay in updating the replication configuration on that Outpost can be significant.
This action requires permissions for the s3-outposts:GetReplicationConfiguration action. The Outposts bucket owner has this permission by default and can grant it to others. For more information about permissions, see Setting up IAM with S3 on Outposts and Managing access to S3 on Outposts bucket in the Amazon S3 User Guide.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
If you include the Filter element in a replication configuration, you must also include the DeleteMarkerReplication, Status, and Priority elements. The response also returns those elements.
For information about S3 on Outposts replication failure reasons, see Replication failure reasons in the Amazon S3 User Guide.
The following operations are related to GetBucketReplication:
This action gets an Amazon S3 on Outposts bucket\'s tags. To get an S3 bucket tags, see GetBucketTagging in the Amazon S3 API Reference.
Returns the tag set associated with the Outposts bucket. For more information, see Using Amazon S3 on Outposts in the Amazon S3 User Guide.
To use this action, you must have permission to perform the GetBucketTagging action. By default, the bucket owner has this permission and can grant this permission to others.
GetBucketTagging has the following special error:
Error code: NoSuchTagSetError
Description: There is no tag set associated with the bucket.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following actions are related to GetBucketTagging:
This operation returns the versioning state for S3 on Outposts buckets only. To return the versioning state for an S3 bucket, see GetBucketVersioning in the Amazon S3 API Reference.
Returns the versioning state for an S3 on Outposts bucket. With S3 Versioning, you can save multiple distinct copies of your objects and recover from unintended user actions and application failures.
If you\'ve never set versioning on your bucket, it has no versioning state. In that case, the GetBucketVersioning request does not return a versioning state value.
For more information about versioning, see Versioning in the Amazon S3 User Guide.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following operations are related to GetBucketVersioning for S3 on Outposts.
Returns the tags on an S3 Batch Operations job. To use the GetJobTagging operation, you must have permission to perform the s3:GetJobTagging action. For more information, see Controlling access and labeling jobs using tags in the Amazon S3 User Guide.
Related actions include:
', 'GetMultiRegionAccessPoint' => 'Returns configuration information about the specified Multi-Region Access Point.
This action will always be routed to the US West (Oregon) Region. For more information about the restrictions around managing Multi-Region Access Points, see Managing Multi-Region Access Points in the Amazon S3 User Guide.
The following actions are related to GetMultiRegionAccessPoint:
Returns the access control policy of the specified Multi-Region Access Point.
This action will always be routed to the US West (Oregon) Region. For more information about the restrictions around managing Multi-Region Access Points, see Managing Multi-Region Access Points in the Amazon S3 User Guide.
The following actions are related to GetMultiRegionAccessPointPolicy:
Indicates whether the specified Multi-Region Access Point has an access control policy that allows public access.
This action will always be routed to the US West (Oregon) Region. For more information about the restrictions around managing Multi-Region Access Points, see Managing Multi-Region Access Points in the Amazon S3 User Guide.
The following actions are related to GetMultiRegionAccessPointPolicyStatus:
Returns the routing configuration for a Multi-Region Access Point, indicating which Regions are active or passive.
To obtain routing control changes and failover requests, use the Amazon S3 failover control infrastructure endpoints in these five Amazon Web Services Regions:
us-east-1
us-west-2
ap-southeast-2
ap-northeast-1
eu-west-1
Your Amazon S3 bucket does not need to be in these five Regions.
Retrieves the PublicAccessBlock configuration for an Amazon Web Services account. For more information, see Using Amazon S3 block public access.
Related actions include:
', 'GetStorageLensConfiguration' => 'Gets the Amazon S3 Storage Lens configuration. For more information, see Assessing your storage activity and usage with Amazon S3 Storage Lens in the Amazon S3 User Guide. For a complete list of S3 Storage Lens metrics, see S3 Storage Lens metrics glossary in the Amazon S3 User Guide.
To use this action, you must have permission to perform the s3:GetStorageLensConfiguration action. For more information, see Setting permissions to use Amazon S3 Storage Lens in the Amazon S3 User Guide.
Gets the tags of Amazon S3 Storage Lens configuration. For more information about S3 Storage Lens, see Assessing your storage activity and usage with Amazon S3 Storage Lens in the Amazon S3 User Guide.
To use this action, you must have permission to perform the s3:GetStorageLensConfigurationTagging action. For more information, see Setting permissions to use Amazon S3 Storage Lens in the Amazon S3 User Guide.
Retrieves the Storage Lens group configuration details.
To use this operation, you must have the permission to perform the s3:GetStorageLensGroup action. For more information about the required Storage Lens Groups permissions, see Setting account permissions to use S3 Storage Lens groups.
For information about Storage Lens groups errors, see List of Amazon S3 Storage Lens error codes.
', 'ListAccessPoints' => 'Returns a list of the access points that are owned by the current account that\'s associated with the specified bucket. You can retrieve up to 1000 access points per call. If the specified bucket has more than 1,000 access points (or the number specified in maxResults, whichever is less), the response will include a continuation token that you can use to list the additional access points.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following actions are related to ListAccessPoints:
Returns some or all (up to 1,000) access points associated with the Object Lambda Access Point per call. If there are more access points than what can be returned in one call, the response will include a continuation token that you can use to list the additional access points.
The following actions are related to ListAccessPointsForObjectLambda:
Lists current S3 Batch Operations jobs and jobs that have ended within the last 30 days for the Amazon Web Services account making the request. For more information, see S3 Batch Operations in the Amazon S3 User Guide.
Related actions include:
', 'ListMultiRegionAccessPoints' => 'Returns a list of the Multi-Region Access Points currently associated with the specified Amazon Web Services account. Each call can return up to 100 Multi-Region Access Points, the maximum number of Multi-Region Access Points that can be associated with a single account.
This action will always be routed to the US West (Oregon) Region. For more information about the restrictions around managing Multi-Region Access Points, see Managing Multi-Region Access Points in the Amazon S3 User Guide.
The following actions are related to ListMultiRegionAccessPoint:
Returns a list of all Outposts buckets in an Outpost that are owned by the authenticated sender of the request. For more information, see Using Amazon S3 on Outposts in the Amazon S3 User Guide.
For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and x-amz-outpost-id in your request, see the Examples section.
Gets a list of Amazon S3 Storage Lens configurations. For more information about S3 Storage Lens, see Assessing your storage activity and usage with Amazon S3 Storage Lens in the Amazon S3 User Guide.
To use this action, you must have permission to perform the s3:ListStorageLensConfigurations action. For more information, see Setting permissions to use Amazon S3 Storage Lens in the Amazon S3 User Guide.
Lists all the Storage Lens groups in the specified home Region.
To use this operation, you must have the permission to perform the s3:ListStorageLensGroups action. For more information about the required Storage Lens Groups permissions, see Setting account permissions to use S3 Storage Lens groups.
For information about Storage Lens groups errors, see List of Amazon S3 Storage Lens error codes.
', 'ListTagsForResource' => 'This operation allows you to list all the Amazon Web Services resource tags for the specified resource.
To use this operation, you must have the permission to perform the s3:ListTagsForResource action. For more information about the required Storage Lens Groups permissions, see Setting account permissions to use S3 Storage Lens groups.
For information about S3 Tagging errors, see List of Amazon S3 Tagging error codes.
This operation is only supported for S3 Storage Lens groups.
Replaces configuration for an Object Lambda Access Point.
The following actions are related to PutAccessPointConfigurationForObjectLambda:
Associates an access policy with the specified access point. Each access point can have only one policy, so a request made to this API replaces any existing policy associated with the specified access point.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following actions are related to PutAccessPointPolicy:
Creates or replaces resource policy for an Object Lambda Access Point. For an example policy, see Creating Object Lambda Access Points in the Amazon S3 User Guide.
The following actions are related to PutAccessPointPolicyForObjectLambda:
This action puts a lifecycle configuration to an Amazon S3 on Outposts bucket. To put a lifecycle configuration to an S3 bucket, see PutBucketLifecycleConfiguration in the Amazon S3 API Reference.
Creates a new lifecycle configuration for the S3 on Outposts bucket or replaces an existing lifecycle configuration. Outposts buckets only support lifecycle configurations that delete/expire objects after a certain period of time and abort incomplete multipart uploads.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following actions are related to PutBucketLifecycleConfiguration:
This action puts a bucket policy to an Amazon S3 on Outposts bucket. To put a policy on an S3 bucket, see PutBucketPolicy in the Amazon S3 API Reference.
Applies an Amazon S3 bucket policy to an Outposts bucket. For more information, see Using Amazon S3 on Outposts in the Amazon S3 User Guide.
If you are using an identity other than the root user of the Amazon Web Services account that owns the Outposts bucket, the calling identity must have the PutBucketPolicy permissions on the specified Outposts bucket and belong to the bucket owner\'s account in order to use this action.
If you don\'t have PutBucketPolicy permissions, Amazon S3 returns a 403 Access Denied error. If you have the correct permissions, but you\'re not using an identity that belongs to the bucket owner\'s account, Amazon S3 returns a 405 Method Not Allowed error.
As a security precaution, the root user of the Amazon Web Services account that owns a bucket can always use this action, even if the policy explicitly denies the root user the ability to perform this action.
For more information about bucket policies, see Using Bucket Policies and User Policies.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following actions are related to PutBucketPolicy:
This action creates an Amazon S3 on Outposts bucket\'s replication configuration. To create an S3 bucket\'s replication configuration, see PutBucketReplication in the Amazon S3 API Reference.
Creates a replication configuration or replaces an existing one. For information about S3 replication on Outposts configuration, see Replicating objects for S3 on Outposts in the Amazon S3 User Guide.
It can take a while to propagate PUT or DELETE requests for a replication configuration to all S3 on Outposts systems. Therefore, the replication configuration that\'s returned by a GET request soon after a PUT or DELETE request might return a more recent result than what\'s on the Outpost. If an Outpost is offline, the delay in updating the replication configuration on that Outpost can be significant.
Specify the replication configuration in the request body. In the replication configuration, you provide the following information:
The name of the destination bucket or buckets where you want S3 on Outposts to replicate objects
The Identity and Access Management (IAM) role that S3 on Outposts can assume to replicate objects on your behalf
Other relevant information, such as replication rules
A replication configuration must include at least one rule and can contain a maximum of 100. Each rule identifies a subset of objects to replicate by filtering the objects in the source Outposts bucket. To choose additional subsets of objects to replicate, add a rule for each subset.
To specify a subset of the objects in the source Outposts bucket to apply a replication rule to, add the Filter element as a child of the Rule element. You can filter objects based on an object key prefix, one or more object tags, or both. When you add the Filter element in the configuration, you must also add the following elements: DeleteMarkerReplication, Status, and Priority.
Using PutBucketReplication on Outposts requires that both the source and destination buckets must have versioning enabled. For information about enabling versioning on a bucket, see Managing S3 Versioning for your S3 on Outposts bucket.
For information about S3 on Outposts replication failure reasons, see Replication failure reasons in the Amazon S3 User Guide.
Handling Replication of Encrypted Objects
Outposts buckets are encrypted at all times. All the objects in the source Outposts bucket are encrypted and can be replicated. Also, all the replicas in the destination Outposts bucket are encrypted with the same encryption key as the objects in the source Outposts bucket.
Permissions
To create a PutBucketReplication request, you must have s3-outposts:PutReplicationConfiguration permissions for the bucket. The Outposts bucket owner has this permission by default and can grant it to others. For more information about permissions, see Setting up IAM with S3 on Outposts and Managing access to S3 on Outposts buckets.
To perform this operation, the user or role must also have the iam:CreateRole and iam:PassRole permissions. For more information, see Granting a user permissions to pass a role to an Amazon Web Services service.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following operations are related to PutBucketReplication:
This action puts tags on an Amazon S3 on Outposts bucket. To put tags on an S3 bucket, see PutBucketTagging in the Amazon S3 API Reference.
Sets the tags for an S3 on Outposts bucket. For more information, see Using Amazon S3 on Outposts in the Amazon S3 User Guide.
Use tags to organize your Amazon Web Services bill to reflect your own cost structure. To do this, sign up to get your Amazon Web Services account bill with tag key values included. Then, to see the cost of combined resources, organize your billing information according to resources with the same tag key values. For example, you can tag several resources with a specific application name, and then organize your billing information to see the total cost of that application across several services. For more information, see Cost allocation and tagging.
Within a bucket, if you add a tag that has the same key as an existing tag, the new value overwrites the old value. For more information, see Using cost allocation in Amazon S3 bucket tags.
To use this action, you must have permissions to perform the s3-outposts:PutBucketTagging action. The Outposts bucket owner has this permission by default and can grant this permission to others. For more information about permissions, see Permissions Related to Bucket Subresource Operations and Managing access permissions to your Amazon S3 resources.
PutBucketTagging has the following special errors:
Error code: InvalidTagError
Description: The tag provided was not a valid tag. This error can occur if the tag did not pass input validation. For information about tag restrictions, see User-Defined Tag Restrictions and Amazon Web Services-Generated Cost Allocation Tag Restrictions.
Error code: MalformedXMLError
Description: The XML provided does not match the schema.
Error code: OperationAbortedError
Description: A conflicting conditional action is currently in progress against this resource. Try again.
Error code: InternalError
Description: The service was unable to apply the provided tag to the bucket.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following actions are related to PutBucketTagging:
This operation sets the versioning state for S3 on Outposts buckets only. To set the versioning state for an S3 bucket, see PutBucketVersioning in the Amazon S3 API Reference.
Sets the versioning state for an S3 on Outposts bucket. With S3 Versioning, you can save multiple distinct copies of your objects and recover from unintended user actions and application failures.
You can set the versioning state to one of the following:
Enabled - Enables versioning for the objects in the bucket. All objects added to the bucket receive a unique version ID.
Suspended - Suspends versioning for the objects in the bucket. All objects added to the bucket receive the version ID null.
If you\'ve never set versioning on your bucket, it has no versioning state. In that case, a GetBucketVersioning request does not return a versioning state value.
When you enable S3 Versioning, for each object in your bucket, you have a current version and zero or more noncurrent versions. You can configure your bucket S3 Lifecycle rules to expire noncurrent versions after a specified time period. For more information, see Creating and managing a lifecycle configuration for your S3 on Outposts bucket in the Amazon S3 User Guide.
If you have an object expiration lifecycle configuration in your non-versioned bucket and you want to maintain the same permanent delete behavior when you enable versioning, you must add a noncurrent expiration policy. The noncurrent expiration lifecycle configuration will manage the deletes of the noncurrent object versions in the version-enabled bucket. For more information, see Versioning in the Amazon S3 User Guide.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following operations are related to PutBucketVersioning for S3 on Outposts.
Sets the supplied tag-set on an S3 Batch Operations job.
A tag is a key-value pair. You can associate S3 Batch Operations tags with any job by sending a PUT request against the tagging subresource that is associated with the job. To modify the existing tag set, you can either replace the existing tag set entirely, or make changes within the existing tag set by retrieving the existing tag set using GetJobTagging, modify that tag set, and use this action to replace the tag set with the one you modified. For more information, see Controlling access and labeling jobs using tags in the Amazon S3 User Guide.
If you send this request with an empty tag set, Amazon S3 deletes the existing tag set on the Batch Operations job. If you use this method, you are charged for a Tier 1 Request (PUT). For more information, see Amazon S3 pricing.
For deleting existing tags for your Batch Operations job, a DeleteJobTagging request is preferred because it achieves the same result without incurring charges.
A few things to consider about using tags:
Amazon S3 limits the maximum number of tags to 50 tags per job.
You can associate up to 50 tags with a job as long as they have unique tag keys.
A tag key can be up to 128 Unicode characters in length, and tag values can be up to 256 Unicode characters in length.
The key and values are case sensitive.
For tagging-related restrictions related to characters and encodings, see User-Defined Tag Restrictions in the Billing and Cost Management User Guide.
To use the PutJobTagging operation, you must have permission to perform the s3:PutJobTagging action.
Related actions include:
', 'PutMultiRegionAccessPointPolicy' => 'Associates an access control policy with the specified Multi-Region Access Point. Each Multi-Region Access Point can have only one policy, so a request made to this action replaces any existing policy that is associated with the specified Multi-Region Access Point.
This action will always be routed to the US West (Oregon) Region. For more information about the restrictions around managing Multi-Region Access Points, see Managing Multi-Region Access Points in the Amazon S3 User Guide.
The following actions are related to PutMultiRegionAccessPointPolicy:
Creates or modifies the PublicAccessBlock configuration for an Amazon Web Services account. For this operation, users must have the s3:PutAccountPublicAccessBlock permission. For more information, see Using Amazon S3 block public access.
Related actions include:
', 'PutStorageLensConfiguration' => 'Puts an Amazon S3 Storage Lens configuration. For more information about S3 Storage Lens, see Working with Amazon S3 Storage Lens in the Amazon S3 User Guide. For a complete list of S3 Storage Lens metrics, see S3 Storage Lens metrics glossary in the Amazon S3 User Guide.
To use this action, you must have permission to perform the s3:PutStorageLensConfiguration action. For more information, see Setting permissions to use Amazon S3 Storage Lens in the Amazon S3 User Guide.
Put or replace tags on an existing Amazon S3 Storage Lens configuration. For more information about S3 Storage Lens, see Assessing your storage activity and usage with Amazon S3 Storage Lens in the Amazon S3 User Guide.
To use this action, you must have permission to perform the s3:PutStorageLensConfigurationTagging action. For more information, see Setting permissions to use Amazon S3 Storage Lens in the Amazon S3 User Guide.
Submits an updated route configuration for a Multi-Region Access Point. This API operation updates the routing status for the specified Regions from active to passive, or from passive to active. A value of 0 indicates a passive status, which means that traffic won\'t be routed to the specified Region. A value of 100 indicates an active status, which means that traffic will be routed to the specified Region. At least one Region must be active at all times.
When the routing configuration is changed, any in-progress operations (uploads, copies, deletes, and so on) to formerly active Regions will continue to run to their final completion state (success or failure). The routing configurations of any Regions that aren’t specified remain unchanged.
Updated routing configurations might not be immediately applied. It can take up to 2 minutes for your changes to take effect.
To submit routing control changes and failover requests, use the Amazon S3 failover control infrastructure endpoints in these five Amazon Web Services Regions:
us-east-1
us-west-2
ap-southeast-2
ap-northeast-1
eu-west-1
Your Amazon S3 bucket does not need to be in these five Regions.
Creates a new Amazon Web Services resource tag or updates an existing resource tag. You can add up to 50 Amazon Web Services resource tags for each S3 resource.
To use this operation, you must have the permission to perform the s3:TagResource action. For more information about the required Storage Lens Groups permissions, see Setting account permissions to use S3 Storage Lens groups.
For information about S3 Tagging errors, see List of Amazon S3 Tagging error codes.
This operation is only supported for S3 Storage Lens groups.
This operation removes the specified Amazon Web Services resource tags from an S3 resource.
To use this operation, you must have the permission to perform the s3:UntagResource action. For more information about the required Storage Lens Groups permissions, see Setting account permissions to use S3 Storage Lens groups.
For information about S3 Tagging errors, see List of Amazon S3 Tagging error codes.
This operation is only supported for S3 Storage Lens groups.
Updates an existing S3 Batch Operations job\'s priority. For more information, see S3 Batch Operations in the Amazon S3 User Guide.
Related actions include:
', 'UpdateJobStatus' => 'Updates the status for the specified job. Use this action to confirm that you want to run a job or to cancel an existing job. For more information, see S3 Batch Operations in the Amazon S3 User Guide.
Related actions include:
', 'UpdateStorageLensGroup' => 'Updates the existing Storage Lens group.
To use this operation, you must have the permission to perform the s3:UpdateStorageLensGroup action. For more information about the required Storage Lens Groups permissions, see Setting account permissions to use S3 Storage Lens groups.
For information about Storage Lens groups errors, see List of Amazon S3 Storage Lens error codes.
', ], 'shapes' => [ 'AbortIncompleteMultipartUpload' => [ 'base' => 'The container for abort incomplete multipart upload
', 'refs' => [ 'LifecycleRule$AbortIncompleteMultipartUpload' => 'Specifies the days since the initiation of an incomplete multipart upload that Amazon S3 waits before permanently removing all parts of the upload. For more information, see Aborting Incomplete Multipart Uploads Using a Bucket Lifecycle Configuration in the Amazon S3 User Guide.
', ], ], 'AccessControlTranslation' => [ 'base' => 'A container for information about access control for replicas.
This is not supported by Amazon S3 on Outposts buckets.
Specify this property only in a cross-account scenario (where the source and destination bucket owners are not the same), and you want to change replica ownership to the Amazon Web Services account that owns the destination bucket. If this property is not specified in the replication configuration, the replicas are owned by same Amazon Web Services account that owns the source object.
This is not supported by Amazon S3 on Outposts buckets.
An access point used to access a bucket.
', 'refs' => [ 'AccessPointList$member' => NULL, ], ], 'AccessPointList' => [ 'base' => NULL, 'refs' => [ 'ListAccessPointsResult$AccessPointList' => 'Contains identification and configuration information for one or more access points associated with the specified bucket.
', ], ], 'AccessPointName' => [ 'base' => NULL, 'refs' => [ 'AccessPoint$Name' => 'The name of this access point.
', 'CreateAccessPointRequest$Name' => 'The name you want to assign to this access point.
', 'DeleteAccessPointPolicyRequest$Name' => 'The name of the access point whose policy you want to delete.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the access point accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/accesspoint/<my-accesspoint-name>. For example, to access the access point reports-ap through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/accesspoint/reports-ap. The value must be URL encoded.
The name of the access point you want to delete.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the access point accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/accesspoint/<my-accesspoint-name>. For example, to access the access point reports-ap through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/accesspoint/reports-ap. The value must be URL encoded.
The name of the access point whose policy you want to retrieve.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the access point accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/accesspoint/<my-accesspoint-name>. For example, to access the access point reports-ap through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/accesspoint/reports-ap. The value must be URL encoded.
The name of the access point whose policy status you want to retrieve.
', 'GetAccessPointRequest$Name' => 'The name of the access point whose configuration information you want to retrieve.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the access point accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/accesspoint/<my-accesspoint-name>. For example, to access the access point reports-ap through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/accesspoint/reports-ap. The value must be URL encoded.
The name of the specified access point.
', 'PutAccessPointPolicyRequest$Name' => 'The name of the access point that you want to associate with the specified policy.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the access point accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/accesspoint/<my-accesspoint-name>. For example, to access the access point reports-ap through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/accesspoint/reports-ap. The value must be URL encoded.
The Amazon Web Services account ID associated with the S3 bucket associated with this access point.
', 'CreateAccessPointForObjectLambdaRequest$AccountId' => 'The Amazon Web Services account ID for owner of the specified Object Lambda Access Point.
', 'CreateAccessPointRequest$AccountId' => 'The Amazon Web Services account ID for the account that owns the specified access point.
', 'CreateAccessPointRequest$BucketAccountId' => 'The Amazon Web Services account ID associated with the S3 bucket associated with this access point.
', 'CreateJobRequest$AccountId' => 'The Amazon Web Services account ID that creates the job.
', 'CreateMultiRegionAccessPointRequest$AccountId' => 'The Amazon Web Services account ID for the owner of the Multi-Region Access Point. The owner of the Multi-Region Access Point also must own the underlying buckets.
', 'CreateStorageLensGroupRequest$AccountId' => 'The Amazon Web Services account ID that the Storage Lens group is created from and associated with.
', 'DeleteAccessPointForObjectLambdaRequest$AccountId' => 'The account ID for the account that owns the specified Object Lambda Access Point.
', 'DeleteAccessPointPolicyForObjectLambdaRequest$AccountId' => 'The account ID for the account that owns the specified Object Lambda Access Point.
', 'DeleteAccessPointPolicyRequest$AccountId' => 'The account ID for the account that owns the specified access point.
', 'DeleteAccessPointRequest$AccountId' => 'The Amazon Web Services account ID for the account that owns the specified access point.
', 'DeleteBucketLifecycleConfigurationRequest$AccountId' => 'The account ID of the lifecycle configuration to delete.
', 'DeleteBucketPolicyRequest$AccountId' => 'The account ID of the Outposts bucket.
', 'DeleteBucketReplicationRequest$AccountId' => 'The Amazon Web Services account ID of the Outposts bucket to delete the replication configuration for.
', 'DeleteBucketRequest$AccountId' => 'The account ID that owns the Outposts bucket.
', 'DeleteBucketTaggingRequest$AccountId' => 'The Amazon Web Services account ID of the Outposts bucket tag set to be removed.
', 'DeleteJobTaggingRequest$AccountId' => 'The Amazon Web Services account ID associated with the S3 Batch Operations job.
', 'DeleteMultiRegionAccessPointRequest$AccountId' => 'The Amazon Web Services account ID for the owner of the Multi-Region Access Point.
', 'DeletePublicAccessBlockRequest$AccountId' => 'The account ID for the Amazon Web Services account whose PublicAccessBlock configuration you want to remove.
The account ID of the requester.
', 'DeleteStorageLensConfigurationTaggingRequest$AccountId' => 'The account ID of the requester.
', 'DeleteStorageLensGroupRequest$AccountId' => 'The Amazon Web Services account ID used to create the Storage Lens group that you\'re trying to delete.
', 'DescribeJobRequest$AccountId' => 'The Amazon Web Services account ID associated with the S3 Batch Operations job.
', 'DescribeMultiRegionAccessPointOperationRequest$AccountId' => 'The Amazon Web Services account ID for the owner of the Multi-Region Access Point.
', 'Destination$Account' => 'The destination bucket owner\'s account ID.
', 'GetAccessPointConfigurationForObjectLambdaRequest$AccountId' => 'The account ID for the account that owns the specified Object Lambda Access Point.
', 'GetAccessPointForObjectLambdaRequest$AccountId' => 'The account ID for the account that owns the specified Object Lambda Access Point.
', 'GetAccessPointPolicyForObjectLambdaRequest$AccountId' => 'The account ID for the account that owns the specified Object Lambda Access Point.
', 'GetAccessPointPolicyRequest$AccountId' => 'The account ID for the account that owns the specified access point.
', 'GetAccessPointPolicyStatusForObjectLambdaRequest$AccountId' => 'The account ID for the account that owns the specified Object Lambda Access Point.
', 'GetAccessPointPolicyStatusRequest$AccountId' => 'The account ID for the account that owns the specified access point.
', 'GetAccessPointRequest$AccountId' => 'The Amazon Web Services account ID for the account that owns the specified access point.
', 'GetAccessPointResult$BucketAccountId' => 'The Amazon Web Services account ID associated with the S3 bucket associated with this access point.
', 'GetBucketLifecycleConfigurationRequest$AccountId' => 'The Amazon Web Services account ID of the Outposts bucket.
', 'GetBucketPolicyRequest$AccountId' => 'The Amazon Web Services account ID of the Outposts bucket.
', 'GetBucketReplicationRequest$AccountId' => 'The Amazon Web Services account ID of the Outposts bucket.
', 'GetBucketRequest$AccountId' => 'The Amazon Web Services account ID of the Outposts bucket.
', 'GetBucketTaggingRequest$AccountId' => 'The Amazon Web Services account ID of the Outposts bucket.
', 'GetBucketVersioningRequest$AccountId' => 'The Amazon Web Services account ID of the S3 on Outposts bucket.
', 'GetJobTaggingRequest$AccountId' => 'The Amazon Web Services account ID associated with the S3 Batch Operations job.
', 'GetMultiRegionAccessPointPolicyRequest$AccountId' => 'The Amazon Web Services account ID for the owner of the Multi-Region Access Point.
', 'GetMultiRegionAccessPointPolicyStatusRequest$AccountId' => 'The Amazon Web Services account ID for the owner of the Multi-Region Access Point.
', 'GetMultiRegionAccessPointRequest$AccountId' => 'The Amazon Web Services account ID for the owner of the Multi-Region Access Point.
', 'GetMultiRegionAccessPointRoutesRequest$AccountId' => 'The Amazon Web Services account ID for the owner of the Multi-Region Access Point.
', 'GetPublicAccessBlockRequest$AccountId' => 'The account ID for the Amazon Web Services account whose PublicAccessBlock configuration you want to retrieve.
The account ID of the requester.
', 'GetStorageLensConfigurationTaggingRequest$AccountId' => 'The account ID of the requester.
', 'GetStorageLensGroupRequest$AccountId' => 'The Amazon Web Services account ID associated with the Storage Lens group that you\'re trying to retrieve the details for.
', 'ListAccessPointsForObjectLambdaRequest$AccountId' => 'The account ID for the account that owns the specified Object Lambda Access Point.
', 'ListAccessPointsRequest$AccountId' => 'The Amazon Web Services account ID for the account that owns the specified access points.
', 'ListJobsRequest$AccountId' => 'The Amazon Web Services account ID associated with the S3 Batch Operations job.
', 'ListMultiRegionAccessPointsRequest$AccountId' => 'The Amazon Web Services account ID for the owner of the Multi-Region Access Point.
', 'ListRegionalBucketsRequest$AccountId' => 'The Amazon Web Services account ID of the Outposts bucket.
', 'ListStorageLensConfigurationsRequest$AccountId' => 'The account ID of the requester.
', 'ListStorageLensGroupsRequest$AccountId' => 'The Amazon Web Services account ID that owns the Storage Lens groups.
', 'ListTagsForResourceRequest$AccountId' => 'The Amazon Web Services account ID of the resource owner.
', 'PutAccessPointConfigurationForObjectLambdaRequest$AccountId' => 'The account ID for the account that owns the specified Object Lambda Access Point.
', 'PutAccessPointPolicyForObjectLambdaRequest$AccountId' => 'The account ID for the account that owns the specified Object Lambda Access Point.
', 'PutAccessPointPolicyRequest$AccountId' => 'The Amazon Web Services account ID for owner of the bucket associated with the specified access point.
', 'PutBucketLifecycleConfigurationRequest$AccountId' => 'The Amazon Web Services account ID of the Outposts bucket.
', 'PutBucketPolicyRequest$AccountId' => 'The Amazon Web Services account ID of the Outposts bucket.
', 'PutBucketReplicationRequest$AccountId' => 'The Amazon Web Services account ID of the Outposts bucket.
', 'PutBucketTaggingRequest$AccountId' => 'The Amazon Web Services account ID of the Outposts bucket.
', 'PutBucketVersioningRequest$AccountId' => 'The Amazon Web Services account ID of the S3 on Outposts bucket.
', 'PutJobTaggingRequest$AccountId' => 'The Amazon Web Services account ID associated with the S3 Batch Operations job.
', 'PutMultiRegionAccessPointPolicyRequest$AccountId' => 'The Amazon Web Services account ID for the owner of the Multi-Region Access Point.
', 'PutPublicAccessBlockRequest$AccountId' => 'The account ID for the Amazon Web Services account whose PublicAccessBlock configuration you want to set.
The account ID of the requester.
', 'PutStorageLensConfigurationTaggingRequest$AccountId' => 'The account ID of the requester.
', 'Region$BucketAccountId' => 'The Amazon Web Services account ID that owns the Amazon S3 bucket that\'s associated with this Multi-Region Access Point.
', 'RegionReport$BucketAccountId' => 'The Amazon Web Services account ID that owns the Amazon S3 bucket that\'s associated with this Multi-Region Access Point.
', 'S3BucketDestination$AccountId' => 'The account ID of the owner of the S3 Storage Lens metrics export bucket.
', 'S3JobManifestGenerator$ExpectedBucketOwner' => 'The Amazon Web Services account ID that owns the bucket the generated manifest is written to. If provided the generated manifest bucket\'s owner Amazon Web Services account ID must match this value, else the job fails.
', 'S3ManifestOutputLocation$ExpectedManifestBucketOwner' => 'The Account ID that owns the bucket the generated manifest is written to.
', 'SubmitMultiRegionAccessPointRoutesRequest$AccountId' => 'The Amazon Web Services account ID for the owner of the Multi-Region Access Point.
', 'TagResourceRequest$AccountId' => 'The Amazon Web Services account ID that created the S3 resource that you\'re trying to add tags to.
', 'UntagResourceRequest$AccountId' => 'The Amazon Web Services account ID that owns the resource that you\'re trying to remove the tags from.
', 'UpdateJobPriorityRequest$AccountId' => 'The Amazon Web Services account ID associated with the S3 Batch Operations job.
', 'UpdateJobStatusRequest$AccountId' => 'The Amazon Web Services account ID associated with the S3 Batch Operations job.
', 'UpdateStorageLensGroupRequest$AccountId' => 'The Amazon Web Services account ID of the Storage Lens group owner.
', ], ], 'AccountLevel' => [ 'base' => 'A container element for the account-level Amazon S3 Storage Lens configuration.
For more information about S3 Storage Lens, see Assessing your storage activity and usage with S3 Storage Lens in the Amazon S3 User Guide. For a complete list of S3 Storage Lens metrics, see S3 Storage Lens metrics glossary in the Amazon S3 User Guide.
', 'refs' => [ 'StorageLensConfiguration$AccountLevel' => 'A container for all the account-level configurations of your S3 Storage Lens configuration.
', ], ], 'ActivityMetrics' => [ 'base' => 'The container element for Amazon S3 Storage Lens activity metrics. Activity metrics show details about how your storage is requested, such as requests (for example, All requests, Get requests, Put requests), bytes uploaded or downloaded, and errors.
For more information about S3 Storage Lens, see Assessing your storage activity and usage with S3 Storage Lens in the Amazon S3 User Guide. For a complete list of S3 Storage Lens metrics, see S3 Storage Lens metrics glossary in the Amazon S3 User Guide.
', 'refs' => [ 'AccountLevel$ActivityMetrics' => 'A container element for S3 Storage Lens activity metrics.
', 'BucketLevel$ActivityMetrics' => 'A container for the bucket-level activity metrics for S3 Storage Lens.
', ], ], 'AdvancedCostOptimizationMetrics' => [ 'base' => 'The container element for Amazon S3 Storage Lens advanced cost-optimization metrics. Advanced cost-optimization metrics provide insights that you can use to manage and optimize your storage costs, for example, lifecycle rule counts for transitions, expirations, and incomplete multipart uploads.
For more information about S3 Storage Lens, see Assessing your storage activity and usage with S3 Storage Lens in the Amazon S3 User Guide. For a complete list of S3 Storage Lens metrics, see S3 Storage Lens metrics glossary in the Amazon S3 User Guide.
', 'refs' => [ 'AccountLevel$AdvancedCostOptimizationMetrics' => 'A container element for S3 Storage Lens advanced cost-optimization metrics.
', 'BucketLevel$AdvancedCostOptimizationMetrics' => 'A container for bucket-level advanced cost-optimization metrics for S3 Storage Lens.
', ], ], 'AdvancedDataProtectionMetrics' => [ 'base' => 'The container element for Amazon S3 Storage Lens advanced data-protection metrics. Advanced data-protection metrics provide insights that you can use to perform audits and protect your data, for example replication rule counts within and across Regions.
For more information about S3 Storage Lens, see Assessing your storage activity and usage with S3 Storage Lens in the Amazon S3 User Guide. For a complete list of S3 Storage Lens metrics, see S3 Storage Lens metrics glossary in the Amazon S3 User Guide.
', 'refs' => [ 'AccountLevel$AdvancedDataProtectionMetrics' => 'A container element for S3 Storage Lens advanced data-protection metrics.
', 'BucketLevel$AdvancedDataProtectionMetrics' => 'A container for bucket-level advanced data-protection metrics for S3 Storage Lens.
', ], ], 'Alias' => [ 'base' => NULL, 'refs' => [ 'AccessPoint$Alias' => 'The name or alias of the access point.
', 'CreateAccessPointResult$Alias' => 'The name or alias of the access point.
', 'GetAccessPointResult$Alias' => 'The name or alias of the access point.
', ], ], 'AsyncCreationTimestamp' => [ 'base' => NULL, 'refs' => [ 'AsyncOperation$CreationTime' => 'The time that the request was sent to the service.
', ], ], 'AsyncErrorDetails' => [ 'base' => 'Error details for the failed asynchronous operation.
', 'refs' => [ 'AsyncResponseDetails$ErrorDetails' => 'Error details for an asynchronous request.
', ], ], 'AsyncOperation' => [ 'base' => 'A container for the information about an asynchronous operation.
', 'refs' => [ 'DescribeMultiRegionAccessPointOperationResult$AsyncOperation' => 'A container element containing the details of the asynchronous operation.
', ], ], 'AsyncOperationName' => [ 'base' => NULL, 'refs' => [ 'AsyncOperation$Operation' => 'The specific operation for the asynchronous request.
', ], ], 'AsyncRequestParameters' => [ 'base' => 'A container for the request parameters associated with an asynchronous request.
', 'refs' => [ 'AsyncOperation$RequestParameters' => 'The parameters associated with the request.
', ], ], 'AsyncRequestStatus' => [ 'base' => NULL, 'refs' => [ 'AsyncOperation$RequestStatus' => 'The current status of the request.
', 'MultiRegionAccessPointRegionalResponse$RequestStatus' => 'The current status of the Multi-Region Access Point in this Region.
', ], ], 'AsyncRequestTokenARN' => [ 'base' => NULL, 'refs' => [ 'AsyncOperation$RequestTokenARN' => 'The request token associated with the request.
', 'CreateMultiRegionAccessPointResult$RequestTokenARN' => 'The request token associated with the request. You can use this token with DescribeMultiRegionAccessPointOperation to determine the status of asynchronous requests.
', 'DeleteMultiRegionAccessPointResult$RequestTokenARN' => 'The request token associated with the request. You can use this token with DescribeMultiRegionAccessPointOperation to determine the status of asynchronous requests.
', 'DescribeMultiRegionAccessPointOperationRequest$RequestTokenARN' => 'The request token associated with the request you want to know about. This request token is returned as part of the response when you make an asynchronous request. You provide this token to query about the status of the asynchronous action.
', 'PutMultiRegionAccessPointPolicyResult$RequestTokenARN' => 'The request token associated with the request. You can use this token with DescribeMultiRegionAccessPointOperation to determine the status of asynchronous requests.
', ], ], 'AsyncResponseDetails' => [ 'base' => 'A container for the response details that are returned when querying about an asynchronous request.
', 'refs' => [ 'AsyncOperation$ResponseDetails' => 'The details of the response.
', ], ], 'AwsLambdaTransformation' => [ 'base' => 'Lambda function used to transform objects through an Object Lambda Access Point.
', 'refs' => [ 'ObjectLambdaContentTransformation$AwsLambda' => 'A container for an Lambda function.
', ], ], 'AwsLambdaTransformationPayload' => [ 'base' => NULL, 'refs' => [ 'AwsLambdaTransformation$FunctionPayload' => 'Additional JSON that provides supplemental data to the Lambda function used to transform objects.
', ], ], 'AwsOrgArn' => [ 'base' => NULL, 'refs' => [ 'StorageLensAwsOrg$Arn' => 'A container for the Amazon Resource Name (ARN) of the Amazon Web Services organization. This property is read-only and follows the following format: arn:aws:organizations:us-east-1:example-account-id:organization/o-ex2l495dck
Include objects in the generated manifest only if they are eligible for replication according to the Replication configuration on the source bucket.
', 'JobReport$Enabled' => 'Indicates whether the specified job will generate a job-completion report.
', 'ObjectLambdaConfiguration$CloudWatchMetricsEnabled' => 'A container for whether the CloudWatch metrics configuration is enabled.
', 'S3CopyObjectOperation$RequesterPays' => '', 'S3CopyObjectOperation$BucketKeyEnabled' => 'Specifies whether Amazon S3 should use an S3 Bucket Key for object encryption with server-side encryption using Amazon Web Services KMS (SSE-KMS). Setting this header to true causes Amazon S3 to use an S3 Bucket Key for object encryption with SSE-KMS.
Specifying this header with an object action doesn’t affect bucket-level settings for S3 Bucket Key.
', 'S3JobManifestGenerator$EnableManifestOutput' => 'Determines whether or not to write the job\'s generated manifest to a bucket.
', 'S3ObjectMetadata$RequesterCharged' => '', 'S3SetObjectRetentionOperation$BypassGovernanceRetention' => 'Indicates if the action should be applied to objects in the Batch Operations job even if they have Object Lock GOVERNANCE type in place.
The requested Outposts bucket name is not available. The bucket namespace is shared by all users of the Outposts in this Region. Select a different name and try again.
', 'refs' => [], ], 'BucketAlreadyOwnedByYou' => [ 'base' => 'The Outposts bucket you tried to create already exists, and you own it.
', 'refs' => [], ], 'BucketCannedACL' => [ 'base' => NULL, 'refs' => [ 'CreateBucketRequest$ACL' => 'The canned ACL to apply to the bucket.
This is not supported by Amazon S3 on Outposts buckets.
The Amazon Resource Name (ARN) of the access point for the destination bucket where you want S3 on Outposts to store the replication results.
', 'ReplicationRule$Bucket' => 'The Amazon Resource Name (ARN) of the access point for the source Outposts bucket that you want S3 on Outposts to replicate the objects from.
', ], ], 'BucketLevel' => [ 'base' => 'A container for the bucket-level configuration for Amazon S3 Storage Lens.
For more information about S3 Storage Lens, see Assessing your storage activity and usage with S3 Storage Lens in the Amazon S3 User Guide.
', 'refs' => [ 'AccountLevel$BucketLevel' => 'A container element for the S3 Storage Lens bucket-level configuration.
', ], ], 'BucketLocationConstraint' => [ 'base' => NULL, 'refs' => [ 'CreateBucketConfiguration$LocationConstraint' => 'Specifies the Region where the bucket will be created. If you are creating a bucket on the US East (N. Virginia) Region (us-east-1), you do not need to specify the location.
This is not supported by Amazon S3 on Outposts buckets.
The name of the bucket associated with this access point.
', 'CreateAccessPointRequest$Bucket' => 'The name of the bucket that you want to associate this access point with.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
The name of the bucket.
', 'DeleteBucketLifecycleConfigurationRequest$Bucket' => 'Specifies the bucket.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
Specifies the bucket.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
Specifies the S3 on Outposts bucket to delete the replication configuration for.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
Specifies the bucket being deleted.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
The bucket ARN that has the tag set to be removed.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
The name of the bucket associated with the specified access point.
', 'GetBucketLifecycleConfigurationRequest$Bucket' => 'The Amazon Resource Name (ARN) of the bucket.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
Specifies the bucket.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
Specifies the bucket to get the replication information for.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
Specifies the bucket.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
The Outposts bucket requested.
', 'GetBucketTaggingRequest$Bucket' => 'Specifies the bucket.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
The S3 on Outposts bucket to return the versioning state for.
', 'ListAccessPointsRequest$Bucket' => 'The name of the bucket whose associated access points you want to list.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
The name of the Amazon S3 bucket for which you\'ll submit a routing configuration change. Either the Bucket or the Region value must be provided. If both are provided, the bucket must be in the specified Region.
The name of the bucket for which to set the configuration.
', 'PutBucketPolicyRequest$Bucket' => 'Specifies the bucket.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
Specifies the S3 on Outposts bucket to set the configuration for.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
The Amazon Resource Name (ARN) of the bucket.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
The S3 on Outposts bucket to set the versioning state for.
', 'Region$Bucket' => 'The name of the associated bucket for the Region.
', 'RegionReport$Bucket' => 'The name of the bucket.
', 'RegionalBucket$Bucket' => '', ], ], 'BucketVersioningStatus' => [ 'base' => NULL, 'refs' => [ 'GetBucketVersioningResult$Status' => 'The versioning state of the S3 on Outposts bucket.
', 'VersioningConfiguration$Status' => 'Sets the versioning state of the S3 on Outposts bucket.
', ], ], 'Buckets' => [ 'base' => NULL, 'refs' => [ 'Exclude$Buckets' => 'A container for the S3 Storage Lens bucket excludes.
', 'Include$Buckets' => 'A container for the S3 Storage Lens bucket includes.
', ], ], 'CloudWatchMetrics' => [ 'base' => 'A container for enabling Amazon CloudWatch publishing for S3 Storage Lens metrics.
For more information about publishing S3 Storage Lens metrics to CloudWatch, see Monitor S3 Storage Lens metrics in CloudWatch in the Amazon S3 User Guide.
', 'refs' => [ 'StorageLensDataExport$CloudWatchMetrics' => 'A container for enabling Amazon CloudWatch publishing for S3 Storage Lens metrics.
', ], ], 'ConfigId' => [ 'base' => NULL, 'refs' => [ 'DeleteStorageLensConfigurationRequest$ConfigId' => 'The ID of the S3 Storage Lens configuration.
', 'DeleteStorageLensConfigurationTaggingRequest$ConfigId' => 'The ID of the S3 Storage Lens configuration.
', 'GetStorageLensConfigurationRequest$ConfigId' => 'The ID of the Amazon S3 Storage Lens configuration.
', 'GetStorageLensConfigurationTaggingRequest$ConfigId' => 'The ID of the Amazon S3 Storage Lens configuration.
', 'ListStorageLensConfigurationEntry$Id' => 'A container for the S3 Storage Lens configuration ID.
', 'PutStorageLensConfigurationRequest$ConfigId' => 'The ID of the S3 Storage Lens configuration.
', 'PutStorageLensConfigurationTaggingRequest$ConfigId' => 'The ID of the S3 Storage Lens configuration.
', 'StorageLensConfiguration$Id' => 'A container for the Amazon S3 Storage Lens configuration ID.
', ], ], 'ConfirmRemoveSelfBucketAccess' => [ 'base' => NULL, 'refs' => [ 'PutBucketPolicyRequest$ConfirmRemoveSelfBucketAccess' => 'Set this parameter to true to confirm that you want to remove your permissions to change this bucket policy in the future.
This is not supported by Amazon S3 on Outposts buckets.
Indicates whether confirmation is required before Amazon S3 runs the job. Confirmation is only required for jobs created through the Amazon S3 console.
', 'JobDescriptor$ConfirmationRequired' => 'Indicates whether confirmation is required before Amazon S3 begins running the specified job. Confirmation is required only for jobs created through the Amazon S3 console.
', ], ], 'ContinuationToken' => [ 'base' => NULL, 'refs' => [ 'ListStorageLensConfigurationsRequest$NextToken' => 'A pagination token to request the next page of results.
', 'ListStorageLensConfigurationsResult$NextToken' => 'If the request produced more than the maximum number of S3 Storage Lens configuration results, you can pass this value into a subsequent request to retrieve the next page of results.
', 'ListStorageLensGroupsRequest$NextToken' => 'The token for the next set of results, or null if there are no more results.
If NextToken is returned, there are more Storage Lens groups results available. The value of NextToken is a unique pagination token for each page. Make the call again using the returned token to retrieve the next page. Keep all other arguments unchanged. Each pagination token expires after 24 hours.
The container for the bucket configuration.
This is not supported by Amazon S3 on Outposts buckets.
The configuration information for the bucket.
This is not supported by Amazon S3 on Outposts buckets.
A container for the information associated with a CreateMultiRegionAccessPoint request.
', 'refs' => [ 'AsyncRequestParameters$CreateMultiRegionAccessPointRequest' => 'A container of the parameters for a CreateMultiRegionAccessPoint request.
', 'CreateMultiRegionAccessPointRequest$Details' => 'A container element containing details about the Multi-Region Access Point.
', ], ], 'CreateMultiRegionAccessPointRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateMultiRegionAccessPointResult' => [ 'base' => NULL, 'refs' => [], ], 'CreateStorageLensGroupRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreationDate' => [ 'base' => NULL, 'refs' => [ 'GetAccessPointForObjectLambdaResult$CreationDate' => 'The date and time when the specified Object Lambda Access Point was created.
', 'GetAccessPointResult$CreationDate' => 'The date and time when the specified access point was created.
', 'GetBucketResult$CreationDate' => 'The creation date of the Outposts bucket.
', 'RegionalBucket$CreationDate' => 'The creation date of the regional bucket
', ], ], 'CreationTimestamp' => [ 'base' => NULL, 'refs' => [ 'MultiRegionAccessPointReport$CreatedAt' => 'When the Multi-Region Access Point create request was received.
', ], ], 'Date' => [ 'base' => NULL, 'refs' => [ 'LifecycleExpiration$Date' => 'Indicates at what date the object is to be deleted. Should be in GMT ISO 8601 format.
', 'Transition$Date' => 'Indicates when objects are transitioned to the specified storage class. The date value must be in ISO 8601 format. The time is always midnight UTC.
', ], ], 'Days' => [ 'base' => NULL, 'refs' => [ 'LifecycleExpiration$Days' => 'Indicates the lifetime, in days, of the objects that are subject to the rule. The value must be a non-zero positive integer.
', 'NoncurrentVersionExpiration$NoncurrentDays' => 'Specifies the number of days an object is noncurrent before Amazon S3 can perform the associated action. For information about the noncurrent days calculations, see How Amazon S3 Calculates When an Object Became Noncurrent in the Amazon S3 User Guide.
', 'NoncurrentVersionTransition$NoncurrentDays' => 'Specifies the number of days an object is noncurrent before Amazon S3 can perform the associated action. For information about the noncurrent days calculations, see How Amazon S3 Calculates How Long an Object Has Been Noncurrent in the Amazon S3 User Guide.
', 'Transition$Days' => 'Indicates the number of days after creation when objects are transitioned to the specified storage class. The value must be a positive integer.
', ], ], 'DaysAfterInitiation' => [ 'base' => NULL, 'refs' => [ 'AbortIncompleteMultipartUpload$DaysAfterInitiation' => 'Specifies the number of days after which Amazon S3 aborts an incomplete multipart upload to the Outposts bucket.
', ], ], 'DeleteAccessPointForObjectLambdaRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteAccessPointPolicyForObjectLambdaRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteAccessPointPolicyRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteAccessPointRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteBucketLifecycleConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteBucketPolicyRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteBucketReplicationRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteBucketRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteBucketTaggingRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteJobTaggingRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteJobTaggingResult' => [ 'base' => NULL, 'refs' => [], ], 'DeleteMarkerReplication' => [ 'base' => 'Specifies whether S3 on Outposts replicates delete markers. If you specify a Filter element in your replication configuration, you must also include a DeleteMarkerReplication element. If your Filter includes a Tag element, the DeleteMarkerReplication element\'s Status child element must be set to Disabled, because S3 on Outposts does not support replicating delete markers for tag-based rules.
For more information about delete marker replication, see How delete operations affect replication in the Amazon S3 User Guide.
', 'refs' => [ 'ReplicationRule$DeleteMarkerReplication' => 'Specifies whether S3 on Outposts replicates delete markers. If you specify a Filter element in your replication configuration, you must also include a DeleteMarkerReplication element. If your Filter includes a Tag element, the DeleteMarkerReplication element\'s Status child element must be set to Disabled, because S3 on Outposts doesn\'t support replicating delete markers for tag-based rules.
For more information about delete marker replication, see How delete operations affect replication in the Amazon S3 User Guide.
', ], ], 'DeleteMarkerReplicationStatus' => [ 'base' => NULL, 'refs' => [ 'DeleteMarkerReplication$Status' => 'Indicates whether to replicate delete markers.
', ], ], 'DeleteMultiRegionAccessPointInput' => [ 'base' => 'A container for the information associated with a DeleteMultiRegionAccessPoint request.
', 'refs' => [ 'AsyncRequestParameters$DeleteMultiRegionAccessPointRequest' => 'A container of the parameters for a DeleteMultiRegionAccessPoint request.
', 'DeleteMultiRegionAccessPointRequest$Details' => 'A container element containing details about the Multi-Region Access Point.
', ], ], 'DeleteMultiRegionAccessPointRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteMultiRegionAccessPointResult' => [ 'base' => NULL, 'refs' => [], ], 'DeletePublicAccessBlockRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteStorageLensConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteStorageLensConfigurationTaggingRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteStorageLensConfigurationTaggingResult' => [ 'base' => NULL, 'refs' => [], ], 'DeleteStorageLensGroupRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeJobResult' => [ 'base' => NULL, 'refs' => [], ], 'DescribeMultiRegionAccessPointOperationRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeMultiRegionAccessPointOperationResult' => [ 'base' => NULL, 'refs' => [], ], 'Destination' => [ 'base' => 'Specifies information about the replication destination bucket and its settings for an S3 on Outposts replication configuration.
', 'refs' => [ 'ReplicationRule$Destination' => 'A container for information about the replication destination and its configurations.
', ], ], 'DetailedStatusCodesMetrics' => [ 'base' => 'The container element for Amazon S3 Storage Lens detailed status code metrics. Detailed status code metrics generate metrics for HTTP status codes, such as 200 OK, 403 Forbidden, 503 Service Unavailable and others.
For more information about S3 Storage Lens, see Assessing your storage activity and usage with S3 Storage Lens in the Amazon S3 User Guide. For a complete list of S3 Storage Lens metrics, see S3 Storage Lens metrics glossary in the Amazon S3 User Guide.
', 'refs' => [ 'AccountLevel$DetailedStatusCodesMetrics' => 'A container element for detailed status code metrics.
', 'BucketLevel$DetailedStatusCodesMetrics' => 'A container for bucket-level detailed status code metrics for S3 Storage Lens.
', ], ], 'EncryptionConfiguration' => [ 'base' => 'Specifies encryption-related information for an Amazon S3 bucket that is a destination for replicated objects.
This is not supported by Amazon S3 on Outposts buckets.
A container that provides information about encryption. If SourceSelectionCriteria is specified, you must specify this element.
This is not supported by Amazon S3 on Outposts buckets.
The VPC endpoint for the access point.
', ], ], 'EstablishedMultiRegionAccessPointPolicy' => [ 'base' => 'The last established access control policy for a Multi-Region Access Point.
When you update the policy, the update is first listed as the proposed policy. After the update is finished and all Regions have been updated, the proposed policy is listed as the established policy. If both policies have the same version number, the proposed policy is the established policy.
', 'refs' => [ 'MultiRegionAccessPointPolicyDocument$Established' => 'The last established policy for the Multi-Region Access Point.
', ], ], 'ExceptionMessage' => [ 'base' => NULL, 'refs' => [ 'BadRequestException$Message' => NULL, 'IdempotencyException$Message' => NULL, 'InternalServiceException$Message' => NULL, 'InvalidNextTokenException$Message' => NULL, 'InvalidRequestException$Message' => NULL, 'JobStatusException$Message' => NULL, 'NotFoundException$Message' => NULL, 'TooManyRequestsException$Message' => NULL, 'TooManyTagsException$Message' => NULL, ], ], 'Exclude' => [ 'base' => 'A container for what Amazon S3 Storage Lens will exclude.
', 'refs' => [ 'StorageLensConfiguration$Exclude' => 'A container for what is excluded in this configuration. This container can only be valid if there is no Include container submitted, and it\'s not empty.
An optional configuration to replicate existing source bucket objects.
This is not supported by Amazon S3 on Outposts buckets.
An optional configuration to replicate existing source bucket objects.
This is not supported by Amazon S3 on Outposts buckets.
Specifies whether Amazon S3 replicates existing source bucket objects.
', ], ], 'ExpirationStatus' => [ 'base' => NULL, 'refs' => [ 'LifecycleRule$Status' => 'If \'Enabled\', the rule is currently being applied. If \'Disabled\', the rule is not currently being applied.
', ], ], 'ExpiredObjectDeleteMarker' => [ 'base' => NULL, 'refs' => [ 'LifecycleExpiration$ExpiredObjectDeleteMarker' => 'Indicates whether Amazon S3 will remove a delete marker with no noncurrent versions. If set to true, the delete marker will be expired. If set to false, the policy takes no action. This cannot be specified with Days or Date in a Lifecycle Expiration Policy.
', ], ], 'Format' => [ 'base' => NULL, 'refs' => [ 'S3BucketDestination$Format' => '', ], ], 'FunctionArnString' => [ 'base' => NULL, 'refs' => [ 'AwsLambdaTransformation$FunctionArn' => 'The Amazon Resource Name (ARN) of the Lambda function.
', 'LambdaInvokeOperation$FunctionArn' => 'The Amazon Resource Name (ARN) for the Lambda function that the specified job will invoke on every object in the manifest.
', ], ], 'GeneratedManifestEncryption' => [ 'base' => 'The encryption configuration to use when storing the generated manifest.
', 'refs' => [ 'S3ManifestOutputLocation$ManifestEncryption' => 'Specifies what encryption should be used when the generated manifest objects are written.
', ], ], 'GeneratedManifestFormat' => [ 'base' => NULL, 'refs' => [ 'S3GeneratedManifestDescriptor$Format' => 'The format of the generated manifest.
', 'S3ManifestOutputLocation$ManifestFormat' => 'The format of the generated manifest.
', ], ], 'GetAccessPointConfigurationForObjectLambdaRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetAccessPointConfigurationForObjectLambdaResult' => [ 'base' => NULL, 'refs' => [], ], 'GetAccessPointForObjectLambdaRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetAccessPointForObjectLambdaResult' => [ 'base' => NULL, 'refs' => [], ], 'GetAccessPointPolicyForObjectLambdaRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetAccessPointPolicyForObjectLambdaResult' => [ 'base' => NULL, 'refs' => [], ], 'GetAccessPointPolicyRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetAccessPointPolicyResult' => [ 'base' => NULL, 'refs' => [], ], 'GetAccessPointPolicyStatusForObjectLambdaRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetAccessPointPolicyStatusForObjectLambdaResult' => [ 'base' => NULL, 'refs' => [], ], 'GetAccessPointPolicyStatusRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetAccessPointPolicyStatusResult' => [ 'base' => NULL, 'refs' => [], ], 'GetAccessPointRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetAccessPointResult' => [ 'base' => NULL, 'refs' => [], ], 'GetBucketLifecycleConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetBucketLifecycleConfigurationResult' => [ 'base' => NULL, 'refs' => [], ], 'GetBucketPolicyRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetBucketPolicyResult' => [ 'base' => NULL, 'refs' => [], ], 'GetBucketReplicationRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetBucketReplicationResult' => [ 'base' => NULL, 'refs' => [], ], 'GetBucketRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetBucketResult' => [ 'base' => NULL, 'refs' => [], ], 'GetBucketTaggingRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetBucketTaggingResult' => [ 'base' => NULL, 'refs' => [], ], 'GetBucketVersioningRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetBucketVersioningResult' => [ 'base' => NULL, 'refs' => [], ], 'GetJobTaggingRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetJobTaggingResult' => [ 'base' => NULL, 'refs' => [], ], 'GetMultiRegionAccessPointPolicyRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetMultiRegionAccessPointPolicyResult' => [ 'base' => NULL, 'refs' => [], ], 'GetMultiRegionAccessPointPolicyStatusRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetMultiRegionAccessPointPolicyStatusResult' => [ 'base' => NULL, 'refs' => [], ], 'GetMultiRegionAccessPointRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetMultiRegionAccessPointResult' => [ 'base' => NULL, 'refs' => [], ], 'GetMultiRegionAccessPointRoutesRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetMultiRegionAccessPointRoutesResult' => [ 'base' => NULL, 'refs' => [], ], 'GetPublicAccessBlockOutput' => [ 'base' => NULL, 'refs' => [], ], 'GetPublicAccessBlockRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetStorageLensConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetStorageLensConfigurationResult' => [ 'base' => NULL, 'refs' => [], ], 'GetStorageLensConfigurationTaggingRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetStorageLensConfigurationTaggingResult' => [ 'base' => NULL, 'refs' => [], ], 'GetStorageLensGroupRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetStorageLensGroupResult' => [ 'base' => NULL, 'refs' => [], ], 'GrantFullControl' => [ 'base' => NULL, 'refs' => [ 'CreateBucketRequest$GrantFullControl' => 'Allows grantee the read, write, read ACP, and write ACP permissions on the bucket.
This is not supported by Amazon S3 on Outposts buckets.
Allows grantee to list the objects in the bucket.
This is not supported by Amazon S3 on Outposts buckets.
Allows grantee to read the bucket ACL.
This is not supported by Amazon S3 on Outposts buckets.
Allows grantee to create, overwrite, and delete any object in the bucket.
This is not supported by Amazon S3 on Outposts buckets.
Allows grantee to write the ACL for the applicable bucket.
This is not supported by Amazon S3 on Outposts buckets.
The Amazon Resource Name (ARN) for the Identity and Access Management (IAM) role that Batch Operations will use to run this job\'s action on every object in the manifest.
', 'JobDescriptor$RoleArn' => 'The Amazon Resource Name (ARN) for the Identity and Access Management (IAM) role assigned to run the tasks for this job.
', ], ], 'ID' => [ 'base' => NULL, 'refs' => [ 'LifecycleRule$ID' => 'Unique identifier for the rule. The value cannot be longer than 255 characters.
', 'ReplicationRule$ID' => 'A unique identifier for the rule. The maximum value is 255 characters.
', ], ], 'IdempotencyException' => [ 'base' => '', 'refs' => [], ], 'Include' => [ 'base' => 'A container for what Amazon S3 Storage Lens configuration includes.
', 'refs' => [ 'StorageLensConfiguration$Include' => 'A container for what is included in this configuration. This container can only be valid if there is no Exclude container submitted, and it\'s not empty.
A container that indicates whether activity metrics are enabled.
', 'AdvancedCostOptimizationMetrics$IsEnabled' => 'A container that indicates whether advanced cost-optimization metrics are enabled.
', 'AdvancedDataProtectionMetrics$IsEnabled' => 'A container that indicates whether advanced data-protection metrics are enabled.
', 'CloudWatchMetrics$IsEnabled' => 'A container that indicates whether CloudWatch publishing for S3 Storage Lens metrics is enabled. A value of true indicates that CloudWatch publishing for S3 Storage Lens metrics is enabled.
A container that indicates whether detailed status code metrics are enabled.
', 'ListStorageLensConfigurationEntry$IsEnabled' => 'A container for whether the S3 Storage Lens configuration is enabled. This property is required.
', 'PrefixLevelStorageMetrics$IsEnabled' => 'A container for whether prefix-level storage metrics are enabled.
', 'StorageLensConfiguration$IsEnabled' => 'A container for whether the S3 Storage Lens configuration is enabled.
', ], ], 'IsPublic' => [ 'base' => NULL, 'refs' => [ 'PolicyStatus$IsPublic' => '', ], ], 'JobArn' => [ 'base' => NULL, 'refs' => [ 'JobDescriptor$JobArn' => 'The Amazon Resource Name (ARN) for this job.
', ], ], 'JobCreationTime' => [ 'base' => NULL, 'refs' => [ 'JobDescriptor$CreationTime' => 'A timestamp indicating when this job was created.
', 'JobListDescriptor$CreationTime' => 'A timestamp indicating when the specified job was created.
', ], ], 'JobDescriptor' => [ 'base' => 'A container element for the job configuration and status information returned by a Describe Job request.
Contains the configuration parameters and status for the job specified in the Describe Job request.
If this job failed, this element indicates why the job failed.
', 'refs' => [ 'JobFailureList$member' => NULL, ], ], 'JobFailureCode' => [ 'base' => NULL, 'refs' => [ 'JobFailure$FailureCode' => 'The failure code, if any, for the specified job.
', ], ], 'JobFailureList' => [ 'base' => NULL, 'refs' => [ 'JobDescriptor$FailureReasons' => 'If the specified job failed, this field contains information describing the failure.
', ], ], 'JobFailureReason' => [ 'base' => NULL, 'refs' => [ 'JobFailure$FailureReason' => 'The failure reason, if any, for the specified job.
', ], ], 'JobId' => [ 'base' => NULL, 'refs' => [ 'CreateJobResult$JobId' => 'The ID for this job. Amazon S3 generates this ID automatically and returns it after a successful Create Job request.
The ID for the S3 Batch Operations job whose tags you want to delete.
', 'DescribeJobRequest$JobId' => 'The ID for the job whose information you want to retrieve.
', 'GetJobTaggingRequest$JobId' => 'The ID for the S3 Batch Operations job whose tags you want to retrieve.
', 'JobDescriptor$JobId' => 'The ID for the specified job.
', 'JobListDescriptor$JobId' => 'The ID for the specified job.
', 'PutJobTaggingRequest$JobId' => 'The ID for the S3 Batch Operations job whose tags you want to replace.
', 'UpdateJobPriorityRequest$JobId' => 'The ID for the job whose priority you want to update.
', 'UpdateJobPriorityResult$JobId' => 'The ID for the job whose priority Amazon S3 updated.
', 'UpdateJobStatusRequest$JobId' => 'The ID of the job whose status you want to update.
', 'UpdateJobStatusResult$JobId' => 'The ID for the job whose status was updated.
', ], ], 'JobListDescriptor' => [ 'base' => 'Contains the configuration and status information for a single job retrieved as part of a job list.
', 'refs' => [ 'JobListDescriptorList$member' => NULL, ], ], 'JobListDescriptorList' => [ 'base' => NULL, 'refs' => [ 'ListJobsResult$Jobs' => 'The list of current jobs and jobs that have ended within the last 30 days.
', ], ], 'JobManifest' => [ 'base' => 'Contains the configuration information for a job\'s manifest.
', 'refs' => [ 'CreateJobRequest$Manifest' => 'Configuration parameters for the manifest.
', 'JobDescriptor$Manifest' => 'The configuration information for the specified job\'s manifest object.
', ], ], 'JobManifestFieldList' => [ 'base' => NULL, 'refs' => [ 'JobManifestSpec$Fields' => 'If the specified manifest object is in the S3BatchOperations_CSV_20180820 format, this element describes which columns contain the required data.
Indicates which of the available formats the specified manifest uses.
', ], ], 'JobManifestGenerator' => [ 'base' => 'Configures the type of the job\'s ManifestGenerator.
', 'refs' => [ 'CreateJobRequest$ManifestGenerator' => 'The attribute container for the ManifestGenerator details. Jobs must be created with either a manifest file or a ManifestGenerator, but not both.
', 'JobDescriptor$ManifestGenerator' => 'The manifest generator that was used to generate a job manifest for this job.
', ], ], 'JobManifestGeneratorFilter' => [ 'base' => 'The filter used to describe a set of objects for the job\'s manifest.
', 'refs' => [ 'S3JobManifestGenerator$Filter' => 'Specifies rules the S3JobManifestGenerator should use to use to decide whether an object in the source bucket should or should not be included in the generated job manifest.
', ], ], 'JobManifestLocation' => [ 'base' => 'Contains the information required to locate a manifest object.
', 'refs' => [ 'JobManifest$Location' => 'Contains the information required to locate the specified job\'s manifest.
', 'S3GeneratedManifestDescriptor$Location' => NULL, ], ], 'JobManifestSpec' => [ 'base' => 'Describes the format of a manifest. If the manifest is in CSV format, also describes the columns contained within the manifest.
', 'refs' => [ 'JobManifest$Spec' => 'Describes the format of the specified job\'s manifest. If the manifest is in CSV format, also describes the columns contained within the manifest.
', ], ], 'JobNumberOfTasksFailed' => [ 'base' => NULL, 'refs' => [ 'JobProgressSummary$NumberOfTasksFailed' => '', ], ], 'JobNumberOfTasksSucceeded' => [ 'base' => NULL, 'refs' => [ 'JobProgressSummary$NumberOfTasksSucceeded' => '', ], ], 'JobOperation' => [ 'base' => 'The operation that you want this job to perform on every object listed in the manifest. For more information about the available operations, see Operations in the Amazon S3 User Guide.
', 'refs' => [ 'CreateJobRequest$Operation' => 'The action that you want this job to perform on every object listed in the manifest. For more information about the available actions, see Operations in the Amazon S3 User Guide.
', 'JobDescriptor$Operation' => 'The operation that the specified job is configured to run on the objects listed in the manifest.
', ], ], 'JobPriority' => [ 'base' => NULL, 'refs' => [ 'CreateJobRequest$Priority' => 'The numerical priority for this job. Higher numbers indicate higher priority.
', 'JobDescriptor$Priority' => 'The priority of the specified job.
', 'JobListDescriptor$Priority' => 'The current priority for the specified job.
', 'UpdateJobPriorityRequest$Priority' => 'The priority you want to assign to this job.
', 'UpdateJobPriorityResult$Priority' => 'The new priority assigned to the specified job.
', ], ], 'JobProgressSummary' => [ 'base' => 'Describes the total number of tasks that the specified job has started, the number of tasks that succeeded, and the number of tasks that failed.
', 'refs' => [ 'JobDescriptor$ProgressSummary' => 'Describes the total number of tasks that the specified job has run, the number of tasks that succeeded, and the number of tasks that failed.
', 'JobListDescriptor$ProgressSummary' => 'Describes the total number of tasks that the specified job has run, the number of tasks that succeeded, and the number of tasks that failed.
', ], ], 'JobReport' => [ 'base' => 'Contains the configuration parameters for a job-completion report.
', 'refs' => [ 'CreateJobRequest$Report' => 'Configuration parameters for the optional job-completion report.
', 'JobDescriptor$Report' => 'Contains the configuration information for the job-completion report if you requested one in the Create Job request.
The format of the specified job-completion report.
', ], ], 'JobReportScope' => [ 'base' => NULL, 'refs' => [ 'JobReport$ReportScope' => 'Indicates whether the job-completion report will include details of all tasks or only failed tasks.
', ], ], 'JobStatus' => [ 'base' => NULL, 'refs' => [ 'JobDescriptor$Status' => 'The current status of the specified job.
', 'JobListDescriptor$Status' => 'The specified job\'s current status.
', 'JobStatusList$member' => NULL, 'UpdateJobStatusResult$Status' => 'The current status for the specified job.
', ], ], 'JobStatusException' => [ 'base' => '', 'refs' => [], ], 'JobStatusList' => [ 'base' => NULL, 'refs' => [ 'ListJobsRequest$JobStatuses' => 'The List Jobs request returns jobs that match the statuses listed in this element.
The reason for updating the job.
', 'UpdateJobStatusRequest$StatusUpdateReason' => 'A description of the reason why you want to change the specified job\'s status. This field can be any string up to the maximum length.
', 'UpdateJobStatusResult$StatusUpdateReason' => 'The reason that the specified job\'s status was updated.
', ], ], 'JobTerminationDate' => [ 'base' => NULL, 'refs' => [ 'JobDescriptor$TerminationDate' => 'A timestamp indicating when this job terminated. A job\'s termination date is the date and time when it succeeded, failed, or was canceled.
', 'JobListDescriptor$TerminationDate' => 'A timestamp indicating when the specified job terminated. A job\'s termination date is the date and time when it succeeded, failed, or was canceled.
', ], ], 'JobTimeInStateSeconds' => [ 'base' => NULL, 'refs' => [ 'JobTimers$ElapsedTimeInActiveSeconds' => 'Indicates the elapsed time in seconds the job has been in the Active job state.
', ], ], 'JobTimers' => [ 'base' => 'Provides timing details for the job.
', 'refs' => [ 'JobProgressSummary$Timers' => 'The JobTimers attribute of a job\'s progress summary.
', ], ], 'JobTotalNumberOfTasks' => [ 'base' => NULL, 'refs' => [ 'JobProgressSummary$TotalNumberOfTasks' => '', ], ], 'KmsKeyArnString' => [ 'base' => NULL, 'refs' => [ 'S3CopyObjectOperation$SSEAwsKmsKeyId' => '', 'SSEKMSEncryption$KeyId' => 'Specifies the ID of the Amazon Web Services Key Management Service (Amazon Web Services KMS) symmetric encryption customer managed key to use for encrypting generated manifest objects.
', ], ], 'LambdaInvokeOperation' => [ 'base' => 'Contains the configuration parameters for a Lambda Invoke operation.
Directs the specified job to invoke an Lambda function on every object in the manifest.
', ], ], 'LifecycleConfiguration' => [ 'base' => 'The container for the Outposts bucket lifecycle configuration.
', 'refs' => [ 'PutBucketLifecycleConfigurationRequest$LifecycleConfiguration' => 'Container for lifecycle rules. You can add as many as 1,000 rules.
', ], ], 'LifecycleExpiration' => [ 'base' => 'The container of the Outposts bucket lifecycle expiration.
', 'refs' => [ 'LifecycleRule$Expiration' => 'Specifies the expiration for the lifecycle of the object in the form of date, days and, whether the object has a delete marker.
', ], ], 'LifecycleRule' => [ 'base' => 'The container for the Outposts bucket lifecycle rule.
', 'refs' => [ 'LifecycleRules$member' => NULL, ], ], 'LifecycleRuleAndOperator' => [ 'base' => 'The container for the Outposts bucket lifecycle rule and operator.
', 'refs' => [ 'LifecycleRuleFilter$And' => 'The container for the AND condition for the lifecycle rule.
The container for the filter of the lifecycle rule.
', 'refs' => [ 'LifecycleRule$Filter' => 'The container for the filter of lifecycle rule.
', ], ], 'LifecycleRules' => [ 'base' => NULL, 'refs' => [ 'GetBucketLifecycleConfigurationResult$Rules' => 'Container for the lifecycle rule of the Outposts bucket.
', 'LifecycleConfiguration$Rules' => 'A lifecycle rule for individual objects in an Outposts bucket.
', ], ], 'ListAccessPointsForObjectLambdaRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListAccessPointsForObjectLambdaResult' => [ 'base' => NULL, 'refs' => [], ], 'ListAccessPointsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListAccessPointsResult' => [ 'base' => NULL, 'refs' => [], ], 'ListJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListJobsResult' => [ 'base' => NULL, 'refs' => [], ], 'ListMultiRegionAccessPointsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListMultiRegionAccessPointsResult' => [ 'base' => NULL, 'refs' => [], ], 'ListRegionalBucketsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListRegionalBucketsResult' => [ 'base' => NULL, 'refs' => [], ], 'ListStorageLensConfigurationEntry' => [ 'base' => 'Part of ListStorageLensConfigurationResult. Each entry includes the description of the S3 Storage Lens configuration, its home Region, whether it is enabled, its Amazon Resource Name (ARN), and config ID.
Each entry contains a Storage Lens group that exists in the specified home Region.
', 'refs' => [ 'StorageLensGroupList$member' => NULL, ], ], 'ListStorageLensGroupsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListStorageLensGroupsResult' => [ 'base' => NULL, 'refs' => [], ], 'ListTagsForResourceRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListTagsForResourceResult' => [ 'base' => NULL, 'refs' => [], ], 'Location' => [ 'base' => NULL, 'refs' => [ 'CreateBucketResult$Location' => 'The location of the bucket.
', ], ], 'MFA' => [ 'base' => NULL, 'refs' => [ 'PutBucketVersioningRequest$MFA' => 'The concatenation of the authentication device\'s serial number, a space, and the value that is displayed on your authentication device.
', ], ], 'MFADelete' => [ 'base' => NULL, 'refs' => [ 'VersioningConfiguration$MFADelete' => 'Specifies whether MFA delete is enabled or disabled in the bucket versioning configuration for the S3 on Outposts bucket.
', ], ], 'MFADeleteStatus' => [ 'base' => NULL, 'refs' => [ 'GetBucketVersioningResult$MFADelete' => 'Specifies whether MFA delete is enabled in the bucket versioning configuration. This element is returned only if the bucket has been configured with MFA delete. If MFA delete has never been configured for the bucket, this element is not returned.
', ], ], 'ManifestPrefixString' => [ 'base' => NULL, 'refs' => [ 'S3ManifestOutputLocation$ManifestPrefix' => 'Prefix identifying one or more objects to which the manifest applies.
', ], ], 'MatchAnyPrefix' => [ 'base' => NULL, 'refs' => [ 'StorageLensGroupAndOperator$MatchAnyPrefix' => 'Contains a list of prefixes. At least one prefix must be specified. Up to 10 prefixes are allowed.
', 'StorageLensGroupFilter$MatchAnyPrefix' => 'Contains a list of prefixes. At least one prefix must be specified. Up to 10 prefixes are allowed.
', 'StorageLensGroupOrOperator$MatchAnyPrefix' => 'Filters objects that match any of the specified prefixes.
', ], ], 'MatchAnySuffix' => [ 'base' => NULL, 'refs' => [ 'StorageLensGroupAndOperator$MatchAnySuffix' => 'Contains a list of suffixes. At least one suffix must be specified. Up to 10 suffixes are allowed.
', 'StorageLensGroupFilter$MatchAnySuffix' => 'Contains a list of suffixes. At least one suffix must be specified. Up to 10 suffixes are allowed.
', 'StorageLensGroupOrOperator$MatchAnySuffix' => 'Filters objects that match any of the specified suffixes.
', ], ], 'MatchAnyTag' => [ 'base' => NULL, 'refs' => [ 'StorageLensGroupAndOperator$MatchAnyTag' => 'Contains the list of object tags. At least one object tag must be specified. Up to 10 object tags are allowed.
', 'StorageLensGroupFilter$MatchAnyTag' => 'Contains the list of S3 object tags. At least one object tag must be specified. Up to 10 object tags are allowed.
', 'StorageLensGroupOrOperator$MatchAnyTag' => 'Filters objects that match any of the specified S3 object tags.
', ], ], 'MatchObjectAge' => [ 'base' => 'A filter condition that specifies the object age range of included objects in days. Only integers are supported.
', 'refs' => [ 'StorageLensGroupAndOperator$MatchObjectAge' => ' Contains DaysGreaterThan and DaysLessThan to define the object age range (minimum and maximum number of days).
Contains DaysGreaterThan and DaysLessThan to define the object age range (minimum and maximum number of days).
Filters objects that match the specified object age range.
', ], ], 'MatchObjectSize' => [ 'base' => 'A filter condition that specifies the object size range of included objects in bytes. Only integers are supported.
', 'refs' => [ 'StorageLensGroupAndOperator$MatchObjectSize' => ' Contains BytesGreaterThan and BytesLessThan to define the object size range (minimum and maximum number of Bytes).
Contains BytesGreaterThan and BytesLessThan to define the object size range (minimum and maximum number of Bytes).
Filters objects that match the specified object size range.
', ], ], 'MaxLength1024String' => [ 'base' => NULL, 'refs' => [ 'AsyncErrorDetails$Code' => 'A string that uniquely identifies the error condition.
', 'AsyncErrorDetails$Message' => 'A generic description of the error condition in English.
', 'AsyncErrorDetails$Resource' => 'The identifier of the resource associated with the error.
', 'AsyncErrorDetails$RequestId' => 'The ID of the request associated with the error.
', 'S3UserMetadata$value' => NULL, ], ], 'MaxResults' => [ 'base' => NULL, 'refs' => [ 'ListAccessPointsForObjectLambdaRequest$MaxResults' => 'The maximum number of access points that you want to include in the list. The response may contain fewer access points but will never contain more. If there are more than this number of access points, then the response will include a continuation token in the NextToken field that you can use to retrieve the next page of access points.
The maximum number of access points that you want to include in the list. If the specified bucket has more than this number of access points, then the response will include a continuation token in the NextToken field that you can use to retrieve the next page of access points.
The maximum number of jobs that Amazon S3 will include in the List Jobs response. If there are more jobs than this number, the response will include a pagination token in the NextToken field to enable you to retrieve the next page of results.
Not currently used. Do not use this parameter.
', 'ListRegionalBucketsRequest$MaxResults' => '', ], ], 'Metrics' => [ 'base' => 'A container that specifies replication metrics-related settings.
', 'refs' => [ 'Destination$Metrics' => 'A container that specifies replication metrics-related settings.
', ], ], 'MetricsStatus' => [ 'base' => NULL, 'refs' => [ 'Metrics$Status' => 'Specifies whether replication metrics are enabled.
', ], ], 'MinStorageBytesPercentage' => [ 'base' => NULL, 'refs' => [ 'SelectionCriteria$MinStorageBytesPercentage' => 'The minimum number of storage bytes percentage whose metrics will be selected.
You must choose a value greater than or equal to 1.0.
Contains an integer that specifies the time period in minutes.
Valid value: 15
', ], ], 'MultiRegionAccessPointAlias' => [ 'base' => NULL, 'refs' => [ 'MultiRegionAccessPointReport$Alias' => 'The alias for the Multi-Region Access Point. For more information about the distinction between the name and the alias of an Multi-Region Access Point, see Managing Multi-Region Access Points.
', ], ], 'MultiRegionAccessPointClientToken' => [ 'base' => NULL, 'refs' => [ 'CreateMultiRegionAccessPointRequest$ClientToken' => 'An idempotency token used to identify the request and guarantee that requests are unique.
', 'DeleteMultiRegionAccessPointRequest$ClientToken' => 'An idempotency token used to identify the request and guarantee that requests are unique.
', 'PutMultiRegionAccessPointPolicyRequest$ClientToken' => 'An idempotency token used to identify the request and guarantee that requests are unique.
', ], ], 'MultiRegionAccessPointId' => [ 'base' => NULL, 'refs' => [ 'GetMultiRegionAccessPointRoutesRequest$Mrap' => 'The Multi-Region Access Point ARN.
', 'GetMultiRegionAccessPointRoutesResult$Mrap' => 'The Multi-Region Access Point ARN.
', 'SubmitMultiRegionAccessPointRoutesRequest$Mrap' => 'The Multi-Region Access Point ARN.
', ], ], 'MultiRegionAccessPointName' => [ 'base' => NULL, 'refs' => [ 'CreateMultiRegionAccessPointInput$Name' => 'The name of the Multi-Region Access Point associated with this request.
', 'DeleteMultiRegionAccessPointInput$Name' => 'The name of the Multi-Region Access Point associated with this request.
', 'GetMultiRegionAccessPointPolicyRequest$Name' => 'Specifies the Multi-Region Access Point. The name of the Multi-Region Access Point is different from the alias. For more information about the distinction between the name and the alias of an Multi-Region Access Point, see Managing Multi-Region Access Points in the Amazon S3 User Guide.
', 'GetMultiRegionAccessPointPolicyStatusRequest$Name' => 'Specifies the Multi-Region Access Point. The name of the Multi-Region Access Point is different from the alias. For more information about the distinction between the name and the alias of an Multi-Region Access Point, see Managing Multi-Region Access Points in the Amazon S3 User Guide.
', 'GetMultiRegionAccessPointRequest$Name' => 'The name of the Multi-Region Access Point whose configuration information you want to receive. The name of the Multi-Region Access Point is different from the alias. For more information about the distinction between the name and the alias of an Multi-Region Access Point, see Managing Multi-Region Access Points in the Amazon S3 User Guide.
', 'MultiRegionAccessPointReport$Name' => 'The name of the Multi-Region Access Point.
', 'PutMultiRegionAccessPointPolicyInput$Name' => 'The name of the Multi-Region Access Point associated with the request.
', ], ], 'MultiRegionAccessPointPolicyDocument' => [ 'base' => 'The Multi-Region Access Point access control policy.
When you update the policy, the update is first listed as the proposed policy. After the update is finished and all Regions have been updated, the proposed policy is listed as the established policy. If both policies have the same version number, the proposed policy is the established policy.
', 'refs' => [ 'GetMultiRegionAccessPointPolicyResult$Policy' => 'The policy associated with the specified Multi-Region Access Point.
', ], ], 'MultiRegionAccessPointRegionalResponse' => [ 'base' => 'Status information for a single Multi-Region Access Point Region.
', 'refs' => [ 'MultiRegionAccessPointRegionalResponseList$member' => NULL, ], ], 'MultiRegionAccessPointRegionalResponseList' => [ 'base' => NULL, 'refs' => [ 'MultiRegionAccessPointsAsyncResponse$Regions' => 'A collection of status information for the different Regions that a Multi-Region Access Point supports.
', ], ], 'MultiRegionAccessPointReport' => [ 'base' => 'A collection of statuses for a Multi-Region Access Point in the various Regions it supports.
', 'refs' => [ 'GetMultiRegionAccessPointResult$AccessPoint' => 'A container element containing the details of the requested Multi-Region Access Point.
', 'MultiRegionAccessPointReportList$member' => NULL, ], ], 'MultiRegionAccessPointReportList' => [ 'base' => NULL, 'refs' => [ 'ListMultiRegionAccessPointsResult$AccessPoints' => 'The list of Multi-Region Access Points associated with the user.
', ], ], 'MultiRegionAccessPointRoute' => [ 'base' => 'A structure for a Multi-Region Access Point that indicates where Amazon S3 traffic can be routed. Routes can be either active or passive. Active routes can process Amazon S3 requests through the Multi-Region Access Point, but passive routes are not eligible to process Amazon S3 requests.
Each route contains the Amazon S3 bucket name and the Amazon Web Services Region that the bucket is located in. The route also includes the TrafficDialPercentage value, which shows whether the bucket and Region are active (indicated by a value of 100) or passive (indicated by a value of 0).
The current status of the Multi-Region Access Point.
CREATING and DELETING are temporary states that exist while the request is propagating and being completed. If a Multi-Region Access Point has a status of PARTIALLY_CREATED, you can retry creation or send a request to delete the Multi-Region Access Point. If a Multi-Region Access Point has a status of PARTIALLY_DELETED, you can retry a delete request to finish the deletion of the Multi-Region Access Point.
The Multi-Region Access Point details that are returned when querying about an asynchronous request.
', 'refs' => [ 'AsyncResponseDetails$MultiRegionAccessPointDetails' => 'The details for the Multi-Region Access Point.
', ], ], 'NetworkOrigin' => [ 'base' => NULL, 'refs' => [ 'AccessPoint$NetworkOrigin' => 'Indicates whether this access point allows access from the public internet. If VpcConfiguration is specified for this access point, then NetworkOrigin is VPC, and the access point doesn\'t allow access from the public internet. Otherwise, NetworkOrigin is Internet, and the access point allows access from the public internet, subject to the access point and bucket access policies.
Indicates whether this access point allows access from the public internet. If VpcConfiguration is specified for this access point, then NetworkOrigin is VPC, and the access point doesn\'t allow access from the public internet. Otherwise, NetworkOrigin is Internet, and the access point allows access from the public internet, subject to the access point and bucket access policies.
This will always be true for an Amazon S3 on Outposts access point
', ], ], 'NoSuchPublicAccessBlockConfiguration' => [ 'base' => 'Amazon S3 throws this exception if you make a GetPublicAccessBlock request against an account that doesn\'t have a PublicAccessBlockConfiguration set.
The ETag for the specified manifest object.
', 'ListAccessPointsForObjectLambdaRequest$NextToken' => 'If the list has more access points than can be returned in one call to this API, this field contains a continuation token that you can provide in subsequent calls to this API to retrieve additional access points.
', 'ListAccessPointsForObjectLambdaResult$NextToken' => 'If the list has more access points than can be returned in one call to this API, this field contains a continuation token that you can provide in subsequent calls to this API to retrieve additional access points.
', 'ListAccessPointsRequest$NextToken' => 'A continuation token. If a previous call to ListAccessPoints returned a continuation token in the NextToken field, then providing that value here causes Amazon S3 to retrieve the next page of results.
If the specified bucket has more access points than can be returned in one call to this API, this field contains a continuation token that you can provide in subsequent calls to this API to retrieve additional access points.
', 'ListMultiRegionAccessPointsRequest$NextToken' => 'Not currently used. Do not use this parameter.
', 'ListMultiRegionAccessPointsResult$NextToken' => 'If the specified bucket has more Multi-Region Access Points than can be returned in one call to this action, this field contains a continuation token. You can use this token tin subsequent calls to this action to retrieve additional Multi-Region Access Points.
', 'ListRegionalBucketsRequest$NextToken' => '', 'ListRegionalBucketsResult$NextToken' => ' NextToken is sent when isTruncated is true, which means there are more buckets that can be listed. The next list requests to Amazon S3 can be continued with this NextToken. NextToken is obfuscated and is not a real key.
Specifies the folder prefix that you want the objects to be copied into. For example, to copy objects into a folder named Folder1 in the destination bucket, set the TargetKeyPrefix property to Folder1.
Specifies an optional metadata property for website redirects, x-amz-website-redirect-location. Allows webpage redirects if the object is accessed through a website endpoint.
A description for this job. You can use any string within the permitted length. Descriptions don\'t need to be unique and can be used for multiple jobs.
', 'JobDescriptor$Description' => 'The description for this job, if one was provided in this job\'s Create Job request.
The user-specified description that was included in the specified job\'s Create Job request.
The ID of the Outposts where the bucket is being created.
This ID is required by Amazon S3 on Outposts buckets.
An idempotency token to ensure that you don\'t accidentally submit the same request twice. You can use any string up to the maximum length.
', 'Endpoints$key' => NULL, 'ListRegionalBucketsRequest$OutpostId' => 'The ID of the Outposts resource.
This ID is required by Amazon S3 on Outposts buckets.
The Outposts ID of the regional bucket.
', ], ], 'NoncurrentVersionCount' => [ 'base' => NULL, 'refs' => [ 'NoncurrentVersionExpiration$NewerNoncurrentVersions' => 'Specifies how many noncurrent versions S3 on Outposts will retain. If there are this many more recent noncurrent versions, S3 on Outposts will take the associated action. For more information about noncurrent versions, see Lifecycle configuration elements in the Amazon S3 User Guide.
', ], ], 'NoncurrentVersionExpiration' => [ 'base' => 'The container of the noncurrent version expiration.
', 'refs' => [ 'LifecycleRule$NoncurrentVersionExpiration' => 'The noncurrent version expiration of the lifecycle rule.
', ], ], 'NoncurrentVersionTransition' => [ 'base' => 'The container for the noncurrent version transition.
', 'refs' => [ 'NoncurrentVersionTransitionList$member' => NULL, ], ], 'NoncurrentVersionTransitionList' => [ 'base' => NULL, 'refs' => [ 'LifecycleRule$NoncurrentVersionTransitions' => 'Specifies the transition rule for the lifecycle rule that describes when noncurrent objects transition to a specific storage class. If your bucket is versioning-enabled (or versioning is suspended), you can set this action to request that Amazon S3 transition noncurrent object versions to a specific storage class at a set period in the object\'s lifetime.
This is not supported by Amazon S3 on Outposts buckets.
Specifies the maximum object age in days. Must be a positive whole number, greater than the minimum object age and less than or equal to 2,147,483,647.
', 'MatchObjectAge$DaysLessThan' => 'Specifies the minimum object age in days. The value must be a positive whole number, greater than 0 and less than or equal to 2,147,483,647.
', ], ], 'ObjectCreationTime' => [ 'base' => NULL, 'refs' => [ 'JobManifestGeneratorFilter$CreatedAfter' => 'If provided, the generated manifest should include only source bucket objects that were created after this time.
', 'JobManifestGeneratorFilter$CreatedBefore' => 'If provided, the generated manifest should include only source bucket objects that were created before this time.
', ], ], 'ObjectLambdaAccessPoint' => [ 'base' => 'An access point with an attached Lambda function used to access transformed data from an Amazon S3 bucket.
', 'refs' => [ 'ObjectLambdaAccessPointList$member' => NULL, ], ], 'ObjectLambdaAccessPointAlias' => [ 'base' => 'The alias of an Object Lambda Access Point. For more information, see How to use a bucket-style alias for your S3 bucket Object Lambda Access Point.
', 'refs' => [ 'CreateAccessPointForObjectLambdaResult$Alias' => 'The alias of the Object Lambda Access Point.
', 'GetAccessPointForObjectLambdaResult$Alias' => 'The alias of the Object Lambda Access Point.
', 'ObjectLambdaAccessPoint$Alias' => 'The alias of the Object Lambda Access Point.
', ], ], 'ObjectLambdaAccessPointAliasStatus' => [ 'base' => NULL, 'refs' => [ 'ObjectLambdaAccessPointAlias$Status' => 'The status of the Object Lambda Access Point alias. If the status is PROVISIONING, the Object Lambda Access Point is provisioning the alias and the alias is not ready for use yet. If the status is READY, the Object Lambda Access Point alias is successfully provisioned and ready for use.
The alias value of the Object Lambda Access Point.
', ], ], 'ObjectLambdaAccessPointArn' => [ 'base' => NULL, 'refs' => [ 'CreateAccessPointForObjectLambdaResult$ObjectLambdaAccessPointArn' => 'Specifies the ARN for the Object Lambda Access Point.
', 'ObjectLambdaAccessPoint$ObjectLambdaAccessPointArn' => 'Specifies the ARN for the Object Lambda Access Point.
', ], ], 'ObjectLambdaAccessPointList' => [ 'base' => NULL, 'refs' => [ 'ListAccessPointsForObjectLambdaResult$ObjectLambdaAccessPointList' => 'Returns list of Object Lambda Access Points.
', ], ], 'ObjectLambdaAccessPointName' => [ 'base' => NULL, 'refs' => [ 'CreateAccessPointForObjectLambdaRequest$Name' => 'The name you want to assign to this Object Lambda Access Point.
', 'DeleteAccessPointForObjectLambdaRequest$Name' => 'The name of the access point you want to delete.
', 'DeleteAccessPointPolicyForObjectLambdaRequest$Name' => 'The name of the Object Lambda Access Point you want to delete the policy for.
', 'GetAccessPointConfigurationForObjectLambdaRequest$Name' => 'The name of the Object Lambda Access Point you want to return the configuration for.
', 'GetAccessPointForObjectLambdaRequest$Name' => 'The name of the Object Lambda Access Point.
', 'GetAccessPointForObjectLambdaResult$Name' => 'The name of the Object Lambda Access Point.
', 'GetAccessPointPolicyForObjectLambdaRequest$Name' => 'The name of the Object Lambda Access Point.
', 'GetAccessPointPolicyStatusForObjectLambdaRequest$Name' => 'The name of the Object Lambda Access Point.
', 'ObjectLambdaAccessPoint$Name' => 'The name of the Object Lambda Access Point.
', 'PutAccessPointConfigurationForObjectLambdaRequest$Name' => 'The name of the Object Lambda Access Point.
', 'PutAccessPointPolicyForObjectLambdaRequest$Name' => 'The name of the Object Lambda Access Point.
', ], ], 'ObjectLambdaAllowedFeature' => [ 'base' => NULL, 'refs' => [ 'ObjectLambdaAllowedFeaturesList$member' => NULL, ], ], 'ObjectLambdaAllowedFeaturesList' => [ 'base' => NULL, 'refs' => [ 'ObjectLambdaConfiguration$AllowedFeatures' => 'A container for allowed features. Valid inputs are GetObject-Range, GetObject-PartNumber, HeadObject-Range, and HeadObject-PartNumber.
A configuration used when creating an Object Lambda Access Point.
', 'refs' => [ 'CreateAccessPointForObjectLambdaRequest$Configuration' => 'Object Lambda Access Point configuration as a JSON document.
', 'GetAccessPointConfigurationForObjectLambdaResult$Configuration' => 'Object Lambda Access Point configuration document.
', 'PutAccessPointConfigurationForObjectLambdaRequest$Configuration' => 'Object Lambda Access Point configuration document.
', ], ], 'ObjectLambdaContentTransformation' => [ 'base' => 'A container for AwsLambdaTransformation.
', 'refs' => [ 'ObjectLambdaTransformationConfiguration$ContentTransformation' => 'A container for the content transformation of an Object Lambda Access Point configuration.
', ], ], 'ObjectLambdaPolicy' => [ 'base' => NULL, 'refs' => [ 'GetAccessPointPolicyForObjectLambdaResult$Policy' => 'Object Lambda Access Point resource policy document.
', 'PutAccessPointPolicyForObjectLambdaRequest$Policy' => 'Object Lambda Access Point resource policy document.
', ], ], 'ObjectLambdaSupportingAccessPointArn' => [ 'base' => NULL, 'refs' => [ 'ObjectLambdaConfiguration$SupportingAccessPoint' => 'Standard access point associated with the Object Lambda Access Point.
', ], ], 'ObjectLambdaTransformationConfiguration' => [ 'base' => 'A configuration used when creating an Object Lambda Access Point transformation.
', 'refs' => [ 'ObjectLambdaTransformationConfigurationsList$member' => NULL, ], ], 'ObjectLambdaTransformationConfigurationAction' => [ 'base' => NULL, 'refs' => [ 'ObjectLambdaTransformationConfigurationActionsList$member' => NULL, ], ], 'ObjectLambdaTransformationConfigurationActionsList' => [ 'base' => NULL, 'refs' => [ 'ObjectLambdaTransformationConfiguration$Actions' => 'A container for the action of an Object Lambda Access Point configuration. Valid inputs are GetObject, ListObjects, HeadObject, and ListObjectsV2.
A container for transformation configurations for an Object Lambda Access Point.
', ], ], 'ObjectLockEnabledForBucket' => [ 'base' => NULL, 'refs' => [ 'CreateBucketRequest$ObjectLockEnabledForBucket' => 'Specifies whether you want S3 Object Lock to be enabled for the new bucket.
This is not supported by Amazon S3 on Outposts buckets.
Minimum object size to which the rule applies.
', 'LifecycleRuleFilter$ObjectSizeGreaterThan' => 'Minimum object size to which the rule applies.
', ], ], 'ObjectSizeLessThanBytes' => [ 'base' => NULL, 'refs' => [ 'LifecycleRuleAndOperator$ObjectSizeLessThan' => 'Maximum object size to which the rule applies.
', 'LifecycleRuleFilter$ObjectSizeLessThan' => 'Maximum object size to which the rule applies.
', ], ], 'ObjectSizeValue' => [ 'base' => NULL, 'refs' => [ 'MatchObjectSize$BytesGreaterThan' => 'Specifies the minimum object size in Bytes. The value must be a positive number, greater than 0 and less than 5 TB.
', 'MatchObjectSize$BytesLessThan' => 'Specifies the maximum object size in Bytes. The value must be a positive number, greater than the minimum object size and less than 5 TB.
', ], ], 'OperationName' => [ 'base' => NULL, 'refs' => [ 'JobListDescriptor$Operation' => 'The operation that the specified job is configured to run on every object listed in the manifest.
', ], ], 'OutputSchemaVersion' => [ 'base' => NULL, 'refs' => [ 'S3BucketDestination$OutputSchemaVersion' => 'The schema version of the export file.
', ], ], 'OwnerOverride' => [ 'base' => NULL, 'refs' => [ 'AccessControlTranslation$Owner' => 'Specifies the replica ownership.
', ], ], 'Policy' => [ 'base' => NULL, 'refs' => [ 'EstablishedMultiRegionAccessPointPolicy$Policy' => 'The details of the last established policy.
', 'GetAccessPointPolicyResult$Policy' => 'The access point policy associated with the specified access point.
', 'GetBucketPolicyResult$Policy' => 'The policy of the Outposts bucket.
', 'ProposedMultiRegionAccessPointPolicy$Policy' => 'The details of the proposed policy.
', 'PutAccessPointPolicyRequest$Policy' => 'The policy that you want to apply to the specified access point. For more information about access point policies, see Managing data access with Amazon S3 access points in the Amazon S3 User Guide.
', 'PutBucketPolicyRequest$Policy' => 'The bucket policy as a JSON document.
', 'PutMultiRegionAccessPointPolicyInput$Policy' => 'The policy details for the PutMultiRegionAccessPoint request.
Indicates whether this access point policy is public. For more information about how Amazon S3 evaluates policies to determine whether they are public, see The Meaning of "Public" in the Amazon S3 User Guide.
', 'refs' => [ 'GetAccessPointPolicyStatusForObjectLambdaResult$PolicyStatus' => NULL, 'GetAccessPointPolicyStatusResult$PolicyStatus' => 'Indicates the current policy status of the specified access point.
', 'GetMultiRegionAccessPointPolicyStatusResult$Established' => NULL, ], ], 'Prefix' => [ 'base' => NULL, 'refs' => [ 'LifecycleRuleAndOperator$Prefix' => 'Prefix identifying one or more objects to which the rule applies.
', 'LifecycleRuleFilter$Prefix' => 'Prefix identifying one or more objects to which the rule applies.
When you\'re using XML requests, you must replace special characters (such as carriage returns) in object keys with their equivalent XML entity codes. For more information, see XML-related object key constraints in the Amazon S3 User Guide.
An object key name prefix that identifies the object or objects to which the rule applies. The maximum prefix length is 1,024 characters. To include all objects in an Outposts bucket, specify an empty string.
When you\'re using XML requests, you must replace special characters (such as carriage returns) in object keys with their equivalent XML entity codes. For more information, see XML-related object key constraints in the Amazon S3 User Guide.
An object key name prefix that identifies the subset of objects that the rule applies to.
', 'ReplicationRuleFilter$Prefix' => 'An object key name prefix that identifies the subset of objects that the rule applies to.
When you\'re using XML requests, you must replace special characters (such as carriage returns) in object keys with their equivalent XML entity codes. For more information, see XML-related object key constraints in the Amazon S3 User Guide.
The prefix of the destination bucket where the metrics export will be delivered.
', ], ], 'PrefixLevel' => [ 'base' => 'A container for the prefix-level configuration.
', 'refs' => [ 'BucketLevel$PrefixLevel' => 'A container for the prefix-level metrics for S3 Storage Lens.
', ], ], 'PrefixLevelStorageMetrics' => [ 'base' => 'A container for the prefix-level storage metrics for S3 Storage Lens.
', 'refs' => [ 'PrefixLevel$StorageMetrics' => 'A container for the prefix-level storage metrics for S3 Storage Lens.
', ], ], 'Priority' => [ 'base' => NULL, 'refs' => [ 'ReplicationRule$Priority' => 'The priority indicates which rule has precedence whenever two or more replication rules conflict. S3 on Outposts attempts to replicate objects according to all replication rules. However, if there are two or more rules with the same destination Outposts bucket, then objects will be replicated according to the rule with the highest priority. The higher the number, the higher the priority.
For more information, see Creating replication rules on Outposts in the Amazon S3 User Guide.
', ], ], 'ProposedMultiRegionAccessPointPolicy' => [ 'base' => 'The proposed access control policy for the Multi-Region Access Point.
When you update the policy, the update is first listed as the proposed policy. After the update is finished and all Regions have been updated, the proposed policy is listed as the established policy. If both policies have the same version number, the proposed policy is the established policy.
', 'refs' => [ 'MultiRegionAccessPointPolicyDocument$Proposed' => 'The proposed policy for the Multi-Region Access Point.
', ], ], 'PublicAccessBlockConfiguration' => [ 'base' => 'The PublicAccessBlock configuration that you want to apply to this Amazon S3 account. You can enable the configuration options in any combination. For more information about when Amazon S3 considers a bucket or object public, see The Meaning of "Public" in the Amazon S3 User Guide.
This data type is not supported for Amazon S3 on Outposts.
', 'refs' => [ 'CreateAccessPointRequest$PublicAccessBlockConfiguration' => ' The PublicAccessBlock configuration that you want to apply to the access point.
Configuration to block all public access. This setting is turned on and can not be edited.
', 'GetAccessPointResult$PublicAccessBlockConfiguration' => NULL, 'GetPublicAccessBlockOutput$PublicAccessBlockConfiguration' => 'The PublicAccessBlock configuration currently in effect for this Amazon Web Services account.
The PublicAccessBlock configuration that you want to apply to the specified Amazon Web Services account.
A container for the information associated with a PutMultiRegionAccessPoint request.
', 'refs' => [ 'AsyncRequestParameters$PutMultiRegionAccessPointPolicyRequest' => 'A container of the parameters for a PutMultiRegionAccessPoint request.
', 'PutMultiRegionAccessPointPolicyRequest$Details' => 'A container element containing the details of the policy for the Multi-Region Access Point.
', ], ], 'PutMultiRegionAccessPointPolicyRequest' => [ 'base' => NULL, 'refs' => [], ], 'PutMultiRegionAccessPointPolicyResult' => [ 'base' => NULL, 'refs' => [], ], 'PutPublicAccessBlockRequest' => [ 'base' => NULL, 'refs' => [], ], 'PutStorageLensConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'PutStorageLensConfigurationTaggingRequest' => [ 'base' => NULL, 'refs' => [], ], 'PutStorageLensConfigurationTaggingResult' => [ 'base' => NULL, 'refs' => [], ], 'Region' => [ 'base' => 'A Region that supports a Multi-Region Access Point as well as the associated bucket for the Region.
', 'refs' => [ 'RegionCreationList$member' => NULL, ], ], 'RegionCreationList' => [ 'base' => NULL, 'refs' => [ 'CreateMultiRegionAccessPointInput$Regions' => 'The buckets in different Regions that are associated with the Multi-Region Access Point.
', ], ], 'RegionName' => [ 'base' => NULL, 'refs' => [ 'MultiRegionAccessPointRegionalResponse$Name' => 'The name of the Region in the Multi-Region Access Point.
', 'MultiRegionAccessPointRoute$Region' => 'The Amazon Web Services Region to which you\'ll be submitting a routing configuration change. Either the Bucket or the Region value must be provided. If both are provided, the bucket must be in the specified Region.
The name of the Region.
', ], ], 'RegionReport' => [ 'base' => 'A combination of a bucket and Region that\'s part of a Multi-Region Access Point.
', 'refs' => [ 'RegionReportList$member' => NULL, ], ], 'RegionReportList' => [ 'base' => NULL, 'refs' => [ 'MultiRegionAccessPointReport$Regions' => 'A collection of the Regions and buckets associated with the Multi-Region Access Point.
', ], ], 'RegionalBucket' => [ 'base' => 'The container for the regional bucket.
', 'refs' => [ 'RegionalBucketList$member' => NULL, ], ], 'RegionalBucketList' => [ 'base' => NULL, 'refs' => [ 'ListRegionalBucketsResult$RegionalBucketList' => '', ], ], 'Regions' => [ 'base' => NULL, 'refs' => [ 'Exclude$Regions' => 'A container for the S3 Storage Lens Region excludes.
', 'Include$Regions' => 'A container for the S3 Storage Lens Region includes.
', ], ], 'ReplicaKmsKeyID' => [ 'base' => NULL, 'refs' => [ 'EncryptionConfiguration$ReplicaKmsKeyID' => 'Specifies the ID of the customer managed KMS key that\'s stored in Key Management Service (KMS) for the destination bucket. This ID is either the Amazon Resource Name (ARN) for the KMS key or the alias ARN for the KMS key. Amazon S3 uses this KMS key to encrypt replica objects. Amazon S3 supports only symmetric encryption KMS keys. For more information, see Symmetric encryption KMS keys in the Amazon Web Services Key Management Service Developer Guide.
', ], ], 'ReplicaModifications' => [ 'base' => 'A filter that you can use to specify whether replica modification sync is enabled. S3 on Outposts replica modification sync can help you keep object metadata synchronized between replicas and source objects. By default, S3 on Outposts replicates metadata from the source objects to the replicas only. When replica modification sync is enabled, S3 on Outposts replicates metadata changes made to the replica copies back to the source object, making the replication bidirectional.
To replicate object metadata modifications on replicas, you can specify this element and set the Status of this element to Enabled.
You must enable replica modification sync on the source and destination buckets to replicate replica metadata changes between the source and the replicas.
A filter that you can use to specify whether replica modification sync is enabled. S3 on Outposts replica modification sync can help you keep object metadata synchronized between replicas and source objects. By default, S3 on Outposts replicates metadata from the source objects to the replicas only. When replica modification sync is enabled, S3 on Outposts replicates metadata changes made to the replica copies back to the source object, making the replication bidirectional.
To replicate object metadata modifications on replicas, you can specify this element and set the Status of this element to Enabled.
You must enable replica modification sync on the source and destination buckets to replicate replica metadata changes between the source and the replicas.
Specifies whether S3 on Outposts replicates modifications to object metadata on replicas.
', ], ], 'ReplicationConfiguration' => [ 'base' => 'A container for one or more replication rules. A replication configuration must have at least one rule and you can add up to 100 rules. The maximum size of a replication configuration is 128 KB.
', 'refs' => [ 'GetBucketReplicationResult$ReplicationConfiguration' => 'A container for one or more replication rules. A replication configuration must have at least one rule and you can add up to 100 rules. The maximum size of a replication configuration is 128 KB.
', 'PutBucketReplicationRequest$ReplicationConfiguration' => '', ], ], 'ReplicationRule' => [ 'base' => 'Specifies which S3 on Outposts objects to replicate and where to store the replicas.
', 'refs' => [ 'ReplicationRules$member' => NULL, ], ], 'ReplicationRuleAndOperator' => [ 'base' => 'A container for specifying rule filters. The filters determine the subset of objects to which the rule applies. This element is required only if you specify more than one filter.
For example:
If you specify both a Prefix and a Tag filter, wrap these filters in an And element.
If you specify a filter based on multiple tags, wrap the Tag elements in an And element.
A container for specifying rule filters. The filters determine the subset of objects that the rule applies to. This element is required only if you specify more than one filter. For example:
If you specify both a Prefix and a Tag filter, wrap these filters in an And element.
If you specify a filter based on multiple tags, wrap the Tag elements in an And element.
A filter that identifies the subset of objects to which the replication rule applies. A Filter element must specify exactly one Prefix, Tag, or And child element.
A filter that identifies the subset of objects to which the replication rule applies. A Filter element must specify exactly one Prefix, Tag, or And child element.
Specifies whether the rule is enabled.
', ], ], 'ReplicationRules' => [ 'base' => NULL, 'refs' => [ 'ReplicationConfiguration$Rules' => 'A container for one or more replication rules. A replication configuration must have at least one rule and can contain an array of 100 rules at the most.
', ], ], 'ReplicationStatus' => [ 'base' => NULL, 'refs' => [ 'ReplicationStatusFilterList$member' => NULL, ], ], 'ReplicationStatusFilterList' => [ 'base' => NULL, 'refs' => [ 'JobManifestGeneratorFilter$ObjectReplicationStatuses' => 'If provided, the generated manifest should include only source bucket objects that have one of the specified Replication statuses.
', ], ], 'ReplicationStorageClass' => [ 'base' => NULL, 'refs' => [ 'Destination$StorageClass' => ' The storage class to use when replicating objects. All objects stored on S3 on Outposts are stored in the OUTPOSTS storage class. S3 on Outposts uses the OUTPOSTS storage class to create the object replicas.
Values other than OUTPOSTS are not supported by Amazon S3 on Outposts.
A container that specifies S3 Replication Time Control (S3 RTC) related information, including whether S3 RTC is enabled and the time when all objects and operations on objects must be replicated.
This is not supported by Amazon S3 on Outposts buckets.
A container that specifies S3 Replication Time Control (S3 RTC) settings, including whether S3 RTC is enabled and the time when all objects and operations on objects must be replicated. Must be specified together with a Metrics block.
This is not supported by Amazon S3 on Outposts buckets.
Specifies whether S3 Replication Time Control (S3 RTC) is enabled.
', ], ], 'ReplicationTimeValue' => [ 'base' => 'A container that specifies the time value for S3 Replication Time Control (S3 RTC). This value is also used for the replication metrics EventThreshold element.
This is not supported by Amazon S3 on Outposts buckets.
A container that specifies the time threshold for emitting the s3:Replication:OperationMissedThreshold event.
This is not supported by Amazon S3 on Outposts buckets.
A container that specifies the time by which replication should be complete for all objects and operations on objects.
', ], ], 'ReportPrefixString' => [ 'base' => NULL, 'refs' => [ 'JobReport$Prefix' => 'An optional prefix to describe where in the specified bucket the job-completion report will be stored. Amazon S3 stores the job-completion report at <prefix>/job-<job-id>/report.json.
The status that you want to move the specified job to.
', ], ], 'Role' => [ 'base' => NULL, 'refs' => [ 'ReplicationConfiguration$Role' => 'The Amazon Resource Name (ARN) of the Identity and Access Management (IAM) role that S3 on Outposts assumes when replicating objects. For information about S3 replication on Outposts configuration, see Setting up replication in the Amazon S3 User Guide.
', ], ], 'RouteList' => [ 'base' => NULL, 'refs' => [ 'GetMultiRegionAccessPointRoutesResult$Routes' => 'The different routes that make up the route configuration. Active routes return a value of 100, and passive routes return a value of 0.
The different routes that make up the new route configuration. Active routes return a value of 100, and passive routes return a value of 0.
A container for the S3 Storage Lens home Region. Your metrics data is stored and retained in your designated S3 Storage Lens home Region.
', 'ListStorageLensGroupEntry$HomeRegion' => 'Contains the Amazon Web Services Region where the Storage Lens group was created.
', 'Regions$member' => NULL, ], ], 'S3AccessControlList' => [ 'base' => '', 'refs' => [ 'S3AccessControlPolicy$AccessControlList' => '', ], ], 'S3AccessControlPolicy' => [ 'base' => '', 'refs' => [ 'S3SetObjectAclOperation$AccessControlPolicy' => '', ], ], 'S3AccessPointArn' => [ 'base' => NULL, 'refs' => [ 'AccessPoint$AccessPointArn' => 'The ARN for the access point.
', 'CreateAccessPointResult$AccessPointArn' => 'The ARN of the access point.
This is only supported by Amazon S3 on Outposts.
The ARN of the access point.
', ], ], 'S3BucketArnString' => [ 'base' => NULL, 'refs' => [ 'Buckets$member' => NULL, 'JobReport$Bucket' => 'The Amazon Resource Name (ARN) for the bucket where specified job-completion report will be stored.
', 'S3BucketDestination$Arn' => 'The Amazon Resource Name (ARN) of the bucket. This property is read-only and follows the following format: arn:aws:s3:us-east-1:example-account-id:bucket/your-destination-bucket-name
Specifies the destination bucket Amazon Resource Name (ARN) for the batch copy operation. For example, to copy objects to a bucket named destinationBucket, set the TargetResource property to arn:aws:s3:::destinationBucket.
The source bucket used by the ManifestGenerator.
', 'S3ManifestOutputLocation$Bucket' => 'The bucket ARN the generated manifest should be written to.
', ], ], 'S3BucketDestination' => [ 'base' => 'A container for the bucket where the Amazon S3 Storage Lens metrics export files are located.
', 'refs' => [ 'StorageLensDataExport$S3BucketDestination' => 'A container for the bucket where the S3 Storage Lens metrics export will be located.
This bucket must be located in the same Region as the storage lens configuration.
Indicates the algorithm that you want Amazon S3 to use to create the checksum. For more information, see Checking object integrity in the Amazon S3 User Guide.
', ], ], 'S3ContentLength' => [ 'base' => NULL, 'refs' => [ 'S3ObjectMetadata$ContentLength' => '', ], ], 'S3CopyObjectOperation' => [ 'base' => 'Contains the configuration parameters for a PUT Copy object operation. S3 Batch Operations passes every object to the underlying CopyObject API operation. For more information about the parameters for this operation, see CopyObject.
Directs the specified job to run a PUT Copy object call on every object in the manifest.
', ], ], 'S3DeleteObjectTaggingOperation' => [ 'base' => 'Contains no configuration parameters because the DELETE Object tagging (DeleteObjectTagging) API operation accepts only the bucket name and key name as parameters, which are defined in the job\'s manifest.
Directs the specified job to execute a DELETE Object tagging call on every object in the manifest.
', ], ], 'S3ExpirationInDays' => [ 'base' => NULL, 'refs' => [ 'S3InitiateRestoreObjectOperation$ExpirationInDays' => 'This argument specifies how long the S3 Glacier or S3 Glacier Deep Archive object remains available in Amazon S3. S3 Initiate Restore Object jobs that target S3 Glacier and S3 Glacier Deep Archive objects require ExpirationInDays set to 1 or greater.
Conversely, do not set ExpirationInDays when creating S3 Initiate Restore Object jobs that target S3 Intelligent-Tiering Archive Access and Deep Archive Access tier objects. Objects in S3 Intelligent-Tiering archive access tiers are not subject to restore expiry, so specifying ExpirationInDays results in restore request failure.
S3 Batch Operations jobs can operate either on S3 Glacier and S3 Glacier Deep Archive storage class objects or on S3 Intelligent-Tiering Archive Access and Deep Archive Access storage tier objects, but not both types in the same job. If you need to restore objects of both types you must create separate Batch Operations jobs.
', ], ], 'S3GeneratedManifestDescriptor' => [ 'base' => 'Describes the specified job\'s generated manifest. Batch Operations jobs created with a ManifestGenerator populate details of this descriptor after execution of the ManifestGenerator.
', 'refs' => [ 'JobDescriptor$GeneratedManifestDescriptor' => 'The attribute of the JobDescriptor containing details about the job\'s generated manifest.
', ], ], 'S3GlacierJobTier' => [ 'base' => NULL, 'refs' => [ 'S3InitiateRestoreObjectOperation$GlacierJobTier' => 'S3 Batch Operations supports STANDARD and BULK retrieval tiers, but not the EXPEDITED retrieval tier.
Contains the configuration parameters for a POST Object restore job. S3 Batch Operations passes every object to the underlying RestoreObject API operation. For more information about the parameters for this operation, see RestoreObject.
Directs the specified job to initiate restore requests for every archived object in the manifest.
', ], ], 'S3JobManifestGenerator' => [ 'base' => 'The container for the service that will create the S3 manifest.
', 'refs' => [ 'JobManifestGenerator$S3JobManifestGenerator' => 'The S3 job ManifestGenerator\'s configuration details.
', ], ], 'S3KeyArnString' => [ 'base' => NULL, 'refs' => [ 'JobManifestLocation$ObjectArn' => 'The Amazon Resource Name (ARN) for a manifest object.
When you\'re using XML requests, you must replace special characters (such as carriage returns) in object keys with their equivalent XML entity codes. For more information, see XML-related object key constraints in the Amazon S3 User Guide.
Location details for where the generated manifest should be written.
', 'refs' => [ 'S3JobManifestGenerator$ManifestOutputLocation' => 'Specifies the location the generated manifest will be written to.
', ], ], 'S3MetadataDirective' => [ 'base' => NULL, 'refs' => [ 'S3CopyObjectOperation$MetadataDirective' => '', ], ], 'S3ObjectLockLegalHold' => [ 'base' => 'Whether S3 Object Lock legal hold will be applied to objects in an S3 Batch Operations job.
', 'refs' => [ 'S3SetObjectLegalHoldOperation$LegalHold' => 'Contains the Object Lock legal hold status to be applied to all objects in the Batch Operations job.
', ], ], 'S3ObjectLockLegalHoldStatus' => [ 'base' => NULL, 'refs' => [ 'S3CopyObjectOperation$ObjectLockLegalHoldStatus' => 'The legal hold status to be applied to all objects in the Batch Operations job.
', 'S3ObjectLockLegalHold$Status' => 'The Object Lock legal hold status to be applied to all objects in the Batch Operations job.
', ], ], 'S3ObjectLockMode' => [ 'base' => NULL, 'refs' => [ 'S3CopyObjectOperation$ObjectLockMode' => 'The retention mode to be applied to all objects in the Batch Operations job.
', ], ], 'S3ObjectLockRetentionMode' => [ 'base' => NULL, 'refs' => [ 'S3Retention$Mode' => 'The Object Lock retention mode to be applied to all objects in the Batch Operations job.
', ], ], 'S3ObjectMetadata' => [ 'base' => '', 'refs' => [ 'S3CopyObjectOperation$NewObjectMetadata' => 'If you don\'t provide this parameter, Amazon S3 copies all the metadata from the original objects. If you specify an empty set, the new objects will have no tags. Otherwise, Amazon S3 assigns the supplied tags to the new objects.
', ], ], 'S3ObjectOwner' => [ 'base' => '', 'refs' => [ 'S3AccessControlList$Owner' => '', ], ], 'S3ObjectVersionId' => [ 'base' => NULL, 'refs' => [ 'JobManifestLocation$ObjectVersionId' => 'The optional version ID to identify a specific version of the manifest object.
', ], ], 'S3Permission' => [ 'base' => NULL, 'refs' => [ 'S3Grant$Permission' => '', ], ], 'S3RegionalBucketArn' => [ 'base' => NULL, 'refs' => [ 'CreateBucketResult$BucketArn' => 'The Amazon Resource Name (ARN) of the bucket.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
The Amazon Resource Name (ARN) for the regional bucket.
', ], ], 'S3ReplicateObjectOperation' => [ 'base' => 'Directs the specified job to invoke ReplicateObject on every object in the job\'s manifest.
Directs the specified job to invoke ReplicateObject on every object in the job\'s manifest.
The Amazon Resource Name (ARN) of the S3 resource that you want to list the tags for.
', 'TagResourceRequest$ResourceArn' => 'The Amazon Resource Name (ARN) of the S3 resource that you\'re trying to add tags to.
', 'UntagResourceRequest$ResourceArn' => 'The Amazon Resource Name (ARN) of the S3 resource that you want to remove the resource tags from.
', ], ], 'S3Retention' => [ 'base' => 'Contains the S3 Object Lock retention mode to be applied to all objects in the S3 Batch Operations job. If you don\'t provide Mode and RetainUntilDate data types in your operation, you will remove the retention from your objects. For more information, see Using S3 Object Lock retention with S3 Batch Operations in the Amazon S3 User Guide.
Contains the Object Lock retention mode to be applied to all objects in the Batch Operations job. For more information, see Using S3 Object Lock retention with S3 Batch Operations in the Amazon S3 User Guide.
', ], ], 'S3SSEAlgorithm' => [ 'base' => NULL, 'refs' => [ 'S3ObjectMetadata$SSEAlgorithm' => '', ], ], 'S3SetObjectAclOperation' => [ 'base' => 'Contains the configuration parameters for a PUT Object ACL operation. S3 Batch Operations passes every object to the underlying PutObjectAcl API operation. For more information about the parameters for this operation, see PutObjectAcl.
Directs the specified job to run a PutObjectAcl call on every object in the manifest.
Contains the configuration for an S3 Object Lock legal hold operation that an S3 Batch Operations job passes to every object to the underlying PutObjectLegalHold API operation. For more information, see Using S3 Object Lock legal hold with S3 Batch Operations in the Amazon S3 User Guide.
Contains the configuration parameters for the Object Lock retention action for an S3 Batch Operations job. Batch Operations passes every object to the underlying PutObjectRetention API operation. For more information, see Using S3 Object Lock retention with S3 Batch Operations in the Amazon S3 User Guide.
Contains the configuration parameters for a PUT Object Tagging operation. S3 Batch Operations passes every object to the underlying PutObjectTagging API operation. For more information about the parameters for this operation, see PutObjectTagging.
Directs the specified job to run a PUT Object tagging call on every object in the manifest.
', ], ], 'S3StorageClass' => [ 'base' => NULL, 'refs' => [ 'S3CopyObjectOperation$StorageClass' => '', ], ], 'S3Tag' => [ 'base' => 'A container for a key-value name pair.
', 'refs' => [ 'LifecycleRuleFilter$Tag' => NULL, 'MatchAnyTag$member' => NULL, 'ReplicationRuleFilter$Tag' => NULL, 'S3TagSet$member' => NULL, ], ], 'S3TagSet' => [ 'base' => NULL, 'refs' => [ 'CreateJobRequest$Tags' => 'A set of tags to associate with the S3 Batch Operations job. This is an optional parameter.
', 'GetBucketTaggingResult$TagSet' => 'The tags set of the Outposts bucket.
', 'GetJobTaggingResult$Tags' => 'The set of tags associated with the S3 Batch Operations job.
', 'LifecycleRuleAndOperator$Tags' => 'All of these tags must exist in the object\'s tag set in order for the rule to apply.
', 'PutJobTaggingRequest$Tags' => 'The set of tags to associate with the S3 Batch Operations job.
', 'ReplicationRuleAndOperator$Tags' => 'An array of tags that contain key and value pairs.
', 'S3CopyObjectOperation$NewObjectTagging' => '', 'S3SetObjectTaggingOperation$TagSet' => '', 'Tagging$TagSet' => 'A collection for a set of tags.
', ], ], 'S3UserMetadata' => [ 'base' => NULL, 'refs' => [ 'S3ObjectMetadata$UserMetadata' => '', ], ], 'SSEKMS' => [ 'base' => '', 'refs' => [ 'StorageLensDataExportEncryption$SSEKMS' => '', ], ], 'SSEKMSEncryption' => [ 'base' => 'Configuration for the use of SSE-KMS to encrypt generated manifest objects.
', 'refs' => [ 'GeneratedManifestEncryption$SSEKMS' => 'Configuration details on how SSE-KMS is used to encrypt generated manifest objects.
', ], ], 'SSEKMSKeyId' => [ 'base' => NULL, 'refs' => [ 'SSEKMS$KeyId' => 'A container for the ARN of the SSE-KMS encryption. This property is read-only and follows the following format: arn:aws:kms:us-east-1:example-account-id:key/example-9a73-4afc-8d29-8f5900cef44e
Configuration for the use of SSE-S3 to encrypt generated manifest objects.
', 'refs' => [ 'GeneratedManifestEncryption$SSES3' => 'Specifies the use of SSE-S3 to encrypt generated manifest objects.
', ], ], 'SelectionCriteria' => [ 'base' => '', 'refs' => [ 'PrefixLevelStorageMetrics$SelectionCriteria' => NULL, ], ], 'Setting' => [ 'base' => NULL, 'refs' => [ 'PublicAccessBlockConfiguration$BlockPublicAcls' => 'Specifies whether Amazon S3 should block public access control lists (ACLs) for buckets in this account. Setting this element to TRUE causes the following behavior:
PutBucketAcl and PutObjectAcl calls fail if the specified ACL is public.
PUT Object calls fail if the request includes a public ACL.
PUT Bucket calls fail if the request includes a public ACL.
Enabling this setting doesn\'t affect existing policies or ACLs.
This property is not supported for Amazon S3 on Outposts.
', 'PublicAccessBlockConfiguration$IgnorePublicAcls' => 'Specifies whether Amazon S3 should ignore public ACLs for buckets in this account. Setting this element to TRUE causes Amazon S3 to ignore all public ACLs on buckets in this account and any objects that they contain.
Enabling this setting doesn\'t affect the persistence of any existing ACLs and doesn\'t prevent new public ACLs from being set.
This property is not supported for Amazon S3 on Outposts.
', 'PublicAccessBlockConfiguration$BlockPublicPolicy' => 'Specifies whether Amazon S3 should block public bucket policies for buckets in this account. Setting this element to TRUE causes Amazon S3 to reject calls to PUT Bucket policy if the specified bucket policy allows public access.
Enabling this setting doesn\'t affect existing bucket policies.
This property is not supported for Amazon S3 on Outposts.
', 'PublicAccessBlockConfiguration$RestrictPublicBuckets' => 'Specifies whether Amazon S3 should restrict public bucket policies for buckets in this account. Setting this element to TRUE restricts access to buckets with public policies to only Amazon Web Service principals and authorized users within this account.
Enabling this setting doesn\'t affect previously stored bucket policies, except that public and cross-account access within any public bucket policy, including non-public delegation to specific accounts, is blocked.
This property is not supported for Amazon S3 on Outposts.
', ], ], 'SourceSelectionCriteria' => [ 'base' => 'A container that describes additional filters for identifying the source objects that you want to replicate. You can choose to enable or disable the replication of these objects.
', 'refs' => [ 'ReplicationRule$SourceSelectionCriteria' => 'A container that describes additional filters for identifying the source Outposts objects that you want to replicate. You can choose to enable or disable the replication of these objects.
', ], ], 'SseKmsEncryptedObjects' => [ 'base' => 'A container for filter information that you can use to select S3 objects that are encrypted with Key Management Service (KMS).
This is not supported by Amazon S3 on Outposts buckets.
A filter that you can use to select Amazon S3 objects that are encrypted with server-side encryption by using Key Management Service (KMS) keys. If you include SourceSelectionCriteria in the replication configuration, this element is required.
This is not supported by Amazon S3 on Outposts buckets.
Specifies whether Amazon S3 replicates objects that are created with server-side encryption by using an KMS key stored in Key Management Service.
', ], ], 'StorageLensArn' => [ 'base' => NULL, 'refs' => [ 'ListStorageLensConfigurationEntry$StorageLensArn' => 'The ARN of the S3 Storage Lens configuration. This property is read-only.
', 'StorageLensConfiguration$StorageLensArn' => 'The Amazon Resource Name (ARN) of the S3 Storage Lens configuration. This property is read-only and follows the following format: arn:aws:s3:us-east-1:example-account-id:storage-lens/your-dashboard-name
The Amazon Web Services organization for your S3 Storage Lens.
', 'refs' => [ 'StorageLensConfiguration$AwsOrg' => 'A container for the Amazon Web Services organization for this S3 Storage Lens configuration.
', ], ], 'StorageLensConfiguration' => [ 'base' => 'A container for the Amazon S3 Storage Lens configuration.
', 'refs' => [ 'GetStorageLensConfigurationResult$StorageLensConfiguration' => 'The S3 Storage Lens configuration requested.
', 'PutStorageLensConfigurationRequest$StorageLensConfiguration' => 'The S3 Storage Lens configuration.
', ], ], 'StorageLensConfigurationList' => [ 'base' => NULL, 'refs' => [ 'ListStorageLensConfigurationsResult$StorageLensConfigurationList' => 'A list of S3 Storage Lens configurations.
', ], ], 'StorageLensDataExport' => [ 'base' => 'A container to specify the properties of your S3 Storage Lens metrics export, including the destination, schema, and format.
', 'refs' => [ 'StorageLensConfiguration$DataExport' => 'A container to specify the properties of your S3 Storage Lens metrics export including, the destination, schema and format.
', ], ], 'StorageLensDataExportEncryption' => [ 'base' => 'A container for the encryption of the S3 Storage Lens metrics exports.
', 'refs' => [ 'S3BucketDestination$Encryption' => 'The container for the type encryption of the metrics exports in this bucket.
', ], ], 'StorageLensGroup' => [ 'base' => 'A custom grouping of objects that include filters for prefixes, suffixes, object tags, object size, or object age. You can create an S3 Storage Lens group that includes a single filter or multiple filter conditions. To specify multiple filter conditions, you use AND or OR logical operators.
The Storage Lens group configuration.
', 'GetStorageLensGroupResult$StorageLensGroup' => 'The name of the Storage Lens group that you\'re trying to retrieve the configuration details for.
', 'UpdateStorageLensGroupRequest$StorageLensGroup' => 'The JSON file that contains the Storage Lens group configuration.
', ], ], 'StorageLensGroupAndOperator' => [ 'base' => 'A logical operator that allows multiple filter conditions to be joined for more complex comparisons of Storage Lens group data.
', 'refs' => [ 'StorageLensGroupFilter$And' => 'A logical operator that allows multiple filter conditions to be joined for more complex comparisons of Storage Lens group data. Objects must match all of the listed filter conditions that are joined by the And logical operator. Only one of each filter condition is allowed.
Contains the Amazon Resource Name (ARN) of the Storage Lens group. This property is read-only.
', 'StorageLensGroup$StorageLensGroupArn' => 'Contains the Amazon Resource Name (ARN) of the Storage Lens group. This property is read-only.
', 'StorageLensGroupLevelExclude$member' => NULL, 'StorageLensGroupLevelInclude$member' => NULL, ], ], 'StorageLensGroupFilter' => [ 'base' => 'The filter element sets the criteria for the Storage Lens group data that is displayed. For multiple filter conditions, the AND or OR logical operator is used.
Sets the criteria for the Storage Lens group data that is displayed. For multiple filter conditions, the AND or OR logical operator is used.
Specifies the Storage Lens groups to include in the Storage Lens group aggregation.
', 'refs' => [ 'AccountLevel$StorageLensGroupLevel' => 'A container element for S3 Storage Lens groups metrics.
', ], ], 'StorageLensGroupLevelExclude' => [ 'base' => NULL, 'refs' => [ 'StorageLensGroupLevelSelectionCriteria$Exclude' => 'Indicates which Storage Lens group ARNs to exclude from the Storage Lens group aggregation.
', ], ], 'StorageLensGroupLevelInclude' => [ 'base' => NULL, 'refs' => [ 'StorageLensGroupLevelSelectionCriteria$Include' => 'Indicates which Storage Lens group ARNs to include in the Storage Lens group aggregation.
', ], ], 'StorageLensGroupLevelSelectionCriteria' => [ 'base' => 'Indicates which Storage Lens group ARNs to include or exclude in the Storage Lens group aggregation. You can only attach Storage Lens groups to your Storage Lens dashboard if they\'re included in your Storage Lens group aggregation. If this value is left null, then all Storage Lens groups are selected.
', 'refs' => [ 'StorageLensGroupLevel$SelectionCriteria' => 'Indicates which Storage Lens group ARNs to include or exclude in the Storage Lens group aggregation. If this value is left null, then all Storage Lens groups are selected.
', ], ], 'StorageLensGroupList' => [ 'base' => NULL, 'refs' => [ 'ListStorageLensGroupsResult$StorageLensGroupList' => 'The list of Storage Lens groups that exist in the specified home Region.
', ], ], 'StorageLensGroupName' => [ 'base' => NULL, 'refs' => [ 'DeleteStorageLensGroupRequest$Name' => 'The name of the Storage Lens group that you\'re trying to delete.
', 'GetStorageLensGroupRequest$Name' => 'The name of the Storage Lens group that you\'re trying to retrieve the configuration details for.
', 'ListStorageLensGroupEntry$Name' => 'Contains the name of the Storage Lens group that exists in the specified home Region.
', 'StorageLensGroup$Name' => 'Contains the name of the Storage Lens group.
', 'UpdateStorageLensGroupRequest$Name' => 'The name of the Storage Lens group that you want to update.
', ], ], 'StorageLensGroupOrOperator' => [ 'base' => 'A container element for specifying Or rule conditions. The rule conditions determine the subset of objects to which the Or rule applies. Objects can match any of the listed filter conditions, which are joined by the Or logical operator. Only one of each filter condition is allowed.
A single logical operator that allows multiple filter conditions to be joined. Objects can match any of the listed filter conditions, which are joined by the Or logical operator. Only one of each filter condition is allowed.
A container for the delimiter of the selection criteria being used.
', ], ], 'StorageLensPrefixLevelMaxDepth' => [ 'base' => NULL, 'refs' => [ 'SelectionCriteria$MaxDepth' => 'The max depth of the selection criteria
', ], ], 'StorageLensTag' => [ 'base' => '', 'refs' => [ 'StorageLensTags$member' => NULL, ], ], 'StorageLensTags' => [ 'base' => NULL, 'refs' => [ 'GetStorageLensConfigurationTaggingResult$Tags' => 'The tags of S3 Storage Lens configuration requested.
', 'PutStorageLensConfigurationRequest$Tags' => 'The tag set of the S3 Storage Lens configuration.
You can set up to a maximum of 50 tags.
The tag set of the S3 Storage Lens configuration.
You can set up to a maximum of 50 tags.
A pagination token to request the next page of results. Use the token that Amazon S3 returned in the NextToken element of the ListJobsResult from the previous List Jobs request.
If the List Jobs request produced more than the maximum number of results, you can pass this value into a subsequent List Jobs request in order to retrieve the next page of results.
The reason why the specified job was suspended. A job is only suspended if you create it through the Amazon S3 console. When you create the job, it enters the Suspended state to await confirmation before running. After you confirm the job, it automatically exits the Suspended state.
The timestamp when this job was suspended, if it has been suspended.
', ], ], 'Tag' => [ 'base' => 'An Amazon Web Services resource tag that\'s associated with your S3 resource. You can add tags to new objects when you upload them, or you can add object tags to existing objects.
This data type is only supported for S3 Storage Lens groups.
The tag key pair of the S3 resource tag that you\'re trying to remove.
', ], ], 'TagKeyString' => [ 'base' => NULL, 'refs' => [ 'S3Tag$Key' => 'Key of the tag
', 'StorageLensTag$Key' => '', 'Tag$Key' => ' The tag key for your Amazon Web Services resource. A tag key can be up to 128 Unicode characters in length and is case-sensitive. System created tags that begin with aws: aren’t supported.
The Amazon Web Services resource tags that you\'re adding to your Storage Lens group. This parameter is optional.
', 'ListTagsForResourceResult$Tags' => 'The Amazon Web Services resource tags that are associated with the resource.
', 'TagResourceRequest$Tags' => 'The Amazon Web Services resource tags that you want to add to the specified S3 resource.
', ], ], 'TagResourceRequest' => [ 'base' => NULL, 'refs' => [], ], 'TagResourceResult' => [ 'base' => NULL, 'refs' => [], ], 'TagValueString' => [ 'base' => NULL, 'refs' => [ 'S3Tag$Value' => 'Value of the tag
', 'StorageLensTag$Value' => '', 'Tag$Value' => 'The tag value for your Amazon Web Services resource. A tag value can be up to 256 Unicode characters in length and is case-sensitive.
', ], ], 'Tagging' => [ 'base' => '', 'refs' => [ 'PutBucketTaggingRequest$Tagging' => '', ], ], 'TimeStamp' => [ 'base' => NULL, 'refs' => [ 'S3CopyObjectOperation$ModifiedSinceConstraint' => '', 'S3CopyObjectOperation$UnModifiedSinceConstraint' => '', 'S3CopyObjectOperation$ObjectLockRetainUntilDate' => 'The date when the applied object retention configuration expires on all objects in the Batch Operations job.
', 'S3ObjectMetadata$HttpExpiresDate' => '', 'S3Retention$RetainUntilDate' => 'The date when the applied Object Lock retention will expire on all objects set by the Batch Operations job.
', ], ], 'TooManyRequestsException' => [ 'base' => '', 'refs' => [], ], 'TooManyTagsException' => [ 'base' => 'Amazon S3 throws this exception if you have too many tags in your tag set.
', 'refs' => [], ], 'TrafficDialPercentage' => [ 'base' => NULL, 'refs' => [ 'MultiRegionAccessPointRoute$TrafficDialPercentage' => 'The traffic state for the specified bucket or Amazon Web Services Region.
A value of 0 indicates a passive state, which means that no new traffic will be routed to the Region.
A value of 100 indicates an active state, which means that traffic will be routed to the specified Region.
When the routing configuration for a Region is changed from active to passive, any in-progress operations (uploads, copies, deletes, and so on) to the formerly active Region will continue to run to until a final success or failure status is reached.
If all Regions in the routing configuration are designated as passive, you\'ll receive an InvalidRequest error.
Specifies when an object transitions to a specified storage class. For more information about Amazon S3 Lifecycle configuration rules, see Transitioning objects using Amazon S3 Lifecycle in the Amazon S3 User Guide.
', 'refs' => [ 'TransitionList$member' => NULL, ], ], 'TransitionList' => [ 'base' => NULL, 'refs' => [ 'LifecycleRule$Transitions' => 'Specifies when an Amazon S3 object transitions to a specified storage class.
This is not supported by Amazon S3 on Outposts buckets.
The class of storage used to store the object.
', 'Transition$StorageClass' => 'The storage class to which you want the object to transition.
', ], ], 'UntagResourceRequest' => [ 'base' => NULL, 'refs' => [], ], 'UntagResourceResult' => [ 'base' => NULL, 'refs' => [], ], 'UpdateJobPriorityRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateJobPriorityResult' => [ 'base' => NULL, 'refs' => [], ], 'UpdateJobStatusRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateJobStatusResult' => [ 'base' => NULL, 'refs' => [], ], 'UpdateStorageLensGroupRequest' => [ 'base' => NULL, 'refs' => [], ], 'VersioningConfiguration' => [ 'base' => 'Describes the versioning state of an Amazon S3 on Outposts bucket. For more information, see PutBucketVersioning.
', 'refs' => [ 'PutBucketVersioningRequest$VersioningConfiguration' => 'The root-level tag for the VersioningConfiguration parameters.
The virtual private cloud (VPC) configuration for an access point.
', 'refs' => [ 'AccessPoint$VpcConfiguration' => 'The virtual private cloud (VPC) configuration for this access point, if one exists.
This element is empty if this access point is an Amazon S3 on Outposts access point that is used by other Amazon Web Services.
If you include this field, Amazon S3 restricts access to this access point to requests from the specified virtual private cloud (VPC).
This is required for creating an access point for Amazon S3 on Outposts buckets.
Contains the virtual private cloud (VPC) configuration for the specified access point.
This element is empty if this access point is an Amazon S3 on Outposts access point that is used by other Amazon Web Services.
If this field is specified, this access point will only allow connections from the specified VPC ID.
', ], ], ],]; +return [ 'version' => '2.0', 'service' => 'Amazon Web Services S3 Control provides access to Amazon S3 control plane actions.
', 'operations' => [ 'CreateAccessPoint' => 'Creates an access point and associates it with the specified bucket. For more information, see Managing Data Access with Amazon S3 Access Points in the Amazon S3 User Guide.
S3 on Outposts only supports VPC-style access points.
For more information, see Accessing Amazon S3 on Outposts using virtual private cloud (VPC) only access points in the Amazon S3 User Guide.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following actions are related to CreateAccessPoint:
Creates an Object Lambda Access Point. For more information, see Transforming objects with Object Lambda Access Points in the Amazon S3 User Guide.
The following actions are related to CreateAccessPointForObjectLambda:
This action creates an Amazon S3 on Outposts bucket. To create an S3 bucket, see Create Bucket in the Amazon S3 API Reference.
Creates a new Outposts bucket. By creating the bucket, you become the bucket owner. To create an Outposts bucket, you must have S3 on Outposts. For more information, see Using Amazon S3 on Outposts in Amazon S3 User Guide.
Not every string is an acceptable bucket name. For information on bucket naming restrictions, see Working with Amazon S3 Buckets.
S3 on Outposts buckets support:
Tags
LifecycleConfigurations for deleting expired objects
For a complete list of restrictions and Amazon S3 feature limitations on S3 on Outposts, see Amazon S3 on Outposts Restrictions and Limitations.
For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and x-amz-outpost-id in your API request, see the Examples section.
The following actions are related to CreateBucket for Amazon S3 on Outposts:
You can use S3 Batch Operations to perform large-scale batch actions on Amazon S3 objects. Batch Operations can run a single action on lists of Amazon S3 objects that you specify. For more information, see S3 Batch Operations in the Amazon S3 User Guide.
This action creates a S3 Batch Operations job.
Related actions include:
', 'CreateMultiRegionAccessPoint' => 'Creates a Multi-Region Access Point and associates it with the specified buckets. For more information about creating Multi-Region Access Points, see Creating Multi-Region Access Points in the Amazon S3 User Guide.
This action will always be routed to the US West (Oregon) Region. For more information about the restrictions around managing Multi-Region Access Points, see Managing Multi-Region Access Points in the Amazon S3 User Guide.
This request is asynchronous, meaning that you might receive a response before the command has completed. When this request provides a response, it provides a token that you can use to monitor the status of the request with DescribeMultiRegionAccessPointOperation.
The following actions are related to CreateMultiRegionAccessPoint:
Creates a new S3 Storage Lens group and associates it with the specified Amazon Web Services account ID. An S3 Storage Lens group is a custom grouping of objects based on prefix, suffix, object tags, object size, object age, or a combination of these filters. For each Storage Lens group that you’ve created, you can also optionally add Amazon Web Services resource tags. For more information about S3 Storage Lens groups, see Working with S3 Storage Lens groups.
To use this operation, you must have the permission to perform the s3:CreateStorageLensGroup action. If you’re trying to create a Storage Lens group with Amazon Web Services resource tags, you must also have permission to perform the s3:TagResource action. For more information about the required Storage Lens Groups permissions, see Setting account permissions to use S3 Storage Lens groups.
For information about Storage Lens groups errors, see List of Amazon S3 Storage Lens error codes.
', 'DeleteAccessPoint' => 'Deletes the specified access point.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following actions are related to DeleteAccessPoint:
Deletes the specified Object Lambda Access Point.
The following actions are related to DeleteAccessPointForObjectLambda:
Deletes the access point policy for the specified access point.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following actions are related to DeleteAccessPointPolicy:
Removes the resource policy for an Object Lambda Access Point.
The following actions are related to DeleteAccessPointPolicyForObjectLambda:
This action deletes an Amazon S3 on Outposts bucket. To delete an S3 bucket, see DeleteBucket in the Amazon S3 API Reference.
Deletes the Amazon S3 on Outposts bucket. All objects (including all object versions and delete markers) in the bucket must be deleted before the bucket itself can be deleted. For more information, see Using Amazon S3 on Outposts in Amazon S3 User Guide.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
Related Resources
', 'DeleteBucketLifecycleConfiguration' => 'This action deletes an Amazon S3 on Outposts bucket\'s lifecycle configuration. To delete an S3 bucket\'s lifecycle configuration, see DeleteBucketLifecycle in the Amazon S3 API Reference.
Deletes the lifecycle configuration from the specified Outposts bucket. Amazon S3 on Outposts removes all the lifecycle configuration rules in the lifecycle subresource associated with the bucket. Your objects never expire, and Amazon S3 on Outposts no longer automatically deletes any objects on the basis of rules contained in the deleted lifecycle configuration. For more information, see Using Amazon S3 on Outposts in Amazon S3 User Guide.
To use this operation, you must have permission to perform the s3-outposts:PutLifecycleConfiguration action. By default, the bucket owner has this permission and the Outposts bucket owner can grant this permission to others.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
For more information about object expiration, see Elements to Describe Lifecycle Actions.
Related actions include:
', 'DeleteBucketPolicy' => 'This action deletes an Amazon S3 on Outposts bucket policy. To delete an S3 bucket policy, see DeleteBucketPolicy in the Amazon S3 API Reference.
This implementation of the DELETE action uses the policy subresource to delete the policy of a specified Amazon S3 on Outposts bucket. If you are using an identity other than the root user of the Amazon Web Services account that owns the bucket, the calling identity must have the s3-outposts:DeleteBucketPolicy permissions on the specified Outposts bucket and belong to the bucket owner\'s account to use this action. For more information, see Using Amazon S3 on Outposts in Amazon S3 User Guide.
If you don\'t have DeleteBucketPolicy permissions, Amazon S3 returns a 403 Access Denied error. If you have the correct permissions, but you\'re not using an identity that belongs to the bucket owner\'s account, Amazon S3 returns a 405 Method Not Allowed error.
As a security precaution, the root user of the Amazon Web Services account that owns a bucket can always use this action, even if the policy explicitly denies the root user the ability to perform this action.
For more information about bucket policies, see Using Bucket Policies and User Policies.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following actions are related to DeleteBucketPolicy:
This operation deletes an Amazon S3 on Outposts bucket\'s replication configuration. To delete an S3 bucket\'s replication configuration, see DeleteBucketReplication in the Amazon S3 API Reference.
Deletes the replication configuration from the specified S3 on Outposts bucket.
To use this operation, you must have permissions to perform the s3-outposts:PutReplicationConfiguration action. The Outposts bucket owner has this permission by default and can grant it to others. For more information about permissions, see Setting up IAM with S3 on Outposts and Managing access to S3 on Outposts buckets in the Amazon S3 User Guide.
It can take a while to propagate PUT or DELETE requests for a replication configuration to all S3 on Outposts systems. Therefore, the replication configuration that\'s returned by a GET request soon after a PUT or DELETE request might return a more recent result than what\'s on the Outpost. If an Outpost is offline, the delay in updating the replication configuration on that Outpost can be significant.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
For information about S3 replication on Outposts configuration, see Replicating objects for S3 on Outposts in the Amazon S3 User Guide.
The following operations are related to DeleteBucketReplication:
This action deletes an Amazon S3 on Outposts bucket\'s tags. To delete an S3 bucket tags, see DeleteBucketTagging in the Amazon S3 API Reference.
Deletes the tags from the Outposts bucket. For more information, see Using Amazon S3 on Outposts in Amazon S3 User Guide.
To use this action, you must have permission to perform the PutBucketTagging action. By default, the bucket owner has this permission and can grant this permission to others.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following actions are related to DeleteBucketTagging:
Removes the entire tag set from the specified S3 Batch Operations job. To use the DeleteJobTagging operation, you must have permission to perform the s3:DeleteJobTagging action. For more information, see Controlling access and labeling jobs using tags in the Amazon S3 User Guide.
Related actions include:
', 'DeleteMultiRegionAccessPoint' => 'Deletes a Multi-Region Access Point. This action does not delete the buckets associated with the Multi-Region Access Point, only the Multi-Region Access Point itself.
This action will always be routed to the US West (Oregon) Region. For more information about the restrictions around managing Multi-Region Access Points, see Managing Multi-Region Access Points in the Amazon S3 User Guide.
This request is asynchronous, meaning that you might receive a response before the command has completed. When this request provides a response, it provides a token that you can use to monitor the status of the request with DescribeMultiRegionAccessPointOperation.
The following actions are related to DeleteMultiRegionAccessPoint:
Removes the PublicAccessBlock configuration for an Amazon Web Services account. For more information, see Using Amazon S3 block public access.
Related actions include:
', 'DeleteStorageLensConfiguration' => 'Deletes the Amazon S3 Storage Lens configuration. For more information about S3 Storage Lens, see Assessing your storage activity and usage with Amazon S3 Storage Lens in the Amazon S3 User Guide.
To use this action, you must have permission to perform the s3:DeleteStorageLensConfiguration action. For more information, see Setting permissions to use Amazon S3 Storage Lens in the Amazon S3 User Guide.
Deletes the Amazon S3 Storage Lens configuration tags. For more information about S3 Storage Lens, see Assessing your storage activity and usage with Amazon S3 Storage Lens in the Amazon S3 User Guide.
To use this action, you must have permission to perform the s3:DeleteStorageLensConfigurationTagging action. For more information, see Setting permissions to use Amazon S3 Storage Lens in the Amazon S3 User Guide.
Deletes an existing S3 Storage Lens group.
To use this operation, you must have the permission to perform the s3:DeleteStorageLensGroup action. For more information about the required Storage Lens Groups permissions, see Setting account permissions to use S3 Storage Lens groups.
For information about Storage Lens groups errors, see List of Amazon S3 Storage Lens error codes.
', 'DescribeJob' => 'Retrieves the configuration parameters and status for a Batch Operations job. For more information, see S3 Batch Operations in the Amazon S3 User Guide.
Related actions include:
', 'DescribeMultiRegionAccessPointOperation' => 'Retrieves the status of an asynchronous request to manage a Multi-Region Access Point. For more information about managing Multi-Region Access Points and how asynchronous requests work, see Managing Multi-Region Access Points in the Amazon S3 User Guide.
The following actions are related to GetMultiRegionAccessPoint:
Returns configuration information about the specified access point.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following actions are related to GetAccessPoint:
Returns configuration for an Object Lambda Access Point.
The following actions are related to GetAccessPointConfigurationForObjectLambda:
Returns configuration information about the specified Object Lambda Access Point
The following actions are related to GetAccessPointForObjectLambda:
Returns the access point policy associated with the specified access point.
The following actions are related to GetAccessPointPolicy:
Returns the resource policy for an Object Lambda Access Point.
The following actions are related to GetAccessPointPolicyForObjectLambda:
Indicates whether the specified access point currently has a policy that allows public access. For more information about public access through access points, see Managing Data Access with Amazon S3 access points in the Amazon S3 User Guide.
', 'GetAccessPointPolicyStatusForObjectLambda' => 'Returns the status of the resource policy associated with an Object Lambda Access Point.
', 'GetBucket' => 'Gets an Amazon S3 on Outposts bucket. For more information, see Using Amazon S3 on Outposts in the Amazon S3 User Guide.
If you are using an identity other than the root user of the Amazon Web Services account that owns the Outposts bucket, the calling identity must have the s3-outposts:GetBucket permissions on the specified Outposts bucket and belong to the Outposts bucket owner\'s account in order to use this action. Only users from Outposts bucket owner account with the right permissions can perform actions on an Outposts bucket.
If you don\'t have s3-outposts:GetBucket permissions or you\'re not using an identity that belongs to the bucket owner\'s account, Amazon S3 returns a 403 Access Denied error.
The following actions are related to GetBucket for Amazon S3 on Outposts:
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
This action gets an Amazon S3 on Outposts bucket\'s lifecycle configuration. To get an S3 bucket\'s lifecycle configuration, see GetBucketLifecycleConfiguration in the Amazon S3 API Reference.
Returns the lifecycle configuration information set on the Outposts bucket. For more information, see Using Amazon S3 on Outposts and for information about lifecycle configuration, see Object Lifecycle Management in Amazon S3 User Guide.
To use this action, you must have permission to perform the s3-outposts:GetLifecycleConfiguration action. The Outposts bucket owner has this permission, by default. The bucket owner can grant this permission to others. For more information about permissions, see Permissions Related to Bucket Subresource Operations and Managing Access Permissions to Your Amazon S3 Resources.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
GetBucketLifecycleConfiguration has the following special error:
Error code: NoSuchLifecycleConfiguration
Description: The lifecycle configuration does not exist.
HTTP Status Code: 404 Not Found
SOAP Fault Code Prefix: Client
The following actions are related to GetBucketLifecycleConfiguration:
This action gets a bucket policy for an Amazon S3 on Outposts bucket. To get a policy for an S3 bucket, see GetBucketPolicy in the Amazon S3 API Reference.
Returns the policy of a specified Outposts bucket. For more information, see Using Amazon S3 on Outposts in the Amazon S3 User Guide.
If you are using an identity other than the root user of the Amazon Web Services account that owns the bucket, the calling identity must have the GetBucketPolicy permissions on the specified bucket and belong to the bucket owner\'s account in order to use this action.
Only users from Outposts bucket owner account with the right permissions can perform actions on an Outposts bucket. If you don\'t have s3-outposts:GetBucketPolicy permissions or you\'re not using an identity that belongs to the bucket owner\'s account, Amazon S3 returns a 403 Access Denied error.
As a security precaution, the root user of the Amazon Web Services account that owns a bucket can always use this action, even if the policy explicitly denies the root user the ability to perform this action.
For more information about bucket policies, see Using Bucket Policies and User Policies.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following actions are related to GetBucketPolicy:
This operation gets an Amazon S3 on Outposts bucket\'s replication configuration. To get an S3 bucket\'s replication configuration, see GetBucketReplication in the Amazon S3 API Reference.
Returns the replication configuration of an S3 on Outposts bucket. For more information about S3 on Outposts, see Using Amazon S3 on Outposts in the Amazon S3 User Guide. For information about S3 replication on Outposts configuration, see Replicating objects for S3 on Outposts in the Amazon S3 User Guide.
It can take a while to propagate PUT or DELETE requests for a replication configuration to all S3 on Outposts systems. Therefore, the replication configuration that\'s returned by a GET request soon after a PUT or DELETE request might return a more recent result than what\'s on the Outpost. If an Outpost is offline, the delay in updating the replication configuration on that Outpost can be significant.
This action requires permissions for the s3-outposts:GetReplicationConfiguration action. The Outposts bucket owner has this permission by default and can grant it to others. For more information about permissions, see Setting up IAM with S3 on Outposts and Managing access to S3 on Outposts bucket in the Amazon S3 User Guide.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
If you include the Filter element in a replication configuration, you must also include the DeleteMarkerReplication, Status, and Priority elements. The response also returns those elements.
For information about S3 on Outposts replication failure reasons, see Replication failure reasons in the Amazon S3 User Guide.
The following operations are related to GetBucketReplication:
This action gets an Amazon S3 on Outposts bucket\'s tags. To get an S3 bucket tags, see GetBucketTagging in the Amazon S3 API Reference.
Returns the tag set associated with the Outposts bucket. For more information, see Using Amazon S3 on Outposts in the Amazon S3 User Guide.
To use this action, you must have permission to perform the GetBucketTagging action. By default, the bucket owner has this permission and can grant this permission to others.
GetBucketTagging has the following special error:
Error code: NoSuchTagSetError
Description: There is no tag set associated with the bucket.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following actions are related to GetBucketTagging:
This operation returns the versioning state for S3 on Outposts buckets only. To return the versioning state for an S3 bucket, see GetBucketVersioning in the Amazon S3 API Reference.
Returns the versioning state for an S3 on Outposts bucket. With S3 Versioning, you can save multiple distinct copies of your objects and recover from unintended user actions and application failures.
If you\'ve never set versioning on your bucket, it has no versioning state. In that case, the GetBucketVersioning request does not return a versioning state value.
For more information about versioning, see Versioning in the Amazon S3 User Guide.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following operations are related to GetBucketVersioning for S3 on Outposts.
Returns the tags on an S3 Batch Operations job. To use the GetJobTagging operation, you must have permission to perform the s3:GetJobTagging action. For more information, see Controlling access and labeling jobs using tags in the Amazon S3 User Guide.
Related actions include:
', 'GetMultiRegionAccessPoint' => 'Returns configuration information about the specified Multi-Region Access Point.
This action will always be routed to the US West (Oregon) Region. For more information about the restrictions around managing Multi-Region Access Points, see Managing Multi-Region Access Points in the Amazon S3 User Guide.
The following actions are related to GetMultiRegionAccessPoint:
Returns the access control policy of the specified Multi-Region Access Point.
This action will always be routed to the US West (Oregon) Region. For more information about the restrictions around managing Multi-Region Access Points, see Managing Multi-Region Access Points in the Amazon S3 User Guide.
The following actions are related to GetMultiRegionAccessPointPolicy:
Indicates whether the specified Multi-Region Access Point has an access control policy that allows public access.
This action will always be routed to the US West (Oregon) Region. For more information about the restrictions around managing Multi-Region Access Points, see Managing Multi-Region Access Points in the Amazon S3 User Guide.
The following actions are related to GetMultiRegionAccessPointPolicyStatus:
Returns the routing configuration for a Multi-Region Access Point, indicating which Regions are active or passive.
To obtain routing control changes and failover requests, use the Amazon S3 failover control infrastructure endpoints in these five Amazon Web Services Regions:
us-east-1
us-west-2
ap-southeast-2
ap-northeast-1
eu-west-1
Your Amazon S3 bucket does not need to be in these five Regions.
Retrieves the PublicAccessBlock configuration for an Amazon Web Services account. For more information, see Using Amazon S3 block public access.
Related actions include:
', 'GetStorageLensConfiguration' => 'Gets the Amazon S3 Storage Lens configuration. For more information, see Assessing your storage activity and usage with Amazon S3 Storage Lens in the Amazon S3 User Guide. For a complete list of S3 Storage Lens metrics, see S3 Storage Lens metrics glossary in the Amazon S3 User Guide.
To use this action, you must have permission to perform the s3:GetStorageLensConfiguration action. For more information, see Setting permissions to use Amazon S3 Storage Lens in the Amazon S3 User Guide.
Gets the tags of Amazon S3 Storage Lens configuration. For more information about S3 Storage Lens, see Assessing your storage activity and usage with Amazon S3 Storage Lens in the Amazon S3 User Guide.
To use this action, you must have permission to perform the s3:GetStorageLensConfigurationTagging action. For more information, see Setting permissions to use Amazon S3 Storage Lens in the Amazon S3 User Guide.
Retrieves the Storage Lens group configuration details.
To use this operation, you must have the permission to perform the s3:GetStorageLensGroup action. For more information about the required Storage Lens Groups permissions, see Setting account permissions to use S3 Storage Lens groups.
For information about Storage Lens groups errors, see List of Amazon S3 Storage Lens error codes.
', 'ListAccessPoints' => 'Returns a list of the access points that are owned by the current account that\'s associated with the specified bucket. You can retrieve up to 1000 access points per call. If the specified bucket has more than 1,000 access points (or the number specified in maxResults, whichever is less), the response will include a continuation token that you can use to list the additional access points.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following actions are related to ListAccessPoints:
Returns some or all (up to 1,000) access points associated with the Object Lambda Access Point per call. If there are more access points than what can be returned in one call, the response will include a continuation token that you can use to list the additional access points.
The following actions are related to ListAccessPointsForObjectLambda:
Lists current S3 Batch Operations jobs and jobs that have ended within the last 30 days for the Amazon Web Services account making the request. For more information, see S3 Batch Operations in the Amazon S3 User Guide.
Related actions include:
', 'ListMultiRegionAccessPoints' => 'Returns a list of the Multi-Region Access Points currently associated with the specified Amazon Web Services account. Each call can return up to 100 Multi-Region Access Points, the maximum number of Multi-Region Access Points that can be associated with a single account.
This action will always be routed to the US West (Oregon) Region. For more information about the restrictions around managing Multi-Region Access Points, see Managing Multi-Region Access Points in the Amazon S3 User Guide.
The following actions are related to ListMultiRegionAccessPoint:
Returns a list of all Outposts buckets in an Outpost that are owned by the authenticated sender of the request. For more information, see Using Amazon S3 on Outposts in the Amazon S3 User Guide.
For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and x-amz-outpost-id in your request, see the Examples section.
Gets a list of Amazon S3 Storage Lens configurations. For more information about S3 Storage Lens, see Assessing your storage activity and usage with Amazon S3 Storage Lens in the Amazon S3 User Guide.
To use this action, you must have permission to perform the s3:ListStorageLensConfigurations action. For more information, see Setting permissions to use Amazon S3 Storage Lens in the Amazon S3 User Guide.
Lists all the Storage Lens groups in the specified home Region.
To use this operation, you must have the permission to perform the s3:ListStorageLensGroups action. For more information about the required Storage Lens Groups permissions, see Setting account permissions to use S3 Storage Lens groups.
For information about Storage Lens groups errors, see List of Amazon S3 Storage Lens error codes.
', 'ListTagsForResource' => 'This operation allows you to list all the Amazon Web Services resource tags for the specified resource.
To use this operation, you must have the permission to perform the s3:ListTagsForResource action. For more information about the required Storage Lens Groups permissions, see Setting account permissions to use S3 Storage Lens groups.
For information about S3 Tagging errors, see List of Amazon S3 Tagging error codes.
This operation is only supported for S3 Storage Lens groups.
Replaces configuration for an Object Lambda Access Point.
The following actions are related to PutAccessPointConfigurationForObjectLambda:
Associates an access policy with the specified access point. Each access point can have only one policy, so a request made to this API replaces any existing policy associated with the specified access point.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following actions are related to PutAccessPointPolicy:
Creates or replaces resource policy for an Object Lambda Access Point. For an example policy, see Creating Object Lambda Access Points in the Amazon S3 User Guide.
The following actions are related to PutAccessPointPolicyForObjectLambda:
This action puts a lifecycle configuration to an Amazon S3 on Outposts bucket. To put a lifecycle configuration to an S3 bucket, see PutBucketLifecycleConfiguration in the Amazon S3 API Reference.
Creates a new lifecycle configuration for the S3 on Outposts bucket or replaces an existing lifecycle configuration. Outposts buckets only support lifecycle configurations that delete/expire objects after a certain period of time and abort incomplete multipart uploads.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following actions are related to PutBucketLifecycleConfiguration:
This action puts a bucket policy to an Amazon S3 on Outposts bucket. To put a policy on an S3 bucket, see PutBucketPolicy in the Amazon S3 API Reference.
Applies an Amazon S3 bucket policy to an Outposts bucket. For more information, see Using Amazon S3 on Outposts in the Amazon S3 User Guide.
If you are using an identity other than the root user of the Amazon Web Services account that owns the Outposts bucket, the calling identity must have the PutBucketPolicy permissions on the specified Outposts bucket and belong to the bucket owner\'s account in order to use this action.
If you don\'t have PutBucketPolicy permissions, Amazon S3 returns a 403 Access Denied error. If you have the correct permissions, but you\'re not using an identity that belongs to the bucket owner\'s account, Amazon S3 returns a 405 Method Not Allowed error.
As a security precaution, the root user of the Amazon Web Services account that owns a bucket can always use this action, even if the policy explicitly denies the root user the ability to perform this action.
For more information about bucket policies, see Using Bucket Policies and User Policies.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following actions are related to PutBucketPolicy:
This action creates an Amazon S3 on Outposts bucket\'s replication configuration. To create an S3 bucket\'s replication configuration, see PutBucketReplication in the Amazon S3 API Reference.
Creates a replication configuration or replaces an existing one. For information about S3 replication on Outposts configuration, see Replicating objects for S3 on Outposts in the Amazon S3 User Guide.
It can take a while to propagate PUT or DELETE requests for a replication configuration to all S3 on Outposts systems. Therefore, the replication configuration that\'s returned by a GET request soon after a PUT or DELETE request might return a more recent result than what\'s on the Outpost. If an Outpost is offline, the delay in updating the replication configuration on that Outpost can be significant.
Specify the replication configuration in the request body. In the replication configuration, you provide the following information:
The name of the destination bucket or buckets where you want S3 on Outposts to replicate objects
The Identity and Access Management (IAM) role that S3 on Outposts can assume to replicate objects on your behalf
Other relevant information, such as replication rules
A replication configuration must include at least one rule and can contain a maximum of 100. Each rule identifies a subset of objects to replicate by filtering the objects in the source Outposts bucket. To choose additional subsets of objects to replicate, add a rule for each subset.
To specify a subset of the objects in the source Outposts bucket to apply a replication rule to, add the Filter element as a child of the Rule element. You can filter objects based on an object key prefix, one or more object tags, or both. When you add the Filter element in the configuration, you must also add the following elements: DeleteMarkerReplication, Status, and Priority.
Using PutBucketReplication on Outposts requires that both the source and destination buckets must have versioning enabled. For information about enabling versioning on a bucket, see Managing S3 Versioning for your S3 on Outposts bucket.
For information about S3 on Outposts replication failure reasons, see Replication failure reasons in the Amazon S3 User Guide.
Handling Replication of Encrypted Objects
Outposts buckets are encrypted at all times. All the objects in the source Outposts bucket are encrypted and can be replicated. Also, all the replicas in the destination Outposts bucket are encrypted with the same encryption key as the objects in the source Outposts bucket.
Permissions
To create a PutBucketReplication request, you must have s3-outposts:PutReplicationConfiguration permissions for the bucket. The Outposts bucket owner has this permission by default and can grant it to others. For more information about permissions, see Setting up IAM with S3 on Outposts and Managing access to S3 on Outposts buckets.
To perform this operation, the user or role must also have the iam:CreateRole and iam:PassRole permissions. For more information, see Granting a user permissions to pass a role to an Amazon Web Services service.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following operations are related to PutBucketReplication:
This action puts tags on an Amazon S3 on Outposts bucket. To put tags on an S3 bucket, see PutBucketTagging in the Amazon S3 API Reference.
Sets the tags for an S3 on Outposts bucket. For more information, see Using Amazon S3 on Outposts in the Amazon S3 User Guide.
Use tags to organize your Amazon Web Services bill to reflect your own cost structure. To do this, sign up to get your Amazon Web Services account bill with tag key values included. Then, to see the cost of combined resources, organize your billing information according to resources with the same tag key values. For example, you can tag several resources with a specific application name, and then organize your billing information to see the total cost of that application across several services. For more information, see Cost allocation and tagging.
Within a bucket, if you add a tag that has the same key as an existing tag, the new value overwrites the old value. For more information, see Using cost allocation in Amazon S3 bucket tags.
To use this action, you must have permissions to perform the s3-outposts:PutBucketTagging action. The Outposts bucket owner has this permission by default and can grant this permission to others. For more information about permissions, see Permissions Related to Bucket Subresource Operations and Managing access permissions to your Amazon S3 resources.
PutBucketTagging has the following special errors:
Error code: InvalidTagError
Description: The tag provided was not a valid tag. This error can occur if the tag did not pass input validation. For information about tag restrictions, see User-Defined Tag Restrictions and Amazon Web Services-Generated Cost Allocation Tag Restrictions.
Error code: MalformedXMLError
Description: The XML provided does not match the schema.
Error code: OperationAbortedError
Description: A conflicting conditional action is currently in progress against this resource. Try again.
Error code: InternalError
Description: The service was unable to apply the provided tag to the bucket.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following actions are related to PutBucketTagging:
This operation sets the versioning state for S3 on Outposts buckets only. To set the versioning state for an S3 bucket, see PutBucketVersioning in the Amazon S3 API Reference.
Sets the versioning state for an S3 on Outposts bucket. With S3 Versioning, you can save multiple distinct copies of your objects and recover from unintended user actions and application failures.
You can set the versioning state to one of the following:
Enabled - Enables versioning for the objects in the bucket. All objects added to the bucket receive a unique version ID.
Suspended - Suspends versioning for the objects in the bucket. All objects added to the bucket receive the version ID null.
If you\'ve never set versioning on your bucket, it has no versioning state. In that case, a GetBucketVersioning request does not return a versioning state value.
When you enable S3 Versioning, for each object in your bucket, you have a current version and zero or more noncurrent versions. You can configure your bucket S3 Lifecycle rules to expire noncurrent versions after a specified time period. For more information, see Creating and managing a lifecycle configuration for your S3 on Outposts bucket in the Amazon S3 User Guide.
If you have an object expiration lifecycle configuration in your non-versioned bucket and you want to maintain the same permanent delete behavior when you enable versioning, you must add a noncurrent expiration policy. The noncurrent expiration lifecycle configuration will manage the deletes of the noncurrent object versions in the version-enabled bucket. For more information, see Versioning in the Amazon S3 User Guide.
All Amazon S3 on Outposts REST API requests for this action require an additional parameter of x-amz-outpost-id to be passed with the request. In addition, you must use an S3 on Outposts endpoint hostname prefix instead of s3-control. For an example of the request syntax for Amazon S3 on Outposts that uses the S3 on Outposts endpoint hostname prefix and the x-amz-outpost-id derived by using the access point ARN, see the Examples section.
The following operations are related to PutBucketVersioning for S3 on Outposts.
Sets the supplied tag-set on an S3 Batch Operations job.
A tag is a key-value pair. You can associate S3 Batch Operations tags with any job by sending a PUT request against the tagging subresource that is associated with the job. To modify the existing tag set, you can either replace the existing tag set entirely, or make changes within the existing tag set by retrieving the existing tag set using GetJobTagging, modify that tag set, and use this action to replace the tag set with the one you modified. For more information, see Controlling access and labeling jobs using tags in the Amazon S3 User Guide.
If you send this request with an empty tag set, Amazon S3 deletes the existing tag set on the Batch Operations job. If you use this method, you are charged for a Tier 1 Request (PUT). For more information, see Amazon S3 pricing.
For deleting existing tags for your Batch Operations job, a DeleteJobTagging request is preferred because it achieves the same result without incurring charges.
A few things to consider about using tags:
Amazon S3 limits the maximum number of tags to 50 tags per job.
You can associate up to 50 tags with a job as long as they have unique tag keys.
A tag key can be up to 128 Unicode characters in length, and tag values can be up to 256 Unicode characters in length.
The key and values are case sensitive.
For tagging-related restrictions related to characters and encodings, see User-Defined Tag Restrictions in the Billing and Cost Management User Guide.
To use the PutJobTagging operation, you must have permission to perform the s3:PutJobTagging action.
Related actions include:
', 'PutMultiRegionAccessPointPolicy' => 'Associates an access control policy with the specified Multi-Region Access Point. Each Multi-Region Access Point can have only one policy, so a request made to this action replaces any existing policy that is associated with the specified Multi-Region Access Point.
This action will always be routed to the US West (Oregon) Region. For more information about the restrictions around managing Multi-Region Access Points, see Managing Multi-Region Access Points in the Amazon S3 User Guide.
The following actions are related to PutMultiRegionAccessPointPolicy:
Creates or modifies the PublicAccessBlock configuration for an Amazon Web Services account. For this operation, users must have the s3:PutAccountPublicAccessBlock permission. For more information, see Using Amazon S3 block public access.
Related actions include:
', 'PutStorageLensConfiguration' => 'Puts an Amazon S3 Storage Lens configuration. For more information about S3 Storage Lens, see Working with Amazon S3 Storage Lens in the Amazon S3 User Guide. For a complete list of S3 Storage Lens metrics, see S3 Storage Lens metrics glossary in the Amazon S3 User Guide.
To use this action, you must have permission to perform the s3:PutStorageLensConfiguration action. For more information, see Setting permissions to use Amazon S3 Storage Lens in the Amazon S3 User Guide.
Put or replace tags on an existing Amazon S3 Storage Lens configuration. For more information about S3 Storage Lens, see Assessing your storage activity and usage with Amazon S3 Storage Lens in the Amazon S3 User Guide.
To use this action, you must have permission to perform the s3:PutStorageLensConfigurationTagging action. For more information, see Setting permissions to use Amazon S3 Storage Lens in the Amazon S3 User Guide.
Submits an updated route configuration for a Multi-Region Access Point. This API operation updates the routing status for the specified Regions from active to passive, or from passive to active. A value of 0 indicates a passive status, which means that traffic won\'t be routed to the specified Region. A value of 100 indicates an active status, which means that traffic will be routed to the specified Region. At least one Region must be active at all times.
When the routing configuration is changed, any in-progress operations (uploads, copies, deletes, and so on) to formerly active Regions will continue to run to their final completion state (success or failure). The routing configurations of any Regions that aren’t specified remain unchanged.
Updated routing configurations might not be immediately applied. It can take up to 2 minutes for your changes to take effect.
To submit routing control changes and failover requests, use the Amazon S3 failover control infrastructure endpoints in these five Amazon Web Services Regions:
us-east-1
us-west-2
ap-southeast-2
ap-northeast-1
eu-west-1
Your Amazon S3 bucket does not need to be in these five Regions.
Creates a new Amazon Web Services resource tag or updates an existing resource tag. You can add up to 50 Amazon Web Services resource tags for each S3 resource.
To use this operation, you must have the permission to perform the s3:TagResource action. For more information about the required Storage Lens Groups permissions, see Setting account permissions to use S3 Storage Lens groups.
For information about S3 Tagging errors, see List of Amazon S3 Tagging error codes.
This operation is only supported for S3 Storage Lens groups.
This operation removes the specified Amazon Web Services resource tags from an S3 resource.
To use this operation, you must have the permission to perform the s3:UntagResource action. For more information about the required Storage Lens Groups permissions, see Setting account permissions to use S3 Storage Lens groups.
For information about S3 Tagging errors, see List of Amazon S3 Tagging error codes.
This operation is only supported for S3 Storage Lens groups.
Updates an existing S3 Batch Operations job\'s priority. For more information, see S3 Batch Operations in the Amazon S3 User Guide.
Related actions include:
', 'UpdateJobStatus' => 'Updates the status for the specified job. Use this action to confirm that you want to run a job or to cancel an existing job. For more information, see S3 Batch Operations in the Amazon S3 User Guide.
Related actions include:
', 'UpdateStorageLensGroup' => 'Updates the existing Storage Lens group.
To use this operation, you must have the permission to perform the s3:UpdateStorageLensGroup action. For more information about the required Storage Lens Groups permissions, see Setting account permissions to use S3 Storage Lens groups.
For information about Storage Lens groups errors, see List of Amazon S3 Storage Lens error codes.
', ], 'shapes' => [ 'AbortIncompleteMultipartUpload' => [ 'base' => 'The container for abort incomplete multipart upload
', 'refs' => [ 'LifecycleRule$AbortIncompleteMultipartUpload' => 'Specifies the days since the initiation of an incomplete multipart upload that Amazon S3 waits before permanently removing all parts of the upload. For more information, see Aborting Incomplete Multipart Uploads Using a Bucket Lifecycle Configuration in the Amazon S3 User Guide.
', ], ], 'AccessControlTranslation' => [ 'base' => 'A container for information about access control for replicas.
This is not supported by Amazon S3 on Outposts buckets.
Specify this property only in a cross-account scenario (where the source and destination bucket owners are not the same), and you want to change replica ownership to the Amazon Web Services account that owns the destination bucket. If this property is not specified in the replication configuration, the replicas are owned by same Amazon Web Services account that owns the source object.
This is not supported by Amazon S3 on Outposts buckets.
An access point used to access a bucket.
', 'refs' => [ 'AccessPointList$member' => NULL, ], ], 'AccessPointList' => [ 'base' => NULL, 'refs' => [ 'ListAccessPointsResult$AccessPointList' => 'Contains identification and configuration information for one or more access points associated with the specified bucket.
', ], ], 'AccessPointName' => [ 'base' => NULL, 'refs' => [ 'AccessPoint$Name' => 'The name of this access point.
', 'CreateAccessPointRequest$Name' => 'The name you want to assign to this access point.
', 'DeleteAccessPointPolicyRequest$Name' => 'The name of the access point whose policy you want to delete.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the access point accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/accesspoint/<my-accesspoint-name>. For example, to access the access point reports-ap through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/accesspoint/reports-ap. The value must be URL encoded.
The name of the access point you want to delete.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the access point accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/accesspoint/<my-accesspoint-name>. For example, to access the access point reports-ap through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/accesspoint/reports-ap. The value must be URL encoded.
The name of the access point whose policy you want to retrieve.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the access point accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/accesspoint/<my-accesspoint-name>. For example, to access the access point reports-ap through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/accesspoint/reports-ap. The value must be URL encoded.
The name of the access point whose policy status you want to retrieve.
', 'GetAccessPointRequest$Name' => 'The name of the access point whose configuration information you want to retrieve.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the access point accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/accesspoint/<my-accesspoint-name>. For example, to access the access point reports-ap through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/accesspoint/reports-ap. The value must be URL encoded.
The name of the specified access point.
', 'PutAccessPointPolicyRequest$Name' => 'The name of the access point that you want to associate with the specified policy.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the access point accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/accesspoint/<my-accesspoint-name>. For example, to access the access point reports-ap through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/accesspoint/reports-ap. The value must be URL encoded.
The Amazon Web Services account ID associated with the S3 bucket associated with this access point.
', 'CreateAccessPointForObjectLambdaRequest$AccountId' => 'The Amazon Web Services account ID for owner of the specified Object Lambda Access Point.
', 'CreateAccessPointRequest$AccountId' => 'The Amazon Web Services account ID for the account that owns the specified access point.
', 'CreateAccessPointRequest$BucketAccountId' => 'The Amazon Web Services account ID associated with the S3 bucket associated with this access point.
', 'CreateJobRequest$AccountId' => 'The Amazon Web Services account ID that creates the job.
', 'CreateMultiRegionAccessPointRequest$AccountId' => 'The Amazon Web Services account ID for the owner of the Multi-Region Access Point. The owner of the Multi-Region Access Point also must own the underlying buckets.
', 'CreateStorageLensGroupRequest$AccountId' => 'The Amazon Web Services account ID that the Storage Lens group is created from and associated with.
', 'DeleteAccessPointForObjectLambdaRequest$AccountId' => 'The account ID for the account that owns the specified Object Lambda Access Point.
', 'DeleteAccessPointPolicyForObjectLambdaRequest$AccountId' => 'The account ID for the account that owns the specified Object Lambda Access Point.
', 'DeleteAccessPointPolicyRequest$AccountId' => 'The account ID for the account that owns the specified access point.
', 'DeleteAccessPointRequest$AccountId' => 'The Amazon Web Services account ID for the account that owns the specified access point.
', 'DeleteBucketLifecycleConfigurationRequest$AccountId' => 'The account ID of the lifecycle configuration to delete.
', 'DeleteBucketPolicyRequest$AccountId' => 'The account ID of the Outposts bucket.
', 'DeleteBucketReplicationRequest$AccountId' => 'The Amazon Web Services account ID of the Outposts bucket to delete the replication configuration for.
', 'DeleteBucketRequest$AccountId' => 'The account ID that owns the Outposts bucket.
', 'DeleteBucketTaggingRequest$AccountId' => 'The Amazon Web Services account ID of the Outposts bucket tag set to be removed.
', 'DeleteJobTaggingRequest$AccountId' => 'The Amazon Web Services account ID associated with the S3 Batch Operations job.
', 'DeleteMultiRegionAccessPointRequest$AccountId' => 'The Amazon Web Services account ID for the owner of the Multi-Region Access Point.
', 'DeletePublicAccessBlockRequest$AccountId' => 'The account ID for the Amazon Web Services account whose PublicAccessBlock configuration you want to remove.
The account ID of the requester.
', 'DeleteStorageLensConfigurationTaggingRequest$AccountId' => 'The account ID of the requester.
', 'DeleteStorageLensGroupRequest$AccountId' => 'The Amazon Web Services account ID used to create the Storage Lens group that you\'re trying to delete.
', 'DescribeJobRequest$AccountId' => 'The Amazon Web Services account ID associated with the S3 Batch Operations job.
', 'DescribeMultiRegionAccessPointOperationRequest$AccountId' => 'The Amazon Web Services account ID for the owner of the Multi-Region Access Point.
', 'Destination$Account' => 'The destination bucket owner\'s account ID.
', 'GetAccessPointConfigurationForObjectLambdaRequest$AccountId' => 'The account ID for the account that owns the specified Object Lambda Access Point.
', 'GetAccessPointForObjectLambdaRequest$AccountId' => 'The account ID for the account that owns the specified Object Lambda Access Point.
', 'GetAccessPointPolicyForObjectLambdaRequest$AccountId' => 'The account ID for the account that owns the specified Object Lambda Access Point.
', 'GetAccessPointPolicyRequest$AccountId' => 'The account ID for the account that owns the specified access point.
', 'GetAccessPointPolicyStatusForObjectLambdaRequest$AccountId' => 'The account ID for the account that owns the specified Object Lambda Access Point.
', 'GetAccessPointPolicyStatusRequest$AccountId' => 'The account ID for the account that owns the specified access point.
', 'GetAccessPointRequest$AccountId' => 'The Amazon Web Services account ID for the account that owns the specified access point.
', 'GetAccessPointResult$BucketAccountId' => 'The Amazon Web Services account ID associated with the S3 bucket associated with this access point.
', 'GetBucketLifecycleConfigurationRequest$AccountId' => 'The Amazon Web Services account ID of the Outposts bucket.
', 'GetBucketPolicyRequest$AccountId' => 'The Amazon Web Services account ID of the Outposts bucket.
', 'GetBucketReplicationRequest$AccountId' => 'The Amazon Web Services account ID of the Outposts bucket.
', 'GetBucketRequest$AccountId' => 'The Amazon Web Services account ID of the Outposts bucket.
', 'GetBucketTaggingRequest$AccountId' => 'The Amazon Web Services account ID of the Outposts bucket.
', 'GetBucketVersioningRequest$AccountId' => 'The Amazon Web Services account ID of the S3 on Outposts bucket.
', 'GetJobTaggingRequest$AccountId' => 'The Amazon Web Services account ID associated with the S3 Batch Operations job.
', 'GetMultiRegionAccessPointPolicyRequest$AccountId' => 'The Amazon Web Services account ID for the owner of the Multi-Region Access Point.
', 'GetMultiRegionAccessPointPolicyStatusRequest$AccountId' => 'The Amazon Web Services account ID for the owner of the Multi-Region Access Point.
', 'GetMultiRegionAccessPointRequest$AccountId' => 'The Amazon Web Services account ID for the owner of the Multi-Region Access Point.
', 'GetMultiRegionAccessPointRoutesRequest$AccountId' => 'The Amazon Web Services account ID for the owner of the Multi-Region Access Point.
', 'GetPublicAccessBlockRequest$AccountId' => 'The account ID for the Amazon Web Services account whose PublicAccessBlock configuration you want to retrieve.
The account ID of the requester.
', 'GetStorageLensConfigurationTaggingRequest$AccountId' => 'The account ID of the requester.
', 'GetStorageLensGroupRequest$AccountId' => 'The Amazon Web Services account ID associated with the Storage Lens group that you\'re trying to retrieve the details for.
', 'ListAccessPointsForObjectLambdaRequest$AccountId' => 'The account ID for the account that owns the specified Object Lambda Access Point.
', 'ListAccessPointsRequest$AccountId' => 'The Amazon Web Services account ID for the account that owns the specified access points.
', 'ListJobsRequest$AccountId' => 'The Amazon Web Services account ID associated with the S3 Batch Operations job.
', 'ListMultiRegionAccessPointsRequest$AccountId' => 'The Amazon Web Services account ID for the owner of the Multi-Region Access Point.
', 'ListRegionalBucketsRequest$AccountId' => 'The Amazon Web Services account ID of the Outposts bucket.
', 'ListStorageLensConfigurationsRequest$AccountId' => 'The account ID of the requester.
', 'ListStorageLensGroupsRequest$AccountId' => 'The Amazon Web Services account ID that owns the Storage Lens groups.
', 'ListTagsForResourceRequest$AccountId' => 'The Amazon Web Services account ID of the resource owner.
', 'PutAccessPointConfigurationForObjectLambdaRequest$AccountId' => 'The account ID for the account that owns the specified Object Lambda Access Point.
', 'PutAccessPointPolicyForObjectLambdaRequest$AccountId' => 'The account ID for the account that owns the specified Object Lambda Access Point.
', 'PutAccessPointPolicyRequest$AccountId' => 'The Amazon Web Services account ID for owner of the bucket associated with the specified access point.
', 'PutBucketLifecycleConfigurationRequest$AccountId' => 'The Amazon Web Services account ID of the Outposts bucket.
', 'PutBucketPolicyRequest$AccountId' => 'The Amazon Web Services account ID of the Outposts bucket.
', 'PutBucketReplicationRequest$AccountId' => 'The Amazon Web Services account ID of the Outposts bucket.
', 'PutBucketTaggingRequest$AccountId' => 'The Amazon Web Services account ID of the Outposts bucket.
', 'PutBucketVersioningRequest$AccountId' => 'The Amazon Web Services account ID of the S3 on Outposts bucket.
', 'PutJobTaggingRequest$AccountId' => 'The Amazon Web Services account ID associated with the S3 Batch Operations job.
', 'PutMultiRegionAccessPointPolicyRequest$AccountId' => 'The Amazon Web Services account ID for the owner of the Multi-Region Access Point.
', 'PutPublicAccessBlockRequest$AccountId' => 'The account ID for the Amazon Web Services account whose PublicAccessBlock configuration you want to set.
The account ID of the requester.
', 'PutStorageLensConfigurationTaggingRequest$AccountId' => 'The account ID of the requester.
', 'Region$BucketAccountId' => 'The Amazon Web Services account ID that owns the Amazon S3 bucket that\'s associated with this Multi-Region Access Point.
', 'RegionReport$BucketAccountId' => 'The Amazon Web Services account ID that owns the Amazon S3 bucket that\'s associated with this Multi-Region Access Point.
', 'S3BucketDestination$AccountId' => 'The account ID of the owner of the S3 Storage Lens metrics export bucket.
', 'S3JobManifestGenerator$ExpectedBucketOwner' => 'The Amazon Web Services account ID that owns the bucket the generated manifest is written to. If provided the generated manifest bucket\'s owner Amazon Web Services account ID must match this value, else the job fails.
', 'S3ManifestOutputLocation$ExpectedManifestBucketOwner' => 'The Account ID that owns the bucket the generated manifest is written to.
', 'SubmitMultiRegionAccessPointRoutesRequest$AccountId' => 'The Amazon Web Services account ID for the owner of the Multi-Region Access Point.
', 'TagResourceRequest$AccountId' => 'The Amazon Web Services account ID that created the S3 resource that you\'re trying to add tags to.
', 'UntagResourceRequest$AccountId' => 'The Amazon Web Services account ID that owns the resource that you\'re trying to remove the tags from.
', 'UpdateJobPriorityRequest$AccountId' => 'The Amazon Web Services account ID associated with the S3 Batch Operations job.
', 'UpdateJobStatusRequest$AccountId' => 'The Amazon Web Services account ID associated with the S3 Batch Operations job.
', 'UpdateStorageLensGroupRequest$AccountId' => 'The Amazon Web Services account ID of the Storage Lens group owner.
', ], ], 'AccountLevel' => [ 'base' => 'A container element for the account-level Amazon S3 Storage Lens configuration.
For more information about S3 Storage Lens, see Assessing your storage activity and usage with S3 Storage Lens in the Amazon S3 User Guide. For a complete list of S3 Storage Lens metrics, see S3 Storage Lens metrics glossary in the Amazon S3 User Guide.
', 'refs' => [ 'StorageLensConfiguration$AccountLevel' => 'A container for all the account-level configurations of your S3 Storage Lens configuration.
', ], ], 'ActivityMetrics' => [ 'base' => 'The container element for Amazon S3 Storage Lens activity metrics. Activity metrics show details about how your storage is requested, such as requests (for example, All requests, Get requests, Put requests), bytes uploaded or downloaded, and errors.
For more information about S3 Storage Lens, see Assessing your storage activity and usage with S3 Storage Lens in the Amazon S3 User Guide. For a complete list of S3 Storage Lens metrics, see S3 Storage Lens metrics glossary in the Amazon S3 User Guide.
', 'refs' => [ 'AccountLevel$ActivityMetrics' => 'A container element for S3 Storage Lens activity metrics.
', 'BucketLevel$ActivityMetrics' => 'A container for the bucket-level activity metrics for S3 Storage Lens.
', ], ], 'AdvancedCostOptimizationMetrics' => [ 'base' => 'The container element for Amazon S3 Storage Lens advanced cost-optimization metrics. Advanced cost-optimization metrics provide insights that you can use to manage and optimize your storage costs, for example, lifecycle rule counts for transitions, expirations, and incomplete multipart uploads.
For more information about S3 Storage Lens, see Assessing your storage activity and usage with S3 Storage Lens in the Amazon S3 User Guide. For a complete list of S3 Storage Lens metrics, see S3 Storage Lens metrics glossary in the Amazon S3 User Guide.
', 'refs' => [ 'AccountLevel$AdvancedCostOptimizationMetrics' => 'A container element for S3 Storage Lens advanced cost-optimization metrics.
', 'BucketLevel$AdvancedCostOptimizationMetrics' => 'A container for bucket-level advanced cost-optimization metrics for S3 Storage Lens.
', ], ], 'AdvancedDataProtectionMetrics' => [ 'base' => 'The container element for Amazon S3 Storage Lens advanced data-protection metrics. Advanced data-protection metrics provide insights that you can use to perform audits and protect your data, for example replication rule counts within and across Regions.
For more information about S3 Storage Lens, see Assessing your storage activity and usage with S3 Storage Lens in the Amazon S3 User Guide. For a complete list of S3 Storage Lens metrics, see S3 Storage Lens metrics glossary in the Amazon S3 User Guide.
', 'refs' => [ 'AccountLevel$AdvancedDataProtectionMetrics' => 'A container element for S3 Storage Lens advanced data-protection metrics.
', 'BucketLevel$AdvancedDataProtectionMetrics' => 'A container for bucket-level advanced data-protection metrics for S3 Storage Lens.
', ], ], 'Alias' => [ 'base' => NULL, 'refs' => [ 'AccessPoint$Alias' => 'The name or alias of the access point.
', 'CreateAccessPointResult$Alias' => 'The name or alias of the access point.
', 'GetAccessPointResult$Alias' => 'The name or alias of the access point.
', ], ], 'AsyncCreationTimestamp' => [ 'base' => NULL, 'refs' => [ 'AsyncOperation$CreationTime' => 'The time that the request was sent to the service.
', ], ], 'AsyncErrorDetails' => [ 'base' => 'Error details for the failed asynchronous operation.
', 'refs' => [ 'AsyncResponseDetails$ErrorDetails' => 'Error details for an asynchronous request.
', ], ], 'AsyncOperation' => [ 'base' => 'A container for the information about an asynchronous operation.
', 'refs' => [ 'DescribeMultiRegionAccessPointOperationResult$AsyncOperation' => 'A container element containing the details of the asynchronous operation.
', ], ], 'AsyncOperationName' => [ 'base' => NULL, 'refs' => [ 'AsyncOperation$Operation' => 'The specific operation for the asynchronous request.
', ], ], 'AsyncRequestParameters' => [ 'base' => 'A container for the request parameters associated with an asynchronous request.
', 'refs' => [ 'AsyncOperation$RequestParameters' => 'The parameters associated with the request.
', ], ], 'AsyncRequestStatus' => [ 'base' => NULL, 'refs' => [ 'AsyncOperation$RequestStatus' => 'The current status of the request.
', 'MultiRegionAccessPointRegionalResponse$RequestStatus' => 'The current status of the Multi-Region Access Point in this Region.
', ], ], 'AsyncRequestTokenARN' => [ 'base' => NULL, 'refs' => [ 'AsyncOperation$RequestTokenARN' => 'The request token associated with the request.
', 'CreateMultiRegionAccessPointResult$RequestTokenARN' => 'The request token associated with the request. You can use this token with DescribeMultiRegionAccessPointOperation to determine the status of asynchronous requests.
', 'DeleteMultiRegionAccessPointResult$RequestTokenARN' => 'The request token associated with the request. You can use this token with DescribeMultiRegionAccessPointOperation to determine the status of asynchronous requests.
', 'DescribeMultiRegionAccessPointOperationRequest$RequestTokenARN' => 'The request token associated with the request you want to know about. This request token is returned as part of the response when you make an asynchronous request. You provide this token to query about the status of the asynchronous action.
', 'PutMultiRegionAccessPointPolicyResult$RequestTokenARN' => 'The request token associated with the request. You can use this token with DescribeMultiRegionAccessPointOperation to determine the status of asynchronous requests.
', ], ], 'AsyncResponseDetails' => [ 'base' => 'A container for the response details that are returned when querying about an asynchronous request.
', 'refs' => [ 'AsyncOperation$ResponseDetails' => 'The details of the response.
', ], ], 'AwsLambdaTransformation' => [ 'base' => 'Lambda function used to transform objects through an Object Lambda Access Point.
', 'refs' => [ 'ObjectLambdaContentTransformation$AwsLambda' => 'A container for an Lambda function.
', ], ], 'AwsLambdaTransformationPayload' => [ 'base' => NULL, 'refs' => [ 'AwsLambdaTransformation$FunctionPayload' => 'Additional JSON that provides supplemental data to the Lambda function used to transform objects.
', ], ], 'AwsOrgArn' => [ 'base' => NULL, 'refs' => [ 'StorageLensAwsOrg$Arn' => 'A container for the Amazon Resource Name (ARN) of the Amazon Web Services organization. This property is read-only and follows the following format: arn:aws:organizations:us-east-1:example-account-id:organization/o-ex2l495dck
Include objects in the generated manifest only if they are eligible for replication according to the Replication configuration on the source bucket.
', 'JobReport$Enabled' => 'Indicates whether the specified job will generate a job-completion report.
', 'ObjectLambdaConfiguration$CloudWatchMetricsEnabled' => 'A container for whether the CloudWatch metrics configuration is enabled.
', 'S3CopyObjectOperation$RequesterPays' => '', 'S3CopyObjectOperation$BucketKeyEnabled' => 'Specifies whether Amazon S3 should use an S3 Bucket Key for object encryption with server-side encryption using Amazon Web Services KMS (SSE-KMS). Setting this header to true causes Amazon S3 to use an S3 Bucket Key for object encryption with SSE-KMS.
Specifying this header with an object action doesn’t affect bucket-level settings for S3 Bucket Key.
', 'S3JobManifestGenerator$EnableManifestOutput' => 'Determines whether or not to write the job\'s generated manifest to a bucket.
', 'S3ObjectMetadata$RequesterCharged' => '', 'S3SetObjectRetentionOperation$BypassGovernanceRetention' => 'Indicates if the action should be applied to objects in the Batch Operations job even if they have Object Lock GOVERNANCE type in place.
The requested Outposts bucket name is not available. The bucket namespace is shared by all users of the Outposts in this Region. Select a different name and try again.
', 'refs' => [], ], 'BucketAlreadyOwnedByYou' => [ 'base' => 'The Outposts bucket you tried to create already exists, and you own it.
', 'refs' => [], ], 'BucketCannedACL' => [ 'base' => NULL, 'refs' => [ 'CreateBucketRequest$ACL' => 'The canned ACL to apply to the bucket.
This is not supported by Amazon S3 on Outposts buckets.
The Amazon Resource Name (ARN) of the access point for the destination bucket where you want S3 on Outposts to store the replication results.
', 'ReplicationRule$Bucket' => 'The Amazon Resource Name (ARN) of the access point for the source Outposts bucket that you want S3 on Outposts to replicate the objects from.
', ], ], 'BucketLevel' => [ 'base' => 'A container for the bucket-level configuration for Amazon S3 Storage Lens.
For more information about S3 Storage Lens, see Assessing your storage activity and usage with S3 Storage Lens in the Amazon S3 User Guide.
', 'refs' => [ 'AccountLevel$BucketLevel' => 'A container element for the S3 Storage Lens bucket-level configuration.
', ], ], 'BucketLocationConstraint' => [ 'base' => NULL, 'refs' => [ 'CreateBucketConfiguration$LocationConstraint' => 'Specifies the Region where the bucket will be created. If you are creating a bucket on the US East (N. Virginia) Region (us-east-1), you do not need to specify the location.
This is not supported by Amazon S3 on Outposts buckets.
The name of the bucket associated with this access point.
', 'CreateAccessPointRequest$Bucket' => 'The name of the bucket that you want to associate this access point with.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
The name of the bucket.
', 'DeleteBucketLifecycleConfigurationRequest$Bucket' => 'Specifies the bucket.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
Specifies the bucket.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
Specifies the S3 on Outposts bucket to delete the replication configuration for.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
Specifies the bucket being deleted.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
The bucket ARN that has the tag set to be removed.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
The name of the bucket associated with the specified access point.
', 'GetBucketLifecycleConfigurationRequest$Bucket' => 'The Amazon Resource Name (ARN) of the bucket.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
Specifies the bucket.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
Specifies the bucket to get the replication information for.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
Specifies the bucket.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
The Outposts bucket requested.
', 'GetBucketTaggingRequest$Bucket' => 'Specifies the bucket.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
The S3 on Outposts bucket to return the versioning state for.
', 'ListAccessPointsRequest$Bucket' => 'The name of the bucket whose associated access points you want to list.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
The name of the Amazon S3 bucket for which you\'ll submit a routing configuration change. Either the Bucket or the Region value must be provided. If both are provided, the bucket must be in the specified Region.
The name of the bucket for which to set the configuration.
', 'PutBucketPolicyRequest$Bucket' => 'Specifies the bucket.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
Specifies the S3 on Outposts bucket to set the configuration for.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
The Amazon Resource Name (ARN) of the bucket.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
The S3 on Outposts bucket to set the versioning state for.
', 'Region$Bucket' => 'The name of the associated bucket for the Region.
', 'RegionReport$Bucket' => 'The name of the bucket.
', 'RegionalBucket$Bucket' => '', ], ], 'BucketVersioningStatus' => [ 'base' => NULL, 'refs' => [ 'GetBucketVersioningResult$Status' => 'The versioning state of the S3 on Outposts bucket.
', 'VersioningConfiguration$Status' => 'Sets the versioning state of the S3 on Outposts bucket.
', ], ], 'Buckets' => [ 'base' => NULL, 'refs' => [ 'Exclude$Buckets' => 'A container for the S3 Storage Lens bucket excludes.
', 'Include$Buckets' => 'A container for the S3 Storage Lens bucket includes.
', ], ], 'CloudWatchMetrics' => [ 'base' => 'A container for enabling Amazon CloudWatch publishing for S3 Storage Lens metrics.
For more information about publishing S3 Storage Lens metrics to CloudWatch, see Monitor S3 Storage Lens metrics in CloudWatch in the Amazon S3 User Guide.
', 'refs' => [ 'StorageLensDataExport$CloudWatchMetrics' => 'A container for enabling Amazon CloudWatch publishing for S3 Storage Lens metrics.
', ], ], 'ConfigId' => [ 'base' => NULL, 'refs' => [ 'DeleteStorageLensConfigurationRequest$ConfigId' => 'The ID of the S3 Storage Lens configuration.
', 'DeleteStorageLensConfigurationTaggingRequest$ConfigId' => 'The ID of the S3 Storage Lens configuration.
', 'GetStorageLensConfigurationRequest$ConfigId' => 'The ID of the Amazon S3 Storage Lens configuration.
', 'GetStorageLensConfigurationTaggingRequest$ConfigId' => 'The ID of the Amazon S3 Storage Lens configuration.
', 'ListStorageLensConfigurationEntry$Id' => 'A container for the S3 Storage Lens configuration ID.
', 'PutStorageLensConfigurationRequest$ConfigId' => 'The ID of the S3 Storage Lens configuration.
', 'PutStorageLensConfigurationTaggingRequest$ConfigId' => 'The ID of the S3 Storage Lens configuration.
', 'StorageLensConfiguration$Id' => 'A container for the Amazon S3 Storage Lens configuration ID.
', ], ], 'ConfirmRemoveSelfBucketAccess' => [ 'base' => NULL, 'refs' => [ 'PutBucketPolicyRequest$ConfirmRemoveSelfBucketAccess' => 'Set this parameter to true to confirm that you want to remove your permissions to change this bucket policy in the future.
This is not supported by Amazon S3 on Outposts buckets.
Indicates whether confirmation is required before Amazon S3 runs the job. Confirmation is only required for jobs created through the Amazon S3 console.
', 'JobDescriptor$ConfirmationRequired' => 'Indicates whether confirmation is required before Amazon S3 begins running the specified job. Confirmation is required only for jobs created through the Amazon S3 console.
', ], ], 'ContinuationToken' => [ 'base' => NULL, 'refs' => [ 'ListStorageLensConfigurationsRequest$NextToken' => 'A pagination token to request the next page of results.
', 'ListStorageLensConfigurationsResult$NextToken' => 'If the request produced more than the maximum number of S3 Storage Lens configuration results, you can pass this value into a subsequent request to retrieve the next page of results.
', 'ListStorageLensGroupsRequest$NextToken' => 'The token for the next set of results, or null if there are no more results.
If NextToken is returned, there are more Storage Lens groups results available. The value of NextToken is a unique pagination token for each page. Make the call again using the returned token to retrieve the next page. Keep all other arguments unchanged. Each pagination token expires after 24 hours.
The container for the bucket configuration.
This is not supported by Amazon S3 on Outposts buckets.
The configuration information for the bucket.
This is not supported by Amazon S3 on Outposts buckets.
A container for the information associated with a CreateMultiRegionAccessPoint request.
', 'refs' => [ 'AsyncRequestParameters$CreateMultiRegionAccessPointRequest' => 'A container of the parameters for a CreateMultiRegionAccessPoint request.
', 'CreateMultiRegionAccessPointRequest$Details' => 'A container element containing details about the Multi-Region Access Point.
', ], ], 'CreateMultiRegionAccessPointRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateMultiRegionAccessPointResult' => [ 'base' => NULL, 'refs' => [], ], 'CreateStorageLensGroupRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreationDate' => [ 'base' => NULL, 'refs' => [ 'GetAccessPointForObjectLambdaResult$CreationDate' => 'The date and time when the specified Object Lambda Access Point was created.
', 'GetAccessPointResult$CreationDate' => 'The date and time when the specified access point was created.
', 'GetBucketResult$CreationDate' => 'The creation date of the Outposts bucket.
', 'RegionalBucket$CreationDate' => 'The creation date of the regional bucket
', ], ], 'CreationTimestamp' => [ 'base' => NULL, 'refs' => [ 'MultiRegionAccessPointReport$CreatedAt' => 'When the Multi-Region Access Point create request was received.
', ], ], 'Date' => [ 'base' => NULL, 'refs' => [ 'LifecycleExpiration$Date' => 'Indicates at what date the object is to be deleted. Should be in GMT ISO 8601 format.
', 'Transition$Date' => 'Indicates when objects are transitioned to the specified storage class. The date value must be in ISO 8601 format. The time is always midnight UTC.
', ], ], 'Days' => [ 'base' => NULL, 'refs' => [ 'LifecycleExpiration$Days' => 'Indicates the lifetime, in days, of the objects that are subject to the rule. The value must be a non-zero positive integer.
', 'NoncurrentVersionExpiration$NoncurrentDays' => 'Specifies the number of days an object is noncurrent before Amazon S3 can perform the associated action. For information about the noncurrent days calculations, see How Amazon S3 Calculates When an Object Became Noncurrent in the Amazon S3 User Guide.
', 'NoncurrentVersionTransition$NoncurrentDays' => 'Specifies the number of days an object is noncurrent before Amazon S3 can perform the associated action. For information about the noncurrent days calculations, see How Amazon S3 Calculates How Long an Object Has Been Noncurrent in the Amazon S3 User Guide.
', 'Transition$Days' => 'Indicates the number of days after creation when objects are transitioned to the specified storage class. The value must be a positive integer.
', ], ], 'DaysAfterInitiation' => [ 'base' => NULL, 'refs' => [ 'AbortIncompleteMultipartUpload$DaysAfterInitiation' => 'Specifies the number of days after which Amazon S3 aborts an incomplete multipart upload to the Outposts bucket.
', ], ], 'DeleteAccessPointForObjectLambdaRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteAccessPointPolicyForObjectLambdaRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteAccessPointPolicyRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteAccessPointRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteBucketLifecycleConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteBucketPolicyRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteBucketReplicationRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteBucketRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteBucketTaggingRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteJobTaggingRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteJobTaggingResult' => [ 'base' => NULL, 'refs' => [], ], 'DeleteMarkerReplication' => [ 'base' => 'Specifies whether S3 on Outposts replicates delete markers. If you specify a Filter element in your replication configuration, you must also include a DeleteMarkerReplication element. If your Filter includes a Tag element, the DeleteMarkerReplication element\'s Status child element must be set to Disabled, because S3 on Outposts does not support replicating delete markers for tag-based rules.
For more information about delete marker replication, see How delete operations affect replication in the Amazon S3 User Guide.
', 'refs' => [ 'ReplicationRule$DeleteMarkerReplication' => 'Specifies whether S3 on Outposts replicates delete markers. If you specify a Filter element in your replication configuration, you must also include a DeleteMarkerReplication element. If your Filter includes a Tag element, the DeleteMarkerReplication element\'s Status child element must be set to Disabled, because S3 on Outposts doesn\'t support replicating delete markers for tag-based rules.
For more information about delete marker replication, see How delete operations affect replication in the Amazon S3 User Guide.
', ], ], 'DeleteMarkerReplicationStatus' => [ 'base' => NULL, 'refs' => [ 'DeleteMarkerReplication$Status' => 'Indicates whether to replicate delete markers.
', ], ], 'DeleteMultiRegionAccessPointInput' => [ 'base' => 'A container for the information associated with a DeleteMultiRegionAccessPoint request.
', 'refs' => [ 'AsyncRequestParameters$DeleteMultiRegionAccessPointRequest' => 'A container of the parameters for a DeleteMultiRegionAccessPoint request.
', 'DeleteMultiRegionAccessPointRequest$Details' => 'A container element containing details about the Multi-Region Access Point.
', ], ], 'DeleteMultiRegionAccessPointRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteMultiRegionAccessPointResult' => [ 'base' => NULL, 'refs' => [], ], 'DeletePublicAccessBlockRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteStorageLensConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteStorageLensConfigurationTaggingRequest' => [ 'base' => NULL, 'refs' => [], ], 'DeleteStorageLensConfigurationTaggingResult' => [ 'base' => NULL, 'refs' => [], ], 'DeleteStorageLensGroupRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeJobResult' => [ 'base' => NULL, 'refs' => [], ], 'DescribeMultiRegionAccessPointOperationRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeMultiRegionAccessPointOperationResult' => [ 'base' => NULL, 'refs' => [], ], 'Destination' => [ 'base' => 'Specifies information about the replication destination bucket and its settings for an S3 on Outposts replication configuration.
', 'refs' => [ 'ReplicationRule$Destination' => 'A container for information about the replication destination and its configurations.
', ], ], 'DetailedStatusCodesMetrics' => [ 'base' => 'The container element for Amazon S3 Storage Lens detailed status code metrics. Detailed status code metrics generate metrics for HTTP status codes, such as 200 OK, 403 Forbidden, 503 Service Unavailable and others.
For more information about S3 Storage Lens, see Assessing your storage activity and usage with S3 Storage Lens in the Amazon S3 User Guide. For a complete list of S3 Storage Lens metrics, see S3 Storage Lens metrics glossary in the Amazon S3 User Guide.
', 'refs' => [ 'AccountLevel$DetailedStatusCodesMetrics' => 'A container element for detailed status code metrics.
', 'BucketLevel$DetailedStatusCodesMetrics' => 'A container for bucket-level detailed status code metrics for S3 Storage Lens.
', ], ], 'EncryptionConfiguration' => [ 'base' => 'Specifies encryption-related information for an Amazon S3 bucket that is a destination for replicated objects.
This is not supported by Amazon S3 on Outposts buckets.
A container that provides information about encryption. If SourceSelectionCriteria is specified, you must specify this element.
This is not supported by Amazon S3 on Outposts buckets.
The VPC endpoint for the access point.
', ], ], 'EstablishedMultiRegionAccessPointPolicy' => [ 'base' => 'The last established access control policy for a Multi-Region Access Point.
When you update the policy, the update is first listed as the proposed policy. After the update is finished and all Regions have been updated, the proposed policy is listed as the established policy. If both policies have the same version number, the proposed policy is the established policy.
', 'refs' => [ 'MultiRegionAccessPointPolicyDocument$Established' => 'The last established policy for the Multi-Region Access Point.
', ], ], 'ExceptionMessage' => [ 'base' => NULL, 'refs' => [ 'BadRequestException$Message' => NULL, 'IdempotencyException$Message' => NULL, 'InternalServiceException$Message' => NULL, 'InvalidNextTokenException$Message' => NULL, 'InvalidRequestException$Message' => NULL, 'JobStatusException$Message' => NULL, 'NotFoundException$Message' => NULL, 'TooManyRequestsException$Message' => NULL, 'TooManyTagsException$Message' => NULL, ], ], 'Exclude' => [ 'base' => 'A container for what Amazon S3 Storage Lens will exclude.
', 'refs' => [ 'StorageLensConfiguration$Exclude' => 'A container for what is excluded in this configuration. This container can only be valid if there is no Include container submitted, and it\'s not empty.
An optional configuration to replicate existing source bucket objects.
This is not supported by Amazon S3 on Outposts buckets.
An optional configuration to replicate existing source bucket objects.
This is not supported by Amazon S3 on Outposts buckets.
Specifies whether Amazon S3 replicates existing source bucket objects.
', ], ], 'ExpirationStatus' => [ 'base' => NULL, 'refs' => [ 'LifecycleRule$Status' => 'If \'Enabled\', the rule is currently being applied. If \'Disabled\', the rule is not currently being applied.
', ], ], 'ExpiredObjectDeleteMarker' => [ 'base' => NULL, 'refs' => [ 'LifecycleExpiration$ExpiredObjectDeleteMarker' => 'Indicates whether Amazon S3 will remove a delete marker with no noncurrent versions. If set to true, the delete marker will be expired. If set to false, the policy takes no action. This cannot be specified with Days or Date in a Lifecycle Expiration Policy.
', ], ], 'Format' => [ 'base' => NULL, 'refs' => [ 'S3BucketDestination$Format' => '', ], ], 'FunctionArnString' => [ 'base' => NULL, 'refs' => [ 'AwsLambdaTransformation$FunctionArn' => 'The Amazon Resource Name (ARN) of the Lambda function.
', 'LambdaInvokeOperation$FunctionArn' => 'The Amazon Resource Name (ARN) for the Lambda function that the specified job will invoke on every object in the manifest.
', ], ], 'GeneratedManifestEncryption' => [ 'base' => 'The encryption configuration to use when storing the generated manifest.
', 'refs' => [ 'S3ManifestOutputLocation$ManifestEncryption' => 'Specifies what encryption should be used when the generated manifest objects are written.
', ], ], 'GeneratedManifestFormat' => [ 'base' => NULL, 'refs' => [ 'S3GeneratedManifestDescriptor$Format' => 'The format of the generated manifest.
', 'S3ManifestOutputLocation$ManifestFormat' => 'The format of the generated manifest.
', ], ], 'GetAccessPointConfigurationForObjectLambdaRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetAccessPointConfigurationForObjectLambdaResult' => [ 'base' => NULL, 'refs' => [], ], 'GetAccessPointForObjectLambdaRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetAccessPointForObjectLambdaResult' => [ 'base' => NULL, 'refs' => [], ], 'GetAccessPointPolicyForObjectLambdaRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetAccessPointPolicyForObjectLambdaResult' => [ 'base' => NULL, 'refs' => [], ], 'GetAccessPointPolicyRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetAccessPointPolicyResult' => [ 'base' => NULL, 'refs' => [], ], 'GetAccessPointPolicyStatusForObjectLambdaRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetAccessPointPolicyStatusForObjectLambdaResult' => [ 'base' => NULL, 'refs' => [], ], 'GetAccessPointPolicyStatusRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetAccessPointPolicyStatusResult' => [ 'base' => NULL, 'refs' => [], ], 'GetAccessPointRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetAccessPointResult' => [ 'base' => NULL, 'refs' => [], ], 'GetBucketLifecycleConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetBucketLifecycleConfigurationResult' => [ 'base' => NULL, 'refs' => [], ], 'GetBucketPolicyRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetBucketPolicyResult' => [ 'base' => NULL, 'refs' => [], ], 'GetBucketReplicationRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetBucketReplicationResult' => [ 'base' => NULL, 'refs' => [], ], 'GetBucketRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetBucketResult' => [ 'base' => NULL, 'refs' => [], ], 'GetBucketTaggingRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetBucketTaggingResult' => [ 'base' => NULL, 'refs' => [], ], 'GetBucketVersioningRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetBucketVersioningResult' => [ 'base' => NULL, 'refs' => [], ], 'GetJobTaggingRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetJobTaggingResult' => [ 'base' => NULL, 'refs' => [], ], 'GetMultiRegionAccessPointPolicyRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetMultiRegionAccessPointPolicyResult' => [ 'base' => NULL, 'refs' => [], ], 'GetMultiRegionAccessPointPolicyStatusRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetMultiRegionAccessPointPolicyStatusResult' => [ 'base' => NULL, 'refs' => [], ], 'GetMultiRegionAccessPointRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetMultiRegionAccessPointResult' => [ 'base' => NULL, 'refs' => [], ], 'GetMultiRegionAccessPointRoutesRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetMultiRegionAccessPointRoutesResult' => [ 'base' => NULL, 'refs' => [], ], 'GetPublicAccessBlockOutput' => [ 'base' => NULL, 'refs' => [], ], 'GetPublicAccessBlockRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetStorageLensConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetStorageLensConfigurationResult' => [ 'base' => NULL, 'refs' => [], ], 'GetStorageLensConfigurationTaggingRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetStorageLensConfigurationTaggingResult' => [ 'base' => NULL, 'refs' => [], ], 'GetStorageLensGroupRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetStorageLensGroupResult' => [ 'base' => NULL, 'refs' => [], ], 'GrantFullControl' => [ 'base' => NULL, 'refs' => [ 'CreateBucketRequest$GrantFullControl' => 'Allows grantee the read, write, read ACP, and write ACP permissions on the bucket.
This is not supported by Amazon S3 on Outposts buckets.
Allows grantee to list the objects in the bucket.
This is not supported by Amazon S3 on Outposts buckets.
Allows grantee to read the bucket ACL.
This is not supported by Amazon S3 on Outposts buckets.
Allows grantee to create, overwrite, and delete any object in the bucket.
This is not supported by Amazon S3 on Outposts buckets.
Allows grantee to write the ACL for the applicable bucket.
This is not supported by Amazon S3 on Outposts buckets.
The Amazon Resource Name (ARN) for the Identity and Access Management (IAM) role that Batch Operations will use to run this job\'s action on every object in the manifest.
', 'JobDescriptor$RoleArn' => 'The Amazon Resource Name (ARN) for the Identity and Access Management (IAM) role assigned to run the tasks for this job.
', ], ], 'ID' => [ 'base' => NULL, 'refs' => [ 'LifecycleRule$ID' => 'Unique identifier for the rule. The value cannot be longer than 255 characters.
', 'ReplicationRule$ID' => 'A unique identifier for the rule. The maximum value is 255 characters.
', ], ], 'IdempotencyException' => [ 'base' => '', 'refs' => [], ], 'Include' => [ 'base' => 'A container for what Amazon S3 Storage Lens configuration includes.
', 'refs' => [ 'StorageLensConfiguration$Include' => 'A container for what is included in this configuration. This container can only be valid if there is no Exclude container submitted, and it\'s not empty.
A container that indicates whether activity metrics are enabled.
', 'AdvancedCostOptimizationMetrics$IsEnabled' => 'A container that indicates whether advanced cost-optimization metrics are enabled.
', 'AdvancedDataProtectionMetrics$IsEnabled' => 'A container that indicates whether advanced data-protection metrics are enabled.
', 'CloudWatchMetrics$IsEnabled' => 'A container that indicates whether CloudWatch publishing for S3 Storage Lens metrics is enabled. A value of true indicates that CloudWatch publishing for S3 Storage Lens metrics is enabled.
A container that indicates whether detailed status code metrics are enabled.
', 'ListStorageLensConfigurationEntry$IsEnabled' => 'A container for whether the S3 Storage Lens configuration is enabled. This property is required.
', 'PrefixLevelStorageMetrics$IsEnabled' => 'A container for whether prefix-level storage metrics are enabled.
', 'StorageLensConfiguration$IsEnabled' => 'A container for whether the S3 Storage Lens configuration is enabled.
', ], ], 'IsPublic' => [ 'base' => NULL, 'refs' => [ 'PolicyStatus$IsPublic' => '', ], ], 'JobArn' => [ 'base' => NULL, 'refs' => [ 'JobDescriptor$JobArn' => 'The Amazon Resource Name (ARN) for this job.
', ], ], 'JobCreationTime' => [ 'base' => NULL, 'refs' => [ 'JobDescriptor$CreationTime' => 'A timestamp indicating when this job was created.
', 'JobListDescriptor$CreationTime' => 'A timestamp indicating when the specified job was created.
', ], ], 'JobDescriptor' => [ 'base' => 'A container element for the job configuration and status information returned by a Describe Job request.
Contains the configuration parameters and status for the job specified in the Describe Job request.
If this job failed, this element indicates why the job failed.
', 'refs' => [ 'JobFailureList$member' => NULL, ], ], 'JobFailureCode' => [ 'base' => NULL, 'refs' => [ 'JobFailure$FailureCode' => 'The failure code, if any, for the specified job.
', ], ], 'JobFailureList' => [ 'base' => NULL, 'refs' => [ 'JobDescriptor$FailureReasons' => 'If the specified job failed, this field contains information describing the failure.
', ], ], 'JobFailureReason' => [ 'base' => NULL, 'refs' => [ 'JobFailure$FailureReason' => 'The failure reason, if any, for the specified job.
', ], ], 'JobId' => [ 'base' => NULL, 'refs' => [ 'CreateJobResult$JobId' => 'The ID for this job. Amazon S3 generates this ID automatically and returns it after a successful Create Job request.
The ID for the S3 Batch Operations job whose tags you want to delete.
', 'DescribeJobRequest$JobId' => 'The ID for the job whose information you want to retrieve.
', 'GetJobTaggingRequest$JobId' => 'The ID for the S3 Batch Operations job whose tags you want to retrieve.
', 'JobDescriptor$JobId' => 'The ID for the specified job.
', 'JobListDescriptor$JobId' => 'The ID for the specified job.
', 'PutJobTaggingRequest$JobId' => 'The ID for the S3 Batch Operations job whose tags you want to replace.
', 'UpdateJobPriorityRequest$JobId' => 'The ID for the job whose priority you want to update.
', 'UpdateJobPriorityResult$JobId' => 'The ID for the job whose priority Amazon S3 updated.
', 'UpdateJobStatusRequest$JobId' => 'The ID of the job whose status you want to update.
', 'UpdateJobStatusResult$JobId' => 'The ID for the job whose status was updated.
', ], ], 'JobListDescriptor' => [ 'base' => 'Contains the configuration and status information for a single job retrieved as part of a job list.
', 'refs' => [ 'JobListDescriptorList$member' => NULL, ], ], 'JobListDescriptorList' => [ 'base' => NULL, 'refs' => [ 'ListJobsResult$Jobs' => 'The list of current jobs and jobs that have ended within the last 30 days.
', ], ], 'JobManifest' => [ 'base' => 'Contains the configuration information for a job\'s manifest.
', 'refs' => [ 'CreateJobRequest$Manifest' => 'Configuration parameters for the manifest.
', 'JobDescriptor$Manifest' => 'The configuration information for the specified job\'s manifest object.
', ], ], 'JobManifestFieldList' => [ 'base' => NULL, 'refs' => [ 'JobManifestSpec$Fields' => 'If the specified manifest object is in the S3BatchOperations_CSV_20180820 format, this element describes which columns contain the required data.
Indicates which of the available formats the specified manifest uses.
', ], ], 'JobManifestGenerator' => [ 'base' => 'Configures the type of the job\'s ManifestGenerator.
', 'refs' => [ 'CreateJobRequest$ManifestGenerator' => 'The attribute container for the ManifestGenerator details. Jobs must be created with either a manifest file or a ManifestGenerator, but not both.
', 'JobDescriptor$ManifestGenerator' => 'The manifest generator that was used to generate a job manifest for this job.
', ], ], 'JobManifestGeneratorFilter' => [ 'base' => 'The filter used to describe a set of objects for the job\'s manifest.
', 'refs' => [ 'S3JobManifestGenerator$Filter' => 'Specifies rules the S3JobManifestGenerator should use to use to decide whether an object in the source bucket should or should not be included in the generated job manifest.
', ], ], 'JobManifestLocation' => [ 'base' => 'Contains the information required to locate a manifest object.
', 'refs' => [ 'JobManifest$Location' => 'Contains the information required to locate the specified job\'s manifest.
', 'S3GeneratedManifestDescriptor$Location' => NULL, ], ], 'JobManifestSpec' => [ 'base' => 'Describes the format of a manifest. If the manifest is in CSV format, also describes the columns contained within the manifest.
', 'refs' => [ 'JobManifest$Spec' => 'Describes the format of the specified job\'s manifest. If the manifest is in CSV format, also describes the columns contained within the manifest.
', ], ], 'JobNumberOfTasksFailed' => [ 'base' => NULL, 'refs' => [ 'JobProgressSummary$NumberOfTasksFailed' => '', ], ], 'JobNumberOfTasksSucceeded' => [ 'base' => NULL, 'refs' => [ 'JobProgressSummary$NumberOfTasksSucceeded' => '', ], ], 'JobOperation' => [ 'base' => 'The operation that you want this job to perform on every object listed in the manifest. For more information about the available operations, see Operations in the Amazon S3 User Guide.
', 'refs' => [ 'CreateJobRequest$Operation' => 'The action that you want this job to perform on every object listed in the manifest. For more information about the available actions, see Operations in the Amazon S3 User Guide.
', 'JobDescriptor$Operation' => 'The operation that the specified job is configured to run on the objects listed in the manifest.
', ], ], 'JobPriority' => [ 'base' => NULL, 'refs' => [ 'CreateJobRequest$Priority' => 'The numerical priority for this job. Higher numbers indicate higher priority.
', 'JobDescriptor$Priority' => 'The priority of the specified job.
', 'JobListDescriptor$Priority' => 'The current priority for the specified job.
', 'UpdateJobPriorityRequest$Priority' => 'The priority you want to assign to this job.
', 'UpdateJobPriorityResult$Priority' => 'The new priority assigned to the specified job.
', ], ], 'JobProgressSummary' => [ 'base' => 'Describes the total number of tasks that the specified job has started, the number of tasks that succeeded, and the number of tasks that failed.
', 'refs' => [ 'JobDescriptor$ProgressSummary' => 'Describes the total number of tasks that the specified job has run, the number of tasks that succeeded, and the number of tasks that failed.
', 'JobListDescriptor$ProgressSummary' => 'Describes the total number of tasks that the specified job has run, the number of tasks that succeeded, and the number of tasks that failed.
', ], ], 'JobReport' => [ 'base' => 'Contains the configuration parameters for a job-completion report.
', 'refs' => [ 'CreateJobRequest$Report' => 'Configuration parameters for the optional job-completion report.
', 'JobDescriptor$Report' => 'Contains the configuration information for the job-completion report if you requested one in the Create Job request.
The format of the specified job-completion report.
', ], ], 'JobReportScope' => [ 'base' => NULL, 'refs' => [ 'JobReport$ReportScope' => 'Indicates whether the job-completion report will include details of all tasks or only failed tasks.
', ], ], 'JobStatus' => [ 'base' => NULL, 'refs' => [ 'JobDescriptor$Status' => 'The current status of the specified job.
', 'JobListDescriptor$Status' => 'The specified job\'s current status.
', 'JobStatusList$member' => NULL, 'UpdateJobStatusResult$Status' => 'The current status for the specified job.
', ], ], 'JobStatusException' => [ 'base' => '', 'refs' => [], ], 'JobStatusList' => [ 'base' => NULL, 'refs' => [ 'ListJobsRequest$JobStatuses' => 'The List Jobs request returns jobs that match the statuses listed in this element.
The reason for updating the job.
', 'UpdateJobStatusRequest$StatusUpdateReason' => 'A description of the reason why you want to change the specified job\'s status. This field can be any string up to the maximum length.
', 'UpdateJobStatusResult$StatusUpdateReason' => 'The reason that the specified job\'s status was updated.
', ], ], 'JobTerminationDate' => [ 'base' => NULL, 'refs' => [ 'JobDescriptor$TerminationDate' => 'A timestamp indicating when this job terminated. A job\'s termination date is the date and time when it succeeded, failed, or was canceled.
', 'JobListDescriptor$TerminationDate' => 'A timestamp indicating when the specified job terminated. A job\'s termination date is the date and time when it succeeded, failed, or was canceled.
', ], ], 'JobTimeInStateSeconds' => [ 'base' => NULL, 'refs' => [ 'JobTimers$ElapsedTimeInActiveSeconds' => 'Indicates the elapsed time in seconds the job has been in the Active job state.
', ], ], 'JobTimers' => [ 'base' => 'Provides timing details for the job.
', 'refs' => [ 'JobProgressSummary$Timers' => 'The JobTimers attribute of a job\'s progress summary.
', ], ], 'JobTotalNumberOfTasks' => [ 'base' => NULL, 'refs' => [ 'JobProgressSummary$TotalNumberOfTasks' => '', ], ], 'KeyNameConstraint' => [ 'base' => 'If provided, the generated manifest includes only source bucket objects whose object keys match the string constraints specified for MatchAnyPrefix, MatchAnySuffix, and MatchAnySubstring.
If provided, the generated manifest includes only source bucket objects whose object keys match the string constraints specified for MatchAnyPrefix, MatchAnySuffix, and MatchAnySubstring.
Specifies the ID of the Amazon Web Services Key Management Service (Amazon Web Services KMS) symmetric encryption customer managed key to use for encrypting generated manifest objects.
', ], ], 'LambdaInvokeOperation' => [ 'base' => 'Contains the configuration parameters for a Lambda Invoke operation.
Directs the specified job to invoke an Lambda function on every object in the manifest.
', ], ], 'LifecycleConfiguration' => [ 'base' => 'The container for the Outposts bucket lifecycle configuration.
', 'refs' => [ 'PutBucketLifecycleConfigurationRequest$LifecycleConfiguration' => 'Container for lifecycle rules. You can add as many as 1,000 rules.
', ], ], 'LifecycleExpiration' => [ 'base' => 'The container of the Outposts bucket lifecycle expiration.
', 'refs' => [ 'LifecycleRule$Expiration' => 'Specifies the expiration for the lifecycle of the object in the form of date, days and, whether the object has a delete marker.
', ], ], 'LifecycleRule' => [ 'base' => 'The container for the Outposts bucket lifecycle rule.
', 'refs' => [ 'LifecycleRules$member' => NULL, ], ], 'LifecycleRuleAndOperator' => [ 'base' => 'The container for the Outposts bucket lifecycle rule and operator.
', 'refs' => [ 'LifecycleRuleFilter$And' => 'The container for the AND condition for the lifecycle rule.
The container for the filter of the lifecycle rule.
', 'refs' => [ 'LifecycleRule$Filter' => 'The container for the filter of lifecycle rule.
', ], ], 'LifecycleRules' => [ 'base' => NULL, 'refs' => [ 'GetBucketLifecycleConfigurationResult$Rules' => 'Container for the lifecycle rule of the Outposts bucket.
', 'LifecycleConfiguration$Rules' => 'A lifecycle rule for individual objects in an Outposts bucket.
', ], ], 'ListAccessPointsForObjectLambdaRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListAccessPointsForObjectLambdaResult' => [ 'base' => NULL, 'refs' => [], ], 'ListAccessPointsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListAccessPointsResult' => [ 'base' => NULL, 'refs' => [], ], 'ListJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListJobsResult' => [ 'base' => NULL, 'refs' => [], ], 'ListMultiRegionAccessPointsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListMultiRegionAccessPointsResult' => [ 'base' => NULL, 'refs' => [], ], 'ListRegionalBucketsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListRegionalBucketsResult' => [ 'base' => NULL, 'refs' => [], ], 'ListStorageLensConfigurationEntry' => [ 'base' => 'Part of ListStorageLensConfigurationResult. Each entry includes the description of the S3 Storage Lens configuration, its home Region, whether it is enabled, its Amazon Resource Name (ARN), and config ID.
Each entry contains a Storage Lens group that exists in the specified home Region.
', 'refs' => [ 'StorageLensGroupList$member' => NULL, ], ], 'ListStorageLensGroupsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListStorageLensGroupsResult' => [ 'base' => NULL, 'refs' => [], ], 'ListTagsForResourceRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListTagsForResourceResult' => [ 'base' => NULL, 'refs' => [], ], 'Location' => [ 'base' => NULL, 'refs' => [ 'CreateBucketResult$Location' => 'The location of the bucket.
', ], ], 'MFA' => [ 'base' => NULL, 'refs' => [ 'PutBucketVersioningRequest$MFA' => 'The concatenation of the authentication device\'s serial number, a space, and the value that is displayed on your authentication device.
', ], ], 'MFADelete' => [ 'base' => NULL, 'refs' => [ 'VersioningConfiguration$MFADelete' => 'Specifies whether MFA delete is enabled or disabled in the bucket versioning configuration for the S3 on Outposts bucket.
', ], ], 'MFADeleteStatus' => [ 'base' => NULL, 'refs' => [ 'GetBucketVersioningResult$MFADelete' => 'Specifies whether MFA delete is enabled in the bucket versioning configuration. This element is returned only if the bucket has been configured with MFA delete. If MFA delete has never been configured for the bucket, this element is not returned.
', ], ], 'ManifestPrefixString' => [ 'base' => NULL, 'refs' => [ 'S3ManifestOutputLocation$ManifestPrefix' => 'Prefix identifying one or more objects to which the manifest applies.
', ], ], 'MatchAnyPrefix' => [ 'base' => NULL, 'refs' => [ 'StorageLensGroupAndOperator$MatchAnyPrefix' => 'Contains a list of prefixes. At least one prefix must be specified. Up to 10 prefixes are allowed.
', 'StorageLensGroupFilter$MatchAnyPrefix' => 'Contains a list of prefixes. At least one prefix must be specified. Up to 10 prefixes are allowed.
', 'StorageLensGroupOrOperator$MatchAnyPrefix' => 'Filters objects that match any of the specified prefixes.
', ], ], 'MatchAnySuffix' => [ 'base' => NULL, 'refs' => [ 'StorageLensGroupAndOperator$MatchAnySuffix' => 'Contains a list of suffixes. At least one suffix must be specified. Up to 10 suffixes are allowed.
', 'StorageLensGroupFilter$MatchAnySuffix' => 'Contains a list of suffixes. At least one suffix must be specified. Up to 10 suffixes are allowed.
', 'StorageLensGroupOrOperator$MatchAnySuffix' => 'Filters objects that match any of the specified suffixes.
', ], ], 'MatchAnyTag' => [ 'base' => NULL, 'refs' => [ 'StorageLensGroupAndOperator$MatchAnyTag' => 'Contains the list of object tags. At least one object tag must be specified. Up to 10 object tags are allowed.
', 'StorageLensGroupFilter$MatchAnyTag' => 'Contains the list of S3 object tags. At least one object tag must be specified. Up to 10 object tags are allowed.
', 'StorageLensGroupOrOperator$MatchAnyTag' => 'Filters objects that match any of the specified S3 object tags.
', ], ], 'MatchObjectAge' => [ 'base' => 'A filter condition that specifies the object age range of included objects in days. Only integers are supported.
', 'refs' => [ 'StorageLensGroupAndOperator$MatchObjectAge' => ' Contains DaysGreaterThan and DaysLessThan to define the object age range (minimum and maximum number of days).
Contains DaysGreaterThan and DaysLessThan to define the object age range (minimum and maximum number of days).
Filters objects that match the specified object age range.
', ], ], 'MatchObjectSize' => [ 'base' => 'A filter condition that specifies the object size range of included objects in bytes. Only integers are supported.
', 'refs' => [ 'StorageLensGroupAndOperator$MatchObjectSize' => ' Contains BytesGreaterThan and BytesLessThan to define the object size range (minimum and maximum number of Bytes).
Contains BytesGreaterThan and BytesLessThan to define the object size range (minimum and maximum number of Bytes).
Filters objects that match the specified object size range.
', ], ], 'MaxLength1024String' => [ 'base' => NULL, 'refs' => [ 'AsyncErrorDetails$Code' => 'A string that uniquely identifies the error condition.
', 'AsyncErrorDetails$Message' => 'A generic description of the error condition in English.
', 'AsyncErrorDetails$Resource' => 'The identifier of the resource associated with the error.
', 'AsyncErrorDetails$RequestId' => 'The ID of the request associated with the error.
', 'S3UserMetadata$value' => NULL, ], ], 'MaxResults' => [ 'base' => NULL, 'refs' => [ 'ListAccessPointsForObjectLambdaRequest$MaxResults' => 'The maximum number of access points that you want to include in the list. The response may contain fewer access points but will never contain more. If there are more than this number of access points, then the response will include a continuation token in the NextToken field that you can use to retrieve the next page of access points.
The maximum number of access points that you want to include in the list. If the specified bucket has more than this number of access points, then the response will include a continuation token in the NextToken field that you can use to retrieve the next page of access points.
The maximum number of jobs that Amazon S3 will include in the List Jobs response. If there are more jobs than this number, the response will include a pagination token in the NextToken field to enable you to retrieve the next page of results.
Not currently used. Do not use this parameter.
', 'ListRegionalBucketsRequest$MaxResults' => '', ], ], 'Metrics' => [ 'base' => 'A container that specifies replication metrics-related settings.
', 'refs' => [ 'Destination$Metrics' => 'A container that specifies replication metrics-related settings.
', ], ], 'MetricsStatus' => [ 'base' => NULL, 'refs' => [ 'Metrics$Status' => 'Specifies whether replication metrics are enabled.
', ], ], 'MinStorageBytesPercentage' => [ 'base' => NULL, 'refs' => [ 'SelectionCriteria$MinStorageBytesPercentage' => 'The minimum number of storage bytes percentage whose metrics will be selected.
You must choose a value greater than or equal to 1.0.
Contains an integer that specifies the time period in minutes.
Valid value: 15
', ], ], 'MultiRegionAccessPointAlias' => [ 'base' => NULL, 'refs' => [ 'MultiRegionAccessPointReport$Alias' => 'The alias for the Multi-Region Access Point. For more information about the distinction between the name and the alias of an Multi-Region Access Point, see Managing Multi-Region Access Points.
', ], ], 'MultiRegionAccessPointClientToken' => [ 'base' => NULL, 'refs' => [ 'CreateMultiRegionAccessPointRequest$ClientToken' => 'An idempotency token used to identify the request and guarantee that requests are unique.
', 'DeleteMultiRegionAccessPointRequest$ClientToken' => 'An idempotency token used to identify the request and guarantee that requests are unique.
', 'PutMultiRegionAccessPointPolicyRequest$ClientToken' => 'An idempotency token used to identify the request and guarantee that requests are unique.
', ], ], 'MultiRegionAccessPointId' => [ 'base' => NULL, 'refs' => [ 'GetMultiRegionAccessPointRoutesRequest$Mrap' => 'The Multi-Region Access Point ARN.
', 'GetMultiRegionAccessPointRoutesResult$Mrap' => 'The Multi-Region Access Point ARN.
', 'SubmitMultiRegionAccessPointRoutesRequest$Mrap' => 'The Multi-Region Access Point ARN.
', ], ], 'MultiRegionAccessPointName' => [ 'base' => NULL, 'refs' => [ 'CreateMultiRegionAccessPointInput$Name' => 'The name of the Multi-Region Access Point associated with this request.
', 'DeleteMultiRegionAccessPointInput$Name' => 'The name of the Multi-Region Access Point associated with this request.
', 'GetMultiRegionAccessPointPolicyRequest$Name' => 'Specifies the Multi-Region Access Point. The name of the Multi-Region Access Point is different from the alias. For more information about the distinction between the name and the alias of an Multi-Region Access Point, see Managing Multi-Region Access Points in the Amazon S3 User Guide.
', 'GetMultiRegionAccessPointPolicyStatusRequest$Name' => 'Specifies the Multi-Region Access Point. The name of the Multi-Region Access Point is different from the alias. For more information about the distinction between the name and the alias of an Multi-Region Access Point, see Managing Multi-Region Access Points in the Amazon S3 User Guide.
', 'GetMultiRegionAccessPointRequest$Name' => 'The name of the Multi-Region Access Point whose configuration information you want to receive. The name of the Multi-Region Access Point is different from the alias. For more information about the distinction between the name and the alias of an Multi-Region Access Point, see Managing Multi-Region Access Points in the Amazon S3 User Guide.
', 'MultiRegionAccessPointReport$Name' => 'The name of the Multi-Region Access Point.
', 'PutMultiRegionAccessPointPolicyInput$Name' => 'The name of the Multi-Region Access Point associated with the request.
', ], ], 'MultiRegionAccessPointPolicyDocument' => [ 'base' => 'The Multi-Region Access Point access control policy.
When you update the policy, the update is first listed as the proposed policy. After the update is finished and all Regions have been updated, the proposed policy is listed as the established policy. If both policies have the same version number, the proposed policy is the established policy.
', 'refs' => [ 'GetMultiRegionAccessPointPolicyResult$Policy' => 'The policy associated with the specified Multi-Region Access Point.
', ], ], 'MultiRegionAccessPointRegionalResponse' => [ 'base' => 'Status information for a single Multi-Region Access Point Region.
', 'refs' => [ 'MultiRegionAccessPointRegionalResponseList$member' => NULL, ], ], 'MultiRegionAccessPointRegionalResponseList' => [ 'base' => NULL, 'refs' => [ 'MultiRegionAccessPointsAsyncResponse$Regions' => 'A collection of status information for the different Regions that a Multi-Region Access Point supports.
', ], ], 'MultiRegionAccessPointReport' => [ 'base' => 'A collection of statuses for a Multi-Region Access Point in the various Regions it supports.
', 'refs' => [ 'GetMultiRegionAccessPointResult$AccessPoint' => 'A container element containing the details of the requested Multi-Region Access Point.
', 'MultiRegionAccessPointReportList$member' => NULL, ], ], 'MultiRegionAccessPointReportList' => [ 'base' => NULL, 'refs' => [ 'ListMultiRegionAccessPointsResult$AccessPoints' => 'The list of Multi-Region Access Points associated with the user.
', ], ], 'MultiRegionAccessPointRoute' => [ 'base' => 'A structure for a Multi-Region Access Point that indicates where Amazon S3 traffic can be routed. Routes can be either active or passive. Active routes can process Amazon S3 requests through the Multi-Region Access Point, but passive routes are not eligible to process Amazon S3 requests.
Each route contains the Amazon S3 bucket name and the Amazon Web Services Region that the bucket is located in. The route also includes the TrafficDialPercentage value, which shows whether the bucket and Region are active (indicated by a value of 100) or passive (indicated by a value of 0).
The current status of the Multi-Region Access Point.
CREATING and DELETING are temporary states that exist while the request is propagating and being completed. If a Multi-Region Access Point has a status of PARTIALLY_CREATED, you can retry creation or send a request to delete the Multi-Region Access Point. If a Multi-Region Access Point has a status of PARTIALLY_DELETED, you can retry a delete request to finish the deletion of the Multi-Region Access Point.
The Multi-Region Access Point details that are returned when querying about an asynchronous request.
', 'refs' => [ 'AsyncResponseDetails$MultiRegionAccessPointDetails' => 'The details for the Multi-Region Access Point.
', ], ], 'NetworkOrigin' => [ 'base' => NULL, 'refs' => [ 'AccessPoint$NetworkOrigin' => 'Indicates whether this access point allows access from the public internet. If VpcConfiguration is specified for this access point, then NetworkOrigin is VPC, and the access point doesn\'t allow access from the public internet. Otherwise, NetworkOrigin is Internet, and the access point allows access from the public internet, subject to the access point and bucket access policies.
Indicates whether this access point allows access from the public internet. If VpcConfiguration is specified for this access point, then NetworkOrigin is VPC, and the access point doesn\'t allow access from the public internet. Otherwise, NetworkOrigin is Internet, and the access point allows access from the public internet, subject to the access point and bucket access policies.
This will always be true for an Amazon S3 on Outposts access point
', ], ], 'NoSuchPublicAccessBlockConfiguration' => [ 'base' => 'Amazon S3 throws this exception if you make a GetPublicAccessBlock request against an account that doesn\'t have a PublicAccessBlockConfiguration set.
The ETag for the specified manifest object.
', 'ListAccessPointsForObjectLambdaRequest$NextToken' => 'If the list has more access points than can be returned in one call to this API, this field contains a continuation token that you can provide in subsequent calls to this API to retrieve additional access points.
', 'ListAccessPointsForObjectLambdaResult$NextToken' => 'If the list has more access points than can be returned in one call to this API, this field contains a continuation token that you can provide in subsequent calls to this API to retrieve additional access points.
', 'ListAccessPointsRequest$NextToken' => 'A continuation token. If a previous call to ListAccessPoints returned a continuation token in the NextToken field, then providing that value here causes Amazon S3 to retrieve the next page of results.
If the specified bucket has more access points than can be returned in one call to this API, this field contains a continuation token that you can provide in subsequent calls to this API to retrieve additional access points.
', 'ListMultiRegionAccessPointsRequest$NextToken' => 'Not currently used. Do not use this parameter.
', 'ListMultiRegionAccessPointsResult$NextToken' => 'If the specified bucket has more Multi-Region Access Points than can be returned in one call to this action, this field contains a continuation token. You can use this token tin subsequent calls to this action to retrieve additional Multi-Region Access Points.
', 'ListRegionalBucketsRequest$NextToken' => '', 'ListRegionalBucketsResult$NextToken' => ' NextToken is sent when isTruncated is true, which means there are more buckets that can be listed. The next list requests to Amazon S3 can be continued with this NextToken. NextToken is obfuscated and is not a real key.
Specifies the folder prefix that you want the objects to be copied into. For example, to copy objects into a folder named Folder1 in the destination bucket, set the TargetKeyPrefix property to Folder1.
If provided, the generated manifest includes objects where the specified string appears at the start of the object key string.
', 'KeyNameConstraint$MatchAnySuffix' => 'If provided, the generated manifest includes objects where the specified string appears at the end of the object key string.
', 'KeyNameConstraint$MatchAnySubstring' => 'If provided, the generated manifest includes objects where the specified string appears anywhere within the object key string.
', ], ], 'NonEmptyMaxLength2048String' => [ 'base' => NULL, 'refs' => [ 'S3CopyObjectOperation$RedirectLocation' => 'Specifies an optional metadata property for website redirects, x-amz-website-redirect-location. Allows webpage redirects if the object is accessed through a website endpoint.
A description for this job. You can use any string within the permitted length. Descriptions don\'t need to be unique and can be used for multiple jobs.
', 'JobDescriptor$Description' => 'The description for this job, if one was provided in this job\'s Create Job request.
The user-specified description that was included in the specified job\'s Create Job request.
The ID of the Outposts where the bucket is being created.
This ID is required by Amazon S3 on Outposts buckets.
An idempotency token to ensure that you don\'t accidentally submit the same request twice. You can use any string up to the maximum length.
', 'Endpoints$key' => NULL, 'ListRegionalBucketsRequest$OutpostId' => 'The ID of the Outposts resource.
This ID is required by Amazon S3 on Outposts buckets.
The Outposts ID of the regional bucket.
', ], ], 'NoncurrentVersionCount' => [ 'base' => NULL, 'refs' => [ 'NoncurrentVersionExpiration$NewerNoncurrentVersions' => 'Specifies how many noncurrent versions S3 on Outposts will retain. If there are this many more recent noncurrent versions, S3 on Outposts will take the associated action. For more information about noncurrent versions, see Lifecycle configuration elements in the Amazon S3 User Guide.
', ], ], 'NoncurrentVersionExpiration' => [ 'base' => 'The container of the noncurrent version expiration.
', 'refs' => [ 'LifecycleRule$NoncurrentVersionExpiration' => 'The noncurrent version expiration of the lifecycle rule.
', ], ], 'NoncurrentVersionTransition' => [ 'base' => 'The container for the noncurrent version transition.
', 'refs' => [ 'NoncurrentVersionTransitionList$member' => NULL, ], ], 'NoncurrentVersionTransitionList' => [ 'base' => NULL, 'refs' => [ 'LifecycleRule$NoncurrentVersionTransitions' => 'Specifies the transition rule for the lifecycle rule that describes when noncurrent objects transition to a specific storage class. If your bucket is versioning-enabled (or versioning is suspended), you can set this action to request that Amazon S3 transition noncurrent object versions to a specific storage class at a set period in the object\'s lifetime.
This is not supported by Amazon S3 on Outposts buckets.
Specifies the maximum object age in days. Must be a positive whole number, greater than the minimum object age and less than or equal to 2,147,483,647.
', 'MatchObjectAge$DaysLessThan' => 'Specifies the minimum object age in days. The value must be a positive whole number, greater than 0 and less than or equal to 2,147,483,647.
', ], ], 'ObjectCreationTime' => [ 'base' => NULL, 'refs' => [ 'JobManifestGeneratorFilter$CreatedAfter' => 'If provided, the generated manifest includes only source bucket objects that were created after this time.
', 'JobManifestGeneratorFilter$CreatedBefore' => 'If provided, the generated manifest includes only source bucket objects that were created before this time.
', ], ], 'ObjectLambdaAccessPoint' => [ 'base' => 'An access point with an attached Lambda function used to access transformed data from an Amazon S3 bucket.
', 'refs' => [ 'ObjectLambdaAccessPointList$member' => NULL, ], ], 'ObjectLambdaAccessPointAlias' => [ 'base' => 'The alias of an Object Lambda Access Point. For more information, see How to use a bucket-style alias for your S3 bucket Object Lambda Access Point.
', 'refs' => [ 'CreateAccessPointForObjectLambdaResult$Alias' => 'The alias of the Object Lambda Access Point.
', 'GetAccessPointForObjectLambdaResult$Alias' => 'The alias of the Object Lambda Access Point.
', 'ObjectLambdaAccessPoint$Alias' => 'The alias of the Object Lambda Access Point.
', ], ], 'ObjectLambdaAccessPointAliasStatus' => [ 'base' => NULL, 'refs' => [ 'ObjectLambdaAccessPointAlias$Status' => 'The status of the Object Lambda Access Point alias. If the status is PROVISIONING, the Object Lambda Access Point is provisioning the alias and the alias is not ready for use yet. If the status is READY, the Object Lambda Access Point alias is successfully provisioned and ready for use.
The alias value of the Object Lambda Access Point.
', ], ], 'ObjectLambdaAccessPointArn' => [ 'base' => NULL, 'refs' => [ 'CreateAccessPointForObjectLambdaResult$ObjectLambdaAccessPointArn' => 'Specifies the ARN for the Object Lambda Access Point.
', 'ObjectLambdaAccessPoint$ObjectLambdaAccessPointArn' => 'Specifies the ARN for the Object Lambda Access Point.
', ], ], 'ObjectLambdaAccessPointList' => [ 'base' => NULL, 'refs' => [ 'ListAccessPointsForObjectLambdaResult$ObjectLambdaAccessPointList' => 'Returns list of Object Lambda Access Points.
', ], ], 'ObjectLambdaAccessPointName' => [ 'base' => NULL, 'refs' => [ 'CreateAccessPointForObjectLambdaRequest$Name' => 'The name you want to assign to this Object Lambda Access Point.
', 'DeleteAccessPointForObjectLambdaRequest$Name' => 'The name of the access point you want to delete.
', 'DeleteAccessPointPolicyForObjectLambdaRequest$Name' => 'The name of the Object Lambda Access Point you want to delete the policy for.
', 'GetAccessPointConfigurationForObjectLambdaRequest$Name' => 'The name of the Object Lambda Access Point you want to return the configuration for.
', 'GetAccessPointForObjectLambdaRequest$Name' => 'The name of the Object Lambda Access Point.
', 'GetAccessPointForObjectLambdaResult$Name' => 'The name of the Object Lambda Access Point.
', 'GetAccessPointPolicyForObjectLambdaRequest$Name' => 'The name of the Object Lambda Access Point.
', 'GetAccessPointPolicyStatusForObjectLambdaRequest$Name' => 'The name of the Object Lambda Access Point.
', 'ObjectLambdaAccessPoint$Name' => 'The name of the Object Lambda Access Point.
', 'PutAccessPointConfigurationForObjectLambdaRequest$Name' => 'The name of the Object Lambda Access Point.
', 'PutAccessPointPolicyForObjectLambdaRequest$Name' => 'The name of the Object Lambda Access Point.
', ], ], 'ObjectLambdaAllowedFeature' => [ 'base' => NULL, 'refs' => [ 'ObjectLambdaAllowedFeaturesList$member' => NULL, ], ], 'ObjectLambdaAllowedFeaturesList' => [ 'base' => NULL, 'refs' => [ 'ObjectLambdaConfiguration$AllowedFeatures' => 'A container for allowed features. Valid inputs are GetObject-Range, GetObject-PartNumber, HeadObject-Range, and HeadObject-PartNumber.
A configuration used when creating an Object Lambda Access Point.
', 'refs' => [ 'CreateAccessPointForObjectLambdaRequest$Configuration' => 'Object Lambda Access Point configuration as a JSON document.
', 'GetAccessPointConfigurationForObjectLambdaResult$Configuration' => 'Object Lambda Access Point configuration document.
', 'PutAccessPointConfigurationForObjectLambdaRequest$Configuration' => 'Object Lambda Access Point configuration document.
', ], ], 'ObjectLambdaContentTransformation' => [ 'base' => 'A container for AwsLambdaTransformation.
', 'refs' => [ 'ObjectLambdaTransformationConfiguration$ContentTransformation' => 'A container for the content transformation of an Object Lambda Access Point configuration.
', ], ], 'ObjectLambdaPolicy' => [ 'base' => NULL, 'refs' => [ 'GetAccessPointPolicyForObjectLambdaResult$Policy' => 'Object Lambda Access Point resource policy document.
', 'PutAccessPointPolicyForObjectLambdaRequest$Policy' => 'Object Lambda Access Point resource policy document.
', ], ], 'ObjectLambdaSupportingAccessPointArn' => [ 'base' => NULL, 'refs' => [ 'ObjectLambdaConfiguration$SupportingAccessPoint' => 'Standard access point associated with the Object Lambda Access Point.
', ], ], 'ObjectLambdaTransformationConfiguration' => [ 'base' => 'A configuration used when creating an Object Lambda Access Point transformation.
', 'refs' => [ 'ObjectLambdaTransformationConfigurationsList$member' => NULL, ], ], 'ObjectLambdaTransformationConfigurationAction' => [ 'base' => NULL, 'refs' => [ 'ObjectLambdaTransformationConfigurationActionsList$member' => NULL, ], ], 'ObjectLambdaTransformationConfigurationActionsList' => [ 'base' => NULL, 'refs' => [ 'ObjectLambdaTransformationConfiguration$Actions' => 'A container for the action of an Object Lambda Access Point configuration. Valid inputs are GetObject, ListObjects, HeadObject, and ListObjectsV2.
A container for transformation configurations for an Object Lambda Access Point.
', ], ], 'ObjectLockEnabledForBucket' => [ 'base' => NULL, 'refs' => [ 'CreateBucketRequest$ObjectLockEnabledForBucket' => 'Specifies whether you want S3 Object Lock to be enabled for the new bucket.
This is not supported by Amazon S3 on Outposts buckets.
If provided, the generated manifest includes only source bucket objects whose file size is greater than the specified number of bytes.
', 'LifecycleRuleAndOperator$ObjectSizeGreaterThan' => 'Minimum object size to which the rule applies.
', 'LifecycleRuleFilter$ObjectSizeGreaterThan' => 'Minimum object size to which the rule applies.
', ], ], 'ObjectSizeLessThanBytes' => [ 'base' => NULL, 'refs' => [ 'JobManifestGeneratorFilter$ObjectSizeLessThanBytes' => 'If provided, the generated manifest includes only source bucket objects whose file size is less than the specified number of bytes.
', 'LifecycleRuleAndOperator$ObjectSizeLessThan' => 'Maximum object size to which the rule applies.
', 'LifecycleRuleFilter$ObjectSizeLessThan' => 'Maximum object size to which the rule applies.
', ], ], 'ObjectSizeValue' => [ 'base' => NULL, 'refs' => [ 'MatchObjectSize$BytesGreaterThan' => 'Specifies the minimum object size in Bytes. The value must be a positive number, greater than 0 and less than 5 TB.
', 'MatchObjectSize$BytesLessThan' => 'Specifies the maximum object size in Bytes. The value must be a positive number, greater than the minimum object size and less than 5 TB.
', ], ], 'OperationName' => [ 'base' => NULL, 'refs' => [ 'JobListDescriptor$Operation' => 'The operation that the specified job is configured to run on every object listed in the manifest.
', ], ], 'OutputSchemaVersion' => [ 'base' => NULL, 'refs' => [ 'S3BucketDestination$OutputSchemaVersion' => 'The schema version of the export file.
', ], ], 'OwnerOverride' => [ 'base' => NULL, 'refs' => [ 'AccessControlTranslation$Owner' => 'Specifies the replica ownership.
', ], ], 'Policy' => [ 'base' => NULL, 'refs' => [ 'EstablishedMultiRegionAccessPointPolicy$Policy' => 'The details of the last established policy.
', 'GetAccessPointPolicyResult$Policy' => 'The access point policy associated with the specified access point.
', 'GetBucketPolicyResult$Policy' => 'The policy of the Outposts bucket.
', 'ProposedMultiRegionAccessPointPolicy$Policy' => 'The details of the proposed policy.
', 'PutAccessPointPolicyRequest$Policy' => 'The policy that you want to apply to the specified access point. For more information about access point policies, see Managing data access with Amazon S3 access points in the Amazon S3 User Guide.
', 'PutBucketPolicyRequest$Policy' => 'The bucket policy as a JSON document.
', 'PutMultiRegionAccessPointPolicyInput$Policy' => 'The policy details for the PutMultiRegionAccessPoint request.
Indicates whether this access point policy is public. For more information about how Amazon S3 evaluates policies to determine whether they are public, see The Meaning of "Public" in the Amazon S3 User Guide.
', 'refs' => [ 'GetAccessPointPolicyStatusForObjectLambdaResult$PolicyStatus' => NULL, 'GetAccessPointPolicyStatusResult$PolicyStatus' => 'Indicates the current policy status of the specified access point.
', 'GetMultiRegionAccessPointPolicyStatusResult$Established' => NULL, ], ], 'Prefix' => [ 'base' => NULL, 'refs' => [ 'LifecycleRuleAndOperator$Prefix' => 'Prefix identifying one or more objects to which the rule applies.
', 'LifecycleRuleFilter$Prefix' => 'Prefix identifying one or more objects to which the rule applies.
When you\'re using XML requests, you must replace special characters (such as carriage returns) in object keys with their equivalent XML entity codes. For more information, see XML-related object key constraints in the Amazon S3 User Guide.
An object key name prefix that identifies the object or objects to which the rule applies. The maximum prefix length is 1,024 characters. To include all objects in an Outposts bucket, specify an empty string.
When you\'re using XML requests, you must replace special characters (such as carriage returns) in object keys with their equivalent XML entity codes. For more information, see XML-related object key constraints in the Amazon S3 User Guide.
An object key name prefix that identifies the subset of objects that the rule applies to.
', 'ReplicationRuleFilter$Prefix' => 'An object key name prefix that identifies the subset of objects that the rule applies to.
When you\'re using XML requests, you must replace special characters (such as carriage returns) in object keys with their equivalent XML entity codes. For more information, see XML-related object key constraints in the Amazon S3 User Guide.
The prefix of the destination bucket where the metrics export will be delivered.
', ], ], 'PrefixLevel' => [ 'base' => 'A container for the prefix-level configuration.
', 'refs' => [ 'BucketLevel$PrefixLevel' => 'A container for the prefix-level metrics for S3 Storage Lens.
', ], ], 'PrefixLevelStorageMetrics' => [ 'base' => 'A container for the prefix-level storage metrics for S3 Storage Lens.
', 'refs' => [ 'PrefixLevel$StorageMetrics' => 'A container for the prefix-level storage metrics for S3 Storage Lens.
', ], ], 'Priority' => [ 'base' => NULL, 'refs' => [ 'ReplicationRule$Priority' => 'The priority indicates which rule has precedence whenever two or more replication rules conflict. S3 on Outposts attempts to replicate objects according to all replication rules. However, if there are two or more rules with the same destination Outposts bucket, then objects will be replicated according to the rule with the highest priority. The higher the number, the higher the priority.
For more information, see Creating replication rules on Outposts in the Amazon S3 User Guide.
', ], ], 'ProposedMultiRegionAccessPointPolicy' => [ 'base' => 'The proposed access control policy for the Multi-Region Access Point.
When you update the policy, the update is first listed as the proposed policy. After the update is finished and all Regions have been updated, the proposed policy is listed as the established policy. If both policies have the same version number, the proposed policy is the established policy.
', 'refs' => [ 'MultiRegionAccessPointPolicyDocument$Proposed' => 'The proposed policy for the Multi-Region Access Point.
', ], ], 'PublicAccessBlockConfiguration' => [ 'base' => 'The PublicAccessBlock configuration that you want to apply to this Amazon S3 account. You can enable the configuration options in any combination. For more information about when Amazon S3 considers a bucket or object public, see The Meaning of "Public" in the Amazon S3 User Guide.
This data type is not supported for Amazon S3 on Outposts.
', 'refs' => [ 'CreateAccessPointRequest$PublicAccessBlockConfiguration' => ' The PublicAccessBlock configuration that you want to apply to the access point.
Configuration to block all public access. This setting is turned on and can not be edited.
', 'GetAccessPointResult$PublicAccessBlockConfiguration' => NULL, 'GetPublicAccessBlockOutput$PublicAccessBlockConfiguration' => 'The PublicAccessBlock configuration currently in effect for this Amazon Web Services account.
The PublicAccessBlock configuration that you want to apply to the specified Amazon Web Services account.
A container for the information associated with a PutMultiRegionAccessPoint request.
', 'refs' => [ 'AsyncRequestParameters$PutMultiRegionAccessPointPolicyRequest' => 'A container of the parameters for a PutMultiRegionAccessPoint request.
', 'PutMultiRegionAccessPointPolicyRequest$Details' => 'A container element containing the details of the policy for the Multi-Region Access Point.
', ], ], 'PutMultiRegionAccessPointPolicyRequest' => [ 'base' => NULL, 'refs' => [], ], 'PutMultiRegionAccessPointPolicyResult' => [ 'base' => NULL, 'refs' => [], ], 'PutPublicAccessBlockRequest' => [ 'base' => NULL, 'refs' => [], ], 'PutStorageLensConfigurationRequest' => [ 'base' => NULL, 'refs' => [], ], 'PutStorageLensConfigurationTaggingRequest' => [ 'base' => NULL, 'refs' => [], ], 'PutStorageLensConfigurationTaggingResult' => [ 'base' => NULL, 'refs' => [], ], 'Region' => [ 'base' => 'A Region that supports a Multi-Region Access Point as well as the associated bucket for the Region.
', 'refs' => [ 'RegionCreationList$member' => NULL, ], ], 'RegionCreationList' => [ 'base' => NULL, 'refs' => [ 'CreateMultiRegionAccessPointInput$Regions' => 'The buckets in different Regions that are associated with the Multi-Region Access Point.
', ], ], 'RegionName' => [ 'base' => NULL, 'refs' => [ 'MultiRegionAccessPointRegionalResponse$Name' => 'The name of the Region in the Multi-Region Access Point.
', 'MultiRegionAccessPointRoute$Region' => 'The Amazon Web Services Region to which you\'ll be submitting a routing configuration change. Either the Bucket or the Region value must be provided. If both are provided, the bucket must be in the specified Region.
The name of the Region.
', ], ], 'RegionReport' => [ 'base' => 'A combination of a bucket and Region that\'s part of a Multi-Region Access Point.
', 'refs' => [ 'RegionReportList$member' => NULL, ], ], 'RegionReportList' => [ 'base' => NULL, 'refs' => [ 'MultiRegionAccessPointReport$Regions' => 'A collection of the Regions and buckets associated with the Multi-Region Access Point.
', ], ], 'RegionalBucket' => [ 'base' => 'The container for the regional bucket.
', 'refs' => [ 'RegionalBucketList$member' => NULL, ], ], 'RegionalBucketList' => [ 'base' => NULL, 'refs' => [ 'ListRegionalBucketsResult$RegionalBucketList' => '', ], ], 'Regions' => [ 'base' => NULL, 'refs' => [ 'Exclude$Regions' => 'A container for the S3 Storage Lens Region excludes.
', 'Include$Regions' => 'A container for the S3 Storage Lens Region includes.
', ], ], 'ReplicaKmsKeyID' => [ 'base' => NULL, 'refs' => [ 'EncryptionConfiguration$ReplicaKmsKeyID' => 'Specifies the ID of the customer managed KMS key that\'s stored in Key Management Service (KMS) for the destination bucket. This ID is either the Amazon Resource Name (ARN) for the KMS key or the alias ARN for the KMS key. Amazon S3 uses this KMS key to encrypt replica objects. Amazon S3 supports only symmetric encryption KMS keys. For more information, see Symmetric encryption KMS keys in the Amazon Web Services Key Management Service Developer Guide.
', ], ], 'ReplicaModifications' => [ 'base' => 'A filter that you can use to specify whether replica modification sync is enabled. S3 on Outposts replica modification sync can help you keep object metadata synchronized between replicas and source objects. By default, S3 on Outposts replicates metadata from the source objects to the replicas only. When replica modification sync is enabled, S3 on Outposts replicates metadata changes made to the replica copies back to the source object, making the replication bidirectional.
To replicate object metadata modifications on replicas, you can specify this element and set the Status of this element to Enabled.
You must enable replica modification sync on the source and destination buckets to replicate replica metadata changes between the source and the replicas.
A filter that you can use to specify whether replica modification sync is enabled. S3 on Outposts replica modification sync can help you keep object metadata synchronized between replicas and source objects. By default, S3 on Outposts replicates metadata from the source objects to the replicas only. When replica modification sync is enabled, S3 on Outposts replicates metadata changes made to the replica copies back to the source object, making the replication bidirectional.
To replicate object metadata modifications on replicas, you can specify this element and set the Status of this element to Enabled.
You must enable replica modification sync on the source and destination buckets to replicate replica metadata changes between the source and the replicas.
Specifies whether S3 on Outposts replicates modifications to object metadata on replicas.
', ], ], 'ReplicationConfiguration' => [ 'base' => 'A container for one or more replication rules. A replication configuration must have at least one rule and you can add up to 100 rules. The maximum size of a replication configuration is 128 KB.
', 'refs' => [ 'GetBucketReplicationResult$ReplicationConfiguration' => 'A container for one or more replication rules. A replication configuration must have at least one rule and you can add up to 100 rules. The maximum size of a replication configuration is 128 KB.
', 'PutBucketReplicationRequest$ReplicationConfiguration' => '', ], ], 'ReplicationRule' => [ 'base' => 'Specifies which S3 on Outposts objects to replicate and where to store the replicas.
', 'refs' => [ 'ReplicationRules$member' => NULL, ], ], 'ReplicationRuleAndOperator' => [ 'base' => 'A container for specifying rule filters. The filters determine the subset of objects to which the rule applies. This element is required only if you specify more than one filter.
For example:
If you specify both a Prefix and a Tag filter, wrap these filters in an And element.
If you specify a filter based on multiple tags, wrap the Tag elements in an And element.
A container for specifying rule filters. The filters determine the subset of objects that the rule applies to. This element is required only if you specify more than one filter. For example:
If you specify both a Prefix and a Tag filter, wrap these filters in an And element.
If you specify a filter based on multiple tags, wrap the Tag elements in an And element.
A filter that identifies the subset of objects to which the replication rule applies. A Filter element must specify exactly one Prefix, Tag, or And child element.
A filter that identifies the subset of objects to which the replication rule applies. A Filter element must specify exactly one Prefix, Tag, or And child element.
Specifies whether the rule is enabled.
', ], ], 'ReplicationRules' => [ 'base' => NULL, 'refs' => [ 'ReplicationConfiguration$Rules' => 'A container for one or more replication rules. A replication configuration must have at least one rule and can contain an array of 100 rules at the most.
', ], ], 'ReplicationStatus' => [ 'base' => NULL, 'refs' => [ 'ReplicationStatusFilterList$member' => NULL, ], ], 'ReplicationStatusFilterList' => [ 'base' => NULL, 'refs' => [ 'JobManifestGeneratorFilter$ObjectReplicationStatuses' => 'If provided, the generated manifest includes only source bucket objects that have one of the specified Replication statuses.
', ], ], 'ReplicationStorageClass' => [ 'base' => NULL, 'refs' => [ 'Destination$StorageClass' => ' The storage class to use when replicating objects. All objects stored on S3 on Outposts are stored in the OUTPOSTS storage class. S3 on Outposts uses the OUTPOSTS storage class to create the object replicas.
Values other than OUTPOSTS are not supported by Amazon S3 on Outposts.
A container that specifies S3 Replication Time Control (S3 RTC) related information, including whether S3 RTC is enabled and the time when all objects and operations on objects must be replicated.
This is not supported by Amazon S3 on Outposts buckets.
A container that specifies S3 Replication Time Control (S3 RTC) settings, including whether S3 RTC is enabled and the time when all objects and operations on objects must be replicated. Must be specified together with a Metrics block.
This is not supported by Amazon S3 on Outposts buckets.
Specifies whether S3 Replication Time Control (S3 RTC) is enabled.
', ], ], 'ReplicationTimeValue' => [ 'base' => 'A container that specifies the time value for S3 Replication Time Control (S3 RTC). This value is also used for the replication metrics EventThreshold element.
This is not supported by Amazon S3 on Outposts buckets.
A container that specifies the time threshold for emitting the s3:Replication:OperationMissedThreshold event.
This is not supported by Amazon S3 on Outposts buckets.
A container that specifies the time by which replication should be complete for all objects and operations on objects.
', ], ], 'ReportPrefixString' => [ 'base' => NULL, 'refs' => [ 'JobReport$Prefix' => 'An optional prefix to describe where in the specified bucket the job-completion report will be stored. Amazon S3 stores the job-completion report at <prefix>/job-<job-id>/report.json.
The status that you want to move the specified job to.
', ], ], 'Role' => [ 'base' => NULL, 'refs' => [ 'ReplicationConfiguration$Role' => 'The Amazon Resource Name (ARN) of the Identity and Access Management (IAM) role that S3 on Outposts assumes when replicating objects. For information about S3 replication on Outposts configuration, see Setting up replication in the Amazon S3 User Guide.
', ], ], 'RouteList' => [ 'base' => NULL, 'refs' => [ 'GetMultiRegionAccessPointRoutesResult$Routes' => 'The different routes that make up the route configuration. Active routes return a value of 100, and passive routes return a value of 0.
The different routes that make up the new route configuration. Active routes return a value of 100, and passive routes return a value of 0.
A container for the S3 Storage Lens home Region. Your metrics data is stored and retained in your designated S3 Storage Lens home Region.
', 'ListStorageLensGroupEntry$HomeRegion' => 'Contains the Amazon Web Services Region where the Storage Lens group was created.
', 'Regions$member' => NULL, ], ], 'S3AccessControlList' => [ 'base' => '', 'refs' => [ 'S3AccessControlPolicy$AccessControlList' => '', ], ], 'S3AccessControlPolicy' => [ 'base' => '', 'refs' => [ 'S3SetObjectAclOperation$AccessControlPolicy' => '', ], ], 'S3AccessPointArn' => [ 'base' => NULL, 'refs' => [ 'AccessPoint$AccessPointArn' => 'The ARN for the access point.
', 'CreateAccessPointResult$AccessPointArn' => 'The ARN of the access point.
This is only supported by Amazon S3 on Outposts.
The ARN of the access point.
', ], ], 'S3BucketArnString' => [ 'base' => NULL, 'refs' => [ 'Buckets$member' => NULL, 'JobReport$Bucket' => 'The Amazon Resource Name (ARN) for the bucket where specified job-completion report will be stored.
', 'S3BucketDestination$Arn' => 'The Amazon Resource Name (ARN) of the bucket. This property is read-only and follows the following format: arn:aws:s3:us-east-1:example-account-id:bucket/your-destination-bucket-name
Specifies the destination bucket Amazon Resource Name (ARN) for the batch copy operation. For example, to copy objects to a bucket named destinationBucket, set the TargetResource property to arn:aws:s3:::destinationBucket.
The source bucket used by the ManifestGenerator.
', 'S3ManifestOutputLocation$Bucket' => 'The bucket ARN the generated manifest should be written to.
', ], ], 'S3BucketDestination' => [ 'base' => 'A container for the bucket where the Amazon S3 Storage Lens metrics export files are located.
', 'refs' => [ 'StorageLensDataExport$S3BucketDestination' => 'A container for the bucket where the S3 Storage Lens metrics export will be located.
This bucket must be located in the same Region as the storage lens configuration.
Indicates the algorithm that you want Amazon S3 to use to create the checksum. For more information, see Checking object integrity in the Amazon S3 User Guide.
', ], ], 'S3ContentLength' => [ 'base' => NULL, 'refs' => [ 'S3ObjectMetadata$ContentLength' => '', ], ], 'S3CopyObjectOperation' => [ 'base' => 'Contains the configuration parameters for a PUT Copy object operation. S3 Batch Operations passes every object to the underlying CopyObject API operation. For more information about the parameters for this operation, see CopyObject.
Directs the specified job to run a PUT Copy object call on every object in the manifest.
', ], ], 'S3DeleteObjectTaggingOperation' => [ 'base' => 'Contains no configuration parameters because the DELETE Object tagging (DeleteObjectTagging) API operation accepts only the bucket name and key name as parameters, which are defined in the job\'s manifest.
Directs the specified job to execute a DELETE Object tagging call on every object in the manifest.
', ], ], 'S3ExpirationInDays' => [ 'base' => NULL, 'refs' => [ 'S3InitiateRestoreObjectOperation$ExpirationInDays' => 'This argument specifies how long the S3 Glacier or S3 Glacier Deep Archive object remains available in Amazon S3. S3 Initiate Restore Object jobs that target S3 Glacier and S3 Glacier Deep Archive objects require ExpirationInDays set to 1 or greater.
Conversely, do not set ExpirationInDays when creating S3 Initiate Restore Object jobs that target S3 Intelligent-Tiering Archive Access and Deep Archive Access tier objects. Objects in S3 Intelligent-Tiering archive access tiers are not subject to restore expiry, so specifying ExpirationInDays results in restore request failure.
S3 Batch Operations jobs can operate either on S3 Glacier and S3 Glacier Deep Archive storage class objects or on S3 Intelligent-Tiering Archive Access and Deep Archive Access storage tier objects, but not both types in the same job. If you need to restore objects of both types you must create separate Batch Operations jobs.
', ], ], 'S3GeneratedManifestDescriptor' => [ 'base' => 'Describes the specified job\'s generated manifest. Batch Operations jobs created with a ManifestGenerator populate details of this descriptor after execution of the ManifestGenerator.
', 'refs' => [ 'JobDescriptor$GeneratedManifestDescriptor' => 'The attribute of the JobDescriptor containing details about the job\'s generated manifest.
', ], ], 'S3GlacierJobTier' => [ 'base' => NULL, 'refs' => [ 'S3InitiateRestoreObjectOperation$GlacierJobTier' => 'S3 Batch Operations supports STANDARD and BULK retrieval tiers, but not the EXPEDITED retrieval tier.
Contains the configuration parameters for a POST Object restore job. S3 Batch Operations passes every object to the underlying RestoreObject API operation. For more information about the parameters for this operation, see RestoreObject.
Directs the specified job to initiate restore requests for every archived object in the manifest.
', ], ], 'S3JobManifestGenerator' => [ 'base' => 'The container for the service that will create the S3 manifest.
', 'refs' => [ 'JobManifestGenerator$S3JobManifestGenerator' => 'The S3 job ManifestGenerator\'s configuration details.
', ], ], 'S3KeyArnString' => [ 'base' => NULL, 'refs' => [ 'JobManifestLocation$ObjectArn' => 'The Amazon Resource Name (ARN) for a manifest object.
When you\'re using XML requests, you must replace special characters (such as carriage returns) in object keys with their equivalent XML entity codes. For more information, see XML-related object key constraints in the Amazon S3 User Guide.
Location details for where the generated manifest should be written.
', 'refs' => [ 'S3JobManifestGenerator$ManifestOutputLocation' => 'Specifies the location the generated manifest will be written to.
', ], ], 'S3MetadataDirective' => [ 'base' => NULL, 'refs' => [ 'S3CopyObjectOperation$MetadataDirective' => '', ], ], 'S3ObjectLockLegalHold' => [ 'base' => 'Whether S3 Object Lock legal hold will be applied to objects in an S3 Batch Operations job.
', 'refs' => [ 'S3SetObjectLegalHoldOperation$LegalHold' => 'Contains the Object Lock legal hold status to be applied to all objects in the Batch Operations job.
', ], ], 'S3ObjectLockLegalHoldStatus' => [ 'base' => NULL, 'refs' => [ 'S3CopyObjectOperation$ObjectLockLegalHoldStatus' => 'The legal hold status to be applied to all objects in the Batch Operations job.
', 'S3ObjectLockLegalHold$Status' => 'The Object Lock legal hold status to be applied to all objects in the Batch Operations job.
', ], ], 'S3ObjectLockMode' => [ 'base' => NULL, 'refs' => [ 'S3CopyObjectOperation$ObjectLockMode' => 'The retention mode to be applied to all objects in the Batch Operations job.
', ], ], 'S3ObjectLockRetentionMode' => [ 'base' => NULL, 'refs' => [ 'S3Retention$Mode' => 'The Object Lock retention mode to be applied to all objects in the Batch Operations job.
', ], ], 'S3ObjectMetadata' => [ 'base' => '', 'refs' => [ 'S3CopyObjectOperation$NewObjectMetadata' => 'If you don\'t provide this parameter, Amazon S3 copies all the metadata from the original objects. If you specify an empty set, the new objects will have no tags. Otherwise, Amazon S3 assigns the supplied tags to the new objects.
', ], ], 'S3ObjectOwner' => [ 'base' => '', 'refs' => [ 'S3AccessControlList$Owner' => '', ], ], 'S3ObjectVersionId' => [ 'base' => NULL, 'refs' => [ 'JobManifestLocation$ObjectVersionId' => 'The optional version ID to identify a specific version of the manifest object.
', ], ], 'S3Permission' => [ 'base' => NULL, 'refs' => [ 'S3Grant$Permission' => '', ], ], 'S3RegionalBucketArn' => [ 'base' => NULL, 'refs' => [ 'CreateBucketResult$BucketArn' => 'The Amazon Resource Name (ARN) of the bucket.
For using this parameter with Amazon S3 on Outposts with the REST API, you must specify the name and the x-amz-outpost-id as well.
For using this parameter with S3 on Outposts with the Amazon Web Services SDK and CLI, you must specify the ARN of the bucket accessed in the format arn:aws:s3-outposts:<Region>:<account-id>:outpost/<outpost-id>/bucket/<my-bucket-name>. For example, to access the bucket reports through Outpost my-outpost owned by account 123456789012 in Region us-west-2, use the URL encoding of arn:aws:s3-outposts:us-west-2:123456789012:outpost/my-outpost/bucket/reports. The value must be URL encoded.
The Amazon Resource Name (ARN) for the regional bucket.
', ], ], 'S3ReplicateObjectOperation' => [ 'base' => 'Directs the specified job to invoke ReplicateObject on every object in the job\'s manifest.
Directs the specified job to invoke ReplicateObject on every object in the job\'s manifest.
The Amazon Resource Name (ARN) of the S3 resource that you want to list the tags for.
', 'TagResourceRequest$ResourceArn' => 'The Amazon Resource Name (ARN) of the S3 resource that you\'re trying to add tags to.
', 'UntagResourceRequest$ResourceArn' => 'The Amazon Resource Name (ARN) of the S3 resource that you want to remove the resource tags from.
', ], ], 'S3Retention' => [ 'base' => 'Contains the S3 Object Lock retention mode to be applied to all objects in the S3 Batch Operations job. If you don\'t provide Mode and RetainUntilDate data types in your operation, you will remove the retention from your objects. For more information, see Using S3 Object Lock retention with S3 Batch Operations in the Amazon S3 User Guide.
Contains the Object Lock retention mode to be applied to all objects in the Batch Operations job. For more information, see Using S3 Object Lock retention with S3 Batch Operations in the Amazon S3 User Guide.
', ], ], 'S3SSEAlgorithm' => [ 'base' => NULL, 'refs' => [ 'S3ObjectMetadata$SSEAlgorithm' => '', ], ], 'S3SetObjectAclOperation' => [ 'base' => 'Contains the configuration parameters for a PUT Object ACL operation. S3 Batch Operations passes every object to the underlying PutObjectAcl API operation. For more information about the parameters for this operation, see PutObjectAcl.
Directs the specified job to run a PutObjectAcl call on every object in the manifest.
Contains the configuration for an S3 Object Lock legal hold operation that an S3 Batch Operations job passes to every object to the underlying PutObjectLegalHold API operation. For more information, see Using S3 Object Lock legal hold with S3 Batch Operations in the Amazon S3 User Guide.
Contains the configuration parameters for the Object Lock retention action for an S3 Batch Operations job. Batch Operations passes every object to the underlying PutObjectRetention API operation. For more information, see Using S3 Object Lock retention with S3 Batch Operations in the Amazon S3 User Guide.
Contains the configuration parameters for a PUT Object Tagging operation. S3 Batch Operations passes every object to the underlying PutObjectTagging API operation. For more information about the parameters for this operation, see PutObjectTagging.
Directs the specified job to run a PUT Object tagging call on every object in the manifest.
', ], ], 'S3StorageClass' => [ 'base' => NULL, 'refs' => [ 'S3CopyObjectOperation$StorageClass' => '', 'StorageClassList$member' => NULL, ], ], 'S3Tag' => [ 'base' => 'A container for a key-value name pair.
', 'refs' => [ 'LifecycleRuleFilter$Tag' => NULL, 'MatchAnyTag$member' => NULL, 'ReplicationRuleFilter$Tag' => NULL, 'S3TagSet$member' => NULL, ], ], 'S3TagSet' => [ 'base' => NULL, 'refs' => [ 'CreateJobRequest$Tags' => 'A set of tags to associate with the S3 Batch Operations job. This is an optional parameter.
', 'GetBucketTaggingResult$TagSet' => 'The tags set of the Outposts bucket.
', 'GetJobTaggingResult$Tags' => 'The set of tags associated with the S3 Batch Operations job.
', 'LifecycleRuleAndOperator$Tags' => 'All of these tags must exist in the object\'s tag set in order for the rule to apply.
', 'PutJobTaggingRequest$Tags' => 'The set of tags to associate with the S3 Batch Operations job.
', 'ReplicationRuleAndOperator$Tags' => 'An array of tags that contain key and value pairs.
', 'S3CopyObjectOperation$NewObjectTagging' => '', 'S3SetObjectTaggingOperation$TagSet' => '', 'Tagging$TagSet' => 'A collection for a set of tags.
', ], ], 'S3UserMetadata' => [ 'base' => NULL, 'refs' => [ 'S3ObjectMetadata$UserMetadata' => '', ], ], 'SSEKMS' => [ 'base' => '', 'refs' => [ 'StorageLensDataExportEncryption$SSEKMS' => '', ], ], 'SSEKMSEncryption' => [ 'base' => 'Configuration for the use of SSE-KMS to encrypt generated manifest objects.
', 'refs' => [ 'GeneratedManifestEncryption$SSEKMS' => 'Configuration details on how SSE-KMS is used to encrypt generated manifest objects.
', ], ], 'SSEKMSKeyId' => [ 'base' => NULL, 'refs' => [ 'SSEKMS$KeyId' => 'A container for the ARN of the SSE-KMS encryption. This property is read-only and follows the following format: arn:aws:kms:us-east-1:example-account-id:key/example-9a73-4afc-8d29-8f5900cef44e
Configuration for the use of SSE-S3 to encrypt generated manifest objects.
', 'refs' => [ 'GeneratedManifestEncryption$SSES3' => 'Specifies the use of SSE-S3 to encrypt generated manifest objects.
', ], ], 'SelectionCriteria' => [ 'base' => '', 'refs' => [ 'PrefixLevelStorageMetrics$SelectionCriteria' => NULL, ], ], 'Setting' => [ 'base' => NULL, 'refs' => [ 'PublicAccessBlockConfiguration$BlockPublicAcls' => 'Specifies whether Amazon S3 should block public access control lists (ACLs) for buckets in this account. Setting this element to TRUE causes the following behavior:
PutBucketAcl and PutObjectAcl calls fail if the specified ACL is public.
PUT Object calls fail if the request includes a public ACL.
PUT Bucket calls fail if the request includes a public ACL.
Enabling this setting doesn\'t affect existing policies or ACLs.
This property is not supported for Amazon S3 on Outposts.
', 'PublicAccessBlockConfiguration$IgnorePublicAcls' => 'Specifies whether Amazon S3 should ignore public ACLs for buckets in this account. Setting this element to TRUE causes Amazon S3 to ignore all public ACLs on buckets in this account and any objects that they contain.
Enabling this setting doesn\'t affect the persistence of any existing ACLs and doesn\'t prevent new public ACLs from being set.
This property is not supported for Amazon S3 on Outposts.
', 'PublicAccessBlockConfiguration$BlockPublicPolicy' => 'Specifies whether Amazon S3 should block public bucket policies for buckets in this account. Setting this element to TRUE causes Amazon S3 to reject calls to PUT Bucket policy if the specified bucket policy allows public access.
Enabling this setting doesn\'t affect existing bucket policies.
This property is not supported for Amazon S3 on Outposts.
', 'PublicAccessBlockConfiguration$RestrictPublicBuckets' => 'Specifies whether Amazon S3 should restrict public bucket policies for buckets in this account. Setting this element to TRUE restricts access to buckets with public policies to only Amazon Web Service principals and authorized users within this account.
Enabling this setting doesn\'t affect previously stored bucket policies, except that public and cross-account access within any public bucket policy, including non-public delegation to specific accounts, is blocked.
This property is not supported for Amazon S3 on Outposts.
', ], ], 'SourceSelectionCriteria' => [ 'base' => 'A container that describes additional filters for identifying the source objects that you want to replicate. You can choose to enable or disable the replication of these objects.
', 'refs' => [ 'ReplicationRule$SourceSelectionCriteria' => 'A container that describes additional filters for identifying the source Outposts objects that you want to replicate. You can choose to enable or disable the replication of these objects.
', ], ], 'SseKmsEncryptedObjects' => [ 'base' => 'A container for filter information that you can use to select S3 objects that are encrypted with Key Management Service (KMS).
This is not supported by Amazon S3 on Outposts buckets.
A filter that you can use to select Amazon S3 objects that are encrypted with server-side encryption by using Key Management Service (KMS) keys. If you include SourceSelectionCriteria in the replication configuration, this element is required.
This is not supported by Amazon S3 on Outposts buckets.
Specifies whether Amazon S3 replicates objects that are created with server-side encryption by using an KMS key stored in Key Management Service.
', ], ], 'StorageClassList' => [ 'base' => NULL, 'refs' => [ 'JobManifestGeneratorFilter$MatchAnyStorageClass' => 'If provided, the generated manifest includes only source bucket objects that are stored with the specified storage class.
', ], ], 'StorageLensArn' => [ 'base' => NULL, 'refs' => [ 'ListStorageLensConfigurationEntry$StorageLensArn' => 'The ARN of the S3 Storage Lens configuration. This property is read-only.
', 'StorageLensConfiguration$StorageLensArn' => 'The Amazon Resource Name (ARN) of the S3 Storage Lens configuration. This property is read-only and follows the following format: arn:aws:s3:us-east-1:example-account-id:storage-lens/your-dashboard-name
The Amazon Web Services organization for your S3 Storage Lens.
', 'refs' => [ 'StorageLensConfiguration$AwsOrg' => 'A container for the Amazon Web Services organization for this S3 Storage Lens configuration.
', ], ], 'StorageLensConfiguration' => [ 'base' => 'A container for the Amazon S3 Storage Lens configuration.
', 'refs' => [ 'GetStorageLensConfigurationResult$StorageLensConfiguration' => 'The S3 Storage Lens configuration requested.
', 'PutStorageLensConfigurationRequest$StorageLensConfiguration' => 'The S3 Storage Lens configuration.
', ], ], 'StorageLensConfigurationList' => [ 'base' => NULL, 'refs' => [ 'ListStorageLensConfigurationsResult$StorageLensConfigurationList' => 'A list of S3 Storage Lens configurations.
', ], ], 'StorageLensDataExport' => [ 'base' => 'A container to specify the properties of your S3 Storage Lens metrics export, including the destination, schema, and format.
', 'refs' => [ 'StorageLensConfiguration$DataExport' => 'A container to specify the properties of your S3 Storage Lens metrics export including, the destination, schema and format.
', ], ], 'StorageLensDataExportEncryption' => [ 'base' => 'A container for the encryption of the S3 Storage Lens metrics exports.
', 'refs' => [ 'S3BucketDestination$Encryption' => 'The container for the type encryption of the metrics exports in this bucket.
', ], ], 'StorageLensGroup' => [ 'base' => 'A custom grouping of objects that include filters for prefixes, suffixes, object tags, object size, or object age. You can create an S3 Storage Lens group that includes a single filter or multiple filter conditions. To specify multiple filter conditions, you use AND or OR logical operators.
The Storage Lens group configuration.
', 'GetStorageLensGroupResult$StorageLensGroup' => 'The name of the Storage Lens group that you\'re trying to retrieve the configuration details for.
', 'UpdateStorageLensGroupRequest$StorageLensGroup' => 'The JSON file that contains the Storage Lens group configuration.
', ], ], 'StorageLensGroupAndOperator' => [ 'base' => 'A logical operator that allows multiple filter conditions to be joined for more complex comparisons of Storage Lens group data.
', 'refs' => [ 'StorageLensGroupFilter$And' => 'A logical operator that allows multiple filter conditions to be joined for more complex comparisons of Storage Lens group data. Objects must match all of the listed filter conditions that are joined by the And logical operator. Only one of each filter condition is allowed.
Contains the Amazon Resource Name (ARN) of the Storage Lens group. This property is read-only.
', 'StorageLensGroup$StorageLensGroupArn' => 'Contains the Amazon Resource Name (ARN) of the Storage Lens group. This property is read-only.
', 'StorageLensGroupLevelExclude$member' => NULL, 'StorageLensGroupLevelInclude$member' => NULL, ], ], 'StorageLensGroupFilter' => [ 'base' => 'The filter element sets the criteria for the Storage Lens group data that is displayed. For multiple filter conditions, the AND or OR logical operator is used.
Sets the criteria for the Storage Lens group data that is displayed. For multiple filter conditions, the AND or OR logical operator is used.
Specifies the Storage Lens groups to include in the Storage Lens group aggregation.
', 'refs' => [ 'AccountLevel$StorageLensGroupLevel' => 'A container element for S3 Storage Lens groups metrics.
', ], ], 'StorageLensGroupLevelExclude' => [ 'base' => NULL, 'refs' => [ 'StorageLensGroupLevelSelectionCriteria$Exclude' => 'Indicates which Storage Lens group ARNs to exclude from the Storage Lens group aggregation.
', ], ], 'StorageLensGroupLevelInclude' => [ 'base' => NULL, 'refs' => [ 'StorageLensGroupLevelSelectionCriteria$Include' => 'Indicates which Storage Lens group ARNs to include in the Storage Lens group aggregation.
', ], ], 'StorageLensGroupLevelSelectionCriteria' => [ 'base' => 'Indicates which Storage Lens group ARNs to include or exclude in the Storage Lens group aggregation. You can only attach Storage Lens groups to your Storage Lens dashboard if they\'re included in your Storage Lens group aggregation. If this value is left null, then all Storage Lens groups are selected.
', 'refs' => [ 'StorageLensGroupLevel$SelectionCriteria' => 'Indicates which Storage Lens group ARNs to include or exclude in the Storage Lens group aggregation. If this value is left null, then all Storage Lens groups are selected.
', ], ], 'StorageLensGroupList' => [ 'base' => NULL, 'refs' => [ 'ListStorageLensGroupsResult$StorageLensGroupList' => 'The list of Storage Lens groups that exist in the specified home Region.
', ], ], 'StorageLensGroupName' => [ 'base' => NULL, 'refs' => [ 'DeleteStorageLensGroupRequest$Name' => 'The name of the Storage Lens group that you\'re trying to delete.
', 'GetStorageLensGroupRequest$Name' => 'The name of the Storage Lens group that you\'re trying to retrieve the configuration details for.
', 'ListStorageLensGroupEntry$Name' => 'Contains the name of the Storage Lens group that exists in the specified home Region.
', 'StorageLensGroup$Name' => 'Contains the name of the Storage Lens group.
', 'UpdateStorageLensGroupRequest$Name' => 'The name of the Storage Lens group that you want to update.
', ], ], 'StorageLensGroupOrOperator' => [ 'base' => 'A container element for specifying Or rule conditions. The rule conditions determine the subset of objects to which the Or rule applies. Objects can match any of the listed filter conditions, which are joined by the Or logical operator. Only one of each filter condition is allowed.
A single logical operator that allows multiple filter conditions to be joined. Objects can match any of the listed filter conditions, which are joined by the Or logical operator. Only one of each filter condition is allowed.
A container for the delimiter of the selection criteria being used.
', ], ], 'StorageLensPrefixLevelMaxDepth' => [ 'base' => NULL, 'refs' => [ 'SelectionCriteria$MaxDepth' => 'The max depth of the selection criteria
', ], ], 'StorageLensTag' => [ 'base' => '', 'refs' => [ 'StorageLensTags$member' => NULL, ], ], 'StorageLensTags' => [ 'base' => NULL, 'refs' => [ 'GetStorageLensConfigurationTaggingResult$Tags' => 'The tags of S3 Storage Lens configuration requested.
', 'PutStorageLensConfigurationRequest$Tags' => 'The tag set of the S3 Storage Lens configuration.
You can set up to a maximum of 50 tags.
The tag set of the S3 Storage Lens configuration.
You can set up to a maximum of 50 tags.
A pagination token to request the next page of results. Use the token that Amazon S3 returned in the NextToken element of the ListJobsResult from the previous List Jobs request.
If the List Jobs request produced more than the maximum number of results, you can pass this value into a subsequent List Jobs request in order to retrieve the next page of results.
The reason why the specified job was suspended. A job is only suspended if you create it through the Amazon S3 console. When you create the job, it enters the Suspended state to await confirmation before running. After you confirm the job, it automatically exits the Suspended state.
The timestamp when this job was suspended, if it has been suspended.
', ], ], 'Tag' => [ 'base' => 'An Amazon Web Services resource tag that\'s associated with your S3 resource. You can add tags to new objects when you upload them, or you can add object tags to existing objects.
This data type is only supported for S3 Storage Lens groups.
The tag key pair of the S3 resource tag that you\'re trying to remove.
', ], ], 'TagKeyString' => [ 'base' => NULL, 'refs' => [ 'S3Tag$Key' => 'Key of the tag
', 'StorageLensTag$Key' => '', 'Tag$Key' => ' The tag key for your Amazon Web Services resource. A tag key can be up to 128 Unicode characters in length and is case-sensitive. System created tags that begin with aws: aren’t supported.
The Amazon Web Services resource tags that you\'re adding to your Storage Lens group. This parameter is optional.
', 'ListTagsForResourceResult$Tags' => 'The Amazon Web Services resource tags that are associated with the resource.
', 'TagResourceRequest$Tags' => 'The Amazon Web Services resource tags that you want to add to the specified S3 resource.
', ], ], 'TagResourceRequest' => [ 'base' => NULL, 'refs' => [], ], 'TagResourceResult' => [ 'base' => NULL, 'refs' => [], ], 'TagValueString' => [ 'base' => NULL, 'refs' => [ 'S3Tag$Value' => 'Value of the tag
', 'StorageLensTag$Value' => '', 'Tag$Value' => 'The tag value for your Amazon Web Services resource. A tag value can be up to 256 Unicode characters in length and is case-sensitive.
', ], ], 'Tagging' => [ 'base' => '', 'refs' => [ 'PutBucketTaggingRequest$Tagging' => '', ], ], 'TimeStamp' => [ 'base' => NULL, 'refs' => [ 'S3CopyObjectOperation$ModifiedSinceConstraint' => '', 'S3CopyObjectOperation$UnModifiedSinceConstraint' => '', 'S3CopyObjectOperation$ObjectLockRetainUntilDate' => 'The date when the applied object retention configuration expires on all objects in the Batch Operations job.
', 'S3ObjectMetadata$HttpExpiresDate' => '', 'S3Retention$RetainUntilDate' => 'The date when the applied Object Lock retention will expire on all objects set by the Batch Operations job.
', ], ], 'TooManyRequestsException' => [ 'base' => '', 'refs' => [], ], 'TooManyTagsException' => [ 'base' => 'Amazon S3 throws this exception if you have too many tags in your tag set.
', 'refs' => [], ], 'TrafficDialPercentage' => [ 'base' => NULL, 'refs' => [ 'MultiRegionAccessPointRoute$TrafficDialPercentage' => 'The traffic state for the specified bucket or Amazon Web Services Region.
A value of 0 indicates a passive state, which means that no new traffic will be routed to the Region.
A value of 100 indicates an active state, which means that traffic will be routed to the specified Region.
When the routing configuration for a Region is changed from active to passive, any in-progress operations (uploads, copies, deletes, and so on) to the formerly active Region will continue to run to until a final success or failure status is reached.
If all Regions in the routing configuration are designated as passive, you\'ll receive an InvalidRequest error.
Specifies when an object transitions to a specified storage class. For more information about Amazon S3 Lifecycle configuration rules, see Transitioning objects using Amazon S3 Lifecycle in the Amazon S3 User Guide.
', 'refs' => [ 'TransitionList$member' => NULL, ], ], 'TransitionList' => [ 'base' => NULL, 'refs' => [ 'LifecycleRule$Transitions' => 'Specifies when an Amazon S3 object transitions to a specified storage class.
This is not supported by Amazon S3 on Outposts buckets.
The class of storage used to store the object.
', 'Transition$StorageClass' => 'The storage class to which you want the object to transition.
', ], ], 'UntagResourceRequest' => [ 'base' => NULL, 'refs' => [], ], 'UntagResourceResult' => [ 'base' => NULL, 'refs' => [], ], 'UpdateJobPriorityRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateJobPriorityResult' => [ 'base' => NULL, 'refs' => [], ], 'UpdateJobStatusRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateJobStatusResult' => [ 'base' => NULL, 'refs' => [], ], 'UpdateStorageLensGroupRequest' => [ 'base' => NULL, 'refs' => [], ], 'VersioningConfiguration' => [ 'base' => 'Describes the versioning state of an Amazon S3 on Outposts bucket. For more information, see PutBucketVersioning.
', 'refs' => [ 'PutBucketVersioningRequest$VersioningConfiguration' => 'The root-level tag for the VersioningConfiguration parameters.
The virtual private cloud (VPC) configuration for an access point.
', 'refs' => [ 'AccessPoint$VpcConfiguration' => 'The virtual private cloud (VPC) configuration for this access point, if one exists.
This element is empty if this access point is an Amazon S3 on Outposts access point that is used by other Amazon Web Services.
If you include this field, Amazon S3 restricts access to this access point to requests from the specified virtual private cloud (VPC).
This is required for creating an access point for Amazon S3 on Outposts buckets.
Contains the virtual private cloud (VPC) configuration for the specified access point.
This element is empty if this access point is an Amazon S3 on Outposts access point that is used by other Amazon Web Services.
If this field is specified, this access point will only allow connections from the specified VPC ID.
', ], ], ],]; diff --git a/src/data/sagemaker/2017-07-24/api-2.json b/src/data/sagemaker/2017-07-24/api-2.json index e14c29b4c2..cf04d1a414 100644 --- a/src/data/sagemaker/2017-07-24/api-2.json +++ b/src/data/sagemaker/2017-07-24/api-2.json @@ -3405,6 +3405,7 @@ "max":256, "pattern":".*" }, + "AcceptEula":{"type":"boolean"}, "AccountId":{ "type":"string", "pattern":"^\\d+$" @@ -14780,6 +14781,13 @@ "DeploymentRecommendation":{"shape":"DeploymentRecommendation"} } }, + "ModelAccessConfig":{ + "type":"structure", + "required":["AcceptEula"], + "members":{ + "AcceptEula":{"shape":"AcceptEula"} + } + }, "ModelApprovalStatus":{ "type":"string", "enum":[ @@ -18584,7 +18592,8 @@ "members":{ "S3Uri":{"shape":"S3ModelUri"}, "S3DataType":{"shape":"S3ModelDataType"}, - "CompressionType":{"shape":"ModelCompressionType"} + "CompressionType":{"shape":"ModelCompressionType"}, + "ModelAccessConfig":{"shape":"ModelAccessConfig"} } }, "S3ModelDataType":{ diff --git a/src/data/sagemaker/2017-07-24/api-2.json.php b/src/data/sagemaker/2017-07-24/api-2.json.php index eb308f1736..924a30ca17 100644 --- a/src/data/sagemaker/2017-07-24/api-2.json.php +++ b/src/data/sagemaker/2017-07-24/api-2.json.php @@ -1,3 +1,3 @@ '2.0', 'metadata' => [ 'apiVersion' => '2017-07-24', 'endpointPrefix' => 'api.sagemaker', 'jsonVersion' => '1.1', 'protocol' => 'json', 'serviceAbbreviation' => 'SageMaker', 'serviceFullName' => 'Amazon SageMaker Service', 'serviceId' => 'SageMaker', 'signatureVersion' => 'v4', 'signingName' => 'sagemaker', 'targetPrefix' => 'SageMaker', 'uid' => 'sagemaker-2017-07-24', ], 'operations' => [ 'AddAssociation' => [ 'name' => 'AddAssociation', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'AddAssociationRequest', ], 'output' => [ 'shape' => 'AddAssociationResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'AddTags' => [ 'name' => 'AddTags', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'AddTagsInput', ], 'output' => [ 'shape' => 'AddTagsOutput', ], ], 'AssociateTrialComponent' => [ 'name' => 'AssociateTrialComponent', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'AssociateTrialComponentRequest', ], 'output' => [ 'shape' => 'AssociateTrialComponentResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'BatchDescribeModelPackage' => [ 'name' => 'BatchDescribeModelPackage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'BatchDescribeModelPackageInput', ], 'output' => [ 'shape' => 'BatchDescribeModelPackageOutput', ], ], 'CreateAction' => [ 'name' => 'CreateAction', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateActionRequest', ], 'output' => [ 'shape' => 'CreateActionResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateAlgorithm' => [ 'name' => 'CreateAlgorithm', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateAlgorithmInput', ], 'output' => [ 'shape' => 'CreateAlgorithmOutput', ], ], 'CreateApp' => [ 'name' => 'CreateApp', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateAppRequest', ], 'output' => [ 'shape' => 'CreateAppResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateAppImageConfig' => [ 'name' => 'CreateAppImageConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateAppImageConfigRequest', ], 'output' => [ 'shape' => 'CreateAppImageConfigResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], ], ], 'CreateArtifact' => [ 'name' => 'CreateArtifact', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateArtifactRequest', ], 'output' => [ 'shape' => 'CreateArtifactResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateAutoMLJob' => [ 'name' => 'CreateAutoMLJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateAutoMLJobRequest', ], 'output' => [ 'shape' => 'CreateAutoMLJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateAutoMLJobV2' => [ 'name' => 'CreateAutoMLJobV2', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateAutoMLJobV2Request', ], 'output' => [ 'shape' => 'CreateAutoMLJobV2Response', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateCodeRepository' => [ 'name' => 'CreateCodeRepository', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateCodeRepositoryInput', ], 'output' => [ 'shape' => 'CreateCodeRepositoryOutput', ], ], 'CreateCompilationJob' => [ 'name' => 'CreateCompilationJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateCompilationJobRequest', ], 'output' => [ 'shape' => 'CreateCompilationJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateContext' => [ 'name' => 'CreateContext', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateContextRequest', ], 'output' => [ 'shape' => 'CreateContextResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateDataQualityJobDefinition' => [ 'name' => 'CreateDataQualityJobDefinition', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateDataQualityJobDefinitionRequest', ], 'output' => [ 'shape' => 'CreateDataQualityJobDefinitionResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateDeviceFleet' => [ 'name' => 'CreateDeviceFleet', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateDeviceFleetRequest', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateDomain' => [ 'name' => 'CreateDomain', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateDomainRequest', ], 'output' => [ 'shape' => 'CreateDomainResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateEdgeDeploymentPlan' => [ 'name' => 'CreateEdgeDeploymentPlan', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateEdgeDeploymentPlanRequest', ], 'output' => [ 'shape' => 'CreateEdgeDeploymentPlanResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateEdgeDeploymentStage' => [ 'name' => 'CreateEdgeDeploymentStage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateEdgeDeploymentStageRequest', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateEdgePackagingJob' => [ 'name' => 'CreateEdgePackagingJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateEdgePackagingJobRequest', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateEndpoint' => [ 'name' => 'CreateEndpoint', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateEndpointInput', ], 'output' => [ 'shape' => 'CreateEndpointOutput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateEndpointConfig' => [ 'name' => 'CreateEndpointConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateEndpointConfigInput', ], 'output' => [ 'shape' => 'CreateEndpointConfigOutput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateExperiment' => [ 'name' => 'CreateExperiment', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateExperimentRequest', ], 'output' => [ 'shape' => 'CreateExperimentResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateFeatureGroup' => [ 'name' => 'CreateFeatureGroup', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateFeatureGroupRequest', ], 'output' => [ 'shape' => 'CreateFeatureGroupResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateFlowDefinition' => [ 'name' => 'CreateFlowDefinition', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateFlowDefinitionRequest', ], 'output' => [ 'shape' => 'CreateFlowDefinitionResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateHub' => [ 'name' => 'CreateHub', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateHubRequest', ], 'output' => [ 'shape' => 'CreateHubResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateHumanTaskUi' => [ 'name' => 'CreateHumanTaskUi', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateHumanTaskUiRequest', ], 'output' => [ 'shape' => 'CreateHumanTaskUiResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateHyperParameterTuningJob' => [ 'name' => 'CreateHyperParameterTuningJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateHyperParameterTuningJobRequest', ], 'output' => [ 'shape' => 'CreateHyperParameterTuningJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateImage' => [ 'name' => 'CreateImage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateImageRequest', ], 'output' => [ 'shape' => 'CreateImageResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateImageVersion' => [ 'name' => 'CreateImageVersion', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateImageVersionRequest', ], 'output' => [ 'shape' => 'CreateImageVersionResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'CreateInferenceExperiment' => [ 'name' => 'CreateInferenceExperiment', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateInferenceExperimentRequest', ], 'output' => [ 'shape' => 'CreateInferenceExperimentResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateInferenceRecommendationsJob' => [ 'name' => 'CreateInferenceRecommendationsJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateInferenceRecommendationsJobRequest', ], 'output' => [ 'shape' => 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'ResourceNotFound', ], ], ], 'DescribeEdgePackagingJob' => [ 'name' => 'DescribeEdgePackagingJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeEdgePackagingJobRequest', ], 'output' => [ 'shape' => 'DescribeEdgePackagingJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeEndpoint' => [ 'name' => 'DescribeEndpoint', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeEndpointInput', ], 'output' => [ 'shape' => 'DescribeEndpointOutput', ], ], 'DescribeEndpointConfig' => [ 'name' => 'DescribeEndpointConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeEndpointConfigInput', ], 'output' => [ 'shape' => 'DescribeEndpointConfigOutput', ], ], 'DescribeExperiment' => [ 'name' => 'DescribeExperiment', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeExperimentRequest', ], 'output' => [ 'shape' => 'DescribeExperimentResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeFeatureGroup' => [ 'name' => 'DescribeFeatureGroup', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeFeatureGroupRequest', ], 'output' => [ 'shape' => 'DescribeFeatureGroupResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeFeatureMetadata' => [ 'name' => 'DescribeFeatureMetadata', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeFeatureMetadataRequest', ], 'output' => [ 'shape' => 'DescribeFeatureMetadataResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeFlowDefinition' => [ 'name' => 'DescribeFlowDefinition', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeFlowDefinitionRequest', ], 'output' => [ 'shape' => 'DescribeFlowDefinitionResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeHub' => [ 'name' => 'DescribeHub', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeHubRequest', ], 'output' => [ 'shape' => 'DescribeHubResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeHubContent' => [ 'name' => 'DescribeHubContent', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeHubContentRequest', ], 'output' => [ 'shape' => 'DescribeHubContentResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeHumanTaskUi' => [ 'name' => 'DescribeHumanTaskUi', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeHumanTaskUiRequest', ], 'output' => [ 'shape' => 'DescribeHumanTaskUiResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeHyperParameterTuningJob' => [ 'name' => 'DescribeHyperParameterTuningJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeHyperParameterTuningJobRequest', ], 'output' => [ 'shape' => 'DescribeHyperParameterTuningJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeImage' => [ 'name' => 'DescribeImage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeImageRequest', ], 'output' => [ 'shape' => 'DescribeImageResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeImageVersion' => [ 'name' => 'DescribeImageVersion', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeImageVersionRequest', ], 'output' => [ 'shape' => 'DescribeImageVersionResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeInferenceExperiment' => [ 'name' => 'DescribeInferenceExperiment', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeInferenceExperimentRequest', ], 'output' => [ 'shape' => 'DescribeInferenceExperimentResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeInferenceRecommendationsJob' => [ 'name' => 'DescribeInferenceRecommendationsJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeInferenceRecommendationsJobRequest', ], 'output' => [ 'shape' => 'DescribeInferenceRecommendationsJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeLabelingJob' => [ 'name' => 'DescribeLabelingJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeLabelingJobRequest', ], 'output' => [ 'shape' => 'DescribeLabelingJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeLineageGroup' => [ 'name' => 'DescribeLineageGroup', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeLineageGroupRequest', ], 'output' => [ 'shape' => 'DescribeLineageGroupResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeModel' => [ 'name' => 'DescribeModel', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeModelInput', ], 'output' => [ 'shape' => 'DescribeModelOutput', ], ], 'DescribeModelBiasJobDefinition' => [ 'name' => 'DescribeModelBiasJobDefinition', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeModelBiasJobDefinitionRequest', ], 'output' => [ 'shape' => 'DescribeModelBiasJobDefinitionResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeModelCard' => [ 'name' => 'DescribeModelCard', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeModelCardRequest', ], 'output' => [ 'shape' => 'DescribeModelCardResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeModelCardExportJob' => [ 'name' => 'DescribeModelCardExportJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeModelCardExportJobRequest', ], 'output' => [ 'shape' => 'DescribeModelCardExportJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeModelExplainabilityJobDefinition' => [ 'name' => 'DescribeModelExplainabilityJobDefinition', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeModelExplainabilityJobDefinitionRequest', ], 'output' => [ 'shape' => 'DescribeModelExplainabilityJobDefinitionResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeModelPackage' => [ 'name' => 'DescribeModelPackage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeModelPackageInput', ], 'output' => [ 'shape' => 'DescribeModelPackageOutput', ], ], 'DescribeModelPackageGroup' => [ 'name' => 'DescribeModelPackageGroup', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeModelPackageGroupInput', ], 'output' => [ 'shape' => 'DescribeModelPackageGroupOutput', ], ], 'DescribeModelQualityJobDefinition' => [ 'name' => 'DescribeModelQualityJobDefinition', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeModelQualityJobDefinitionRequest', ], 'output' => [ 'shape' => 'DescribeModelQualityJobDefinitionResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeMonitoringSchedule' => [ 'name' => 'DescribeMonitoringSchedule', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeMonitoringScheduleRequest', ], 'output' => [ 'shape' => 'DescribeMonitoringScheduleResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeNotebookInstance' => [ 'name' => 'DescribeNotebookInstance', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeNotebookInstanceInput', ], 'output' => [ 'shape' => 'DescribeNotebookInstanceOutput', ], ], 'DescribeNotebookInstanceLifecycleConfig' => [ 'name' => 'DescribeNotebookInstanceLifecycleConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeNotebookInstanceLifecycleConfigInput', ], 'output' => [ 'shape' => 'DescribeNotebookInstanceLifecycleConfigOutput', ], ], 'DescribePipeline' => [ 'name' => 'DescribePipeline', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribePipelineRequest', ], 'output' => [ 'shape' => 'DescribePipelineResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribePipelineDefinitionForExecution' => [ 'name' => 'DescribePipelineDefinitionForExecution', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribePipelineDefinitionForExecutionRequest', ], 'output' => [ 'shape' => 'DescribePipelineDefinitionForExecutionResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribePipelineExecution' => [ 'name' => 'DescribePipelineExecution', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribePipelineExecutionRequest', ], 'output' => [ 'shape' => 'DescribePipelineExecutionResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeProcessingJob' => [ 'name' => 'DescribeProcessingJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeProcessingJobRequest', ], 'output' => [ 'shape' => 'DescribeProcessingJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeProject' => [ 'name' => 'DescribeProject', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeProjectInput', ], 'output' => [ 'shape' => 'DescribeProjectOutput', ], ], 'DescribeSpace' => [ 'name' => 'DescribeSpace', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeSpaceRequest', ], 'output' => [ 'shape' => 'DescribeSpaceResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeStudioLifecycleConfig' => [ 'name' => 'DescribeStudioLifecycleConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeStudioLifecycleConfigRequest', ], 'output' => [ 'shape' => 'DescribeStudioLifecycleConfigResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeSubscribedWorkteam' => [ 'name' => 'DescribeSubscribedWorkteam', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeSubscribedWorkteamRequest', ], 'output' => [ 'shape' => 'DescribeSubscribedWorkteamResponse', ], ], 'DescribeTrainingJob' => [ 'name' => 'DescribeTrainingJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeTrainingJobRequest', ], 'output' => [ 'shape' => 'DescribeTrainingJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeTransformJob' => [ 'name' => 'DescribeTransformJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeTransformJobRequest', ], 'output' => [ 'shape' => 'DescribeTransformJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeTrial' => [ 'name' => 'DescribeTrial', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeTrialRequest', ], 'output' => [ 'shape' => 'DescribeTrialResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeTrialComponent' => [ 'name' => 'DescribeTrialComponent', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeTrialComponentRequest', ], 'output' => [ 'shape' => 'DescribeTrialComponentResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeUserProfile' => [ 'name' => 'DescribeUserProfile', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeUserProfileRequest', ], 'output' => [ 'shape' => 'DescribeUserProfileResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeWorkforce' => [ 'name' => 'DescribeWorkforce', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeWorkforceRequest', ], 'output' => [ 'shape' => 'DescribeWorkforceResponse', ], ], 'DescribeWorkteam' => [ 'name' => 'DescribeWorkteam', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeWorkteamRequest', ], 'output' => [ 'shape' => 'DescribeWorkteamResponse', ], ], 'DisableSagemakerServicecatalogPortfolio' => [ 'name' => 'DisableSagemakerServicecatalogPortfolio', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DisableSagemakerServicecatalogPortfolioInput', ], 'output' => [ 'shape' => 'DisableSagemakerServicecatalogPortfolioOutput', ], ], 'DisassociateTrialComponent' => [ 'name' => 'DisassociateTrialComponent', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DisassociateTrialComponentRequest', ], 'output' => [ 'shape' => 'DisassociateTrialComponentResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'EnableSagemakerServicecatalogPortfolio' => [ 'name' => 'EnableSagemakerServicecatalogPortfolio', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'EnableSagemakerServicecatalogPortfolioInput', ], 'output' => [ 'shape' => 'EnableSagemakerServicecatalogPortfolioOutput', ], ], 'GetDeviceFleetReport' => [ 'name' => 'GetDeviceFleetReport', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'GetDeviceFleetReportRequest', ], 'output' => [ 'shape' => 'GetDeviceFleetReportResponse', ], ], 'GetLineageGroupPolicy' => [ 'name' => 'GetLineageGroupPolicy', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'GetLineageGroupPolicyRequest', ], 'output' => [ 'shape' => 'GetLineageGroupPolicyResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'GetModelPackageGroupPolicy' => [ 'name' => 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=> '/', ], 'input' => [ 'shape' => 'GetSearchSuggestionsRequest', ], 'output' => [ 'shape' => 'GetSearchSuggestionsResponse', ], ], 'ImportHubContent' => [ 'name' => 'ImportHubContent', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ImportHubContentRequest', ], 'output' => [ 'shape' => 'ImportHubContentResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'ListActions' => [ 'name' => 'ListActions', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListActionsRequest', ], 'output' => [ 'shape' => 'ListActionsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListAlgorithms' => [ 'name' => 'ListAlgorithms', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListAlgorithmsInput', ], 'output' => [ 'shape' => 'ListAlgorithmsOutput', ], ], 'ListAliases' => [ 'name' => 'ListAliases', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListAliasesRequest', ], 'output' => [ 'shape' => 'ListAliasesResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListAppImageConfigs' => [ 'name' => 'ListAppImageConfigs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListAppImageConfigsRequest', ], 'output' => [ 'shape' => 'ListAppImageConfigsResponse', ], ], 'ListApps' => [ 'name' => 'ListApps', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListAppsRequest', ], 'output' => [ 'shape' => 'ListAppsResponse', ], ], 'ListArtifacts' => [ 'name' => 'ListArtifacts', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListArtifactsRequest', ], 'output' => [ 'shape' => 'ListArtifactsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListAssociations' => [ 'name' => 'ListAssociations', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListAssociationsRequest', ], 'output' => [ 'shape' => 'ListAssociationsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListAutoMLJobs' => [ 'name' => 'ListAutoMLJobs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListAutoMLJobsRequest', ], 'output' => [ 'shape' => 'ListAutoMLJobsResponse', ], ], 'ListCandidatesForAutoMLJob' => [ 'name' => 'ListCandidatesForAutoMLJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListCandidatesForAutoMLJobRequest', ], 'output' => [ 'shape' => 'ListCandidatesForAutoMLJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListCodeRepositories' => [ 'name' => 'ListCodeRepositories', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListCodeRepositoriesInput', ], 'output' => [ 'shape' => 'ListCodeRepositoriesOutput', ], ], 'ListCompilationJobs' => [ 'name' => 'ListCompilationJobs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListCompilationJobsRequest', ], 'output' => [ 'shape' => 'ListCompilationJobsResponse', ], ], 'ListContexts' => [ 'name' => 'ListContexts', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListContextsRequest', ], 'output' => [ 'shape' => 'ListContextsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListDataQualityJobDefinitions' => [ 'name' => 'ListDataQualityJobDefinitions', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListDataQualityJobDefinitionsRequest', ], 'output' => [ 'shape' => 'ListDataQualityJobDefinitionsResponse', ], ], 'ListDeviceFleets' => [ 'name' => 'ListDeviceFleets', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListDeviceFleetsRequest', ], 'output' => [ 'shape' => 'ListDeviceFleetsResponse', ], ], 'ListDevices' => [ 'name' => 'ListDevices', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListDevicesRequest', ], 'output' => [ 'shape' => 'ListDevicesResponse', ], ], 'ListDomains' => [ 'name' => 'ListDomains', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListDomainsRequest', ], 'output' => [ 'shape' => 'ListDomainsResponse', ], ], 'ListEdgeDeploymentPlans' => [ 'name' => 'ListEdgeDeploymentPlans', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListEdgeDeploymentPlansRequest', ], 'output' => [ 'shape' => 'ListEdgeDeploymentPlansResponse', ], ], 'ListEdgePackagingJobs' => [ 'name' => 'ListEdgePackagingJobs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListEdgePackagingJobsRequest', ], 'output' => [ 'shape' => 'ListEdgePackagingJobsResponse', ], ], 'ListEndpointConfigs' => [ 'name' => 'ListEndpointConfigs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListEndpointConfigsInput', ], 'output' => [ 'shape' => 'ListEndpointConfigsOutput', ], ], 'ListEndpoints' => [ 'name' => 'ListEndpoints', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListEndpointsInput', ], 'output' => [ 'shape' => 'ListEndpointsOutput', ], ], 'ListExperiments' => [ 'name' => 'ListExperiments', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListExperimentsRequest', ], 'output' => [ 'shape' => 'ListExperimentsResponse', ], ], 'ListFeatureGroups' => [ 'name' => 'ListFeatureGroups', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListFeatureGroupsRequest', ], 'output' => [ 'shape' => 'ListFeatureGroupsResponse', ], ], 'ListFlowDefinitions' => [ 'name' => 'ListFlowDefinitions', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListFlowDefinitionsRequest', ], 'output' => [ 'shape' => 'ListFlowDefinitionsResponse', ], ], 'ListHubContentVersions' => [ 'name' => 'ListHubContentVersions', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListHubContentVersionsRequest', ], 'output' => [ 'shape' => 'ListHubContentVersionsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListHubContents' => [ 'name' => 'ListHubContents', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListHubContentsRequest', ], 'output' => [ 'shape' => 'ListHubContentsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListHubs' => [ 'name' => 'ListHubs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListHubsRequest', ], 'output' => [ 'shape' => 'ListHubsResponse', ], ], 'ListHumanTaskUis' => [ 'name' => 'ListHumanTaskUis', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListHumanTaskUisRequest', ], 'output' => [ 'shape' => 'ListHumanTaskUisResponse', ], ], 'ListHyperParameterTuningJobs' => [ 'name' => 'ListHyperParameterTuningJobs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListHyperParameterTuningJobsRequest', ], 'output' => [ 'shape' => 'ListHyperParameterTuningJobsResponse', ], ], 'ListImageVersions' => [ 'name' => 'ListImageVersions', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListImageVersionsRequest', ], 'output' => [ 'shape' => 'ListImageVersionsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListImages' => [ 'name' => 'ListImages', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListImagesRequest', ], 'output' => [ 'shape' => 'ListImagesResponse', ], ], 'ListInferenceExperiments' => [ 'name' => 'ListInferenceExperiments', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListInferenceExperimentsRequest', ], 'output' => [ 'shape' => 'ListInferenceExperimentsResponse', ], ], 'ListInferenceRecommendationsJobSteps' => [ 'name' => 'ListInferenceRecommendationsJobSteps', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListInferenceRecommendationsJobStepsRequest', ], 'output' => [ 'shape' => 'ListInferenceRecommendationsJobStepsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListInferenceRecommendationsJobs' => [ 'name' => 'ListInferenceRecommendationsJobs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListInferenceRecommendationsJobsRequest', ], 'output' => [ 'shape' => 'ListInferenceRecommendationsJobsResponse', ], ], 'ListLabelingJobs' => [ 'name' => 'ListLabelingJobs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListLabelingJobsRequest', ], 'output' => [ 'shape' => 'ListLabelingJobsResponse', ], ], 'ListLabelingJobsForWorkteam' => [ 'name' => 'ListLabelingJobsForWorkteam', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListLabelingJobsForWorkteamRequest', ], 'output' => [ 'shape' => 'ListLabelingJobsForWorkteamResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListLineageGroups' => [ 'name' => 'ListLineageGroups', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListLineageGroupsRequest', ], 'output' => [ 'shape' => 'ListLineageGroupsResponse', ], ], 'ListModelBiasJobDefinitions' => [ 'name' => 'ListModelBiasJobDefinitions', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelBiasJobDefinitionsRequest', ], 'output' => [ 'shape' => 'ListModelBiasJobDefinitionsResponse', ], ], 'ListModelCardExportJobs' => [ 'name' => 'ListModelCardExportJobs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelCardExportJobsRequest', ], 'output' => [ 'shape' => 'ListModelCardExportJobsResponse', ], ], 'ListModelCardVersions' => [ 'name' => 'ListModelCardVersions', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelCardVersionsRequest', ], 'output' => [ 'shape' => 'ListModelCardVersionsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListModelCards' => [ 'name' => 'ListModelCards', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelCardsRequest', ], 'output' => [ 'shape' => 'ListModelCardsResponse', ], ], 'ListModelExplainabilityJobDefinitions' => [ 'name' => 'ListModelExplainabilityJobDefinitions', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelExplainabilityJobDefinitionsRequest', ], 'output' => [ 'shape' => 'ListModelExplainabilityJobDefinitionsResponse', ], ], 'ListModelMetadata' => [ 'name' => 'ListModelMetadata', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelMetadataRequest', ], 'output' => [ 'shape' => 'ListModelMetadataResponse', ], ], 'ListModelPackageGroups' => [ 'name' => 'ListModelPackageGroups', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelPackageGroupsInput', ], 'output' => [ 'shape' => 'ListModelPackageGroupsOutput', ], ], 'ListModelPackages' => [ 'name' => 'ListModelPackages', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelPackagesInput', ], 'output' => [ 'shape' => 'ListModelPackagesOutput', ], ], 'ListModelQualityJobDefinitions' => [ 'name' => 'ListModelQualityJobDefinitions', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelQualityJobDefinitionsRequest', ], 'output' => [ 'shape' => 'ListModelQualityJobDefinitionsResponse', ], ], 'ListModels' => [ 'name' => 'ListModels', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelsInput', ], 'output' => [ 'shape' => 'ListModelsOutput', ], ], 'ListMonitoringAlertHistory' => [ 'name' => 'ListMonitoringAlertHistory', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListMonitoringAlertHistoryRequest', ], 'output' => [ 'shape' => 'ListMonitoringAlertHistoryResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListMonitoringAlerts' => [ 'name' => 'ListMonitoringAlerts', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListMonitoringAlertsRequest', ], 'output' => [ 'shape' => 'ListMonitoringAlertsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListMonitoringExecutions' => [ 'name' => 'ListMonitoringExecutions', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListMonitoringExecutionsRequest', ], 'output' => [ 'shape' => 'ListMonitoringExecutionsResponse', ], ], 'ListMonitoringSchedules' => [ 'name' => 'ListMonitoringSchedules', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListMonitoringSchedulesRequest', ], 'output' => [ 'shape' => 'ListMonitoringSchedulesResponse', ], ], 'ListNotebookInstanceLifecycleConfigs' => [ 'name' => 'ListNotebookInstanceLifecycleConfigs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListNotebookInstanceLifecycleConfigsInput', ], 'output' => [ 'shape' => 'ListNotebookInstanceLifecycleConfigsOutput', ], ], 'ListNotebookInstances' => [ 'name' => 'ListNotebookInstances', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListNotebookInstancesInput', ], 'output' => [ 'shape' => 'ListNotebookInstancesOutput', ], ], 'ListPipelineExecutionSteps' => [ 'name' => 'ListPipelineExecutionSteps', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListPipelineExecutionStepsRequest', ], 'output' => [ 'shape' => 'ListPipelineExecutionStepsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListPipelineExecutions' => [ 'name' => 'ListPipelineExecutions', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListPipelineExecutionsRequest', ], 'output' => [ 'shape' => 'ListPipelineExecutionsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListPipelineParametersForExecution' => [ 'name' => 'ListPipelineParametersForExecution', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListPipelineParametersForExecutionRequest', ], 'output' => [ 'shape' => 'ListPipelineParametersForExecutionResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListPipelines' => [ 'name' => 'ListPipelines', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListPipelinesRequest', ], 'output' => [ 'shape' => 'ListPipelinesResponse', ], ], 'ListProcessingJobs' => [ 'name' => 'ListProcessingJobs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListProcessingJobsRequest', ], 'output' => [ 'shape' => 'ListProcessingJobsResponse', ], ], 'ListProjects' => [ 'name' => 'ListProjects', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListProjectsInput', ], 'output' => [ 'shape' => 'ListProjectsOutput', ], ], 'ListResourceCatalogs' => [ 'name' => 'ListResourceCatalogs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListResourceCatalogsRequest', ], 'output' => [ 'shape' => 'ListResourceCatalogsResponse', ], ], 'ListSpaces' => [ 'name' => 'ListSpaces', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListSpacesRequest', ], 'output' => [ 'shape' => 'ListSpacesResponse', ], ], 'ListStageDevices' => [ 'name' => 'ListStageDevices', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListStageDevicesRequest', ], 'output' => [ 'shape' => 'ListStageDevicesResponse', ], ], 'ListStudioLifecycleConfigs' => [ 'name' => 'ListStudioLifecycleConfigs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListStudioLifecycleConfigsRequest', ], 'output' => [ 'shape' => 'ListStudioLifecycleConfigsResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], ], ], 'ListSubscribedWorkteams' => [ 'name' => 'ListSubscribedWorkteams', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListSubscribedWorkteamsRequest', ], 'output' => [ 'shape' => 'ListSubscribedWorkteamsResponse', ], ], 'ListTags' => [ 'name' => 'ListTags', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListTagsInput', ], 'output' => [ 'shape' => 'ListTagsOutput', ], ], 'ListTrainingJobs' => [ 'name' => 'ListTrainingJobs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListTrainingJobsRequest', ], 'output' => [ 'shape' => 'ListTrainingJobsResponse', ], ], 'ListTrainingJobsForHyperParameterTuningJob' => [ 'name' => 'ListTrainingJobsForHyperParameterTuningJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListTrainingJobsForHyperParameterTuningJobRequest', ], 'output' => [ 'shape' => 'ListTrainingJobsForHyperParameterTuningJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListTransformJobs' => [ 'name' => 'ListTransformJobs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListTransformJobsRequest', ], 'output' => [ 'shape' => 'ListTransformJobsResponse', ], ], 'ListTrialComponents' => [ 'name' => 'ListTrialComponents', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListTrialComponentsRequest', ], 'output' => [ 'shape' => 'ListTrialComponentsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListTrials' => [ 'name' => 'ListTrials', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListTrialsRequest', ], 'output' => [ 'shape' => 'ListTrialsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListUserProfiles' => [ 'name' => 'ListUserProfiles', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListUserProfilesRequest', ], 'output' => [ 'shape' => 'ListUserProfilesResponse', ], ], 'ListWorkforces' => [ 'name' => 'ListWorkforces', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListWorkforcesRequest', ], 'output' => [ 'shape' => 'ListWorkforcesResponse', ], ], 'ListWorkteams' => [ 'name' => 'ListWorkteams', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListWorkteamsRequest', ], 'output' => [ 'shape' => 'ListWorkteamsResponse', ], ], 'PutModelPackageGroupPolicy' => [ 'name' => 'PutModelPackageGroupPolicy', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'PutModelPackageGroupPolicyInput', ], 'output' => [ 'shape' => 'PutModelPackageGroupPolicyOutput', ], ], 'QueryLineage' => [ 'name' => 'QueryLineage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'QueryLineageRequest', ], 'output' => [ 'shape' => 'QueryLineageResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'RegisterDevices' => [ 'name' => 'RegisterDevices', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'RegisterDevicesRequest', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'RenderUiTemplate' => [ 'name' => 'RenderUiTemplate', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'RenderUiTemplateRequest', ], 'output' => [ 'shape' => 'RenderUiTemplateResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'RetryPipelineExecution' => [ 'name' => 'RetryPipelineExecution', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'RetryPipelineExecutionRequest', ], 'output' => [ 'shape' => 'RetryPipelineExecutionResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ConflictException', ], ], ], 'Search' => [ 'name' => 'Search', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'SearchRequest', ], 'output' => [ 'shape' => 'SearchResponse', ], ], 'SendPipelineExecutionStepFailure' => [ 'name' => 'SendPipelineExecutionStepFailure', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'SendPipelineExecutionStepFailureRequest', ], 'output' => [ 'shape' => 'SendPipelineExecutionStepFailureResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'SendPipelineExecutionStepSuccess' => [ 'name' => 'SendPipelineExecutionStepSuccess', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'SendPipelineExecutionStepSuccessRequest', ], 'output' => [ 'shape' => 'SendPipelineExecutionStepSuccessResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'StartEdgeDeploymentStage' => [ 'name' => 'StartEdgeDeploymentStage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StartEdgeDeploymentStageRequest', ], ], 'StartInferenceExperiment' => [ 'name' => 'StartInferenceExperiment', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StartInferenceExperimentRequest', ], 'output' => [ 'shape' => 'StartInferenceExperimentResponse', ], 'errors' => [ [ 'shape' => 'ConflictException', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'StartMonitoringSchedule' => [ 'name' => 'StartMonitoringSchedule', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StartMonitoringScheduleRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'StartNotebookInstance' => [ 'name' => 'StartNotebookInstance', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StartNotebookInstanceInput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'StartPipelineExecution' => [ 'name' => 'StartPipelineExecution', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StartPipelineExecutionRequest', ], 'output' => [ 'shape' => 'StartPipelineExecutionResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'StopAutoMLJob' => [ 'name' => 'StopAutoMLJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopAutoMLJobRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'StopCompilationJob' => [ 'name' => 'StopCompilationJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopCompilationJobRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'StopEdgeDeploymentStage' => [ 'name' => 'StopEdgeDeploymentStage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopEdgeDeploymentStageRequest', ], ], 'StopEdgePackagingJob' => [ 'name' => 'StopEdgePackagingJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopEdgePackagingJobRequest', ], ], 'StopHyperParameterTuningJob' => [ 'name' => 'StopHyperParameterTuningJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopHyperParameterTuningJobRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'StopInferenceExperiment' => [ 'name' => 'StopInferenceExperiment', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopInferenceExperimentRequest', ], 'output' => [ 'shape' => 'StopInferenceExperimentResponse', ], 'errors' => [ [ 'shape' => 'ConflictException', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'StopInferenceRecommendationsJob' => [ 'name' => 'StopInferenceRecommendationsJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopInferenceRecommendationsJobRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'StopLabelingJob' => [ 'name' => 'StopLabelingJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopLabelingJobRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'StopMonitoringSchedule' => [ 'name' => 'StopMonitoringSchedule', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopMonitoringScheduleRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'StopNotebookInstance' => [ 'name' => 'StopNotebookInstance', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopNotebookInstanceInput', ], ], 'StopPipelineExecution' => [ 'name' => 'StopPipelineExecution', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopPipelineExecutionRequest', ], 'output' => [ 'shape' => 'StopPipelineExecutionResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'StopProcessingJob' => [ 'name' => 'StopProcessingJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopProcessingJobRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'StopTrainingJob' => [ 'name' => 'StopTrainingJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopTrainingJobRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'StopTransformJob' => [ 'name' => 'StopTransformJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'StopTransformJobRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateAction' => [ 'name' => 'UpdateAction', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateActionRequest', ], 'output' => [ 'shape' => 'UpdateActionResponse', ], 'errors' => [ [ 'shape' => 'ConflictException', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateAppImageConfig' => [ 'name' => 'UpdateAppImageConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateAppImageConfigRequest', ], 'output' => [ 'shape' => 'UpdateAppImageConfigResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateArtifact' => [ 'name' => 'UpdateArtifact', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateArtifactRequest', ], 'output' => [ 'shape' => 'UpdateArtifactResponse', ], 'errors' => [ [ 'shape' => 'ConflictException', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateCodeRepository' => [ 'name' => 'UpdateCodeRepository', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateCodeRepositoryInput', ], 'output' => [ 'shape' => 'UpdateCodeRepositoryOutput', ], ], 'UpdateContext' => [ 'name' => 'UpdateContext', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateContextRequest', ], 'output' => [ 'shape' => 'UpdateContextResponse', ], 'errors' => [ [ 'shape' => 'ConflictException', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateDeviceFleet' => [ 'name' => 'UpdateDeviceFleet', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateDeviceFleetRequest', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], ], ], 'UpdateDevices' => [ 'name' => 'UpdateDevices', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateDevicesRequest', ], ], 'UpdateDomain' => [ 'name' => 'UpdateDomain', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateDomainRequest', ], 'output' => [ 'shape' => 'UpdateDomainResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateEndpoint' => [ 'name' => 'UpdateEndpoint', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateEndpointInput', ], 'output' => [ 'shape' => 'UpdateEndpointOutput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'UpdateEndpointWeightsAndCapacities' => [ 'name' => 'UpdateEndpointWeightsAndCapacities', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateEndpointWeightsAndCapacitiesInput', ], 'output' => [ 'shape' => 'UpdateEndpointWeightsAndCapacitiesOutput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'UpdateExperiment' => [ 'name' => 'UpdateExperiment', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateExperimentRequest', ], 'output' => [ 'shape' => 'UpdateExperimentResponse', ], 'errors' => [ [ 'shape' => 'ConflictException', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateFeatureGroup' => [ 'name' => 'UpdateFeatureGroup', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateFeatureGroupRequest', ], 'output' => [ 'shape' => 'UpdateFeatureGroupResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateFeatureMetadata' => [ 'name' => 'UpdateFeatureMetadata', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateFeatureMetadataRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateHub' => [ 'name' => 'UpdateHub', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateHubRequest', ], 'output' => [ 'shape' => 'UpdateHubResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateImage' => [ 'name' => 'UpdateImage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateImageRequest', ], 'output' => [ 'shape' => 'UpdateImageResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateImageVersion' => [ 'name' => 'UpdateImageVersion', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateImageVersionRequest', ], 'output' => [ 'shape' => 'UpdateImageVersionResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateInferenceExperiment' => [ 'name' => 'UpdateInferenceExperiment', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateInferenceExperimentRequest', ], 'output' => [ 'shape' => 'UpdateInferenceExperimentResponse', ], 'errors' => [ [ 'shape' => 'ConflictException', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'UpdateModelCard' => [ 'name' => 'UpdateModelCard', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateModelCardRequest', ], 'output' => [ 'shape' => 'UpdateModelCardResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ConflictException', ], ], ], 'UpdateModelPackage' => [ 'name' => 'UpdateModelPackage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'UpdateModelPackageInput', ], 'output' => [ 'shape' => 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'ContentDigest' => [ 'type' => 'string', 'max' => 72, 'pattern' => '^[Ss][Hh][Aa]256:[0-9a-fA-F]{64}$', ], 'ContentType' => [ 'type' => 'string', 'max' => 256, 'pattern' => '.*', ], 'ContentTypes' => [ 'type' => 'list', 'member' => [ 'shape' => 'ContentType', ], ], 'ContextArn' => [ 'type' => 'string', 'max' => 256, 'pattern' => 'arn:aws[a-z\\-]*:sagemaker:[a-z0-9\\-]*:[0-9]{12}:context/.*', ], 'ContextSource' => [ 'type' => 'structure', 'required' => [ 'SourceUri', ], 'members' => [ 'SourceUri' => [ 'shape' => 'String2048', ], 'SourceType' => [ 'shape' => 'String256', ], 'SourceId' => [ 'shape' => 'String256', ], ], ], 'ContextSummaries' => [ 'type' => 'list', 'member' => [ 'shape' => 'ContextSummary', ], ], 'ContextSummary' => [ 'type' => 'structure', 'members' => [ 'ContextArn' => [ 'shape' => 'ContextArn', ], 'ContextName' => [ 'shape' => 'ExperimentEntityName', ], 'Source' => [ 'shape' => 'ContextSource', ], 'ContextType' => [ 'shape' => 'String256', ], 'CreationTime' => [ 'shape' 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'CreateActionRequest' => [ 'type' => 'structure', 'required' => [ 'ActionName', 'Source', 'ActionType', ], 'members' => [ 'ActionName' => [ 'shape' => 'ExperimentEntityName', ], 'Source' => [ 'shape' => 'ActionSource', ], 'ActionType' => [ 'shape' => 'String256', ], 'Description' => [ 'shape' => 'ExperimentDescription', ], 'Status' => [ 'shape' => 'ActionStatus', ], 'Properties' => [ 'shape' => 'LineageEntityParameters', ], 'MetadataProperties' => [ 'shape' => 'MetadataProperties', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateActionResponse' => [ 'type' => 'structure', 'members' => [ 'ActionArn' => [ 'shape' => 'ActionArn', ], ], ], 'CreateAlgorithmInput' => [ 'type' => 'structure', 'required' => [ 'AlgorithmName', 'TrainingSpecification', ], 'members' => [ 'AlgorithmName' => [ 'shape' => 'EntityName', ], 'AlgorithmDescription' => [ 'shape' => 'EntityDescription', ], 'TrainingSpecification' => [ 'shape' => 'TrainingSpecification', ], 'InferenceSpecification' => [ 'shape' => 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'AutoMLJobName' => [ 'shape' => 'AutoMLJobName', ], 'AutoMLJobInputDataConfig' => [ 'shape' => 'AutoMLJobInputDataConfig', ], 'OutputDataConfig' => [ 'shape' => 'AutoMLOutputDataConfig', ], 'AutoMLProblemTypeConfig' => [ 'shape' => 'AutoMLProblemTypeConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'Tags' => [ 'shape' => 'TagList', ], 'SecurityConfig' => [ 'shape' => 'AutoMLSecurityConfig', ], 'AutoMLJobObjective' => [ 'shape' => 'AutoMLJobObjective', ], 'ModelDeployConfig' => [ 'shape' => 'ModelDeployConfig', ], 'DataSplitConfig' => [ 'shape' => 'AutoMLDataSplitConfig', ], ], ], 'CreateAutoMLJobV2Response' => [ 'type' => 'structure', 'required' => [ 'AutoMLJobArn', ], 'members' => [ 'AutoMLJobArn' => [ 'shape' => 'AutoMLJobArn', ], ], ], 'CreateCodeRepositoryInput' => [ 'type' => 'structure', 'required' => [ 'CodeRepositoryName', 'GitConfig', ], 'members' => [ 'CodeRepositoryName' => [ 'shape' => 'EntityName', ], 'GitConfig' => [ 'shape' => 'GitConfig', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateCodeRepositoryOutput' => [ 'type' => 'structure', 'required' => [ 'CodeRepositoryArn', ], 'members' => [ 'CodeRepositoryArn' => [ 'shape' => 'CodeRepositoryArn', ], ], ], 'CreateCompilationJobRequest' => [ 'type' => 'structure', 'required' => [ 'CompilationJobName', 'RoleArn', 'OutputConfig', 'StoppingCondition', ], 'members' => [ 'CompilationJobName' => [ 'shape' => 'EntityName', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'ModelPackageVersionArn' => [ 'shape' => 'ModelPackageArn', ], 'InputConfig' => [ 'shape' => 'InputConfig', ], 'OutputConfig' => [ 'shape' => 'OutputConfig', ], 'VpcConfig' => [ 'shape' => 'NeoVpcConfig', ], 'StoppingCondition' => [ 'shape' => 'StoppingCondition', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateCompilationJobResponse' => [ 'type' => 'structure', 'required' => [ 'CompilationJobArn', ], 'members' => [ 'CompilationJobArn' => [ 'shape' => 'CompilationJobArn', ], ], ], 'CreateContextRequest' => [ 'type' => 'structure', 'required' => [ 'ContextName', 'Source', 'ContextType', ], 'members' => [ 'ContextName' => [ 'shape' => 'ExperimentEntityName', ], 'Source' => [ 'shape' => 'ContextSource', ], 'ContextType' => [ 'shape' => 'String256', ], 'Description' => [ 'shape' => 'ExperimentDescription', ], 'Properties' => [ 'shape' => 'LineageEntityParameters', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateContextResponse' => [ 'type' => 'structure', 'members' => [ 'ContextArn' => [ 'shape' => 'ContextArn', ], ], ], 'CreateDataQualityJobDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionName', 'DataQualityAppSpecification', 'DataQualityJobInput', 'DataQualityJobOutputConfig', 'JobResources', 'RoleArn', ], 'members' => [ 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], 'DataQualityBaselineConfig' => [ 'shape' => 'DataQualityBaselineConfig', ], 'DataQualityAppSpecification' => [ 'shape' => 'DataQualityAppSpecification', ], 'DataQualityJobInput' => [ 'shape' => 'DataQualityJobInput', ], 'DataQualityJobOutputConfig' => [ 'shape' => 'MonitoringOutputConfig', ], 'JobResources' => [ 'shape' => 'MonitoringResources', ], 'NetworkConfig' => [ 'shape' => 'MonitoringNetworkConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'StoppingCondition' => [ 'shape' => 'MonitoringStoppingCondition', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateDataQualityJobDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionArn', ], 'members' => [ 'JobDefinitionArn' => [ 'shape' => 'MonitoringJobDefinitionArn', ], ], ], 'CreateDeviceFleetRequest' => [ 'type' => 'structure', 'required' => [ 'DeviceFleetName', 'OutputConfig', ], 'members' => [ 'DeviceFleetName' => [ 'shape' => 'EntityName', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'Description' => [ 'shape' => 'DeviceFleetDescription', ], 'OutputConfig' => [ 'shape' => 'EdgeOutputConfig', ], 'Tags' => [ 'shape' => 'TagList', ], 'EnableIotRoleAlias' => [ 'shape' => 'EnableIotRoleAlias', ], ], ], 'CreateDomainRequest' => [ 'type' => 'structure', 'required' => [ 'DomainName', 'AuthMode', 'DefaultUserSettings', 'SubnetIds', 'VpcId', ], 'members' => [ 'DomainName' => [ 'shape' => 'DomainName', ], 'AuthMode' => [ 'shape' => 'AuthMode', ], 'DefaultUserSettings' => [ 'shape' => 'UserSettings', ], 'SubnetIds' => [ 'shape' => 'Subnets', ], 'VpcId' => [ 'shape' => 'VpcId', ], 'Tags' => [ 'shape' => 'TagList', ], 'AppNetworkAccessType' => [ 'shape' => 'AppNetworkAccessType', ], 'HomeEfsFileSystemKmsKeyId' => [ 'shape' => 'KmsKeyId', 'deprecated' => true, 'deprecatedMessage' => 'This property is deprecated, use KmsKeyId instead.', ], 'KmsKeyId' => [ 'shape' => 'KmsKeyId', ], 'AppSecurityGroupManagement' => [ 'shape' => 'AppSecurityGroupManagement', ], 'DomainSettings' => [ 'shape' => 'DomainSettings', ], 'DefaultSpaceSettings' => [ 'shape' => 'DefaultSpaceSettings', ], ], ], 'CreateDomainResponse' => [ 'type' => 'structure', 'members' => [ 'DomainArn' => [ 'shape' => 'DomainArn', ], 'Url' => [ 'shape' => 'String1024', ], ], ], 'CreateEdgeDeploymentPlanRequest' => [ 'type' => 'structure', 'required' => [ 'EdgeDeploymentPlanName', 'ModelConfigs', 'DeviceFleetName', ], 'members' => [ 'EdgeDeploymentPlanName' => [ 'shape' => 'EntityName', ], 'ModelConfigs' => [ 'shape' => 'EdgeDeploymentModelConfigs', ], 'DeviceFleetName' => [ 'shape' => 'EntityName', ], 'Stages' => [ 'shape' => 'DeploymentStages', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateEdgeDeploymentPlanResponse' => [ 'type' => 'structure', 'required' => [ 'EdgeDeploymentPlanArn', ], 'members' => [ 'EdgeDeploymentPlanArn' => [ 'shape' => 'EdgeDeploymentPlanArn', ], ], ], 'CreateEdgeDeploymentStageRequest' => [ 'type' => 'structure', 'required' => [ 'EdgeDeploymentPlanName', 'Stages', ], 'members' => [ 'EdgeDeploymentPlanName' => [ 'shape' => 'EntityName', ], 'Stages' => [ 'shape' => 'DeploymentStages', ], ], ], 'CreateEdgePackagingJobRequest' => [ 'type' => 'structure', 'required' => [ 'EdgePackagingJobName', 'CompilationJobName', 'ModelName', 'ModelVersion', 'RoleArn', 'OutputConfig', ], 'members' => [ 'EdgePackagingJobName' => [ 'shape' => 'EntityName', ], 'CompilationJobName' => [ 'shape' => 'EntityName', ], 'ModelName' => [ 'shape' => 'EntityName', ], 'ModelVersion' => [ 'shape' => 'EdgeVersion', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'OutputConfig' => [ 'shape' => 'EdgeOutputConfig', ], 'ResourceKey' => [ 'shape' => 'KmsKeyId', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateEndpointConfigInput' => [ 'type' => 'structure', 'required' => [ 'EndpointConfigName', 'ProductionVariants', ], 'members' => [ 'EndpointConfigName' => [ 'shape' => 'EndpointConfigName', ], 'ProductionVariants' => [ 'shape' => 'ProductionVariantList', ], 'DataCaptureConfig' => [ 'shape' => 'DataCaptureConfig', ], 'Tags' => [ 'shape' => 'TagList', ], 'KmsKeyId' => [ 'shape' => 'KmsKeyId', ], 'AsyncInferenceConfig' => [ 'shape' => 'AsyncInferenceConfig', ], 'ExplainerConfig' => [ 'shape' => 'ExplainerConfig', ], 'ShadowProductionVariants' => [ 'shape' => 'ProductionVariantList', ], ], ], 'CreateEndpointConfigOutput' => [ 'type' => 'structure', 'required' => [ 'EndpointConfigArn', ], 'members' => [ 'EndpointConfigArn' => [ 'shape' => 'EndpointConfigArn', ], ], ], 'CreateEndpointInput' => [ 'type' => 'structure', 'required' => [ 'EndpointName', 'EndpointConfigName', ], 'members' => [ 'EndpointName' => [ 'shape' => 'EndpointName', ], 'EndpointConfigName' => [ 'shape' => 'EndpointConfigName', ], 'DeploymentConfig' => [ 'shape' => 'DeploymentConfig', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateEndpointOutput' => [ 'type' => 'structure', 'required' => [ 'EndpointArn', ], 'members' => [ 'EndpointArn' => [ 'shape' => 'EndpointArn', ], ], ], 'CreateExperimentRequest' => [ 'type' => 'structure', 'required' => [ 'ExperimentName', ], 'members' => [ 'ExperimentName' => [ 'shape' => 'ExperimentEntityName', ], 'DisplayName' => [ 'shape' => 'ExperimentEntityName', ], 'Description' => [ 'shape' => 'ExperimentDescription', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateExperimentResponse' => [ 'type' => 'structure', 'members' => [ 'ExperimentArn' => [ 'shape' => 'ExperimentArn', ], ], ], 'CreateFeatureGroupRequest' => [ 'type' => 'structure', 'required' => [ 'FeatureGroupName', 'RecordIdentifierFeatureName', 'EventTimeFeatureName', 'FeatureDefinitions', ], 'members' => [ 'FeatureGroupName' => [ 'shape' => 'FeatureGroupName', ], 'RecordIdentifierFeatureName' => [ 'shape' => 'FeatureName', ], 'EventTimeFeatureName' => [ 'shape' => 'FeatureName', ], 'FeatureDefinitions' => [ 'shape' => 'FeatureDefinitions', ], 'OnlineStoreConfig' => [ 'shape' => 'OnlineStoreConfig', ], 'OfflineStoreConfig' => [ 'shape' => 'OfflineStoreConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'Description' => [ 'shape' => 'Description', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateFeatureGroupResponse' => [ 'type' => 'structure', 'required' => [ 'FeatureGroupArn', ], 'members' => [ 'FeatureGroupArn' => [ 'shape' => 'FeatureGroupArn', ], ], ], 'CreateFlowDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'FlowDefinitionName', 'HumanLoopConfig', 'OutputConfig', 'RoleArn', ], 'members' => [ 'FlowDefinitionName' => [ 'shape' => 'FlowDefinitionName', ], 'HumanLoopRequestSource' => [ 'shape' => 'HumanLoopRequestSource', ], 'HumanLoopActivationConfig' => [ 'shape' => 'HumanLoopActivationConfig', ], 'HumanLoopConfig' => [ 'shape' => 'HumanLoopConfig', ], 'OutputConfig' => [ 'shape' => 'FlowDefinitionOutputConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateFlowDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'FlowDefinitionArn', ], 'members' => [ 'FlowDefinitionArn' => [ 'shape' => 'FlowDefinitionArn', ], ], ], 'CreateHubRequest' => [ 'type' => 'structure', 'required' => [ 'HubName', 'HubDescription', ], 'members' => [ 'HubName' => [ 'shape' => 'HubName', ], 'HubDescription' => [ 'shape' => 'HubDescription', ], 'HubDisplayName' => [ 'shape' => 'HubDisplayName', ], 'HubSearchKeywords' => [ 'shape' => 'HubSearchKeywordList', ], 'S3StorageConfig' => [ 'shape' => 'HubS3StorageConfig', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateHubResponse' => [ 'type' => 'structure', 'required' => [ 'HubArn', ], 'members' => [ 'HubArn' => [ 'shape' => 'HubArn', ], ], ], 'CreateHumanTaskUiRequest' => [ 'type' => 'structure', 'required' => [ 'HumanTaskUiName', 'UiTemplate', ], 'members' => [ 'HumanTaskUiName' => [ 'shape' => 'HumanTaskUiName', ], 'UiTemplate' => [ 'shape' => 'UiTemplate', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateHumanTaskUiResponse' => [ 'type' => 'structure', 'required' => [ 'HumanTaskUiArn', ], 'members' => [ 'HumanTaskUiArn' => [ 'shape' => 'HumanTaskUiArn', ], ], ], 'CreateHyperParameterTuningJobRequest' => [ 'type' => 'structure', 'required' => [ 'HyperParameterTuningJobName', 'HyperParameterTuningJobConfig', ], 'members' => [ 'HyperParameterTuningJobName' => [ 'shape' => 'HyperParameterTuningJobName', ], 'HyperParameterTuningJobConfig' => [ 'shape' => 'HyperParameterTuningJobConfig', ], 'TrainingJobDefinition' => [ 'shape' => 'HyperParameterTrainingJobDefinition', ], 'TrainingJobDefinitions' => [ 'shape' => 'HyperParameterTrainingJobDefinitions', ], 'WarmStartConfig' => [ 'shape' => 'HyperParameterTuningJobWarmStartConfig', ], 'Tags' => [ 'shape' => 'TagList', ], 'Autotune' => [ 'shape' => 'Autotune', ], ], ], 'CreateHyperParameterTuningJobResponse' => [ 'type' => 'structure', 'required' => [ 'HyperParameterTuningJobArn', ], 'members' => [ 'HyperParameterTuningJobArn' => [ 'shape' => 'HyperParameterTuningJobArn', ], ], ], 'CreateImageRequest' => [ 'type' => 'structure', 'required' => [ 'ImageName', 'RoleArn', ], 'members' => [ 'Description' => [ 'shape' => 'ImageDescription', ], 'DisplayName' => [ 'shape' => 'ImageDisplayName', ], 'ImageName' => [ 'shape' => 'ImageName', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateImageResponse' => [ 'type' => 'structure', 'members' => [ 'ImageArn' => [ 'shape' => 'ImageArn', ], ], ], 'CreateImageVersionRequest' => [ 'type' => 'structure', 'required' => [ 'BaseImage', 'ClientToken', 'ImageName', ], 'members' => [ 'BaseImage' => [ 'shape' => 'ImageBaseImage', ], 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], 'ImageName' => [ 'shape' => 'ImageName', ], 'Aliases' => [ 'shape' => 'SageMakerImageVersionAliases', ], 'VendorGuidance' => [ 'shape' => 'VendorGuidance', ], 'JobType' => [ 'shape' => 'JobType', ], 'MLFramework' => [ 'shape' => 'MLFramework', ], 'ProgrammingLang' => [ 'shape' => 'ProgrammingLang', ], 'Processor' => [ 'shape' => 'Processor', ], 'Horovod' => [ 'shape' => 'Horovod', ], 'ReleaseNotes' => [ 'shape' => 'ReleaseNotes', ], ], ], 'CreateImageVersionResponse' => [ 'type' => 'structure', 'members' => [ 'ImageVersionArn' => [ 'shape' => 'ImageVersionArn', ], ], ], 'CreateInferenceExperimentRequest' => [ 'type' => 'structure', 'required' => [ 'Name', 'Type', 'RoleArn', 'EndpointName', 'ModelVariants', 'ShadowModeConfig', ], 'members' => [ 'Name' => [ 'shape' => 'InferenceExperimentName', ], 'Type' => [ 'shape' => 'InferenceExperimentType', ], 'Schedule' => [ 'shape' => 'InferenceExperimentSchedule', ], 'Description' => [ 'shape' => 'InferenceExperimentDescription', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'EndpointName' => [ 'shape' => 'EndpointName', ], 'ModelVariants' => [ 'shape' => 'ModelVariantConfigList', ], 'DataStorageConfig' => [ 'shape' => 'InferenceExperimentDataStorageConfig', ], 'ShadowModeConfig' => [ 'shape' => 'ShadowModeConfig', ], 'KmsKey' => [ 'shape' => 'KmsKeyId', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateInferenceExperimentResponse' => [ 'type' => 'structure', 'required' => [ 'InferenceExperimentArn', ], 'members' => [ 'InferenceExperimentArn' => [ 'shape' => 'InferenceExperimentArn', ], ], ], 'CreateInferenceRecommendationsJobRequest' => [ 'type' => 'structure', 'required' => [ 'JobName', 'JobType', 'RoleArn', 'InputConfig', ], 'members' => [ 'JobName' => [ 'shape' => 'RecommendationJobName', ], 'JobType' => [ 'shape' => 'RecommendationJobType', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'InputConfig' => [ 'shape' => 'RecommendationJobInputConfig', ], 'JobDescription' => [ 'shape' => 'RecommendationJobDescription', ], 'StoppingConditions' => [ 'shape' => 'RecommendationJobStoppingConditions', ], 'OutputConfig' => [ 'shape' => 'RecommendationJobOutputConfig', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateInferenceRecommendationsJobResponse' => [ 'type' => 'structure', 'required' => [ 'JobArn', ], 'members' => [ 'JobArn' => [ 'shape' => 'RecommendationJobArn', ], ], ], 'CreateLabelingJobRequest' => [ 'type' => 'structure', 'required' => [ 'LabelingJobName', 'LabelAttributeName', 'InputConfig', 'OutputConfig', 'RoleArn', 'HumanTaskConfig', ], 'members' => [ 'LabelingJobName' => [ 'shape' => 'LabelingJobName', ], 'LabelAttributeName' => [ 'shape' => 'LabelAttributeName', ], 'InputConfig' => [ 'shape' => 'LabelingJobInputConfig', ], 'OutputConfig' => [ 'shape' => 'LabelingJobOutputConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'LabelCategoryConfigS3Uri' => [ 'shape' => 'S3Uri', ], 'StoppingConditions' => [ 'shape' => 'LabelingJobStoppingConditions', ], 'LabelingJobAlgorithmsConfig' => [ 'shape' => 'LabelingJobAlgorithmsConfig', ], 'HumanTaskConfig' => [ 'shape' => 'HumanTaskConfig', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateLabelingJobResponse' => [ 'type' => 'structure', 'required' => [ 'LabelingJobArn', ], 'members' => [ 'LabelingJobArn' => [ 'shape' => 'LabelingJobArn', ], ], ], 'CreateModelBiasJobDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionName', 'ModelBiasAppSpecification', 'ModelBiasJobInput', 'ModelBiasJobOutputConfig', 'JobResources', 'RoleArn', ], 'members' => [ 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], 'ModelBiasBaselineConfig' => [ 'shape' => 'ModelBiasBaselineConfig', ], 'ModelBiasAppSpecification' => [ 'shape' => 'ModelBiasAppSpecification', ], 'ModelBiasJobInput' => [ 'shape' => 'ModelBiasJobInput', ], 'ModelBiasJobOutputConfig' => [ 'shape' => 'MonitoringOutputConfig', ], 'JobResources' => [ 'shape' => 'MonitoringResources', ], 'NetworkConfig' => [ 'shape' => 'MonitoringNetworkConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'StoppingCondition' => [ 'shape' => 'MonitoringStoppingCondition', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateModelBiasJobDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionArn', ], 'members' => [ 'JobDefinitionArn' => [ 'shape' => 'MonitoringJobDefinitionArn', ], ], ], 'CreateModelCardExportJobRequest' => [ 'type' => 'structure', 'required' => [ 'ModelCardName', 'ModelCardExportJobName', 'OutputConfig', ], 'members' => [ 'ModelCardName' => [ 'shape' => 'ModelCardNameOrArn', ], 'ModelCardVersion' => [ 'shape' => 'Integer', ], 'ModelCardExportJobName' => [ 'shape' => 'EntityName', ], 'OutputConfig' => [ 'shape' => 'ModelCardExportOutputConfig', ], ], ], 'CreateModelCardExportJobResponse' => [ 'type' => 'structure', 'required' => [ 'ModelCardExportJobArn', ], 'members' => [ 'ModelCardExportJobArn' => [ 'shape' => 'ModelCardExportJobArn', ], ], ], 'CreateModelCardRequest' => [ 'type' => 'structure', 'required' => [ 'ModelCardName', 'Content', 'ModelCardStatus', ], 'members' => [ 'ModelCardName' => [ 'shape' => 'EntityName', ], 'SecurityConfig' => [ 'shape' => 'ModelCardSecurityConfig', ], 'Content' => [ 'shape' => 'ModelCardContent', ], 'ModelCardStatus' => [ 'shape' => 'ModelCardStatus', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateModelCardResponse' => [ 'type' => 'structure', 'required' => [ 'ModelCardArn', ], 'members' => [ 'ModelCardArn' => [ 'shape' => 'ModelCardArn', ], ], ], 'CreateModelExplainabilityJobDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionName', 'ModelExplainabilityAppSpecification', 'ModelExplainabilityJobInput', 'ModelExplainabilityJobOutputConfig', 'JobResources', 'RoleArn', ], 'members' => [ 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], 'ModelExplainabilityBaselineConfig' => [ 'shape' => 'ModelExplainabilityBaselineConfig', ], 'ModelExplainabilityAppSpecification' => [ 'shape' => 'ModelExplainabilityAppSpecification', ], 'ModelExplainabilityJobInput' => [ 'shape' => 'ModelExplainabilityJobInput', ], 'ModelExplainabilityJobOutputConfig' => [ 'shape' => 'MonitoringOutputConfig', ], 'JobResources' => [ 'shape' => 'MonitoringResources', ], 'NetworkConfig' => [ 'shape' => 'MonitoringNetworkConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'StoppingCondition' => [ 'shape' => 'MonitoringStoppingCondition', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateModelExplainabilityJobDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionArn', ], 'members' => [ 'JobDefinitionArn' => [ 'shape' => 'MonitoringJobDefinitionArn', ], ], ], 'CreateModelInput' => [ 'type' => 'structure', 'required' => [ 'ModelName', 'ExecutionRoleArn', ], 'members' => [ 'ModelName' => [ 'shape' => 'ModelName', ], 'PrimaryContainer' => [ 'shape' => 'ContainerDefinition', ], 'Containers' => [ 'shape' => 'ContainerDefinitionList', ], 'InferenceExecutionConfig' => [ 'shape' => 'InferenceExecutionConfig', ], 'ExecutionRoleArn' => [ 'shape' => 'RoleArn', ], 'Tags' => [ 'shape' => 'TagList', ], 'VpcConfig' => [ 'shape' => 'VpcConfig', ], 'EnableNetworkIsolation' => [ 'shape' => 'Boolean', ], ], ], 'CreateModelOutput' => [ 'type' => 'structure', 'required' => [ 'ModelArn', ], 'members' => [ 'ModelArn' => [ 'shape' => 'ModelArn', ], ], ], 'CreateModelPackageGroupInput' => [ 'type' => 'structure', 'required' => [ 'ModelPackageGroupName', ], 'members' => [ 'ModelPackageGroupName' => [ 'shape' => 'EntityName', ], 'ModelPackageGroupDescription' => [ 'shape' => 'EntityDescription', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateModelPackageGroupOutput' => [ 'type' => 'structure', 'required' => [ 'ModelPackageGroupArn', ], 'members' => [ 'ModelPackageGroupArn' => [ 'shape' => 'ModelPackageGroupArn', ], ], ], 'CreateModelPackageInput' => [ 'type' => 'structure', 'members' => [ 'ModelPackageName' => [ 'shape' => 'EntityName', ], 'ModelPackageGroupName' => [ 'shape' => 'ArnOrName', ], 'ModelPackageDescription' => [ 'shape' => 'EntityDescription', ], 'InferenceSpecification' => [ 'shape' => 'InferenceSpecification', ], 'ValidationSpecification' => [ 'shape' => 'ModelPackageValidationSpecification', ], 'SourceAlgorithmSpecification' => [ 'shape' => 'SourceAlgorithmSpecification', ], 'CertifyForMarketplace' => [ 'shape' => 'CertifyForMarketplace', ], 'Tags' => [ 'shape' => 'TagList', ], 'ModelApprovalStatus' => [ 'shape' => 'ModelApprovalStatus', ], 'MetadataProperties' => [ 'shape' => 'MetadataProperties', ], 'ModelMetrics' => [ 'shape' => 'ModelMetrics', ], 'ClientToken' => [ 'shape' => 'ClientToken', 'idempotencyToken' => true, ], 'CustomerMetadataProperties' => [ 'shape' => 'CustomerMetadataMap', ], 'DriftCheckBaselines' => [ 'shape' => 'DriftCheckBaselines', ], 'Domain' => [ 'shape' => 'String', ], 'Task' => [ 'shape' => 'String', ], 'SamplePayloadUrl' => [ 'shape' => 'S3Uri', ], 'AdditionalInferenceSpecifications' => [ 'shape' => 'AdditionalInferenceSpecifications', ], 'SkipModelValidation' => [ 'shape' => 'SkipModelValidation', ], ], ], 'CreateModelPackageOutput' => [ 'type' => 'structure', 'required' => [ 'ModelPackageArn', ], 'members' => [ 'ModelPackageArn' => [ 'shape' => 'ModelPackageArn', ], ], ], 'CreateModelQualityJobDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionName', 'ModelQualityAppSpecification', 'ModelQualityJobInput', 'ModelQualityJobOutputConfig', 'JobResources', 'RoleArn', ], 'members' => [ 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], 'ModelQualityBaselineConfig' => [ 'shape' => 'ModelQualityBaselineConfig', ], 'ModelQualityAppSpecification' => [ 'shape' => 'ModelQualityAppSpecification', ], 'ModelQualityJobInput' => [ 'shape' => 'ModelQualityJobInput', ], 'ModelQualityJobOutputConfig' => [ 'shape' => 'MonitoringOutputConfig', ], 'JobResources' => [ 'shape' => 'MonitoringResources', ], 'NetworkConfig' => [ 'shape' => 'MonitoringNetworkConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'StoppingCondition' => [ 'shape' => 'MonitoringStoppingCondition', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateModelQualityJobDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionArn', ], 'members' => [ 'JobDefinitionArn' => [ 'shape' => 'MonitoringJobDefinitionArn', ], ], ], 'CreateMonitoringScheduleRequest' => [ 'type' => 'structure', 'required' => [ 'MonitoringScheduleName', 'MonitoringScheduleConfig', ], 'members' => [ 'MonitoringScheduleName' => [ 'shape' => 'MonitoringScheduleName', ], 'MonitoringScheduleConfig' => [ 'shape' => 'MonitoringScheduleConfig', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateMonitoringScheduleResponse' => [ 'type' => 'structure', 'required' => [ 'MonitoringScheduleArn', ], 'members' => [ 'MonitoringScheduleArn' => [ 'shape' => 'MonitoringScheduleArn', ], ], ], 'CreateNotebookInstanceInput' => [ 'type' => 'structure', 'required' => [ 'NotebookInstanceName', 'InstanceType', 'RoleArn', ], 'members' => [ 'NotebookInstanceName' => [ 'shape' => 'NotebookInstanceName', ], 'InstanceType' => [ 'shape' => 'InstanceType', ], 'SubnetId' => [ 'shape' => 'SubnetId', ], 'SecurityGroupIds' => [ 'shape' => 'SecurityGroupIds', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'KmsKeyId' => [ 'shape' => 'KmsKeyId', ], 'Tags' => [ 'shape' => 'TagList', ], 'LifecycleConfigName' => [ 'shape' => 'NotebookInstanceLifecycleConfigName', ], 'DirectInternetAccess' => [ 'shape' => 'DirectInternetAccess', ], 'VolumeSizeInGB' => [ 'shape' => 'NotebookInstanceVolumeSizeInGB', ], 'AcceleratorTypes' => [ 'shape' => 'NotebookInstanceAcceleratorTypes', ], 'DefaultCodeRepository' => [ 'shape' => 'CodeRepositoryNameOrUrl', ], 'AdditionalCodeRepositories' => [ 'shape' => 'AdditionalCodeRepositoryNamesOrUrls', ], 'RootAccess' => [ 'shape' => 'RootAccess', ], 'PlatformIdentifier' => [ 'shape' => 'PlatformIdentifier', ], 'InstanceMetadataServiceConfiguration' => [ 'shape' => 'InstanceMetadataServiceConfiguration', ], ], ], 'CreateNotebookInstanceLifecycleConfigInput' => [ 'type' => 'structure', 'required' => [ 'NotebookInstanceLifecycleConfigName', ], 'members' => [ 'NotebookInstanceLifecycleConfigName' => [ 'shape' => 'NotebookInstanceLifecycleConfigName', ], 'OnCreate' => [ 'shape' => 'NotebookInstanceLifecycleConfigList', ], 'OnStart' => [ 'shape' => 'NotebookInstanceLifecycleConfigList', ], ], ], 'CreateNotebookInstanceLifecycleConfigOutput' => [ 'type' => 'structure', 'members' => [ 'NotebookInstanceLifecycleConfigArn' => [ 'shape' => 'NotebookInstanceLifecycleConfigArn', ], ], ], 'CreateNotebookInstanceOutput' => [ 'type' => 'structure', 'members' => [ 'NotebookInstanceArn' => [ 'shape' => 'NotebookInstanceArn', ], ], ], 'CreatePipelineRequest' => [ 'type' => 'structure', 'required' => [ 'PipelineName', 'ClientRequestToken', 'RoleArn', ], 'members' => [ 'PipelineName' => [ 'shape' => 'PipelineName', ], 'PipelineDisplayName' => [ 'shape' => 'PipelineName', ], 'PipelineDefinition' => [ 'shape' => 'PipelineDefinition', ], 'PipelineDefinitionS3Location' => [ 'shape' => 'PipelineDefinitionS3Location', ], 'PipelineDescription' => [ 'shape' => 'PipelineDescription', ], 'ClientRequestToken' => [ 'shape' => 'IdempotencyToken', 'idempotencyToken' => true, ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'Tags' => [ 'shape' => 'TagList', ], 'ParallelismConfiguration' => [ 'shape' => 'ParallelismConfiguration', ], ], ], 'CreatePipelineResponse' => [ 'type' => 'structure', 'members' => [ 'PipelineArn' => [ 'shape' => 'PipelineArn', ], ], ], 'CreatePresignedDomainUrlRequest' => [ 'type' => 'structure', 'required' => [ 'DomainId', 'UserProfileName', ], 'members' => [ 'DomainId' => [ 'shape' => 'DomainId', ], 'UserProfileName' => [ 'shape' => 'UserProfileName', ], 'SessionExpirationDurationInSeconds' => [ 'shape' => 'SessionExpirationDurationInSeconds', ], 'ExpiresInSeconds' => [ 'shape' => 'ExpiresInSeconds', ], 'SpaceName' => [ 'shape' => 'SpaceName', ], ], ], 'CreatePresignedDomainUrlResponse' => [ 'type' => 'structure', 'members' => [ 'AuthorizedUrl' => [ 'shape' => 'PresignedDomainUrl', ], ], ], 'CreatePresignedNotebookInstanceUrlInput' => [ 'type' => 'structure', 'required' => [ 'NotebookInstanceName', ], 'members' => [ 'NotebookInstanceName' => [ 'shape' => 'NotebookInstanceName', ], 'SessionExpirationDurationInSeconds' => [ 'shape' => 'SessionExpirationDurationInSeconds', ], ], ], 'CreatePresignedNotebookInstanceUrlOutput' => [ 'type' => 'structure', 'members' => [ 'AuthorizedUrl' => [ 'shape' => 'NotebookInstanceUrl', ], ], ], 'CreateProcessingJobRequest' => [ 'type' => 'structure', 'required' => [ 'ProcessingJobName', 'ProcessingResources', 'AppSpecification', 'RoleArn', ], 'members' => [ 'ProcessingInputs' => [ 'shape' => 'ProcessingInputs', ], 'ProcessingOutputConfig' => [ 'shape' => 'ProcessingOutputConfig', ], 'ProcessingJobName' => [ 'shape' => 'ProcessingJobName', ], 'ProcessingResources' => [ 'shape' => 'ProcessingResources', ], 'StoppingCondition' => [ 'shape' => 'ProcessingStoppingCondition', ], 'AppSpecification' => [ 'shape' => 'AppSpecification', ], 'Environment' => [ 'shape' => 'ProcessingEnvironmentMap', ], 'NetworkConfig' => [ 'shape' => 'NetworkConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'Tags' => [ 'shape' => 'TagList', ], 'ExperimentConfig' => [ 'shape' => 'ExperimentConfig', ], ], ], 'CreateProcessingJobResponse' => [ 'type' => 'structure', 'required' => [ 'ProcessingJobArn', ], 'members' => [ 'ProcessingJobArn' => [ 'shape' => 'ProcessingJobArn', ], ], ], 'CreateProjectInput' => [ 'type' => 'structure', 'required' => [ 'ProjectName', 'ServiceCatalogProvisioningDetails', ], 'members' => [ 'ProjectName' => [ 'shape' => 'ProjectEntityName', ], 'ProjectDescription' => [ 'shape' => 'EntityDescription', ], 'ServiceCatalogProvisioningDetails' => [ 'shape' => 'ServiceCatalogProvisioningDetails', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateProjectOutput' => [ 'type' => 'structure', 'required' => [ 'ProjectArn', 'ProjectId', ], 'members' => [ 'ProjectArn' => [ 'shape' => 'ProjectArn', ], 'ProjectId' => [ 'shape' => 'ProjectId', ], ], ], 'CreateSpaceRequest' => [ 'type' => 'structure', 'required' => [ 'DomainId', 'SpaceName', ], 'members' => [ 'DomainId' => [ 'shape' => 'DomainId', ], 'SpaceName' => [ 'shape' => 'SpaceName', ], 'Tags' => [ 'shape' => 'TagList', ], 'SpaceSettings' => [ 'shape' => 'SpaceSettings', ], ], ], 'CreateSpaceResponse' => [ 'type' => 'structure', 'members' => [ 'SpaceArn' => [ 'shape' => 'SpaceArn', ], ], ], 'CreateStudioLifecycleConfigRequest' => [ 'type' => 'structure', 'required' => [ 'StudioLifecycleConfigName', 'StudioLifecycleConfigContent', 'StudioLifecycleConfigAppType', ], 'members' => [ 'StudioLifecycleConfigName' => [ 'shape' => 'StudioLifecycleConfigName', ], 'StudioLifecycleConfigContent' => [ 'shape' => 'StudioLifecycleConfigContent', ], 'StudioLifecycleConfigAppType' => [ 'shape' => 'StudioLifecycleConfigAppType', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateStudioLifecycleConfigResponse' => [ 'type' => 'structure', 'members' => [ 'StudioLifecycleConfigArn' => [ 'shape' => 'StudioLifecycleConfigArn', ], ], ], 'CreateTrainingJobRequest' => [ 'type' => 'structure', 'required' => [ 'TrainingJobName', 'AlgorithmSpecification', 'RoleArn', 'OutputDataConfig', 'ResourceConfig', 'StoppingCondition', ], 'members' => [ 'TrainingJobName' => [ 'shape' => 'TrainingJobName', ], 'HyperParameters' => [ 'shape' => 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'DeviceSelectionConfig', ], 'DeploymentConfig' => [ 'shape' => 'EdgeDeploymentConfig', ], 'DeploymentStatus' => [ 'shape' => 'EdgeDeploymentStatus', ], ], ], 'DeploymentStages' => [ 'type' => 'list', 'member' => [ 'shape' => 'DeploymentStage', ], ], 'DeregisterDevicesRequest' => [ 'type' => 'structure', 'required' => [ 'DeviceFleetName', 'DeviceNames', ], 'members' => [ 'DeviceFleetName' => [ 'shape' => 'EntityName', ], 'DeviceNames' => [ 'shape' => 'DeviceNames', ], ], ], 'DerivedInformation' => [ 'type' => 'structure', 'members' => [ 'DerivedDataInputConfig' => [ 'shape' => 'DataInputConfig', ], ], ], 'DescribeActionRequest' => [ 'type' => 'structure', 'required' => [ 'ActionName', ], 'members' => [ 'ActionName' => [ 'shape' => 'ExperimentEntityName', ], ], ], 'DescribeActionResponse' => [ 'type' => 'structure', 'members' => [ 'ActionName' => [ 'shape' => 'ExperimentEntityNameOrArn', ], 'ActionArn' => [ 'shape' => 'ActionArn', ], 'Source' => [ 'shape' => 'ActionSource', ], 'ActionType' => [ 'shape' => 'String256', ], 'Description' => [ 'shape' => 'ExperimentDescription', ], 'Status' => [ 'shape' => 'ActionStatus', ], 'Properties' => [ 'shape' => 'LineageEntityParameters', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'CreatedBy' => [ 'shape' => 'UserContext', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedBy' => [ 'shape' => 'UserContext', ], 'MetadataProperties' => [ 'shape' => 'MetadataProperties', ], 'LineageGroupArn' => [ 'shape' => 'LineageGroupArn', ], ], ], 'DescribeAlgorithmInput' => [ 'type' => 'structure', 'required' => [ 'AlgorithmName', ], 'members' => [ 'AlgorithmName' => [ 'shape' => 'ArnOrName', ], ], ], 'DescribeAlgorithmOutput' => [ 'type' => 'structure', 'required' => [ 'AlgorithmName', 'AlgorithmArn', 'CreationTime', 'TrainingSpecification', 'AlgorithmStatus', 'AlgorithmStatusDetails', ], 'members' => [ 'AlgorithmName' => [ 'shape' => 'EntityName', ], 'AlgorithmArn' => [ 'shape' => 'AlgorithmArn', ], 'AlgorithmDescription' => [ 'shape' => 'EntityDescription', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'TrainingSpecification' => [ 'shape' => 'TrainingSpecification', ], 'InferenceSpecification' => [ 'shape' => 'InferenceSpecification', ], 'ValidationSpecification' => [ 'shape' => 'AlgorithmValidationSpecification', ], 'AlgorithmStatus' => [ 'shape' => 'AlgorithmStatus', ], 'AlgorithmStatusDetails' => [ 'shape' => 'AlgorithmStatusDetails', ], 'ProductId' => [ 'shape' => 'ProductId', ], 'CertifyForMarketplace' => [ 'shape' => 'CertifyForMarketplace', ], ], ], 'DescribeAppImageConfigRequest' => [ 'type' => 'structure', 'required' => [ 'AppImageConfigName', ], 'members' => [ 'AppImageConfigName' => [ 'shape' => 'AppImageConfigName', ], ], ], 'DescribeAppImageConfigResponse' => [ 'type' => 'structure', 'members' => [ 'AppImageConfigArn' => [ 'shape' => 'AppImageConfigArn', ], 'AppImageConfigName' => [ 'shape' => 'AppImageConfigName', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'KernelGatewayImageConfig' => [ 'shape' => 'KernelGatewayImageConfig', ], ], ], 'DescribeAppRequest' => [ 'type' => 'structure', 'required' => [ 'DomainId', 'AppType', 'AppName', ], 'members' => [ 'DomainId' => [ 'shape' => 'DomainId', ], 'UserProfileName' => [ 'shape' => 'UserProfileName', ], 'AppType' => [ 'shape' => 'AppType', ], 'AppName' => [ 'shape' => 'AppName', ], 'SpaceName' => [ 'shape' => 'SpaceName', ], ], ], 'DescribeAppResponse' => [ 'type' => 'structure', 'members' => [ 'AppArn' => [ 'shape' => 'AppArn', ], 'AppType' => [ 'shape' => 'AppType', ], 'AppName' => [ 'shape' => 'AppName', ], 'DomainId' => [ 'shape' => 'DomainId', ], 'UserProfileName' => [ 'shape' => 'UserProfileName', ], 'Status' => [ 'shape' => 'AppStatus', ], 'LastHealthCheckTimestamp' => [ 'shape' => 'Timestamp', ], 'LastUserActivityTimestamp' => [ 'shape' => 'Timestamp', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'ResourceSpec' => [ 'shape' => 'ResourceSpec', ], 'SpaceName' => [ 'shape' => 'SpaceName', ], ], ], 'DescribeArtifactRequest' => [ 'type' => 'structure', 'required' => [ 'ArtifactArn', ], 'members' => [ 'ArtifactArn' => [ 'shape' => 'ArtifactArn', ], ], ], 'DescribeArtifactResponse' => [ 'type' => 'structure', 'members' => [ 'ArtifactName' => [ 'shape' => 'ExperimentEntityNameOrArn', ], 'ArtifactArn' => [ 'shape' => 'ArtifactArn', ], 'Source' => [ 'shape' => 'ArtifactSource', ], 'ArtifactType' => [ 'shape' => 'String256', ], 'Properties' => [ 'shape' => 'LineageEntityParameters', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'CreatedBy' => [ 'shape' => 'UserContext', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedBy' => [ 'shape' => 'UserContext', ], 'MetadataProperties' => [ 'shape' => 'MetadataProperties', ], 'LineageGroupArn' => [ 'shape' => 'LineageGroupArn', ], ], ], 'DescribeAutoMLJobRequest' => [ 'type' => 'structure', 'required' => [ 'AutoMLJobName', ], 'members' => [ 'AutoMLJobName' => [ 'shape' => 'AutoMLJobName', ], ], ], 'DescribeAutoMLJobResponse' => [ 'type' => 'structure', 'required' => [ 'AutoMLJobName', 'AutoMLJobArn', 'InputDataConfig', 'OutputDataConfig', 'RoleArn', 'CreationTime', 'LastModifiedTime', 'AutoMLJobStatus', 'AutoMLJobSecondaryStatus', ], 'members' => [ 'AutoMLJobName' => [ 'shape' => 'AutoMLJobName', ], 'AutoMLJobArn' => [ 'shape' => 'AutoMLJobArn', ], 'InputDataConfig' => [ 'shape' => 'AutoMLInputDataConfig', ], 'OutputDataConfig' => [ 'shape' => 'AutoMLOutputDataConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'AutoMLJobObjective' => [ 'shape' => 'AutoMLJobObjective', ], 'ProblemType' => [ 'shape' => 'ProblemType', ], 'AutoMLJobConfig' => [ 'shape' => 'AutoMLJobConfig', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'EndTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'FailureReason' => [ 'shape' => 'AutoMLFailureReason', ], 'PartialFailureReasons' => [ 'shape' => 'AutoMLPartialFailureReasons', ], 'BestCandidate' => [ 'shape' => 'AutoMLCandidate', ], 'AutoMLJobStatus' => [ 'shape' => 'AutoMLJobStatus', ], 'AutoMLJobSecondaryStatus' => [ 'shape' => 'AutoMLJobSecondaryStatus', ], 'GenerateCandidateDefinitionsOnly' => [ 'shape' => 'GenerateCandidateDefinitionsOnly', ], 'AutoMLJobArtifacts' => [ 'shape' => 'AutoMLJobArtifacts', ], 'ResolvedAttributes' => [ 'shape' => 'ResolvedAttributes', ], 'ModelDeployConfig' => [ 'shape' => 'ModelDeployConfig', ], 'ModelDeployResult' => [ 'shape' => 'ModelDeployResult', ], ], ], 'DescribeAutoMLJobV2Request' => [ 'type' => 'structure', 'required' => [ 'AutoMLJobName', ], 'members' => [ 'AutoMLJobName' => [ 'shape' => 'AutoMLJobName', ], ], ], 'DescribeAutoMLJobV2Response' => [ 'type' => 'structure', 'required' => [ 'AutoMLJobName', 'AutoMLJobArn', 'AutoMLJobInputDataConfig', 'OutputDataConfig', 'RoleArn', 'CreationTime', 'LastModifiedTime', 'AutoMLJobStatus', 'AutoMLJobSecondaryStatus', ], 'members' => [ 'AutoMLJobName' => [ 'shape' => 'AutoMLJobName', ], 'AutoMLJobArn' => [ 'shape' => 'AutoMLJobArn', ], 'AutoMLJobInputDataConfig' => [ 'shape' => 'AutoMLJobInputDataConfig', ], 'OutputDataConfig' => [ 'shape' => 'AutoMLOutputDataConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'AutoMLJobObjective' => [ 'shape' => 'AutoMLJobObjective', ], 'AutoMLProblemTypeConfig' => [ 'shape' => 'AutoMLProblemTypeConfig', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'EndTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'FailureReason' => [ 'shape' => 'AutoMLFailureReason', ], 'PartialFailureReasons' => [ 'shape' => 'AutoMLPartialFailureReasons', ], 'BestCandidate' => [ 'shape' => 'AutoMLCandidate', ], 'AutoMLJobStatus' => [ 'shape' => 'AutoMLJobStatus', ], 'AutoMLJobSecondaryStatus' => [ 'shape' => 'AutoMLJobSecondaryStatus', ], 'ModelDeployConfig' => [ 'shape' => 'ModelDeployConfig', ], 'ModelDeployResult' => [ 'shape' => 'ModelDeployResult', ], 'DataSplitConfig' => [ 'shape' => 'AutoMLDataSplitConfig', ], 'SecurityConfig' => [ 'shape' => 'AutoMLSecurityConfig', ], 'AutoMLJobArtifacts' => [ 'shape' => 'AutoMLJobArtifacts', ], 'ResolvedAttributes' => [ 'shape' => 'AutoMLResolvedAttributes', ], 'AutoMLProblemTypeConfigName' => [ 'shape' => 'AutoMLProblemTypeConfigName', ], ], ], 'DescribeCodeRepositoryInput' => [ 'type' => 'structure', 'required' => [ 'CodeRepositoryName', ], 'members' => [ 'CodeRepositoryName' => [ 'shape' => 'EntityName', ], ], ], 'DescribeCodeRepositoryOutput' => [ 'type' => 'structure', 'required' => [ 'CodeRepositoryName', 'CodeRepositoryArn', 'CreationTime', 'LastModifiedTime', ], 'members' => [ 'CodeRepositoryName' => [ 'shape' => 'EntityName', ], 'CodeRepositoryArn' => [ 'shape' => 'CodeRepositoryArn', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'GitConfig' => [ 'shape' => 'GitConfig', ], ], ], 'DescribeCompilationJobRequest' => [ 'type' => 'structure', 'required' => [ 'CompilationJobName', ], 'members' => [ 'CompilationJobName' => [ 'shape' => 'EntityName', ], ], ], 'DescribeCompilationJobResponse' => [ 'type' => 'structure', 'required' => [ 'CompilationJobName', 'CompilationJobArn', 'CompilationJobStatus', 'StoppingCondition', 'CreationTime', 'LastModifiedTime', 'FailureReason', 'ModelArtifacts', 'RoleArn', 'InputConfig', 'OutputConfig', ], 'members' => [ 'CompilationJobName' => [ 'shape' => 'EntityName', ], 'CompilationJobArn' => [ 'shape' => 'CompilationJobArn', ], 'CompilationJobStatus' => [ 'shape' => 'CompilationJobStatus', ], 'CompilationStartTime' => [ 'shape' => 'Timestamp', ], 'CompilationEndTime' => [ 'shape' => 'Timestamp', ], 'StoppingCondition' => [ 'shape' => 'StoppingCondition', ], 'InferenceImage' => [ 'shape' => 'InferenceImage', ], 'ModelPackageVersionArn' => [ 'shape' => 'ModelPackageArn', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'ModelArtifacts' => [ 'shape' => 'ModelArtifacts', ], 'ModelDigests' => [ 'shape' => 'ModelDigests', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'InputConfig' => [ 'shape' => 'InputConfig', ], 'OutputConfig' => [ 'shape' => 'OutputConfig', ], 'VpcConfig' => [ 'shape' => 'NeoVpcConfig', ], 'DerivedInformation' => [ 'shape' => 'DerivedInformation', ], ], ], 'DescribeContextRequest' => [ 'type' => 'structure', 'required' => [ 'ContextName', ], 'members' => [ 'ContextName' => [ 'shape' => 'ExperimentEntityNameOrArn', ], ], ], 'DescribeContextResponse' => [ 'type' => 'structure', 'members' => [ 'ContextName' => [ 'shape' => 'ExperimentEntityName', ], 'ContextArn' => [ 'shape' => 'ContextArn', ], 'Source' => [ 'shape' => 'ContextSource', ], 'ContextType' => [ 'shape' => 'String256', ], 'Description' => [ 'shape' => 'ExperimentDescription', ], 'Properties' => [ 'shape' => 'LineageEntityParameters', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'CreatedBy' => [ 'shape' => 'UserContext', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedBy' => [ 'shape' => 'UserContext', ], 'LineageGroupArn' => [ 'shape' => 'LineageGroupArn', ], ], ], 'DescribeDataQualityJobDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionName', ], 'members' => [ 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], ], ], 'DescribeDataQualityJobDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionArn', 'JobDefinitionName', 'CreationTime', 'DataQualityAppSpecification', 'DataQualityJobInput', 'DataQualityJobOutputConfig', 'JobResources', 'RoleArn', ], 'members' => [ 'JobDefinitionArn' => [ 'shape' => 'MonitoringJobDefinitionArn', ], 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'DataQualityBaselineConfig' => [ 'shape' => 'DataQualityBaselineConfig', ], 'DataQualityAppSpecification' => [ 'shape' => 'DataQualityAppSpecification', ], 'DataQualityJobInput' => [ 'shape' => 'DataQualityJobInput', ], 'DataQualityJobOutputConfig' => [ 'shape' => 'MonitoringOutputConfig', ], 'JobResources' => [ 'shape' => 'MonitoringResources', ], 'NetworkConfig' => [ 'shape' => 'MonitoringNetworkConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'StoppingCondition' => [ 'shape' => 'MonitoringStoppingCondition', ], ], ], 'DescribeDeviceFleetRequest' => [ 'type' => 'structure', 'required' => [ 'DeviceFleetName', ], 'members' => [ 'DeviceFleetName' => [ 'shape' => 'EntityName', ], ], ], 'DescribeDeviceFleetResponse' => [ 'type' => 'structure', 'required' => [ 'DeviceFleetName', 'DeviceFleetArn', 'OutputConfig', 'CreationTime', 'LastModifiedTime', ], 'members' => [ 'DeviceFleetName' => [ 'shape' => 'EntityName', ], 'DeviceFleetArn' => [ 'shape' => 'DeviceFleetArn', ], 'OutputConfig' => [ 'shape' => 'EdgeOutputConfig', ], 'Description' => [ 'shape' => 'DeviceFleetDescription', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'IotRoleAlias' => [ 'shape' => 'IotRoleAlias', ], ], ], 'DescribeDeviceRequest' => [ 'type' => 'structure', 'required' => [ 'DeviceName', 'DeviceFleetName', ], 'members' => [ 'NextToken' => [ 'shape' => 'NextToken', ], 'DeviceName' => [ 'shape' => 'EntityName', ], 'DeviceFleetName' => [ 'shape' => 'EntityName', ], ], ], 'DescribeDeviceResponse' => [ 'type' => 'structure', 'required' => [ 'DeviceName', 'DeviceFleetName', 'RegistrationTime', ], 'members' => [ 'DeviceArn' => [ 'shape' => 'DeviceArn', ], 'DeviceName' => [ 'shape' => 'EntityName', ], 'Description' => [ 'shape' => 'DeviceDescription', ], 'DeviceFleetName' => [ 'shape' => 'EntityName', ], 'IotThingName' => [ 'shape' => 'ThingName', ], 'RegistrationTime' => [ 'shape' => 'Timestamp', ], 'LatestHeartbeat' => [ 'shape' => 'Timestamp', ], 'Models' => [ 'shape' => 'EdgeModels', ], 'MaxModels' => [ 'shape' => 'Integer', ], 'NextToken' => [ 'shape' => 'NextToken', ], 'AgentVersion' => [ 'shape' => 'EdgeVersion', ], ], ], 'DescribeDomainRequest' => [ 'type' => 'structure', 'required' => [ 'DomainId', ], 'members' => [ 'DomainId' => [ 'shape' => 'DomainId', ], ], ], 'DescribeDomainResponse' => [ 'type' => 'structure', 'members' => [ 'DomainArn' => [ 'shape' => 'DomainArn', ], 'DomainId' => [ 'shape' => 'DomainId', ], 'DomainName' => [ 'shape' => 'DomainName', ], 'HomeEfsFileSystemId' => [ 'shape' => 'ResourceId', ], 'SingleSignOnManagedApplicationInstanceId' => [ 'shape' => 'String256', ], 'SingleSignOnApplicationArn' => [ 'shape' => 'SingleSignOnApplicationArn', ], 'Status' => [ 'shape' => 'DomainStatus', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'AuthMode' => [ 'shape' => 'AuthMode', ], 'DefaultUserSettings' => [ 'shape' => 'UserSettings', ], 'AppNetworkAccessType' => [ 'shape' => 'AppNetworkAccessType', ], 'HomeEfsFileSystemKmsKeyId' => [ 'shape' => 'KmsKeyId', 'deprecated' => true, 'deprecatedMessage' => 'This property is deprecated, use KmsKeyId instead.', ], 'SubnetIds' => [ 'shape' => 'Subnets', ], 'Url' => [ 'shape' => 'String1024', ], 'VpcId' => [ 'shape' => 'VpcId', ], 'KmsKeyId' => [ 'shape' => 'KmsKeyId', ], 'DomainSettings' => [ 'shape' => 'DomainSettings', ], 'AppSecurityGroupManagement' => [ 'shape' => 'AppSecurityGroupManagement', ], 'SecurityGroupIdForDomainBoundary' => [ 'shape' => 'SecurityGroupId', ], 'DefaultSpaceSettings' => [ 'shape' => 'DefaultSpaceSettings', ], ], ], 'DescribeEdgeDeploymentPlanRequest' => [ 'type' => 'structure', 'required' => [ 'EdgeDeploymentPlanName', ], 'members' => [ 'EdgeDeploymentPlanName' => [ 'shape' => 'EntityName', ], 'NextToken' => [ 'shape' => 'NextToken', ], 'MaxResults' => [ 'shape' => 'DeploymentStageMaxResults', ], ], ], 'DescribeEdgeDeploymentPlanResponse' => [ 'type' => 'structure', 'required' => [ 'EdgeDeploymentPlanArn', 'EdgeDeploymentPlanName', 'ModelConfigs', 'DeviceFleetName', 'Stages', ], 'members' => [ 'EdgeDeploymentPlanArn' => [ 'shape' => 'EdgeDeploymentPlanArn', ], 'EdgeDeploymentPlanName' => [ 'shape' => 'EntityName', ], 'ModelConfigs' => [ 'shape' => 'EdgeDeploymentModelConfigs', ], 'DeviceFleetName' => [ 'shape' => 'EntityName', ], 'EdgeDeploymentSuccess' => [ 'shape' => 'Integer', ], 'EdgeDeploymentPending' => [ 'shape' => 'Integer', ], 'EdgeDeploymentFailed' => [ 'shape' => 'Integer', ], 'Stages' => [ 'shape' => 'DeploymentStageStatusSummaries', ], 'NextToken' => [ 'shape' => 'NextToken', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], ], ], 'DescribeEdgePackagingJobRequest' => [ 'type' => 'structure', 'required' => [ 'EdgePackagingJobName', ], 'members' => [ 'EdgePackagingJobName' => [ 'shape' => 'EntityName', ], ], ], 'DescribeEdgePackagingJobResponse' => [ 'type' => 'structure', 'required' => [ 'EdgePackagingJobArn', 'EdgePackagingJobName', 'EdgePackagingJobStatus', ], 'members' => [ 'EdgePackagingJobArn' => [ 'shape' => 'EdgePackagingJobArn', ], 'EdgePackagingJobName' => [ 'shape' => 'EntityName', ], 'CompilationJobName' => [ 'shape' => 'EntityName', ], 'ModelName' => [ 'shape' => 'EntityName', ], 'ModelVersion' => [ 'shape' => 'EdgeVersion', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'OutputConfig' => [ 'shape' => 'EdgeOutputConfig', ], 'ResourceKey' => [ 'shape' => 'KmsKeyId', ], 'EdgePackagingJobStatus' => [ 'shape' => 'EdgePackagingJobStatus', ], 'EdgePackagingJobStatusMessage' => [ 'shape' => 'String', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'ModelArtifact' => [ 'shape' => 'S3Uri', ], 'ModelSignature' => [ 'shape' => 'String', ], 'PresetDeploymentOutput' => [ 'shape' => 'EdgePresetDeploymentOutput', ], ], ], 'DescribeEndpointConfigInput' => [ 'type' => 'structure', 'required' => [ 'EndpointConfigName', ], 'members' => [ 'EndpointConfigName' => [ 'shape' => 'EndpointConfigName', ], ], ], 'DescribeEndpointConfigOutput' => [ 'type' => 'structure', 'required' => [ 'EndpointConfigName', 'EndpointConfigArn', 'ProductionVariants', 'CreationTime', ], 'members' => [ 'EndpointConfigName' => [ 'shape' => 'EndpointConfigName', ], 'EndpointConfigArn' => [ 'shape' => 'EndpointConfigArn', ], 'ProductionVariants' => [ 'shape' => 'ProductionVariantList', ], 'DataCaptureConfig' => [ 'shape' => 'DataCaptureConfig', ], 'KmsKeyId' => [ 'shape' => 'KmsKeyId', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'AsyncInferenceConfig' => [ 'shape' => 'AsyncInferenceConfig', ], 'ExplainerConfig' => [ 'shape' => 'ExplainerConfig', ], 'ShadowProductionVariants' => [ 'shape' => 'ProductionVariantList', ], ], ], 'DescribeEndpointInput' => [ 'type' => 'structure', 'required' => [ 'EndpointName', ], 'members' => [ 'EndpointName' => [ 'shape' => 'EndpointName', ], ], ], 'DescribeEndpointOutput' => [ 'type' => 'structure', 'required' => [ 'EndpointName', 'EndpointArn', 'EndpointConfigName', 'EndpointStatus', 'CreationTime', 'LastModifiedTime', ], 'members' => [ 'EndpointName' => [ 'shape' => 'EndpointName', ], 'EndpointArn' => [ 'shape' => 'EndpointArn', ], 'EndpointConfigName' => [ 'shape' => 'EndpointConfigName', ], 'ProductionVariants' => [ 'shape' => 'ProductionVariantSummaryList', ], 'DataCaptureConfig' => [ 'shape' => 'DataCaptureConfigSummary', ], 'EndpointStatus' => [ 'shape' => 'EndpointStatus', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastDeploymentConfig' => [ 'shape' => 'DeploymentConfig', ], 'AsyncInferenceConfig' => [ 'shape' => 'AsyncInferenceConfig', ], 'PendingDeploymentSummary' => [ 'shape' => 'PendingDeploymentSummary', ], 'ExplainerConfig' => [ 'shape' => 'ExplainerConfig', ], 'ShadowProductionVariants' => [ 'shape' => 'ProductionVariantSummaryList', ], ], ], 'DescribeExperimentRequest' => [ 'type' => 'structure', 'required' => [ 'ExperimentName', ], 'members' => [ 'ExperimentName' => [ 'shape' => 'ExperimentEntityName', ], ], ], 'DescribeExperimentResponse' => [ 'type' => 'structure', 'members' => [ 'ExperimentName' => [ 'shape' => 'ExperimentEntityName', ], 'ExperimentArn' => [ 'shape' => 'ExperimentArn', ], 'DisplayName' => [ 'shape' => 'ExperimentEntityName', ], 'Source' => [ 'shape' => 'ExperimentSource', ], 'Description' => [ 'shape' => 'ExperimentDescription', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'CreatedBy' => [ 'shape' => 'UserContext', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedBy' => [ 'shape' => 'UserContext', ], ], ], 'DescribeFeatureGroupRequest' => [ 'type' => 'structure', 'required' => [ 'FeatureGroupName', ], 'members' => [ 'FeatureGroupName' => [ 'shape' => 'FeatureGroupNameOrArn', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'DescribeFeatureGroupResponse' => [ 'type' => 'structure', 'required' => [ 'FeatureGroupArn', 'FeatureGroupName', 'RecordIdentifierFeatureName', 'EventTimeFeatureName', 'FeatureDefinitions', 'CreationTime', 'NextToken', ], 'members' => [ 'FeatureGroupArn' => [ 'shape' => 'FeatureGroupArn', ], 'FeatureGroupName' => [ 'shape' => 'FeatureGroupName', ], 'RecordIdentifierFeatureName' => [ 'shape' => 'FeatureName', ], 'EventTimeFeatureName' => [ 'shape' => 'FeatureName', ], 'FeatureDefinitions' => [ 'shape' => 'FeatureDefinitions', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'OnlineStoreConfig' => [ 'shape' => 'OnlineStoreConfig', ], 'OfflineStoreConfig' => [ 'shape' => 'OfflineStoreConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'FeatureGroupStatus' => [ 'shape' => 'FeatureGroupStatus', ], 'OfflineStoreStatus' => [ 'shape' => 'OfflineStoreStatus', ], 'LastUpdateStatus' => [ 'shape' => 'LastUpdateStatus', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'Description' => [ 'shape' => 'Description', ], 'NextToken' => [ 'shape' => 'NextToken', ], 'OnlineStoreTotalSizeBytes' => [ 'shape' => 'OnlineStoreTotalSizeBytes', ], ], ], 'DescribeFeatureMetadataRequest' => [ 'type' => 'structure', 'required' => [ 'FeatureGroupName', 'FeatureName', ], 'members' => [ 'FeatureGroupName' => [ 'shape' => 'FeatureGroupNameOrArn', ], 'FeatureName' => [ 'shape' => 'FeatureName', ], ], ], 'DescribeFeatureMetadataResponse' => [ 'type' => 'structure', 'required' => [ 'FeatureGroupArn', 'FeatureGroupName', 'FeatureName', 'FeatureType', 'CreationTime', 'LastModifiedTime', ], 'members' => [ 'FeatureGroupArn' => [ 'shape' => 'FeatureGroupArn', ], 'FeatureGroupName' => [ 'shape' => 'FeatureGroupName', ], 'FeatureName' => [ 'shape' => 'FeatureName', ], 'FeatureType' => [ 'shape' => 'FeatureType', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'Description' => [ 'shape' => 'FeatureDescription', ], 'Parameters' => [ 'shape' => 'FeatureParameters', ], ], ], 'DescribeFlowDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'FlowDefinitionName', ], 'members' => [ 'FlowDefinitionName' => [ 'shape' => 'FlowDefinitionName', ], ], ], 'DescribeFlowDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'FlowDefinitionArn', 'FlowDefinitionName', 'FlowDefinitionStatus', 'CreationTime', 'HumanLoopConfig', 'OutputConfig', 'RoleArn', ], 'members' => [ 'FlowDefinitionArn' => [ 'shape' => 'FlowDefinitionArn', ], 'FlowDefinitionName' => [ 'shape' => 'FlowDefinitionName', ], 'FlowDefinitionStatus' => [ 'shape' => 'FlowDefinitionStatus', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'HumanLoopRequestSource' => [ 'shape' => 'HumanLoopRequestSource', ], 'HumanLoopActivationConfig' => [ 'shape' => 'HumanLoopActivationConfig', ], 'HumanLoopConfig' => [ 'shape' => 'HumanLoopConfig', ], 'OutputConfig' => [ 'shape' => 'FlowDefinitionOutputConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], ], ], 'DescribeHubContentRequest' => [ 'type' => 'structure', 'required' => [ 'HubName', 'HubContentType', 'HubContentName', ], 'members' => [ 'HubName' => [ 'shape' => 'HubName', ], 'HubContentType' => [ 'shape' => 'HubContentType', ], 'HubContentName' => [ 'shape' => 'HubContentName', ], 'HubContentVersion' => [ 'shape' => 'HubContentVersion', ], ], ], 'DescribeHubContentResponse' => [ 'type' => 'structure', 'required' => [ 'HubContentName', 'HubContentArn', 'HubContentVersion', 'HubContentType', 'DocumentSchemaVersion', 'HubName', 'HubArn', 'HubContentDocument', 'HubContentStatus', 'CreationTime', ], 'members' => [ 'HubContentName' => [ 'shape' => 'HubContentName', ], 'HubContentArn' => [ 'shape' => 'HubContentArn', ], 'HubContentVersion' => [ 'shape' => 'HubContentVersion', ], 'HubContentType' => [ 'shape' => 'HubContentType', ], 'DocumentSchemaVersion' => [ 'shape' => 'DocumentSchemaVersion', ], 'HubName' => [ 'shape' => 'HubName', ], 'HubArn' => [ 'shape' => 'HubArn', ], 'HubContentDisplayName' => [ 'shape' => 'HubContentDisplayName', ], 'HubContentDescription' => [ 'shape' => 'HubContentDescription', ], 'HubContentMarkdown' => [ 'shape' => 'HubContentMarkdown', ], 'HubContentDocument' => [ 'shape' => 'HubContentDocument', ], 'HubContentSearchKeywords' => [ 'shape' => 'HubContentSearchKeywordList', ], 'HubContentDependencies' => [ 'shape' => 'HubContentDependencyList', ], 'HubContentStatus' => [ 'shape' => 'HubContentStatus', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], ], ], 'DescribeHubRequest' => [ 'type' => 'structure', 'required' => [ 'HubName', ], 'members' => [ 'HubName' => [ 'shape' => 'HubName', ], ], ], 'DescribeHubResponse' => [ 'type' => 'structure', 'required' => [ 'HubName', 'HubArn', 'HubStatus', 'CreationTime', 'LastModifiedTime', ], 'members' => [ 'HubName' => [ 'shape' => 'HubName', ], 'HubArn' => [ 'shape' => 'HubArn', ], 'HubDisplayName' => [ 'shape' => 'HubDisplayName', ], 'HubDescription' => [ 'shape' => 'HubDescription', ], 'HubSearchKeywords' => [ 'shape' => 'HubSearchKeywordList', ], 'S3StorageConfig' => [ 'shape' => 'HubS3StorageConfig', ], 'HubStatus' => [ 'shape' => 'HubStatus', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], ], ], 'DescribeHumanTaskUiRequest' => [ 'type' => 'structure', 'required' => [ 'HumanTaskUiName', ], 'members' => [ 'HumanTaskUiName' => [ 'shape' => 'HumanTaskUiName', ], ], ], 'DescribeHumanTaskUiResponse' => [ 'type' => 'structure', 'required' => [ 'HumanTaskUiArn', 'HumanTaskUiName', 'CreationTime', 'UiTemplate', ], 'members' => [ 'HumanTaskUiArn' => [ 'shape' => 'HumanTaskUiArn', ], 'HumanTaskUiName' => [ 'shape' => 'HumanTaskUiName', ], 'HumanTaskUiStatus' => [ 'shape' => 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=> [ 'shape' => 'HyperParameterTrainingJobDefinitions', ], 'HyperParameterTuningJobStatus' => [ 'shape' => 'HyperParameterTuningJobStatus', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'HyperParameterTuningEndTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'TrainingJobStatusCounters' => [ 'shape' => 'TrainingJobStatusCounters', ], 'ObjectiveStatusCounters' => [ 'shape' => 'ObjectiveStatusCounters', ], 'BestTrainingJob' => [ 'shape' => 'HyperParameterTrainingJobSummary', ], 'OverallBestTrainingJob' => [ 'shape' => 'HyperParameterTrainingJobSummary', ], 'WarmStartConfig' => [ 'shape' => 'HyperParameterTuningJobWarmStartConfig', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'TuningJobCompletionDetails' => [ 'shape' => 'HyperParameterTuningJobCompletionDetails', ], 'ConsumedResources' => [ 'shape' => 'HyperParameterTuningJobConsumedResources', ], 'Autotune' => [ 'shape' => 'Autotune', ], ], ], 'DescribeImageRequest' => [ 'type' => 'structure', 'required' => [ 'ImageName', ], 'members' => [ 'ImageName' => [ 'shape' => 'ImageName', ], ], ], 'DescribeImageResponse' => [ 'type' => 'structure', 'members' => [ 'CreationTime' => [ 'shape' => 'Timestamp', ], 'Description' => [ 'shape' => 'ImageDescription', ], 'DisplayName' => [ 'shape' => 'ImageDisplayName', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'ImageArn' => [ 'shape' => 'ImageArn', ], 'ImageName' => [ 'shape' => 'ImageName', ], 'ImageStatus' => [ 'shape' => 'ImageStatus', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], ], ], 'DescribeImageVersionRequest' => [ 'type' => 'structure', 'required' => [ 'ImageName', ], 'members' => [ 'ImageName' => [ 'shape' => 'ImageName', ], 'Version' => [ 'shape' => 'ImageVersionNumber', ], 'Alias' => [ 'shape' => 'SageMakerImageVersionAlias', ], ], ], 'DescribeImageVersionResponse' => [ 'type' => 'structure', 'members' => [ 'BaseImage' => [ 'shape' => 'ImageBaseImage', ], 'ContainerImage' => [ 'shape' => 'ImageContainerImage', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'ImageArn' => [ 'shape' => 'ImageArn', ], 'ImageVersionArn' => [ 'shape' => 'ImageVersionArn', ], 'ImageVersionStatus' => [ 'shape' => 'ImageVersionStatus', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'Version' => [ 'shape' => 'ImageVersionNumber', ], 'VendorGuidance' => [ 'shape' => 'VendorGuidance', ], 'JobType' => [ 'shape' => 'JobType', ], 'MLFramework' => [ 'shape' => 'MLFramework', ], 'ProgrammingLang' => [ 'shape' => 'ProgrammingLang', ], 'Processor' => [ 'shape' => 'Processor', ], 'Horovod' => [ 'shape' => 'Horovod', ], 'ReleaseNotes' => [ 'shape' => 'ReleaseNotes', ], ], ], 'DescribeInferenceExperimentRequest' => [ 'type' => 'structure', 'required' => [ 'Name', ], 'members' => [ 'Name' => [ 'shape' => 'InferenceExperimentName', ], ], ], 'DescribeInferenceExperimentResponse' => [ 'type' => 'structure', 'required' => [ 'Arn', 'Name', 'Type', 'Status', 'EndpointMetadata', 'ModelVariants', ], 'members' => [ 'Arn' => [ 'shape' => 'InferenceExperimentArn', ], 'Name' => [ 'shape' => 'InferenceExperimentName', ], 'Type' => [ 'shape' => 'InferenceExperimentType', ], 'Schedule' => [ 'shape' => 'InferenceExperimentSchedule', ], 'Status' => [ 'shape' => 'InferenceExperimentStatus', ], 'StatusReason' => [ 'shape' => 'InferenceExperimentStatusReason', ], 'Description' => [ 'shape' => 'InferenceExperimentDescription', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'CompletionTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'EndpointMetadata' => [ 'shape' => 'EndpointMetadata', ], 'ModelVariants' => [ 'shape' => 'ModelVariantConfigSummaryList', ], 'DataStorageConfig' => [ 'shape' => 'InferenceExperimentDataStorageConfig', ], 'ShadowModeConfig' => [ 'shape' => 'ShadowModeConfig', ], 'KmsKey' => [ 'shape' => 'KmsKeyId', ], ], ], 'DescribeInferenceRecommendationsJobRequest' => [ 'type' => 'structure', 'required' => [ 'JobName', ], 'members' => [ 'JobName' => [ 'shape' => 'RecommendationJobName', ], ], ], 'DescribeInferenceRecommendationsJobResponse' => [ 'type' => 'structure', 'required' => [ 'JobName', 'JobType', 'JobArn', 'RoleArn', 'Status', 'CreationTime', 'LastModifiedTime', 'InputConfig', ], 'members' => [ 'JobName' => [ 'shape' => 'RecommendationJobName', ], 'JobDescription' => [ 'shape' => 'RecommendationJobDescription', ], 'JobType' => [ 'shape' => 'RecommendationJobType', ], 'JobArn' => [ 'shape' => 'RecommendationJobArn', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'Status' => [ 'shape' => 'RecommendationJobStatus', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'CompletionTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'InputConfig' => [ 'shape' => 'RecommendationJobInputConfig', ], 'StoppingConditions' => [ 'shape' => 'RecommendationJobStoppingConditions', ], 'InferenceRecommendations' => [ 'shape' => 'InferenceRecommendations', ], 'EndpointPerformances' => [ 'shape' => 'EndpointPerformances', ], ], ], 'DescribeLabelingJobRequest' => [ 'type' => 'structure', 'required' => [ 'LabelingJobName', ], 'members' => [ 'LabelingJobName' => [ 'shape' => 'LabelingJobName', ], ], ], 'DescribeLabelingJobResponse' => [ 'type' => 'structure', 'required' => [ 'LabelingJobStatus', 'LabelCounters', 'CreationTime', 'LastModifiedTime', 'JobReferenceCode', 'LabelingJobName', 'LabelingJobArn', 'InputConfig', 'OutputConfig', 'RoleArn', 'HumanTaskConfig', ], 'members' => [ 'LabelingJobStatus' => [ 'shape' => 'LabelingJobStatus', ], 'LabelCounters' => [ 'shape' => 'LabelCounters', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'JobReferenceCode' => [ 'shape' => 'JobReferenceCode', ], 'LabelingJobName' => [ 'shape' => 'LabelingJobName', ], 'LabelingJobArn' => [ 'shape' => 'LabelingJobArn', ], 'LabelAttributeName' => [ 'shape' => 'LabelAttributeName', ], 'InputConfig' => [ 'shape' => 'LabelingJobInputConfig', ], 'OutputConfig' => [ 'shape' => 'LabelingJobOutputConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'LabelCategoryConfigS3Uri' => [ 'shape' => 'S3Uri', ], 'StoppingConditions' => [ 'shape' => 'LabelingJobStoppingConditions', ], 'LabelingJobAlgorithmsConfig' => [ 'shape' => 'LabelingJobAlgorithmsConfig', ], 'HumanTaskConfig' => [ 'shape' => 'HumanTaskConfig', ], 'Tags' => [ 'shape' => 'TagList', ], 'LabelingJobOutput' => [ 'shape' => 'LabelingJobOutput', ], ], ], 'DescribeLineageGroupRequest' => [ 'type' => 'structure', 'required' => [ 'LineageGroupName', ], 'members' => [ 'LineageGroupName' => [ 'shape' => 'ExperimentEntityName', ], ], ], 'DescribeLineageGroupResponse' => [ 'type' => 'structure', 'members' => [ 'LineageGroupName' => [ 'shape' => 'ExperimentEntityName', ], 'LineageGroupArn' => [ 'shape' => 'LineageGroupArn', ], 'DisplayName' => [ 'shape' => 'ExperimentEntityName', ], 'Description' => [ 'shape' => 'ExperimentDescription', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'CreatedBy' => [ 'shape' => 'UserContext', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedBy' => [ 'shape' => 'UserContext', ], ], ], 'DescribeModelBiasJobDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionName', ], 'members' => [ 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], ], ], 'DescribeModelBiasJobDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionArn', 'JobDefinitionName', 'CreationTime', 'ModelBiasAppSpecification', 'ModelBiasJobInput', 'ModelBiasJobOutputConfig', 'JobResources', 'RoleArn', ], 'members' => [ 'JobDefinitionArn' => [ 'shape' => 'MonitoringJobDefinitionArn', ], 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'ModelBiasBaselineConfig' => [ 'shape' => 'ModelBiasBaselineConfig', ], 'ModelBiasAppSpecification' => [ 'shape' => 'ModelBiasAppSpecification', ], 'ModelBiasJobInput' => [ 'shape' => 'ModelBiasJobInput', ], 'ModelBiasJobOutputConfig' => [ 'shape' => 'MonitoringOutputConfig', ], 'JobResources' => [ 'shape' => 'MonitoringResources', ], 'NetworkConfig' => [ 'shape' => 'MonitoringNetworkConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'StoppingCondition' => [ 'shape' => 'MonitoringStoppingCondition', ], ], ], 'DescribeModelCardExportJobRequest' => [ 'type' => 'structure', 'required' => [ 'ModelCardExportJobArn', ], 'members' => [ 'ModelCardExportJobArn' => [ 'shape' => 'ModelCardExportJobArn', ], ], ], 'DescribeModelCardExportJobResponse' => [ 'type' => 'structure', 'required' => [ 'ModelCardExportJobName', 'ModelCardExportJobArn', 'Status', 'ModelCardName', 'ModelCardVersion', 'OutputConfig', 'CreatedAt', 'LastModifiedAt', ], 'members' => [ 'ModelCardExportJobName' => [ 'shape' => 'EntityName', ], 'ModelCardExportJobArn' => [ 'shape' => 'ModelCardExportJobArn', ], 'Status' => [ 'shape' => 'ModelCardExportJobStatus', ], 'ModelCardName' => [ 'shape' => 'EntityName', ], 'ModelCardVersion' => [ 'shape' => 'Integer', ], 'OutputConfig' => [ 'shape' => 'ModelCardExportOutputConfig', ], 'CreatedAt' => [ 'shape' => 'Timestamp', ], 'LastModifiedAt' => [ 'shape' => 'Timestamp', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'ExportArtifacts' => [ 'shape' => 'ModelCardExportArtifacts', ], ], ], 'DescribeModelCardRequest' => [ 'type' => 'structure', 'required' => [ 'ModelCardName', ], 'members' => [ 'ModelCardName' => [ 'shape' => 'ModelCardNameOrArn', ], 'ModelCardVersion' => [ 'shape' => 'Integer', ], ], ], 'DescribeModelCardResponse' => [ 'type' => 'structure', 'required' => [ 'ModelCardArn', 'ModelCardName', 'ModelCardVersion', 'Content', 'ModelCardStatus', 'CreationTime', 'CreatedBy', ], 'members' => [ 'ModelCardArn' => [ 'shape' => 'ModelCardArn', ], 'ModelCardName' => [ 'shape' => 'EntityName', ], 'ModelCardVersion' => [ 'shape' => 'Integer', ], 'Content' => [ 'shape' => 'ModelCardContent', ], 'ModelCardStatus' => [ 'shape' => 'ModelCardStatus', ], 'SecurityConfig' => [ 'shape' => 'ModelCardSecurityConfig', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'CreatedBy' => [ 'shape' => 'UserContext', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedBy' => [ 'shape' => 'UserContext', ], 'ModelCardProcessingStatus' => [ 'shape' => 'ModelCardProcessingStatus', ], ], ], 'DescribeModelExplainabilityJobDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionName', ], 'members' => [ 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], ], ], 'DescribeModelExplainabilityJobDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionArn', 'JobDefinitionName', 'CreationTime', 'ModelExplainabilityAppSpecification', 'ModelExplainabilityJobInput', 'ModelExplainabilityJobOutputConfig', 'JobResources', 'RoleArn', ], 'members' => [ 'JobDefinitionArn' => [ 'shape' => 'MonitoringJobDefinitionArn', ], 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'ModelExplainabilityBaselineConfig' => [ 'shape' => 'ModelExplainabilityBaselineConfig', ], 'ModelExplainabilityAppSpecification' => [ 'shape' => 'ModelExplainabilityAppSpecification', ], 'ModelExplainabilityJobInput' => [ 'shape' => 'ModelExplainabilityJobInput', ], 'ModelExplainabilityJobOutputConfig' => [ 'shape' => 'MonitoringOutputConfig', ], 'JobResources' => [ 'shape' => 'MonitoringResources', ], 'NetworkConfig' => [ 'shape' => 'MonitoringNetworkConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'StoppingCondition' => [ 'shape' => 'MonitoringStoppingCondition', ], ], ], 'DescribeModelInput' => [ 'type' => 'structure', 'required' => [ 'ModelName', ], 'members' => [ 'ModelName' => [ 'shape' => 'ModelName', ], ], ], 'DescribeModelOutput' => [ 'type' => 'structure', 'required' => [ 'ModelName', 'ExecutionRoleArn', 'CreationTime', 'ModelArn', ], 'members' => [ 'ModelName' => [ 'shape' => 'ModelName', ], 'PrimaryContainer' => [ 'shape' => 'ContainerDefinition', ], 'Containers' => [ 'shape' => 'ContainerDefinitionList', ], 'InferenceExecutionConfig' => [ 'shape' => 'InferenceExecutionConfig', ], 'ExecutionRoleArn' => [ 'shape' => 'RoleArn', ], 'VpcConfig' => [ 'shape' => 'VpcConfig', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'ModelArn' => [ 'shape' => 'ModelArn', ], 'EnableNetworkIsolation' => [ 'shape' => 'Boolean', ], 'DeploymentRecommendation' => [ 'shape' => 'DeploymentRecommendation', ], ], ], 'DescribeModelPackageGroupInput' => [ 'type' => 'structure', 'required' => [ 'ModelPackageGroupName', ], 'members' => [ 'ModelPackageGroupName' => [ 'shape' => 'ArnOrName', ], ], ], 'DescribeModelPackageGroupOutput' => [ 'type' => 'structure', 'required' => [ 'ModelPackageGroupName', 'ModelPackageGroupArn', 'CreationTime', 'CreatedBy', 'ModelPackageGroupStatus', ], 'members' => [ 'ModelPackageGroupName' => [ 'shape' => 'EntityName', ], 'ModelPackageGroupArn' => [ 'shape' => 'ModelPackageGroupArn', ], 'ModelPackageGroupDescription' => [ 'shape' => 'EntityDescription', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'CreatedBy' => [ 'shape' => 'UserContext', ], 'ModelPackageGroupStatus' => [ 'shape' => 'ModelPackageGroupStatus', ], ], ], 'DescribeModelPackageInput' => [ 'type' => 'structure', 'required' => [ 'ModelPackageName', ], 'members' => [ 'ModelPackageName' => [ 'shape' => 'VersionedArnOrName', ], ], ], 'DescribeModelPackageOutput' => [ 'type' => 'structure', 'required' => [ 'ModelPackageName', 'ModelPackageArn', 'CreationTime', 'ModelPackageStatus', 'ModelPackageStatusDetails', ], 'members' => [ 'ModelPackageName' => [ 'shape' => 'EntityName', ], 'ModelPackageGroupName' => [ 'shape' => 'EntityName', ], 'ModelPackageVersion' => [ 'shape' => 'ModelPackageVersion', ], 'ModelPackageArn' => [ 'shape' => 'ModelPackageArn', ], 'ModelPackageDescription' => [ 'shape' => 'EntityDescription', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'InferenceSpecification' => [ 'shape' => 'InferenceSpecification', ], 'SourceAlgorithmSpecification' => [ 'shape' => 'SourceAlgorithmSpecification', ], 'ValidationSpecification' => [ 'shape' => 'ModelPackageValidationSpecification', ], 'ModelPackageStatus' => [ 'shape' => 'ModelPackageStatus', ], 'ModelPackageStatusDetails' => [ 'shape' => 'ModelPackageStatusDetails', ], 'CertifyForMarketplace' => [ 'shape' => 'CertifyForMarketplace', ], 'ModelApprovalStatus' => [ 'shape' => 'ModelApprovalStatus', ], 'CreatedBy' => [ 'shape' => 'UserContext', ], 'MetadataProperties' => [ 'shape' => 'MetadataProperties', ], 'ModelMetrics' => [ 'shape' => 'ModelMetrics', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedBy' => [ 'shape' => 'UserContext', ], 'ApprovalDescription' => [ 'shape' => 'ApprovalDescription', ], 'CustomerMetadataProperties' => [ 'shape' => 'CustomerMetadataMap', ], 'DriftCheckBaselines' => [ 'shape' => 'DriftCheckBaselines', ], 'Domain' => [ 'shape' => 'String', ], 'Task' => [ 'shape' => 'String', ], 'SamplePayloadUrl' => [ 'shape' => 'String', ], 'AdditionalInferenceSpecifications' => [ 'shape' => 'AdditionalInferenceSpecifications', ], 'SkipModelValidation' => [ 'shape' => 'SkipModelValidation', ], ], ], 'DescribeModelQualityJobDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionName', ], 'members' => [ 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], ], ], 'DescribeModelQualityJobDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionArn', 'JobDefinitionName', 'CreationTime', 'ModelQualityAppSpecification', 'ModelQualityJobInput', 'ModelQualityJobOutputConfig', 'JobResources', 'RoleArn', ], 'members' => [ 'JobDefinitionArn' => [ 'shape' => 'MonitoringJobDefinitionArn', ], 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'ModelQualityBaselineConfig' => [ 'shape' => 'ModelQualityBaselineConfig', ], 'ModelQualityAppSpecification' => [ 'shape' => 'ModelQualityAppSpecification', ], 'ModelQualityJobInput' => [ 'shape' => 'ModelQualityJobInput', ], 'ModelQualityJobOutputConfig' => [ 'shape' => 'MonitoringOutputConfig', ], 'JobResources' => [ 'shape' => 'MonitoringResources', ], 'NetworkConfig' => [ 'shape' => 'MonitoringNetworkConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'StoppingCondition' => [ 'shape' => 'MonitoringStoppingCondition', ], ], ], 'DescribeMonitoringScheduleRequest' => [ 'type' => 'structure', 'required' => [ 'MonitoringScheduleName', ], 'members' => [ 'MonitoringScheduleName' => [ 'shape' => 'MonitoringScheduleName', ], ], ], 'DescribeMonitoringScheduleResponse' => [ 'type' => 'structure', 'required' => [ 'MonitoringScheduleArn', 'MonitoringScheduleName', 'MonitoringScheduleStatus', 'CreationTime', 'LastModifiedTime', 'MonitoringScheduleConfig', ], 'members' => [ 'MonitoringScheduleArn' => [ 'shape' => 'MonitoringScheduleArn', ], 'MonitoringScheduleName' => [ 'shape' => 'MonitoringScheduleName', ], 'MonitoringScheduleStatus' => [ 'shape' => 'ScheduleStatus', ], 'MonitoringType' => [ 'shape' => 'MonitoringType', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'MonitoringScheduleConfig' => [ 'shape' => 'MonitoringScheduleConfig', ], 'EndpointName' => [ 'shape' => 'EndpointName', ], 'LastMonitoringExecutionSummary' => [ 'shape' => 'MonitoringExecutionSummary', ], ], ], 'DescribeNotebookInstanceInput' => [ 'type' => 'structure', 'required' => [ 'NotebookInstanceName', ], 'members' => [ 'NotebookInstanceName' => [ 'shape' => 'NotebookInstanceName', ], ], ], 'DescribeNotebookInstanceLifecycleConfigInput' => [ 'type' => 'structure', 'required' => [ 'NotebookInstanceLifecycleConfigName', ], 'members' => [ 'NotebookInstanceLifecycleConfigName' => [ 'shape' => 'NotebookInstanceLifecycleConfigName', ], ], ], 'DescribeNotebookInstanceLifecycleConfigOutput' => [ 'type' => 'structure', 'members' => [ 'NotebookInstanceLifecycleConfigArn' => [ 'shape' => 'NotebookInstanceLifecycleConfigArn', ], 'NotebookInstanceLifecycleConfigName' => [ 'shape' => 'NotebookInstanceLifecycleConfigName', ], 'OnCreate' => [ 'shape' => 'NotebookInstanceLifecycleConfigList', ], 'OnStart' => [ 'shape' => 'NotebookInstanceLifecycleConfigList', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], ], ], 'DescribeNotebookInstanceOutput' => [ 'type' => 'structure', 'members' => [ 'NotebookInstanceArn' => [ 'shape' => 'NotebookInstanceArn', ], 'NotebookInstanceName' => [ 'shape' => 'NotebookInstanceName', ], 'NotebookInstanceStatus' => [ 'shape' => 'NotebookInstanceStatus', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'Url' => [ 'shape' => 'NotebookInstanceUrl', ], 'InstanceType' => [ 'shape' => 'InstanceType', ], 'SubnetId' => [ 'shape' => 'SubnetId', ], 'SecurityGroups' => [ 'shape' => 'SecurityGroupIds', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'KmsKeyId' => [ 'shape' => 'KmsKeyId', ], 'NetworkInterfaceId' => [ 'shape' => 'NetworkInterfaceId', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'NotebookInstanceLifecycleConfigName' => [ 'shape' => 'NotebookInstanceLifecycleConfigName', ], 'DirectInternetAccess' => [ 'shape' => 'DirectInternetAccess', ], 'VolumeSizeInGB' => [ 'shape' => 'NotebookInstanceVolumeSizeInGB', ], 'AcceleratorTypes' => [ 'shape' => 'NotebookInstanceAcceleratorTypes', ], 'DefaultCodeRepository' => [ 'shape' => 'CodeRepositoryNameOrUrl', ], 'AdditionalCodeRepositories' => [ 'shape' => 'AdditionalCodeRepositoryNamesOrUrls', ], 'RootAccess' => [ 'shape' => 'RootAccess', ], 'PlatformIdentifier' => [ 'shape' => 'PlatformIdentifier', ], 'InstanceMetadataServiceConfiguration' => [ 'shape' => 'InstanceMetadataServiceConfiguration', ], ], ], 'DescribePipelineDefinitionForExecutionRequest' => [ 'type' => 'structure', 'required' => [ 'PipelineExecutionArn', ], 'members' => [ 'PipelineExecutionArn' => [ 'shape' => 'PipelineExecutionArn', ], ], ], 'DescribePipelineDefinitionForExecutionResponse' => [ 'type' => 'structure', 'members' => [ 'PipelineDefinition' => [ 'shape' => 'PipelineDefinition', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], ], ], 'DescribePipelineExecutionRequest' => [ 'type' => 'structure', 'required' => [ 'PipelineExecutionArn', ], 'members' => [ 'PipelineExecutionArn' => [ 'shape' => 'PipelineExecutionArn', ], ], ], 'DescribePipelineExecutionResponse' => [ 'type' => 'structure', 'members' => [ 'PipelineArn' => [ 'shape' => 'PipelineArn', ], 'PipelineExecutionArn' => [ 'shape' => 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'RoleArn', ], 'SecurityGroups' => [ 'shape' => 'SecurityGroupIds', ], 'SharingSettings' => [ 'shape' => 'SharingSettings', ], 'JupyterServerAppSettings' => [ 'shape' => 'JupyterServerAppSettings', ], 'KernelGatewayAppSettings' => [ 'shape' => 'KernelGatewayAppSettings', ], 'TensorBoardAppSettings' => [ 'shape' => 'TensorBoardAppSettings', ], 'RStudioServerProAppSettings' => [ 'shape' => 'RStudioServerProAppSettings', ], 'RSessionAppSettings' => [ 'shape' => 'RSessionAppSettings', ], 'CanvasAppSettings' => [ 'shape' => 'CanvasAppSettings', ], ], ], 'UsersPerStep' => [ 'type' => 'integer', 'max' => 3, 'min' => 1, ], 'UtilizationMetric' => [ 'type' => 'float', 'min' => 0.0, ], 'UtilizationPercentagePerCore' => [ 'type' => 'integer', 'max' => 100, 'min' => 1, ], 'ValidationFraction' => [ 'type' => 'float', 'max' => 1, 'min' => 0, ], 'VariantName' => [ 'type' => 'string', 'max' => 63, 'pattern' => '^[a-zA-Z0-9](-*[a-zA-Z0-9]){0,62}', ], 'VariantProperty' => [ 'type' => 'structure', 'required' => [ 'VariantPropertyType', ], 'members' => [ 'VariantPropertyType' => [ 'shape' => 'VariantPropertyType', ], ], ], 'VariantPropertyList' => [ 'type' => 'list', 'member' => [ 'shape' => 'VariantProperty', ], 'max' => 3, 'min' => 0, ], 'VariantPropertyType' => [ 'type' => 'string', 'enum' => [ 'DesiredInstanceCount', 'DesiredWeight', 'DataCaptureConfig', ], ], 'VariantStatus' => [ 'type' => 'string', 'enum' => [ 'Creating', 'Updating', 'Deleting', 'ActivatingTraffic', 'Baking', ], ], 'VariantStatusMessage' => [ 'type' => 'string', 'max' => 1024, ], 'VariantWeight' => [ 'type' => 'float', 'min' => 0, ], 'VectorConfig' => [ 'type' => 'structure', 'required' => [ 'Dimension', ], 'members' => [ 'Dimension' => [ 'shape' => 'Dimension', ], ], ], 'VendorGuidance' => [ 'type' => 'string', 'enum' => [ 'NOT_PROVIDED', 'STABLE', 'TO_BE_ARCHIVED', 'ARCHIVED', ], ], 'VersionId' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, 'pattern' => '.+', ], 'VersionedArnOrName' => [ 'type' => 'string', 'max' => 176, 'min' => 1, 'pattern' => '(arn:aws[a-z\\-]*:sagemaker:[a-z0-9\\-]*:[0-9]{12}:[a-z\\-]*\\/)?([a-zA-Z0-9]([a-zA-Z0-9-]){0,62})(? [ 'type' => 'structure', 'members' => [ 'Arn' => [ 'shape' => 'AssociationEntityArn', ], 'Type' => [ 'shape' => 'String40', ], 'LineageType' => [ 'shape' => 'LineageType', ], ], ], 'Vertices' => [ 'type' => 'list', 'member' => [ 'shape' => 'Vertex', ], ], 'VolumeSizeInGB' => [ 'type' => 'integer', 'min' => 1, ], 'VpcConfig' => [ 'type' => 'structure', 'required' => [ 'SecurityGroupIds', 'Subnets', ], 'members' => [ 'SecurityGroupIds' => [ 'shape' => 'VpcSecurityGroupIds', ], 'Subnets' => [ 'shape' => 'Subnets', ], ], ], 'VpcId' => [ 'type' => 'string', 'max' => 32, 'pattern' => '[-0-9a-zA-Z]+', ], 'VpcSecurityGroupIds' => [ 'type' => 'list', 'member' => [ 'shape' => 'SecurityGroupId', ], 'max' => 5, 'min' => 1, ], 'WaitIntervalInSeconds' => [ 'type' => 'integer', 'max' => 3600, 'min' => 0, ], 'WarmPoolResourceStatus' => [ 'type' => 'string', 'enum' => [ 'Available', 'Terminated', 'Reused', 'InUse', ], ], 'WarmPoolStatus' => [ 'type' => 'structure', 'required' => [ 'Status', ], 'members' => [ 'Status' => [ 'shape' => 'WarmPoolResourceStatus', ], 'ResourceRetainedBillableTimeInSeconds' => [ 'shape' => 'ResourceRetainedBillableTimeInSeconds', ], 'ReusedByJob' => [ 'shape' => 'TrainingJobName', ], ], ], 'Workforce' => [ 'type' => 'structure', 'required' => [ 'WorkforceName', 'WorkforceArn', ], 'members' => [ 'WorkforceName' => [ 'shape' => 'WorkforceName', ], 'WorkforceArn' => [ 'shape' => 'WorkforceArn', ], 'LastUpdatedDate' => [ 'shape' => 'Timestamp', ], 'SourceIpConfig' => [ 'shape' => 'SourceIpConfig', ], 'SubDomain' => [ 'shape' => 'String', ], 'CognitoConfig' => [ 'shape' => 'CognitoConfig', ], 'OidcConfig' => [ 'shape' => 'OidcConfigForResponse', ], 'CreateDate' => [ 'shape' => 'Timestamp', ], 'WorkforceVpcConfig' => [ 'shape' => 'WorkforceVpcConfigResponse', ], 'Status' => [ 'shape' => 'WorkforceStatus', ], 'FailureReason' => [ 'shape' => 'WorkforceFailureReason', ], ], ], 'WorkforceArn' => [ 'type' => 'string', 'max' => 256, 'pattern' => 'arn:aws[a-z\\-]*:sagemaker:[a-z0-9\\-]*:[0-9]{12}:workforce/.*', ], 'WorkforceFailureReason' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, 'pattern' => '.+', ], 'WorkforceName' => [ 'type' => 'string', 'max' => 63, 'min' => 1, 'pattern' => '^[a-zA-Z0-9]([a-zA-Z0-9\\-]){0,62}$', ], 'WorkforceSecurityGroupId' => [ 'type' => 'string', 'max' => 32, 'pattern' => '^sg-[0-9a-z]*$', ], 'WorkforceSecurityGroupIds' => [ 'type' => 'list', 'member' => [ 'shape' => 'WorkforceSecurityGroupId', ], 'max' => 5, 'min' => 1, ], 'WorkforceStatus' => [ 'type' => 'string', 'enum' => [ 'Initializing', 'Updating', 'Deleting', 'Failed', 'Active', ], ], 'WorkforceSubnetId' => [ 'type' => 'string', 'max' => 32, 'pattern' => '^subnet-[0-9a-z]*$', ], 'WorkforceSubnets' => [ 'type' => 'list', 'member' => [ 'shape' => 'WorkforceSubnetId', ], 'max' => 16, 'min' => 1, ], 'WorkforceVpcConfigRequest' => [ 'type' => 'structure', 'members' => [ 'VpcId' => [ 'shape' => 'WorkforceVpcId', ], 'SecurityGroupIds' => [ 'shape' => 'WorkforceSecurityGroupIds', ], 'Subnets' => [ 'shape' => 'WorkforceSubnets', ], ], ], 'WorkforceVpcConfigResponse' => [ 'type' => 'structure', 'required' => [ 'VpcId', 'SecurityGroupIds', 'Subnets', ], 'members' => [ 'VpcId' => [ 'shape' => 'WorkforceVpcId', ], 'SecurityGroupIds' => [ 'shape' => 'WorkforceSecurityGroupIds', ], 'Subnets' => [ 'shape' => 'WorkforceSubnets', ], 'VpcEndpointId' => [ 'shape' => 'WorkforceVpcEndpointId', ], ], ], 'WorkforceVpcEndpointId' => [ 'type' => 'string', 'max' => 255, 'min' => 1, 'pattern' => '^vpce-[0-9a-z]*$', ], 'WorkforceVpcId' => [ 'type' => 'string', 'max' => 32, 'pattern' => '^vpc-[0-9a-z]*$', ], 'Workforces' => [ 'type' => 'list', 'member' => [ 'shape' => 'Workforce', ], ], 'WorkspaceSettings' => [ 'type' => 'structure', 'members' => [ 'S3ArtifactPath' => [ 'shape' => 'S3Uri', ], 'S3KmsKeyId' => [ 'shape' => 'KmsKeyId', ], ], ], 'Workteam' => [ 'type' => 'structure', 'required' => [ 'WorkteamName', 'MemberDefinitions', 'WorkteamArn', 'Description', ], 'members' => [ 'WorkteamName' => [ 'shape' => 'WorkteamName', ], 'MemberDefinitions' => [ 'shape' => 'MemberDefinitions', ], 'WorkteamArn' => [ 'shape' => 'WorkteamArn', ], 'WorkforceArn' => [ 'shape' => 'WorkforceArn', ], 'ProductListingIds' => [ 'shape' => 'ProductListings', ], 'Description' => [ 'shape' => 'String200', ], 'SubDomain' => [ 'shape' => 'String', ], 'CreateDate' => [ 'shape' => 'Timestamp', ], 'LastUpdatedDate' => [ 'shape' => 'Timestamp', ], 'NotificationConfiguration' => [ 'shape' => 'NotificationConfiguration', ], ], ], 'WorkteamArn' => [ 'type' => 'string', 'max' => 256, 'pattern' => 'arn:aws[a-z\\-]*:sagemaker:[a-z0-9\\-]*:[0-9]{12}:workteam/.*', ], 'WorkteamName' => [ 'type' => 'string', 'max' => 63, 'min' => 1, 'pattern' => '^[a-zA-Z0-9](-*[a-zA-Z0-9]){0,62}', ], 'Workteams' => [ 'type' => 'list', 'member' => [ 'shape' => 'Workteam', ], ], ],]; +return [ 'version' => '2.0', 'metadata' => [ 'apiVersion' => '2017-07-24', 'endpointPrefix' => 'api.sagemaker', 'jsonVersion' => '1.1', 'protocol' => 'json', 'serviceAbbreviation' => 'SageMaker', 'serviceFullName' => 'Amazon SageMaker Service', 'serviceId' => 'SageMaker', 'signatureVersion' => 'v4', 'signingName' => 'sagemaker', 'targetPrefix' => 'SageMaker', 'uid' => 'sagemaker-2017-07-24', ], 'operations' => [ 'AddAssociation' => [ 'name' => 'AddAssociation', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'AddAssociationRequest', ], 'output' => [ 'shape' => 'AddAssociationResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'AddTags' => [ 'name' => 'AddTags', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'AddTagsInput', ], 'output' => [ 'shape' => 'AddTagsOutput', ], ], 'AssociateTrialComponent' => [ 'name' => 'AssociateTrialComponent', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'AssociateTrialComponentRequest', ], 'output' => [ 'shape' => 'AssociateTrialComponentResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'BatchDescribeModelPackage' => [ 'name' => 'BatchDescribeModelPackage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'BatchDescribeModelPackageInput', ], 'output' => [ 'shape' => 'BatchDescribeModelPackageOutput', ], ], 'CreateAction' => [ 'name' => 'CreateAction', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateActionRequest', ], 'output' => [ 'shape' => 'CreateActionResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateAlgorithm' => [ 'name' => 'CreateAlgorithm', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateAlgorithmInput', ], 'output' => [ 'shape' => 'CreateAlgorithmOutput', ], ], 'CreateApp' => [ 'name' => 'CreateApp', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateAppRequest', ], 'output' => [ 'shape' => 'CreateAppResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateAppImageConfig' => [ 'name' => 'CreateAppImageConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateAppImageConfigRequest', ], 'output' => [ 'shape' => 'CreateAppImageConfigResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], ], ], 'CreateArtifact' => [ 'name' => 'CreateArtifact', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateArtifactRequest', ], 'output' => [ 'shape' => 'CreateArtifactResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateAutoMLJob' => [ 'name' => 'CreateAutoMLJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateAutoMLJobRequest', ], 'output' => [ 'shape' => 'CreateAutoMLJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateAutoMLJobV2' => [ 'name' => 'CreateAutoMLJobV2', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateAutoMLJobV2Request', ], 'output' => [ 'shape' => 'CreateAutoMLJobV2Response', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateCodeRepository' => [ 'name' => 'CreateCodeRepository', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateCodeRepositoryInput', ], 'output' => [ 'shape' => 'CreateCodeRepositoryOutput', ], ], 'CreateCompilationJob' => [ 'name' => 'CreateCompilationJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateCompilationJobRequest', ], 'output' => [ 'shape' => 'CreateCompilationJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateContext' => [ 'name' => 'CreateContext', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateContextRequest', ], 'output' => [ 'shape' => 'CreateContextResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateDataQualityJobDefinition' => [ 'name' => 'CreateDataQualityJobDefinition', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateDataQualityJobDefinitionRequest', ], 'output' => [ 'shape' => 'CreateDataQualityJobDefinitionResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateDeviceFleet' => [ 'name' => 'CreateDeviceFleet', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateDeviceFleetRequest', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateDomain' => [ 'name' => 'CreateDomain', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateDomainRequest', ], 'output' => [ 'shape' => 'CreateDomainResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateEdgeDeploymentPlan' => [ 'name' => 'CreateEdgeDeploymentPlan', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateEdgeDeploymentPlanRequest', ], 'output' => [ 'shape' => 'CreateEdgeDeploymentPlanResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateEdgeDeploymentStage' => [ 'name' => 'CreateEdgeDeploymentStage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateEdgeDeploymentStageRequest', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateEdgePackagingJob' => [ 'name' => 'CreateEdgePackagingJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateEdgePackagingJobRequest', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateEndpoint' => [ 'name' => 'CreateEndpoint', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateEndpointInput', ], 'output' => [ 'shape' => 'CreateEndpointOutput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateEndpointConfig' => [ 'name' => 'CreateEndpointConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateEndpointConfigInput', ], 'output' => [ 'shape' => 'CreateEndpointConfigOutput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateExperiment' => [ 'name' => 'CreateExperiment', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateExperimentRequest', ], 'output' => [ 'shape' => 'CreateExperimentResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateFeatureGroup' => [ 'name' => 'CreateFeatureGroup', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateFeatureGroupRequest', ], 'output' => [ 'shape' => 'CreateFeatureGroupResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateFlowDefinition' => [ 'name' => 'CreateFlowDefinition', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateFlowDefinitionRequest', ], 'output' => [ 'shape' => 'CreateFlowDefinitionResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateHub' => [ 'name' => 'CreateHub', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateHubRequest', ], 'output' => [ 'shape' => 'CreateHubResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateHumanTaskUi' => [ 'name' => 'CreateHumanTaskUi', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateHumanTaskUiRequest', ], 'output' => [ 'shape' => 'CreateHumanTaskUiResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateHyperParameterTuningJob' => [ 'name' => 'CreateHyperParameterTuningJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateHyperParameterTuningJobRequest', ], 'output' => [ 'shape' => 'CreateHyperParameterTuningJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateImage' => [ 'name' => 'CreateImage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateImageRequest', ], 'output' => [ 'shape' => 'CreateImageResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateImageVersion' => [ 'name' => 'CreateImageVersion', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateImageVersionRequest', ], 'output' => [ 'shape' => 'CreateImageVersionResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'CreateInferenceExperiment' => [ 'name' => 'CreateInferenceExperiment', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateInferenceExperimentRequest', ], 'output' => [ 'shape' => 'CreateInferenceExperimentResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateInferenceRecommendationsJob' => [ 'name' => 'CreateInferenceRecommendationsJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateInferenceRecommendationsJobRequest', ], 'output' => [ 'shape' => 'CreateInferenceRecommendationsJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateLabelingJob' => [ 'name' => 'CreateLabelingJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateLabelingJobRequest', ], 'output' => [ 'shape' => 'CreateLabelingJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateModel' => [ 'name' => 'CreateModel', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateModelInput', ], 'output' => [ 'shape' => 'CreateModelOutput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateModelBiasJobDefinition' => [ 'name' => 'CreateModelBiasJobDefinition', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateModelBiasJobDefinitionRequest', ], 'output' => [ 'shape' => 'CreateModelBiasJobDefinitionResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateModelCard' => [ 'name' => 'CreateModelCard', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateModelCardRequest', ], 'output' => [ 'shape' => 'CreateModelCardResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ConflictException', ], ], ], 'CreateModelCardExportJob' => [ 'name' => 'CreateModelCardExportJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateModelCardExportJobRequest', ], 'output' => [ 'shape' => 'CreateModelCardExportJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ConflictException', ], ], ], 'CreateModelExplainabilityJobDefinition' => [ 'name' => 'CreateModelExplainabilityJobDefinition', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateModelExplainabilityJobDefinitionRequest', ], 'output' => [ 'shape' => 'CreateModelExplainabilityJobDefinitionResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateModelPackage' => [ 'name' => 'CreateModelPackage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateModelPackageInput', ], 'output' => [ 'shape' => 'CreateModelPackageOutput', ], 'errors' => [ [ 'shape' => 'ConflictException', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateModelPackageGroup' => [ 'name' => 'CreateModelPackageGroup', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateModelPackageGroupInput', ], 'output' => [ 'shape' => 'CreateModelPackageGroupOutput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateModelQualityJobDefinition' => [ 'name' => 'CreateModelQualityJobDefinition', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateModelQualityJobDefinitionRequest', ], 'output' => [ 'shape' => 'CreateModelQualityJobDefinitionResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateMonitoringSchedule' => [ 'name' => 'CreateMonitoringSchedule', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateMonitoringScheduleRequest', ], 'output' => [ 'shape' => 'CreateMonitoringScheduleResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateNotebookInstance' => [ 'name' => 'CreateNotebookInstance', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateNotebookInstanceInput', ], 'output' => [ 'shape' => 'CreateNotebookInstanceOutput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateNotebookInstanceLifecycleConfig' => [ 'name' => 'CreateNotebookInstanceLifecycleConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateNotebookInstanceLifecycleConfigInput', ], 'output' => [ 'shape' => 'CreateNotebookInstanceLifecycleConfigOutput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreatePipeline' => [ 'name' => 'CreatePipeline', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreatePipelineRequest', ], 'output' => [ 'shape' => 'CreatePipelineResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreatePresignedDomainUrl' => [ 'name' => 'CreatePresignedDomainUrl', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreatePresignedDomainUrlRequest', ], 'output' => [ 'shape' => 'CreatePresignedDomainUrlResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'CreatePresignedNotebookInstanceUrl' => [ 'name' => 'CreatePresignedNotebookInstanceUrl', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreatePresignedNotebookInstanceUrlInput', ], 'output' => [ 'shape' => 'CreatePresignedNotebookInstanceUrlOutput', ], ], 'CreateProcessingJob' => [ 'name' => 'CreateProcessingJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateProcessingJobRequest', ], 'output' => [ 'shape' => 'CreateProcessingJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'CreateProject' => [ 'name' => 'CreateProject', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateProjectInput', ], 'output' => [ 'shape' => 'CreateProjectOutput', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateSpace' => [ 'name' => 'CreateSpace', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateSpaceRequest', ], 'output' => [ 'shape' => 'CreateSpaceResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateStudioLifecycleConfig' => [ 'name' => 'CreateStudioLifecycleConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateStudioLifecycleConfigRequest', ], 'output' => [ 'shape' => 'CreateStudioLifecycleConfigResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], ], ], 'CreateTrainingJob' => [ 'name' => 'CreateTrainingJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateTrainingJobRequest', ], 'output' => [ 'shape' => 'CreateTrainingJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'CreateTransformJob' => [ 'name' => 'CreateTransformJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateTransformJobRequest', ], 'output' => [ 'shape' => 'CreateTransformJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'CreateTrial' => [ 'name' => 'CreateTrial', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateTrialRequest', ], 'output' => [ 'shape' => 'CreateTrialResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateTrialComponent' => [ 'name' => 'CreateTrialComponent', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateTrialComponentRequest', ], 'output' => [ 'shape' => 'CreateTrialComponentResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], ], ], 'CreateUserProfile' => [ 'name' => 'CreateUserProfile', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateUserProfileRequest', ], 'output' => [ 'shape' => 'CreateUserProfileResponse', ], 'errors' => [ [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceInUse', ], ], ], 'CreateWorkforce' => [ 'name' => 'CreateWorkforce', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'CreateWorkforceRequest', ], 'output' => [ 'shape' => 'CreateWorkforceResponse', ], ], 'CreateWorkteam' => [ 'name' => 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[ 'shape' => 'DeleteContextRequest', ], 'output' => [ 'shape' => 'DeleteContextResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DeleteDataQualityJobDefinition' => [ 'name' => 'DeleteDataQualityJobDefinition', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DeleteDataQualityJobDefinitionRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DeleteDeviceFleet' => [ 'name' => 'DeleteDeviceFleet', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DeleteDeviceFleetRequest', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], ], ], 'DeleteDomain' => [ 'name' => 'DeleteDomain', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DeleteDomainRequest', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'DeleteEdgeDeploymentPlan' => [ 'name' => 'DeleteEdgeDeploymentPlan', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DeleteEdgeDeploymentPlanRequest', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], ], ], 'DeleteEdgeDeploymentStage' => [ 'name' => 'DeleteEdgeDeploymentStage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DeleteEdgeDeploymentStageRequest', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], ], ], 'DeleteEndpoint' => [ 'name' => 'DeleteEndpoint', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DeleteEndpointInput', ], ], 'DeleteEndpointConfig' => [ 'name' => 'DeleteEndpointConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DeleteEndpointConfigInput', ], ], 'DeleteExperiment' => [ 'name' => 'DeleteExperiment', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DeleteExperimentRequest', ], 'output' => [ 'shape' => 'DeleteExperimentResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DeleteFeatureGroup' => [ 'name' => 'DeleteFeatureGroup', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DeleteFeatureGroupRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DeleteFlowDefinition' => [ 'name' => 'DeleteFlowDefinition', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DeleteFlowDefinitionRequest', ], 'output' => [ 'shape' => 'DeleteFlowDefinitionResponse', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'DeleteHub' => [ 'name' => 'DeleteHub', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DeleteHubRequest', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'DeleteHubContent' => [ 'name' => 'DeleteHubContent', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DeleteHubContentRequest', ], 'errors' => [ [ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceNotFound', 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'requestUri' => '/', ], 'input' => [ 'shape' => 'DeleteInferenceExperimentRequest', ], 'output' => [ 'shape' => 'DeleteInferenceExperimentResponse', ], 'errors' => [ [ 'shape' => 'ConflictException', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'DeleteModel' => [ 'name' => 'DeleteModel', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DeleteModelInput', ], ], 'DeleteModelBiasJobDefinition' => [ 'name' => 'DeleteModelBiasJobDefinition', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DeleteModelBiasJobDefinitionRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DeleteModelCard' => [ 'name' => 'DeleteModelCard', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DeleteModelCardRequest', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], [ 'shape' => 'ConflictException', ], ], ], 'DeleteModelExplainabilityJobDefinition' => [ 'name' => 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[ 'name' => 'DescribeApp', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeAppRequest', ], 'output' => [ 'shape' => 'DescribeAppResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeAppImageConfig' => [ 'name' => 'DescribeAppImageConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeAppImageConfigRequest', ], 'output' => [ 'shape' => 'DescribeAppImageConfigResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeArtifact' => [ 'name' => 'DescribeArtifact', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeArtifactRequest', ], 'output' => [ 'shape' => 'DescribeArtifactResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeAutoMLJob' => [ 'name' => 'DescribeAutoMLJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeAutoMLJobRequest', ], 'output' => [ 'shape' => 'DescribeAutoMLJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeAutoMLJobV2' => [ 'name' => 'DescribeAutoMLJobV2', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeAutoMLJobV2Request', ], 'output' => [ 'shape' => 'DescribeAutoMLJobV2Response', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeCodeRepository' => [ 'name' => 'DescribeCodeRepository', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeCodeRepositoryInput', ], 'output' => [ 'shape' => 'DescribeCodeRepositoryOutput', ], ], 'DescribeCompilationJob' => [ 'name' => 'DescribeCompilationJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeCompilationJobRequest', ], 'output' => [ 'shape' => 'DescribeCompilationJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeContext' => [ 'name' => 'DescribeContext', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeContextRequest', ], 'output' => [ 'shape' => 'DescribeContextResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeDataQualityJobDefinition' => [ 'name' => 'DescribeDataQualityJobDefinition', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeDataQualityJobDefinitionRequest', ], 'output' => [ 'shape' => 'DescribeDataQualityJobDefinitionResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeDevice' => [ 'name' => 'DescribeDevice', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeDeviceRequest', ], 'output' => [ 'shape' => 'DescribeDeviceResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeDeviceFleet' => [ 'name' => 'DescribeDeviceFleet', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeDeviceFleetRequest', ], 'output' => [ 'shape' => 'DescribeDeviceFleetResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeDomain' => [ 'name' => 'DescribeDomain', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeDomainRequest', ], 'output' => [ 'shape' => 'DescribeDomainResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeEdgeDeploymentPlan' => [ 'name' => 'DescribeEdgeDeploymentPlan', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeEdgeDeploymentPlanRequest', ], 'output' => [ 'shape' => 'DescribeEdgeDeploymentPlanResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeEdgePackagingJob' => [ 'name' => 'DescribeEdgePackagingJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeEdgePackagingJobRequest', ], 'output' => [ 'shape' => 'DescribeEdgePackagingJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeEndpoint' => [ 'name' => 'DescribeEndpoint', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeEndpointInput', ], 'output' => [ 'shape' => 'DescribeEndpointOutput', ], ], 'DescribeEndpointConfig' => [ 'name' => 'DescribeEndpointConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeEndpointConfigInput', ], 'output' => [ 'shape' => 'DescribeEndpointConfigOutput', ], ], 'DescribeExperiment' => [ 'name' => 'DescribeExperiment', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeExperimentRequest', ], 'output' => [ 'shape' => 'DescribeExperimentResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeFeatureGroup' => [ 'name' => 'DescribeFeatureGroup', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeFeatureGroupRequest', ], 'output' => [ 'shape' => 'DescribeFeatureGroupResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeFeatureMetadata' => [ 'name' => 'DescribeFeatureMetadata', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeFeatureMetadataRequest', ], 'output' => [ 'shape' => 'DescribeFeatureMetadataResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeFlowDefinition' => [ 'name' => 'DescribeFlowDefinition', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeFlowDefinitionRequest', ], 'output' => [ 'shape' => 'DescribeFlowDefinitionResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeHub' => [ 'name' => 'DescribeHub', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeHubRequest', ], 'output' => [ 'shape' => 'DescribeHubResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeHubContent' => [ 'name' => 'DescribeHubContent', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeHubContentRequest', ], 'output' => [ 'shape' => 'DescribeHubContentResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeHumanTaskUi' => [ 'name' => 'DescribeHumanTaskUi', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeHumanTaskUiRequest', ], 'output' => [ 'shape' => 'DescribeHumanTaskUiResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeHyperParameterTuningJob' => [ 'name' => 'DescribeHyperParameterTuningJob', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeHyperParameterTuningJobRequest', ], 'output' => [ 'shape' => 'DescribeHyperParameterTuningJobResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeImage' => [ 'name' => 'DescribeImage', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeImageRequest', ], 'output' => [ 'shape' => 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'DescribeMonitoringSchedule' => [ 'name' => 'DescribeMonitoringSchedule', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeMonitoringScheduleRequest', ], 'output' => [ 'shape' => 'DescribeMonitoringScheduleResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'DescribeNotebookInstance' => [ 'name' => 'DescribeNotebookInstance', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeNotebookInstanceInput', ], 'output' => [ 'shape' => 'DescribeNotebookInstanceOutput', ], ], 'DescribeNotebookInstanceLifecycleConfig' => [ 'name' => 'DescribeNotebookInstanceLifecycleConfig', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DescribeNotebookInstanceLifecycleConfigInput', ], 'output' => [ 'shape' => 'DescribeNotebookInstanceLifecycleConfigOutput', ], ], 'DescribePipeline' => [ 'name' => 'DescribePipeline', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 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'/', ], 'input' => [ 'shape' => 'DescribeWorkteamRequest', ], 'output' => [ 'shape' => 'DescribeWorkteamResponse', ], ], 'DisableSagemakerServicecatalogPortfolio' => [ 'name' => 'DisableSagemakerServicecatalogPortfolio', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DisableSagemakerServicecatalogPortfolioInput', ], 'output' => [ 'shape' => 'DisableSagemakerServicecatalogPortfolioOutput', ], ], 'DisassociateTrialComponent' => [ 'name' => 'DisassociateTrialComponent', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'DisassociateTrialComponentRequest', ], 'output' => [ 'shape' => 'DisassociateTrialComponentResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'EnableSagemakerServicecatalogPortfolio' => [ 'name' => 'EnableSagemakerServicecatalogPortfolio', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'EnableSagemakerServicecatalogPortfolioInput', ], 'output' => [ 'shape' => 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[ 'shape' => 'ResourceInUse', ], [ 'shape' => 'ResourceLimitExceeded', ], [ 'shape' => 'ResourceNotFound', ], ], ], 'ListActions' => [ 'name' => 'ListActions', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListActionsRequest', ], 'output' => [ 'shape' => 'ListActionsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListAlgorithms' => [ 'name' => 'ListAlgorithms', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListAlgorithmsInput', ], 'output' => [ 'shape' => 'ListAlgorithmsOutput', ], ], 'ListAliases' => [ 'name' => 'ListAliases', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListAliasesRequest', ], 'output' => [ 'shape' => 'ListAliasesResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListAppImageConfigs' => [ 'name' => 'ListAppImageConfigs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 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'requestUri' => '/', ], 'input' => [ 'shape' => 'ListHubContentsRequest', ], 'output' => [ 'shape' => 'ListHubContentsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListHubs' => [ 'name' => 'ListHubs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListHubsRequest', ], 'output' => [ 'shape' => 'ListHubsResponse', ], ], 'ListHumanTaskUis' => [ 'name' => 'ListHumanTaskUis', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListHumanTaskUisRequest', ], 'output' => [ 'shape' => 'ListHumanTaskUisResponse', ], ], 'ListHyperParameterTuningJobs' => [ 'name' => 'ListHyperParameterTuningJobs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListHyperParameterTuningJobsRequest', ], 'output' => [ 'shape' => 'ListHyperParameterTuningJobsResponse', ], ], 'ListImageVersions' => [ 'name' => 'ListImageVersions', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListImageVersionsRequest', ], 'output' => [ 'shape' => 'ListImageVersionsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListImages' => [ 'name' => 'ListImages', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListImagesRequest', ], 'output' => [ 'shape' => 'ListImagesResponse', ], ], 'ListInferenceExperiments' => [ 'name' => 'ListInferenceExperiments', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListInferenceExperimentsRequest', ], 'output' => [ 'shape' => 'ListInferenceExperimentsResponse', ], ], 'ListInferenceRecommendationsJobSteps' => [ 'name' => 'ListInferenceRecommendationsJobSteps', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListInferenceRecommendationsJobStepsRequest', ], 'output' => [ 'shape' => 'ListInferenceRecommendationsJobStepsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListInferenceRecommendationsJobs' 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'ListLineageGroupsResponse', ], ], 'ListModelBiasJobDefinitions' => [ 'name' => 'ListModelBiasJobDefinitions', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelBiasJobDefinitionsRequest', ], 'output' => [ 'shape' => 'ListModelBiasJobDefinitionsResponse', ], ], 'ListModelCardExportJobs' => [ 'name' => 'ListModelCardExportJobs', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelCardExportJobsRequest', ], 'output' => [ 'shape' => 'ListModelCardExportJobsResponse', ], ], 'ListModelCardVersions' => [ 'name' => 'ListModelCardVersions', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelCardVersionsRequest', ], 'output' => [ 'shape' => 'ListModelCardVersionsResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListModelCards' => [ 'name' => 'ListModelCards', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelCardsRequest', ], 'output' => [ 'shape' => 'ListModelCardsResponse', ], ], 'ListModelExplainabilityJobDefinitions' => [ 'name' => 'ListModelExplainabilityJobDefinitions', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelExplainabilityJobDefinitionsRequest', ], 'output' => [ 'shape' => 'ListModelExplainabilityJobDefinitionsResponse', ], ], 'ListModelMetadata' => [ 'name' => 'ListModelMetadata', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelMetadataRequest', ], 'output' => [ 'shape' => 'ListModelMetadataResponse', ], ], 'ListModelPackageGroups' => [ 'name' => 'ListModelPackageGroups', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelPackageGroupsInput', ], 'output' => [ 'shape' => 'ListModelPackageGroupsOutput', ], ], 'ListModelPackages' => [ 'name' => 'ListModelPackages', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelPackagesInput', ], 'output' => [ 'shape' => 'ListModelPackagesOutput', ], ], 'ListModelQualityJobDefinitions' => [ 'name' => 'ListModelQualityJobDefinitions', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelQualityJobDefinitionsRequest', ], 'output' => [ 'shape' => 'ListModelQualityJobDefinitionsResponse', ], ], 'ListModels' => [ 'name' => 'ListModels', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListModelsInput', ], 'output' => [ 'shape' => 'ListModelsOutput', ], ], 'ListMonitoringAlertHistory' => [ 'name' => 'ListMonitoringAlertHistory', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 'input' => [ 'shape' => 'ListMonitoringAlertHistoryRequest', ], 'output' => [ 'shape' => 'ListMonitoringAlertHistoryResponse', ], 'errors' => [ [ 'shape' => 'ResourceNotFound', ], ], ], 'ListMonitoringAlerts' => [ 'name' => 'ListMonitoringAlerts', 'http' => [ 'method' => 'POST', 'requestUri' => '/', ], 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'min' => 1, 'pattern' => '.*', ], 'ConfigValue' => [ 'type' => 'string', 'max' => 256, 'pattern' => '.*', ], 'ConflictException' => [ 'type' => 'structure', 'members' => [ 'Message' => [ 'shape' => 'FailureReason', ], ], 'exception' => true, ], 'ContainerArgument' => [ 'type' => 'string', 'max' => 256, 'pattern' => '.*', ], 'ContainerArguments' => [ 'type' => 'list', 'member' => [ 'shape' => 'ContainerArgument', ], 'max' => 100, 'min' => 1, ], 'ContainerDefinition' => [ 'type' => 'structure', 'members' => [ 'ContainerHostname' => [ 'shape' => 'ContainerHostname', ], 'Image' => [ 'shape' => 'ContainerImage', ], 'ImageConfig' => [ 'shape' => 'ImageConfig', ], 'Mode' => [ 'shape' => 'ContainerMode', ], 'ModelDataUrl' => [ 'shape' => 'Url', ], 'Environment' => [ 'shape' => 'EnvironmentMap', ], 'ModelPackageName' => [ 'shape' => 'VersionedArnOrName', ], 'InferenceSpecificationName' => [ 'shape' => 'InferenceSpecificationName', ], 'MultiModelConfig' => [ 'shape' => 'MultiModelConfig', ], 'ModelDataSource' => [ 'shape' => 'ModelDataSource', ], ], ], 'ContainerDefinitionList' => [ 'type' => 'list', 'member' => [ 'shape' => 'ContainerDefinition', ], 'max' => 15, ], 'ContainerEntrypoint' => [ 'type' => 'list', 'member' => [ 'shape' => 'ContainerEntrypointString', ], 'max' => 100, 'min' => 1, ], 'ContainerEntrypointString' => [ 'type' => 'string', 'max' => 256, 'pattern' => '.*', ], 'ContainerHostname' => [ 'type' => 'string', 'max' => 63, 'pattern' => '^[a-zA-Z0-9](-*[a-zA-Z0-9]){0,62}', ], 'ContainerImage' => [ 'type' => 'string', 'max' => 255, 'pattern' => '[\\S]+', ], 'ContainerMode' => [ 'type' => 'string', 'enum' => [ 'SingleModel', 'MultiModel', ], ], 'ContentClassifier' => [ 'type' => 'string', 'enum' => [ 'FreeOfPersonallyIdentifiableInformation', 'FreeOfAdultContent', ], ], 'ContentClassifiers' => [ 'type' => 'list', 'member' => [ 'shape' => 'ContentClassifier', ], 'max' => 256, ], 'ContentColumn' => [ 'type' => 'string', 'max' => 256, 'min' => 1, ], 'ContentDigest' => [ 'type' => 'string', 'max' => 72, 'pattern' => '^[Ss][Hh][Aa]256:[0-9a-fA-F]{64}$', ], 'ContentType' => [ 'type' => 'string', 'max' => 256, 'pattern' => '.*', ], 'ContentTypes' => [ 'type' => 'list', 'member' => [ 'shape' => 'ContentType', ], ], 'ContextArn' => [ 'type' => 'string', 'max' => 256, 'pattern' => 'arn:aws[a-z\\-]*:sagemaker:[a-z0-9\\-]*:[0-9]{12}:context/.*', ], 'ContextSource' => [ 'type' => 'structure', 'required' => [ 'SourceUri', ], 'members' => [ 'SourceUri' => [ 'shape' => 'String2048', ], 'SourceType' => [ 'shape' => 'String256', ], 'SourceId' => [ 'shape' => 'String256', ], ], ], 'ContextSummaries' => [ 'type' => 'list', 'member' => [ 'shape' => 'ContextSummary', ], ], 'ContextSummary' => [ 'type' => 'structure', 'members' => [ 'ContextArn' => [ 'shape' => 'ContextArn', ], 'ContextName' => [ 'shape' => 'ExperimentEntityName', ], 'Source' => [ 'shape' => 'ContextSource', ], 'ContextType' => [ 'shape' => 'String256', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], ], ], 'ContinuousParameterRange' => [ 'type' => 'structure', 'required' => [ 'Name', 'MinValue', 'MaxValue', ], 'members' => [ 'Name' => [ 'shape' => 'ParameterKey', ], 'MinValue' => [ 'shape' => 'ParameterValue', ], 'MaxValue' => [ 'shape' => 'ParameterValue', ], 'ScalingType' => [ 'shape' => 'HyperParameterScalingType', ], ], ], 'ContinuousParameterRangeSpecification' => [ 'type' => 'structure', 'required' => [ 'MinValue', 'MaxValue', ], 'members' => [ 'MinValue' => [ 'shape' => 'ParameterValue', ], 'MaxValue' => [ 'shape' => 'ParameterValue', ], ], ], 'ContinuousParameterRanges' => [ 'type' => 'list', 'member' => [ 'shape' => 'ContinuousParameterRange', ], 'max' => 30, 'min' => 0, ], 'ConvergenceDetected' => [ 'type' => 'structure', 'members' => [ 'CompleteOnConvergence' => [ 'shape' => 'CompleteOnConvergence', ], ], ], 'CountryCode' => [ 'type' => 'string', 'max' => 2, 'min' => 2, 'pattern' => '[A-Z]{2}', ], 'CreateActionRequest' => [ 'type' => 'structure', 'required' => [ 'ActionName', 'Source', 'ActionType', ], 'members' => [ 'ActionName' => [ 'shape' => 'ExperimentEntityName', ], 'Source' => [ 'shape' => 'ActionSource', ], 'ActionType' => [ 'shape' => 'String256', ], 'Description' => [ 'shape' => 'ExperimentDescription', ], 'Status' => [ 'shape' => 'ActionStatus', ], 'Properties' => [ 'shape' => 'LineageEntityParameters', ], 'MetadataProperties' => [ 'shape' => 'MetadataProperties', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateActionResponse' => [ 'type' => 'structure', 'members' => [ 'ActionArn' => [ 'shape' => 'ActionArn', ], ], ], 'CreateAlgorithmInput' => [ 'type' => 'structure', 'required' => [ 'AlgorithmName', 'TrainingSpecification', ], 'members' => [ 'AlgorithmName' => [ 'shape' => 'EntityName', ], 'AlgorithmDescription' => [ 'shape' => 'EntityDescription', ], 'TrainingSpecification' => [ 'shape' => 'TrainingSpecification', ], 'InferenceSpecification' => [ 'shape' => 'InferenceSpecification', ], 'ValidationSpecification' => [ 'shape' => 'AlgorithmValidationSpecification', ], 'CertifyForMarketplace' => [ 'shape' => 'CertifyForMarketplace', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateAlgorithmOutput' => [ 'type' => 'structure', 'required' => [ 'AlgorithmArn', ], 'members' => [ 'AlgorithmArn' => [ 'shape' => 'AlgorithmArn', ], ], ], 'CreateAppImageConfigRequest' => [ 'type' => 'structure', 'required' => [ 'AppImageConfigName', ], 'members' => [ 'AppImageConfigName' => [ 'shape' => 'AppImageConfigName', ], 'Tags' => [ 'shape' => 'TagList', ], 'KernelGatewayImageConfig' => [ 'shape' => 'KernelGatewayImageConfig', ], ], ], 'CreateAppImageConfigResponse' => [ 'type' => 'structure', 'members' => [ 'AppImageConfigArn' => [ 'shape' => 'AppImageConfigArn', ], ], ], 'CreateAppRequest' => [ 'type' => 'structure', 'required' => [ 'DomainId', 'AppType', 'AppName', ], 'members' => [ 'DomainId' => [ 'shape' => 'DomainId', ], 'UserProfileName' => [ 'shape' => 'UserProfileName', ], 'AppType' => [ 'shape' => 'AppType', ], 'AppName' => [ 'shape' => 'AppName', ], 'Tags' => [ 'shape' => 'TagList', ], 'ResourceSpec' => [ 'shape' => 'ResourceSpec', ], 'SpaceName' => [ 'shape' => 'SpaceName', ], ], ], 'CreateAppResponse' => [ 'type' => 'structure', 'members' => [ 'AppArn' => [ 'shape' => 'AppArn', ], ], ], 'CreateArtifactRequest' => [ 'type' => 'structure', 'required' => [ 'Source', 'ArtifactType', ], 'members' => [ 'ArtifactName' => [ 'shape' => 'ExperimentEntityName', ], 'Source' => [ 'shape' => 'ArtifactSource', ], 'ArtifactType' => [ 'shape' => 'String256', ], 'Properties' => [ 'shape' => 'LineageEntityParameters', ], 'MetadataProperties' => [ 'shape' => 'MetadataProperties', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateArtifactResponse' => [ 'type' => 'structure', 'members' => [ 'ArtifactArn' => [ 'shape' => 'ArtifactArn', ], ], ], 'CreateAutoMLJobRequest' => [ 'type' => 'structure', 'required' => [ 'AutoMLJobName', 'InputDataConfig', 'OutputDataConfig', 'RoleArn', ], 'members' => [ 'AutoMLJobName' => [ 'shape' => 'AutoMLJobName', ], 'InputDataConfig' => [ 'shape' => 'AutoMLInputDataConfig', ], 'OutputDataConfig' => [ 'shape' => 'AutoMLOutputDataConfig', ], 'ProblemType' => [ 'shape' => 'ProblemType', ], 'AutoMLJobObjective' => [ 'shape' => 'AutoMLJobObjective', ], 'AutoMLJobConfig' => [ 'shape' => 'AutoMLJobConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'GenerateCandidateDefinitionsOnly' => [ 'shape' => 'GenerateCandidateDefinitionsOnly', ], 'Tags' => [ 'shape' => 'TagList', ], 'ModelDeployConfig' => [ 'shape' => 'ModelDeployConfig', ], ], ], 'CreateAutoMLJobResponse' => [ 'type' => 'structure', 'required' => [ 'AutoMLJobArn', ], 'members' => [ 'AutoMLJobArn' => [ 'shape' => 'AutoMLJobArn', ], ], ], 'CreateAutoMLJobV2Request' => [ 'type' => 'structure', 'required' => [ 'AutoMLJobName', 'AutoMLJobInputDataConfig', 'OutputDataConfig', 'AutoMLProblemTypeConfig', 'RoleArn', ], 'members' => [ 'AutoMLJobName' => [ 'shape' => 'AutoMLJobName', ], 'AutoMLJobInputDataConfig' => [ 'shape' => 'AutoMLJobInputDataConfig', ], 'OutputDataConfig' => [ 'shape' => 'AutoMLOutputDataConfig', ], 'AutoMLProblemTypeConfig' => [ 'shape' => 'AutoMLProblemTypeConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'Tags' => [ 'shape' => 'TagList', ], 'SecurityConfig' => [ 'shape' => 'AutoMLSecurityConfig', ], 'AutoMLJobObjective' => [ 'shape' => 'AutoMLJobObjective', ], 'ModelDeployConfig' => [ 'shape' => 'ModelDeployConfig', ], 'DataSplitConfig' => [ 'shape' => 'AutoMLDataSplitConfig', ], ], ], 'CreateAutoMLJobV2Response' => [ 'type' => 'structure', 'required' => [ 'AutoMLJobArn', ], 'members' => [ 'AutoMLJobArn' => [ 'shape' => 'AutoMLJobArn', ], ], ], 'CreateCodeRepositoryInput' => [ 'type' => 'structure', 'required' => [ 'CodeRepositoryName', 'GitConfig', ], 'members' => [ 'CodeRepositoryName' => [ 'shape' => 'EntityName', ], 'GitConfig' => [ 'shape' => 'GitConfig', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateCodeRepositoryOutput' => [ 'type' => 'structure', 'required' => [ 'CodeRepositoryArn', ], 'members' => [ 'CodeRepositoryArn' => [ 'shape' => 'CodeRepositoryArn', ], ], ], 'CreateCompilationJobRequest' => [ 'type' => 'structure', 'required' => [ 'CompilationJobName', 'RoleArn', 'OutputConfig', 'StoppingCondition', ], 'members' => [ 'CompilationJobName' => [ 'shape' => 'EntityName', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'ModelPackageVersionArn' => [ 'shape' => 'ModelPackageArn', ], 'InputConfig' => [ 'shape' => 'InputConfig', ], 'OutputConfig' => [ 'shape' => 'OutputConfig', ], 'VpcConfig' => [ 'shape' => 'NeoVpcConfig', ], 'StoppingCondition' => [ 'shape' => 'StoppingCondition', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateCompilationJobResponse' => [ 'type' => 'structure', 'required' => [ 'CompilationJobArn', ], 'members' => [ 'CompilationJobArn' => [ 'shape' => 'CompilationJobArn', ], ], ], 'CreateContextRequest' => [ 'type' => 'structure', 'required' => [ 'ContextName', 'Source', 'ContextType', ], 'members' => [ 'ContextName' => [ 'shape' => 'ExperimentEntityName', ], 'Source' => [ 'shape' => 'ContextSource', ], 'ContextType' => [ 'shape' => 'String256', ], 'Description' => [ 'shape' => 'ExperimentDescription', ], 'Properties' => [ 'shape' => 'LineageEntityParameters', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateContextResponse' => [ 'type' => 'structure', 'members' => [ 'ContextArn' => [ 'shape' => 'ContextArn', ], ], ], 'CreateDataQualityJobDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionName', 'DataQualityAppSpecification', 'DataQualityJobInput', 'DataQualityJobOutputConfig', 'JobResources', 'RoleArn', ], 'members' => [ 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], 'DataQualityBaselineConfig' => [ 'shape' => 'DataQualityBaselineConfig', ], 'DataQualityAppSpecification' => [ 'shape' => 'DataQualityAppSpecification', ], 'DataQualityJobInput' => [ 'shape' => 'DataQualityJobInput', ], 'DataQualityJobOutputConfig' => [ 'shape' => 'MonitoringOutputConfig', ], 'JobResources' => [ 'shape' => 'MonitoringResources', ], 'NetworkConfig' => [ 'shape' => 'MonitoringNetworkConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'StoppingCondition' => [ 'shape' => 'MonitoringStoppingCondition', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateDataQualityJobDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionArn', ], 'members' => [ 'JobDefinitionArn' => [ 'shape' => 'MonitoringJobDefinitionArn', ], ], ], 'CreateDeviceFleetRequest' => [ 'type' => 'structure', 'required' => [ 'DeviceFleetName', 'OutputConfig', ], 'members' => [ 'DeviceFleetName' => [ 'shape' => 'EntityName', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'Description' => [ 'shape' => 'DeviceFleetDescription', ], 'OutputConfig' => [ 'shape' => 'EdgeOutputConfig', ], 'Tags' => [ 'shape' => 'TagList', ], 'EnableIotRoleAlias' => [ 'shape' => 'EnableIotRoleAlias', ], ], ], 'CreateDomainRequest' => [ 'type' => 'structure', 'required' => [ 'DomainName', 'AuthMode', 'DefaultUserSettings', 'SubnetIds', 'VpcId', ], 'members' => [ 'DomainName' => [ 'shape' => 'DomainName', ], 'AuthMode' => [ 'shape' => 'AuthMode', ], 'DefaultUserSettings' => [ 'shape' => 'UserSettings', ], 'SubnetIds' => [ 'shape' => 'Subnets', ], 'VpcId' => [ 'shape' => 'VpcId', ], 'Tags' => [ 'shape' => 'TagList', ], 'AppNetworkAccessType' => [ 'shape' => 'AppNetworkAccessType', ], 'HomeEfsFileSystemKmsKeyId' => [ 'shape' => 'KmsKeyId', 'deprecated' => true, 'deprecatedMessage' => 'This property is deprecated, use KmsKeyId instead.', ], 'KmsKeyId' => [ 'shape' => 'KmsKeyId', ], 'AppSecurityGroupManagement' => [ 'shape' => 'AppSecurityGroupManagement', ], 'DomainSettings' => [ 'shape' => 'DomainSettings', ], 'DefaultSpaceSettings' => [ 'shape' => 'DefaultSpaceSettings', ], ], ], 'CreateDomainResponse' => [ 'type' => 'structure', 'members' => [ 'DomainArn' => [ 'shape' => 'DomainArn', ], 'Url' => [ 'shape' => 'String1024', ], ], ], 'CreateEdgeDeploymentPlanRequest' => [ 'type' => 'structure', 'required' => [ 'EdgeDeploymentPlanName', 'ModelConfigs', 'DeviceFleetName', ], 'members' => [ 'EdgeDeploymentPlanName' => [ 'shape' => 'EntityName', ], 'ModelConfigs' => [ 'shape' => 'EdgeDeploymentModelConfigs', ], 'DeviceFleetName' => [ 'shape' => 'EntityName', ], 'Stages' => [ 'shape' => 'DeploymentStages', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateEdgeDeploymentPlanResponse' => [ 'type' => 'structure', 'required' => [ 'EdgeDeploymentPlanArn', ], 'members' => [ 'EdgeDeploymentPlanArn' => [ 'shape' => 'EdgeDeploymentPlanArn', ], ], ], 'CreateEdgeDeploymentStageRequest' => [ 'type' => 'structure', 'required' => [ 'EdgeDeploymentPlanName', 'Stages', ], 'members' => [ 'EdgeDeploymentPlanName' => [ 'shape' => 'EntityName', ], 'Stages' => [ 'shape' => 'DeploymentStages', ], ], ], 'CreateEdgePackagingJobRequest' => [ 'type' => 'structure', 'required' => [ 'EdgePackagingJobName', 'CompilationJobName', 'ModelName', 'ModelVersion', 'RoleArn', 'OutputConfig', ], 'members' => [ 'EdgePackagingJobName' => [ 'shape' => 'EntityName', ], 'CompilationJobName' => [ 'shape' => 'EntityName', ], 'ModelName' => [ 'shape' => 'EntityName', ], 'ModelVersion' => [ 'shape' => 'EdgeVersion', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'OutputConfig' => [ 'shape' => 'EdgeOutputConfig', ], 'ResourceKey' => [ 'shape' => 'KmsKeyId', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateEndpointConfigInput' => [ 'type' => 'structure', 'required' => [ 'EndpointConfigName', 'ProductionVariants', ], 'members' => [ 'EndpointConfigName' => [ 'shape' => 'EndpointConfigName', ], 'ProductionVariants' => [ 'shape' => 'ProductionVariantList', ], 'DataCaptureConfig' => [ 'shape' => 'DataCaptureConfig', ], 'Tags' => [ 'shape' => 'TagList', ], 'KmsKeyId' => [ 'shape' => 'KmsKeyId', ], 'AsyncInferenceConfig' => [ 'shape' => 'AsyncInferenceConfig', ], 'ExplainerConfig' => [ 'shape' => 'ExplainerConfig', ], 'ShadowProductionVariants' => [ 'shape' => 'ProductionVariantList', ], ], ], 'CreateEndpointConfigOutput' => [ 'type' => 'structure', 'required' => [ 'EndpointConfigArn', ], 'members' => [ 'EndpointConfigArn' => [ 'shape' => 'EndpointConfigArn', ], ], ], 'CreateEndpointInput' => [ 'type' => 'structure', 'required' => [ 'EndpointName', 'EndpointConfigName', ], 'members' => [ 'EndpointName' => [ 'shape' => 'EndpointName', ], 'EndpointConfigName' => [ 'shape' => 'EndpointConfigName', ], 'DeploymentConfig' => [ 'shape' => 'DeploymentConfig', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateEndpointOutput' => [ 'type' => 'structure', 'required' => [ 'EndpointArn', ], 'members' => [ 'EndpointArn' => [ 'shape' => 'EndpointArn', ], ], ], 'CreateExperimentRequest' => [ 'type' => 'structure', 'required' => [ 'ExperimentName', ], 'members' => [ 'ExperimentName' => [ 'shape' => 'ExperimentEntityName', ], 'DisplayName' => [ 'shape' => 'ExperimentEntityName', ], 'Description' => [ 'shape' => 'ExperimentDescription', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateExperimentResponse' => [ 'type' => 'structure', 'members' => [ 'ExperimentArn' => [ 'shape' => 'ExperimentArn', ], ], ], 'CreateFeatureGroupRequest' => [ 'type' => 'structure', 'required' => [ 'FeatureGroupName', 'RecordIdentifierFeatureName', 'EventTimeFeatureName', 'FeatureDefinitions', ], 'members' => [ 'FeatureGroupName' => [ 'shape' => 'FeatureGroupName', ], 'RecordIdentifierFeatureName' => [ 'shape' => 'FeatureName', ], 'EventTimeFeatureName' => [ 'shape' => 'FeatureName', ], 'FeatureDefinitions' => [ 'shape' => 'FeatureDefinitions', ], 'OnlineStoreConfig' => [ 'shape' => 'OnlineStoreConfig', ], 'OfflineStoreConfig' => [ 'shape' => 'OfflineStoreConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'Description' => [ 'shape' => 'Description', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateFeatureGroupResponse' => [ 'type' => 'structure', 'required' => [ 'FeatureGroupArn', ], 'members' => [ 'FeatureGroupArn' => [ 'shape' => 'FeatureGroupArn', ], ], ], 'CreateFlowDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'FlowDefinitionName', 'HumanLoopConfig', 'OutputConfig', 'RoleArn', ], 'members' => [ 'FlowDefinitionName' => [ 'shape' => 'FlowDefinitionName', ], 'HumanLoopRequestSource' => [ 'shape' => 'HumanLoopRequestSource', ], 'HumanLoopActivationConfig' => [ 'shape' => 'HumanLoopActivationConfig', ], 'HumanLoopConfig' => [ 'shape' => 'HumanLoopConfig', ], 'OutputConfig' => [ 'shape' => 'FlowDefinitionOutputConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateFlowDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'FlowDefinitionArn', ], 'members' => [ 'FlowDefinitionArn' => [ 'shape' => 'FlowDefinitionArn', ], ], ], 'CreateHubRequest' => [ 'type' => 'structure', 'required' => [ 'HubName', 'HubDescription', ], 'members' => [ 'HubName' => [ 'shape' => 'HubName', ], 'HubDescription' => [ 'shape' => 'HubDescription', ], 'HubDisplayName' => [ 'shape' => 'HubDisplayName', ], 'HubSearchKeywords' => [ 'shape' => 'HubSearchKeywordList', ], 'S3StorageConfig' => [ 'shape' => 'HubS3StorageConfig', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateHubResponse' => [ 'type' => 'structure', 'required' => [ 'HubArn', ], 'members' => [ 'HubArn' => [ 'shape' => 'HubArn', ], ], ], 'CreateHumanTaskUiRequest' => [ 'type' => 'structure', 'required' => [ 'HumanTaskUiName', 'UiTemplate', ], 'members' => [ 'HumanTaskUiName' => [ 'shape' => 'HumanTaskUiName', ], 'UiTemplate' => [ 'shape' => 'UiTemplate', ], 'Tags' => [ 'shape' => 'TagList', ], ], ], 'CreateHumanTaskUiResponse' => [ 'type' => 'structure', 'required' => [ 'HumanTaskUiArn', ], 'members' => [ 'HumanTaskUiArn' => [ 'shape' => 'HumanTaskUiArn', ], ], ], 'CreateHyperParameterTuningJobRequest' => [ 'type' => 'structure', 'required' => [ 'HyperParameterTuningJobName', 'HyperParameterTuningJobConfig', ], 'members' => [ 'HyperParameterTuningJobName' => [ 'shape' => 'HyperParameterTuningJobName', ], 'HyperParameterTuningJobConfig' => [ 'shape' => 'HyperParameterTuningJobConfig', ], 'TrainingJobDefinition' => [ 'shape' => 'HyperParameterTrainingJobDefinition', ], 'TrainingJobDefinitions' => [ 'shape' => 'HyperParameterTrainingJobDefinitions', ], 'WarmStartConfig' => [ 'shape' => 'HyperParameterTuningJobWarmStartConfig', ], 'Tags' => [ 'shape' => 'TagList', ], 'Autotune' => [ 'shape' => 'Autotune', ], ], ], 'CreateHyperParameterTuningJobResponse' => [ 'type' => 'structure', 'required' => [ 'HyperParameterTuningJobArn', ], 'members' => [ 'HyperParameterTuningJobArn' => [ 'shape' => 'HyperParameterTuningJobArn', ], ], ], 'CreateImageRequest' => [ 'type' => 'structure', 'required' => [ 'ImageName', 'RoleArn', ], 'members' => [ 'Description' => [ 'shape' => 'ImageDescription', ], 'DisplayName' => [ 'shape' => 'ImageDisplayName', ], 'ImageName' => [ 'shape' => 'ImageName', ], 'RoleArn' => [ 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'PartialFailureReasons' => [ 'shape' => 'AutoMLPartialFailureReasons', ], 'BestCandidate' => [ 'shape' => 'AutoMLCandidate', ], 'AutoMLJobStatus' => [ 'shape' => 'AutoMLJobStatus', ], 'AutoMLJobSecondaryStatus' => [ 'shape' => 'AutoMLJobSecondaryStatus', ], 'GenerateCandidateDefinitionsOnly' => [ 'shape' => 'GenerateCandidateDefinitionsOnly', ], 'AutoMLJobArtifacts' => [ 'shape' => 'AutoMLJobArtifacts', ], 'ResolvedAttributes' => [ 'shape' => 'ResolvedAttributes', ], 'ModelDeployConfig' => [ 'shape' => 'ModelDeployConfig', ], 'ModelDeployResult' => [ 'shape' => 'ModelDeployResult', ], ], ], 'DescribeAutoMLJobV2Request' => [ 'type' => 'structure', 'required' => [ 'AutoMLJobName', ], 'members' => [ 'AutoMLJobName' => [ 'shape' => 'AutoMLJobName', ], ], ], 'DescribeAutoMLJobV2Response' => [ 'type' => 'structure', 'required' => [ 'AutoMLJobName', 'AutoMLJobArn', 'AutoMLJobInputDataConfig', 'OutputDataConfig', 'RoleArn', 'CreationTime', 'LastModifiedTime', 'AutoMLJobStatus', 'AutoMLJobSecondaryStatus', ], 'members' => [ 'AutoMLJobName' => [ 'shape' => 'AutoMLJobName', ], 'AutoMLJobArn' => [ 'shape' => 'AutoMLJobArn', ], 'AutoMLJobInputDataConfig' => [ 'shape' => 'AutoMLJobInputDataConfig', ], 'OutputDataConfig' => [ 'shape' => 'AutoMLOutputDataConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'AutoMLJobObjective' => [ 'shape' => 'AutoMLJobObjective', ], 'AutoMLProblemTypeConfig' => [ 'shape' => 'AutoMLProblemTypeConfig', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'EndTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'FailureReason' => [ 'shape' => 'AutoMLFailureReason', ], 'PartialFailureReasons' => [ 'shape' => 'AutoMLPartialFailureReasons', ], 'BestCandidate' => [ 'shape' => 'AutoMLCandidate', ], 'AutoMLJobStatus' => [ 'shape' => 'AutoMLJobStatus', ], 'AutoMLJobSecondaryStatus' => [ 'shape' => 'AutoMLJobSecondaryStatus', ], 'ModelDeployConfig' => [ 'shape' => 'ModelDeployConfig', ], 'ModelDeployResult' => [ 'shape' => 'ModelDeployResult', ], 'DataSplitConfig' => [ 'shape' => 'AutoMLDataSplitConfig', ], 'SecurityConfig' => [ 'shape' => 'AutoMLSecurityConfig', ], 'AutoMLJobArtifacts' => [ 'shape' => 'AutoMLJobArtifacts', ], 'ResolvedAttributes' => [ 'shape' => 'AutoMLResolvedAttributes', ], 'AutoMLProblemTypeConfigName' => [ 'shape' => 'AutoMLProblemTypeConfigName', ], ], ], 'DescribeCodeRepositoryInput' => [ 'type' => 'structure', 'required' => [ 'CodeRepositoryName', ], 'members' => [ 'CodeRepositoryName' => [ 'shape' => 'EntityName', ], ], ], 'DescribeCodeRepositoryOutput' => [ 'type' => 'structure', 'required' => [ 'CodeRepositoryName', 'CodeRepositoryArn', 'CreationTime', 'LastModifiedTime', ], 'members' => [ 'CodeRepositoryName' => [ 'shape' => 'EntityName', ], 'CodeRepositoryArn' => [ 'shape' => 'CodeRepositoryArn', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'GitConfig' => [ 'shape' => 'GitConfig', ], ], ], 'DescribeCompilationJobRequest' => [ 'type' => 'structure', 'required' => [ 'CompilationJobName', ], 'members' => [ 'CompilationJobName' => [ 'shape' => 'EntityName', ], ], ], 'DescribeCompilationJobResponse' => [ 'type' => 'structure', 'required' => [ 'CompilationJobName', 'CompilationJobArn', 'CompilationJobStatus', 'StoppingCondition', 'CreationTime', 'LastModifiedTime', 'FailureReason', 'ModelArtifacts', 'RoleArn', 'InputConfig', 'OutputConfig', ], 'members' => [ 'CompilationJobName' => [ 'shape' => 'EntityName', ], 'CompilationJobArn' => [ 'shape' => 'CompilationJobArn', ], 'CompilationJobStatus' => [ 'shape' => 'CompilationJobStatus', ], 'CompilationStartTime' => [ 'shape' => 'Timestamp', ], 'CompilationEndTime' => [ 'shape' => 'Timestamp', ], 'StoppingCondition' => [ 'shape' => 'StoppingCondition', ], 'InferenceImage' => [ 'shape' => 'InferenceImage', ], 'ModelPackageVersionArn' => [ 'shape' => 'ModelPackageArn', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'ModelArtifacts' => [ 'shape' => 'ModelArtifacts', ], 'ModelDigests' => [ 'shape' => 'ModelDigests', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'InputConfig' => [ 'shape' => 'InputConfig', ], 'OutputConfig' => [ 'shape' => 'OutputConfig', ], 'VpcConfig' => [ 'shape' => 'NeoVpcConfig', ], 'DerivedInformation' => [ 'shape' => 'DerivedInformation', ], ], ], 'DescribeContextRequest' => [ 'type' => 'structure', 'required' => [ 'ContextName', ], 'members' => [ 'ContextName' => [ 'shape' => 'ExperimentEntityNameOrArn', ], ], ], 'DescribeContextResponse' => [ 'type' => 'structure', 'members' => [ 'ContextName' => [ 'shape' => 'ExperimentEntityName', ], 'ContextArn' => [ 'shape' => 'ContextArn', ], 'Source' => [ 'shape' => 'ContextSource', ], 'ContextType' => [ 'shape' => 'String256', ], 'Description' => [ 'shape' => 'ExperimentDescription', ], 'Properties' => [ 'shape' => 'LineageEntityParameters', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'CreatedBy' => [ 'shape' => 'UserContext', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedBy' => [ 'shape' => 'UserContext', ], 'LineageGroupArn' => [ 'shape' => 'LineageGroupArn', ], ], ], 'DescribeDataQualityJobDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionName', ], 'members' => [ 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], ], ], 'DescribeDataQualityJobDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionArn', 'JobDefinitionName', 'CreationTime', 'DataQualityAppSpecification', 'DataQualityJobInput', 'DataQualityJobOutputConfig', 'JobResources', 'RoleArn', ], 'members' => [ 'JobDefinitionArn' => [ 'shape' => 'MonitoringJobDefinitionArn', ], 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'DataQualityBaselineConfig' => [ 'shape' => 'DataQualityBaselineConfig', ], 'DataQualityAppSpecification' => [ 'shape' => 'DataQualityAppSpecification', ], 'DataQualityJobInput' => [ 'shape' => 'DataQualityJobInput', ], 'DataQualityJobOutputConfig' => [ 'shape' => 'MonitoringOutputConfig', ], 'JobResources' => [ 'shape' => 'MonitoringResources', ], 'NetworkConfig' => [ 'shape' => 'MonitoringNetworkConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'StoppingCondition' => [ 'shape' => 'MonitoringStoppingCondition', ], ], ], 'DescribeDeviceFleetRequest' => [ 'type' => 'structure', 'required' => [ 'DeviceFleetName', ], 'members' => [ 'DeviceFleetName' => [ 'shape' => 'EntityName', ], ], ], 'DescribeDeviceFleetResponse' => [ 'type' => 'structure', 'required' => [ 'DeviceFleetName', 'DeviceFleetArn', 'OutputConfig', 'CreationTime', 'LastModifiedTime', ], 'members' => [ 'DeviceFleetName' => [ 'shape' => 'EntityName', ], 'DeviceFleetArn' => [ 'shape' => 'DeviceFleetArn', ], 'OutputConfig' => [ 'shape' => 'EdgeOutputConfig', ], 'Description' => [ 'shape' => 'DeviceFleetDescription', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'IotRoleAlias' => [ 'shape' => 'IotRoleAlias', ], ], ], 'DescribeDeviceRequest' => [ 'type' => 'structure', 'required' => [ 'DeviceName', 'DeviceFleetName', ], 'members' => [ 'NextToken' => [ 'shape' => 'NextToken', ], 'DeviceName' => [ 'shape' => 'EntityName', ], 'DeviceFleetName' => [ 'shape' => 'EntityName', ], ], ], 'DescribeDeviceResponse' => [ 'type' => 'structure', 'required' => [ 'DeviceName', 'DeviceFleetName', 'RegistrationTime', ], 'members' => [ 'DeviceArn' => [ 'shape' => 'DeviceArn', ], 'DeviceName' => [ 'shape' => 'EntityName', ], 'Description' => [ 'shape' => 'DeviceDescription', ], 'DeviceFleetName' => [ 'shape' => 'EntityName', ], 'IotThingName' => [ 'shape' => 'ThingName', ], 'RegistrationTime' => [ 'shape' => 'Timestamp', ], 'LatestHeartbeat' => [ 'shape' => 'Timestamp', ], 'Models' => [ 'shape' => 'EdgeModels', ], 'MaxModels' => [ 'shape' => 'Integer', ], 'NextToken' => [ 'shape' => 'NextToken', ], 'AgentVersion' => [ 'shape' => 'EdgeVersion', ], ], ], 'DescribeDomainRequest' => [ 'type' => 'structure', 'required' => [ 'DomainId', ], 'members' => [ 'DomainId' => [ 'shape' => 'DomainId', ], ], ], 'DescribeDomainResponse' => [ 'type' => 'structure', 'members' => [ 'DomainArn' => [ 'shape' => 'DomainArn', ], 'DomainId' => [ 'shape' => 'DomainId', ], 'DomainName' => [ 'shape' => 'DomainName', ], 'HomeEfsFileSystemId' => [ 'shape' => 'ResourceId', ], 'SingleSignOnManagedApplicationInstanceId' => [ 'shape' => 'String256', ], 'SingleSignOnApplicationArn' => [ 'shape' => 'SingleSignOnApplicationArn', ], 'Status' => [ 'shape' => 'DomainStatus', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'AuthMode' => [ 'shape' => 'AuthMode', ], 'DefaultUserSettings' => [ 'shape' => 'UserSettings', ], 'AppNetworkAccessType' => [ 'shape' => 'AppNetworkAccessType', ], 'HomeEfsFileSystemKmsKeyId' => [ 'shape' => 'KmsKeyId', 'deprecated' => true, 'deprecatedMessage' => 'This property is deprecated, use KmsKeyId instead.', ], 'SubnetIds' => [ 'shape' => 'Subnets', ], 'Url' => [ 'shape' => 'String1024', ], 'VpcId' => [ 'shape' => 'VpcId', ], 'KmsKeyId' => [ 'shape' => 'KmsKeyId', ], 'DomainSettings' => [ 'shape' => 'DomainSettings', ], 'AppSecurityGroupManagement' => [ 'shape' => 'AppSecurityGroupManagement', ], 'SecurityGroupIdForDomainBoundary' => [ 'shape' => 'SecurityGroupId', ], 'DefaultSpaceSettings' => [ 'shape' => 'DefaultSpaceSettings', ], ], ], 'DescribeEdgeDeploymentPlanRequest' => [ 'type' => 'structure', 'required' => [ 'EdgeDeploymentPlanName', ], 'members' => [ 'EdgeDeploymentPlanName' => [ 'shape' => 'EntityName', ], 'NextToken' => [ 'shape' => 'NextToken', ], 'MaxResults' => [ 'shape' => 'DeploymentStageMaxResults', ], ], ], 'DescribeEdgeDeploymentPlanResponse' => [ 'type' => 'structure', 'required' => [ 'EdgeDeploymentPlanArn', 'EdgeDeploymentPlanName', 'ModelConfigs', 'DeviceFleetName', 'Stages', ], 'members' => [ 'EdgeDeploymentPlanArn' => [ 'shape' => 'EdgeDeploymentPlanArn', ], 'EdgeDeploymentPlanName' => [ 'shape' => 'EntityName', ], 'ModelConfigs' => [ 'shape' => 'EdgeDeploymentModelConfigs', ], 'DeviceFleetName' => [ 'shape' => 'EntityName', ], 'EdgeDeploymentSuccess' => [ 'shape' => 'Integer', ], 'EdgeDeploymentPending' => [ 'shape' => 'Integer', ], 'EdgeDeploymentFailed' => [ 'shape' => 'Integer', ], 'Stages' => [ 'shape' => 'DeploymentStageStatusSummaries', ], 'NextToken' => [ 'shape' => 'NextToken', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], ], ], 'DescribeEdgePackagingJobRequest' => [ 'type' => 'structure', 'required' => [ 'EdgePackagingJobName', ], 'members' => [ 'EdgePackagingJobName' => [ 'shape' => 'EntityName', ], ], ], 'DescribeEdgePackagingJobResponse' => [ 'type' => 'structure', 'required' => [ 'EdgePackagingJobArn', 'EdgePackagingJobName', 'EdgePackagingJobStatus', ], 'members' => [ 'EdgePackagingJobArn' => [ 'shape' => 'EdgePackagingJobArn', ], 'EdgePackagingJobName' => [ 'shape' => 'EntityName', ], 'CompilationJobName' => [ 'shape' => 'EntityName', ], 'ModelName' => [ 'shape' => 'EntityName', ], 'ModelVersion' => [ 'shape' => 'EdgeVersion', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'OutputConfig' => [ 'shape' => 'EdgeOutputConfig', ], 'ResourceKey' => [ 'shape' => 'KmsKeyId', ], 'EdgePackagingJobStatus' => [ 'shape' => 'EdgePackagingJobStatus', ], 'EdgePackagingJobStatusMessage' => [ 'shape' => 'String', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'ModelArtifact' => [ 'shape' => 'S3Uri', ], 'ModelSignature' => [ 'shape' => 'String', ], 'PresetDeploymentOutput' => [ 'shape' => 'EdgePresetDeploymentOutput', ], ], ], 'DescribeEndpointConfigInput' => [ 'type' => 'structure', 'required' => [ 'EndpointConfigName', ], 'members' => [ 'EndpointConfigName' => [ 'shape' => 'EndpointConfigName', ], ], ], 'DescribeEndpointConfigOutput' => [ 'type' => 'structure', 'required' => [ 'EndpointConfigName', 'EndpointConfigArn', 'ProductionVariants', 'CreationTime', ], 'members' => [ 'EndpointConfigName' => [ 'shape' => 'EndpointConfigName', ], 'EndpointConfigArn' => [ 'shape' => 'EndpointConfigArn', ], 'ProductionVariants' => [ 'shape' => 'ProductionVariantList', ], 'DataCaptureConfig' => [ 'shape' => 'DataCaptureConfig', ], 'KmsKeyId' => [ 'shape' => 'KmsKeyId', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'AsyncInferenceConfig' => [ 'shape' => 'AsyncInferenceConfig', ], 'ExplainerConfig' => [ 'shape' => 'ExplainerConfig', ], 'ShadowProductionVariants' => [ 'shape' => 'ProductionVariantList', ], ], ], 'DescribeEndpointInput' => [ 'type' => 'structure', 'required' => [ 'EndpointName', ], 'members' => [ 'EndpointName' => [ 'shape' => 'EndpointName', ], ], ], 'DescribeEndpointOutput' => [ 'type' => 'structure', 'required' => [ 'EndpointName', 'EndpointArn', 'EndpointConfigName', 'EndpointStatus', 'CreationTime', 'LastModifiedTime', ], 'members' => [ 'EndpointName' => [ 'shape' => 'EndpointName', ], 'EndpointArn' => [ 'shape' => 'EndpointArn', ], 'EndpointConfigName' => [ 'shape' => 'EndpointConfigName', ], 'ProductionVariants' => [ 'shape' => 'ProductionVariantSummaryList', ], 'DataCaptureConfig' => [ 'shape' => 'DataCaptureConfigSummary', ], 'EndpointStatus' => [ 'shape' => 'EndpointStatus', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastDeploymentConfig' => [ 'shape' => 'DeploymentConfig', ], 'AsyncInferenceConfig' => [ 'shape' => 'AsyncInferenceConfig', ], 'PendingDeploymentSummary' => [ 'shape' => 'PendingDeploymentSummary', ], 'ExplainerConfig' => [ 'shape' => 'ExplainerConfig', ], 'ShadowProductionVariants' => [ 'shape' => 'ProductionVariantSummaryList', ], ], ], 'DescribeExperimentRequest' => [ 'type' => 'structure', 'required' => [ 'ExperimentName', ], 'members' => [ 'ExperimentName' => [ 'shape' => 'ExperimentEntityName', ], ], ], 'DescribeExperimentResponse' => [ 'type' => 'structure', 'members' => [ 'ExperimentName' => [ 'shape' => 'ExperimentEntityName', ], 'ExperimentArn' => [ 'shape' => 'ExperimentArn', ], 'DisplayName' => [ 'shape' => 'ExperimentEntityName', ], 'Source' => [ 'shape' => 'ExperimentSource', ], 'Description' => [ 'shape' => 'ExperimentDescription', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'CreatedBy' => [ 'shape' => 'UserContext', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedBy' => [ 'shape' => 'UserContext', ], ], ], 'DescribeFeatureGroupRequest' => [ 'type' => 'structure', 'required' => [ 'FeatureGroupName', ], 'members' => [ 'FeatureGroupName' => [ 'shape' => 'FeatureGroupNameOrArn', ], 'NextToken' => [ 'shape' => 'NextToken', ], ], ], 'DescribeFeatureGroupResponse' => [ 'type' => 'structure', 'required' => [ 'FeatureGroupArn', 'FeatureGroupName', 'RecordIdentifierFeatureName', 'EventTimeFeatureName', 'FeatureDefinitions', 'CreationTime', 'NextToken', ], 'members' => [ 'FeatureGroupArn' => [ 'shape' => 'FeatureGroupArn', ], 'FeatureGroupName' => [ 'shape' => 'FeatureGroupName', ], 'RecordIdentifierFeatureName' => [ 'shape' => 'FeatureName', ], 'EventTimeFeatureName' => [ 'shape' => 'FeatureName', ], 'FeatureDefinitions' => [ 'shape' => 'FeatureDefinitions', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'OnlineStoreConfig' => [ 'shape' => 'OnlineStoreConfig', ], 'OfflineStoreConfig' => [ 'shape' => 'OfflineStoreConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'FeatureGroupStatus' => [ 'shape' => 'FeatureGroupStatus', ], 'OfflineStoreStatus' => [ 'shape' => 'OfflineStoreStatus', ], 'LastUpdateStatus' => [ 'shape' => 'LastUpdateStatus', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'Description' => [ 'shape' => 'Description', ], 'NextToken' => [ 'shape' => 'NextToken', ], 'OnlineStoreTotalSizeBytes' => [ 'shape' => 'OnlineStoreTotalSizeBytes', ], ], ], 'DescribeFeatureMetadataRequest' => [ 'type' => 'structure', 'required' => [ 'FeatureGroupName', 'FeatureName', ], 'members' => [ 'FeatureGroupName' => [ 'shape' => 'FeatureGroupNameOrArn', ], 'FeatureName' => [ 'shape' => 'FeatureName', ], ], ], 'DescribeFeatureMetadataResponse' => [ 'type' => 'structure', 'required' => [ 'FeatureGroupArn', 'FeatureGroupName', 'FeatureName', 'FeatureType', 'CreationTime', 'LastModifiedTime', ], 'members' => [ 'FeatureGroupArn' => [ 'shape' => 'FeatureGroupArn', ], 'FeatureGroupName' => [ 'shape' => 'FeatureGroupName', ], 'FeatureName' => [ 'shape' => 'FeatureName', ], 'FeatureType' => [ 'shape' => 'FeatureType', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'Description' => [ 'shape' => 'FeatureDescription', ], 'Parameters' => [ 'shape' => 'FeatureParameters', ], ], ], 'DescribeFlowDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'FlowDefinitionName', ], 'members' => [ 'FlowDefinitionName' => [ 'shape' => 'FlowDefinitionName', ], ], ], 'DescribeFlowDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'FlowDefinitionArn', 'FlowDefinitionName', 'FlowDefinitionStatus', 'CreationTime', 'HumanLoopConfig', 'OutputConfig', 'RoleArn', ], 'members' => [ 'FlowDefinitionArn' => [ 'shape' => 'FlowDefinitionArn', ], 'FlowDefinitionName' => [ 'shape' => 'FlowDefinitionName', ], 'FlowDefinitionStatus' => [ 'shape' => 'FlowDefinitionStatus', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'HumanLoopRequestSource' => [ 'shape' => 'HumanLoopRequestSource', ], 'HumanLoopActivationConfig' => [ 'shape' => 'HumanLoopActivationConfig', ], 'HumanLoopConfig' => [ 'shape' => 'HumanLoopConfig', ], 'OutputConfig' => [ 'shape' => 'FlowDefinitionOutputConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], ], ], 'DescribeHubContentRequest' => [ 'type' => 'structure', 'required' => [ 'HubName', 'HubContentType', 'HubContentName', ], 'members' => [ 'HubName' => [ 'shape' => 'HubName', ], 'HubContentType' => [ 'shape' => 'HubContentType', ], 'HubContentName' => [ 'shape' => 'HubContentName', ], 'HubContentVersion' => [ 'shape' => 'HubContentVersion', ], ], ], 'DescribeHubContentResponse' => [ 'type' => 'structure', 'required' => [ 'HubContentName', 'HubContentArn', 'HubContentVersion', 'HubContentType', 'DocumentSchemaVersion', 'HubName', 'HubArn', 'HubContentDocument', 'HubContentStatus', 'CreationTime', ], 'members' => [ 'HubContentName' => [ 'shape' => 'HubContentName', ], 'HubContentArn' => [ 'shape' => 'HubContentArn', ], 'HubContentVersion' => [ 'shape' => 'HubContentVersion', ], 'HubContentType' => [ 'shape' => 'HubContentType', ], 'DocumentSchemaVersion' => [ 'shape' => 'DocumentSchemaVersion', ], 'HubName' => [ 'shape' => 'HubName', ], 'HubArn' => [ 'shape' => 'HubArn', ], 'HubContentDisplayName' => [ 'shape' => 'HubContentDisplayName', ], 'HubContentDescription' => [ 'shape' => 'HubContentDescription', ], 'HubContentMarkdown' => [ 'shape' => 'HubContentMarkdown', ], 'HubContentDocument' => [ 'shape' => 'HubContentDocument', ], 'HubContentSearchKeywords' => [ 'shape' => 'HubContentSearchKeywordList', ], 'HubContentDependencies' => [ 'shape' => 'HubContentDependencyList', ], 'HubContentStatus' => [ 'shape' => 'HubContentStatus', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], ], ], 'DescribeHubRequest' => [ 'type' => 'structure', 'required' => [ 'HubName', ], 'members' => [ 'HubName' => [ 'shape' => 'HubName', ], ], ], 'DescribeHubResponse' => [ 'type' => 'structure', 'required' => [ 'HubName', 'HubArn', 'HubStatus', 'CreationTime', 'LastModifiedTime', ], 'members' => [ 'HubName' => [ 'shape' => 'HubName', ], 'HubArn' => [ 'shape' => 'HubArn', ], 'HubDisplayName' => [ 'shape' => 'HubDisplayName', ], 'HubDescription' => [ 'shape' => 'HubDescription', ], 'HubSearchKeywords' => [ 'shape' => 'HubSearchKeywordList', ], 'S3StorageConfig' => [ 'shape' => 'HubS3StorageConfig', ], 'HubStatus' => [ 'shape' => 'HubStatus', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], ], ], 'DescribeHumanTaskUiRequest' => [ 'type' => 'structure', 'required' => [ 'HumanTaskUiName', ], 'members' => [ 'HumanTaskUiName' => [ 'shape' => 'HumanTaskUiName', ], ], ], 'DescribeHumanTaskUiResponse' => [ 'type' => 'structure', 'required' => [ 'HumanTaskUiArn', 'HumanTaskUiName', 'CreationTime', 'UiTemplate', ], 'members' => [ 'HumanTaskUiArn' => [ 'shape' => 'HumanTaskUiArn', ], 'HumanTaskUiName' => [ 'shape' => 'HumanTaskUiName', ], 'HumanTaskUiStatus' => [ 'shape' => 'HumanTaskUiStatus', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'UiTemplate' => [ 'shape' => 'UiTemplateInfo', ], ], ], 'DescribeHyperParameterTuningJobRequest' => [ 'type' => 'structure', 'required' => [ 'HyperParameterTuningJobName', ], 'members' => [ 'HyperParameterTuningJobName' => [ 'shape' => 'HyperParameterTuningJobName', ], ], ], 'DescribeHyperParameterTuningJobResponse' => [ 'type' => 'structure', 'required' => [ 'HyperParameterTuningJobName', 'HyperParameterTuningJobArn', 'HyperParameterTuningJobConfig', 'HyperParameterTuningJobStatus', 'CreationTime', 'TrainingJobStatusCounters', 'ObjectiveStatusCounters', ], 'members' => [ 'HyperParameterTuningJobName' => [ 'shape' => 'HyperParameterTuningJobName', ], 'HyperParameterTuningJobArn' => [ 'shape' => 'HyperParameterTuningJobArn', ], 'HyperParameterTuningJobConfig' => [ 'shape' => 'HyperParameterTuningJobConfig', ], 'TrainingJobDefinition' => [ 'shape' => 'HyperParameterTrainingJobDefinition', ], 'TrainingJobDefinitions' => [ 'shape' => 'HyperParameterTrainingJobDefinitions', ], 'HyperParameterTuningJobStatus' => [ 'shape' => 'HyperParameterTuningJobStatus', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'HyperParameterTuningEndTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'TrainingJobStatusCounters' => [ 'shape' => 'TrainingJobStatusCounters', ], 'ObjectiveStatusCounters' => [ 'shape' => 'ObjectiveStatusCounters', ], 'BestTrainingJob' => [ 'shape' => 'HyperParameterTrainingJobSummary', ], 'OverallBestTrainingJob' => [ 'shape' => 'HyperParameterTrainingJobSummary', ], 'WarmStartConfig' => [ 'shape' => 'HyperParameterTuningJobWarmStartConfig', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'TuningJobCompletionDetails' => [ 'shape' => 'HyperParameterTuningJobCompletionDetails', ], 'ConsumedResources' => [ 'shape' => 'HyperParameterTuningJobConsumedResources', ], 'Autotune' => [ 'shape' => 'Autotune', ], ], ], 'DescribeImageRequest' => [ 'type' => 'structure', 'required' => [ 'ImageName', ], 'members' => [ 'ImageName' => [ 'shape' => 'ImageName', ], ], ], 'DescribeImageResponse' => [ 'type' => 'structure', 'members' => [ 'CreationTime' => [ 'shape' => 'Timestamp', ], 'Description' => [ 'shape' => 'ImageDescription', ], 'DisplayName' => [ 'shape' => 'ImageDisplayName', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'ImageArn' => [ 'shape' => 'ImageArn', ], 'ImageName' => [ 'shape' => 'ImageName', ], 'ImageStatus' => [ 'shape' => 'ImageStatus', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], ], ], 'DescribeImageVersionRequest' => [ 'type' => 'structure', 'required' => [ 'ImageName', ], 'members' => [ 'ImageName' => [ 'shape' => 'ImageName', ], 'Version' => [ 'shape' => 'ImageVersionNumber', ], 'Alias' => [ 'shape' => 'SageMakerImageVersionAlias', ], ], ], 'DescribeImageVersionResponse' => [ 'type' => 'structure', 'members' => [ 'BaseImage' => [ 'shape' => 'ImageBaseImage', ], 'ContainerImage' => [ 'shape' => 'ImageContainerImage', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'ImageArn' => [ 'shape' => 'ImageArn', ], 'ImageVersionArn' => [ 'shape' => 'ImageVersionArn', ], 'ImageVersionStatus' => [ 'shape' => 'ImageVersionStatus', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'Version' => [ 'shape' => 'ImageVersionNumber', ], 'VendorGuidance' => [ 'shape' => 'VendorGuidance', ], 'JobType' => [ 'shape' => 'JobType', ], 'MLFramework' => [ 'shape' => 'MLFramework', ], 'ProgrammingLang' => [ 'shape' => 'ProgrammingLang', ], 'Processor' => [ 'shape' => 'Processor', ], 'Horovod' => [ 'shape' => 'Horovod', ], 'ReleaseNotes' => [ 'shape' => 'ReleaseNotes', ], ], ], 'DescribeInferenceExperimentRequest' => [ 'type' => 'structure', 'required' => [ 'Name', ], 'members' => [ 'Name' => [ 'shape' => 'InferenceExperimentName', ], ], ], 'DescribeInferenceExperimentResponse' => [ 'type' => 'structure', 'required' 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'DescribeInferenceRecommendationsJobRequest' => [ 'type' => 'structure', 'required' => [ 'JobName', ], 'members' => [ 'JobName' => [ 'shape' => 'RecommendationJobName', ], ], ], 'DescribeInferenceRecommendationsJobResponse' => [ 'type' => 'structure', 'required' => [ 'JobName', 'JobType', 'JobArn', 'RoleArn', 'Status', 'CreationTime', 'LastModifiedTime', 'InputConfig', ], 'members' => [ 'JobName' => [ 'shape' => 'RecommendationJobName', ], 'JobDescription' => [ 'shape' => 'RecommendationJobDescription', ], 'JobType' => [ 'shape' => 'RecommendationJobType', ], 'JobArn' => [ 'shape' => 'RecommendationJobArn', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'Status' => [ 'shape' => 'RecommendationJobStatus', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'CompletionTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'InputConfig' => [ 'shape' => 'RecommendationJobInputConfig', ], 'StoppingConditions' => [ 'shape' => 'RecommendationJobStoppingConditions', ], 'InferenceRecommendations' => [ 'shape' => 'InferenceRecommendations', ], 'EndpointPerformances' => [ 'shape' => 'EndpointPerformances', ], ], ], 'DescribeLabelingJobRequest' => [ 'type' => 'structure', 'required' => [ 'LabelingJobName', ], 'members' => [ 'LabelingJobName' => [ 'shape' => 'LabelingJobName', ], ], ], 'DescribeLabelingJobResponse' => [ 'type' => 'structure', 'required' => [ 'LabelingJobStatus', 'LabelCounters', 'CreationTime', 'LastModifiedTime', 'JobReferenceCode', 'LabelingJobName', 'LabelingJobArn', 'InputConfig', 'OutputConfig', 'RoleArn', 'HumanTaskConfig', ], 'members' => [ 'LabelingJobStatus' => [ 'shape' => 'LabelingJobStatus', ], 'LabelCounters' => [ 'shape' => 'LabelCounters', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'JobReferenceCode' => [ 'shape' => 'JobReferenceCode', ], 'LabelingJobName' => [ 'shape' => 'LabelingJobName', ], 'LabelingJobArn' => [ 'shape' => 'LabelingJobArn', ], 'LabelAttributeName' => [ 'shape' => 'LabelAttributeName', ], 'InputConfig' => [ 'shape' => 'LabelingJobInputConfig', ], 'OutputConfig' => [ 'shape' => 'LabelingJobOutputConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'LabelCategoryConfigS3Uri' => [ 'shape' => 'S3Uri', ], 'StoppingConditions' => [ 'shape' => 'LabelingJobStoppingConditions', ], 'LabelingJobAlgorithmsConfig' => [ 'shape' => 'LabelingJobAlgorithmsConfig', ], 'HumanTaskConfig' => [ 'shape' => 'HumanTaskConfig', ], 'Tags' => [ 'shape' => 'TagList', ], 'LabelingJobOutput' => [ 'shape' => 'LabelingJobOutput', ], ], ], 'DescribeLineageGroupRequest' => [ 'type' => 'structure', 'required' => [ 'LineageGroupName', ], 'members' => [ 'LineageGroupName' => [ 'shape' => 'ExperimentEntityName', ], ], ], 'DescribeLineageGroupResponse' => [ 'type' => 'structure', 'members' => [ 'LineageGroupName' => [ 'shape' => 'ExperimentEntityName', ], 'LineageGroupArn' => [ 'shape' => 'LineageGroupArn', ], 'DisplayName' => [ 'shape' => 'ExperimentEntityName', ], 'Description' => [ 'shape' => 'ExperimentDescription', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'CreatedBy' => [ 'shape' => 'UserContext', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedBy' => [ 'shape' => 'UserContext', ], ], ], 'DescribeModelBiasJobDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionName', ], 'members' => [ 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], ], ], 'DescribeModelBiasJobDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionArn', 'JobDefinitionName', 'CreationTime', 'ModelBiasAppSpecification', 'ModelBiasJobInput', 'ModelBiasJobOutputConfig', 'JobResources', 'RoleArn', ], 'members' => [ 'JobDefinitionArn' => [ 'shape' => 'MonitoringJobDefinitionArn', ], 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'ModelBiasBaselineConfig' => [ 'shape' => 'ModelBiasBaselineConfig', ], 'ModelBiasAppSpecification' => [ 'shape' => 'ModelBiasAppSpecification', ], 'ModelBiasJobInput' => [ 'shape' => 'ModelBiasJobInput', ], 'ModelBiasJobOutputConfig' => [ 'shape' => 'MonitoringOutputConfig', ], 'JobResources' => [ 'shape' => 'MonitoringResources', ], 'NetworkConfig' => [ 'shape' => 'MonitoringNetworkConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'StoppingCondition' => [ 'shape' => 'MonitoringStoppingCondition', ], ], ], 'DescribeModelCardExportJobRequest' => [ 'type' => 'structure', 'required' => [ 'ModelCardExportJobArn', ], 'members' => [ 'ModelCardExportJobArn' => [ 'shape' => 'ModelCardExportJobArn', ], ], ], 'DescribeModelCardExportJobResponse' => [ 'type' => 'structure', 'required' => [ 'ModelCardExportJobName', 'ModelCardExportJobArn', 'Status', 'ModelCardName', 'ModelCardVersion', 'OutputConfig', 'CreatedAt', 'LastModifiedAt', ], 'members' => [ 'ModelCardExportJobName' => [ 'shape' => 'EntityName', ], 'ModelCardExportJobArn' => [ 'shape' => 'ModelCardExportJobArn', ], 'Status' => [ 'shape' => 'ModelCardExportJobStatus', ], 'ModelCardName' => [ 'shape' => 'EntityName', ], 'ModelCardVersion' => [ 'shape' => 'Integer', ], 'OutputConfig' => [ 'shape' => 'ModelCardExportOutputConfig', ], 'CreatedAt' => [ 'shape' => 'Timestamp', ], 'LastModifiedAt' => [ 'shape' => 'Timestamp', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'ExportArtifacts' => [ 'shape' => 'ModelCardExportArtifacts', ], ], ], 'DescribeModelCardRequest' => [ 'type' => 'structure', 'required' => [ 'ModelCardName', ], 'members' => [ 'ModelCardName' => [ 'shape' => 'ModelCardNameOrArn', ], 'ModelCardVersion' => [ 'shape' => 'Integer', ], ], ], 'DescribeModelCardResponse' => [ 'type' => 'structure', 'required' => [ 'ModelCardArn', 'ModelCardName', 'ModelCardVersion', 'Content', 'ModelCardStatus', 'CreationTime', 'CreatedBy', ], 'members' => [ 'ModelCardArn' => [ 'shape' => 'ModelCardArn', ], 'ModelCardName' => [ 'shape' => 'EntityName', ], 'ModelCardVersion' => [ 'shape' => 'Integer', ], 'Content' => [ 'shape' => 'ModelCardContent', ], 'ModelCardStatus' => [ 'shape' => 'ModelCardStatus', ], 'SecurityConfig' => [ 'shape' => 'ModelCardSecurityConfig', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'CreatedBy' => [ 'shape' => 'UserContext', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedBy' => [ 'shape' => 'UserContext', ], 'ModelCardProcessingStatus' => [ 'shape' => 'ModelCardProcessingStatus', ], ], ], 'DescribeModelExplainabilityJobDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionName', ], 'members' => [ 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], ], ], 'DescribeModelExplainabilityJobDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionArn', 'JobDefinitionName', 'CreationTime', 'ModelExplainabilityAppSpecification', 'ModelExplainabilityJobInput', 'ModelExplainabilityJobOutputConfig', 'JobResources', 'RoleArn', ], 'members' => [ 'JobDefinitionArn' => [ 'shape' => 'MonitoringJobDefinitionArn', ], 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'ModelExplainabilityBaselineConfig' => [ 'shape' => 'ModelExplainabilityBaselineConfig', ], 'ModelExplainabilityAppSpecification' => [ 'shape' => 'ModelExplainabilityAppSpecification', ], 'ModelExplainabilityJobInput' => [ 'shape' => 'ModelExplainabilityJobInput', ], 'ModelExplainabilityJobOutputConfig' => [ 'shape' => 'MonitoringOutputConfig', ], 'JobResources' => [ 'shape' => 'MonitoringResources', ], 'NetworkConfig' => [ 'shape' => 'MonitoringNetworkConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'StoppingCondition' => [ 'shape' => 'MonitoringStoppingCondition', ], ], ], 'DescribeModelInput' => [ 'type' => 'structure', 'required' => [ 'ModelName', ], 'members' => [ 'ModelName' => [ 'shape' => 'ModelName', ], ], ], 'DescribeModelOutput' => [ 'type' => 'structure', 'required' => [ 'ModelName', 'ExecutionRoleArn', 'CreationTime', 'ModelArn', ], 'members' => [ 'ModelName' => [ 'shape' => 'ModelName', ], 'PrimaryContainer' => [ 'shape' => 'ContainerDefinition', ], 'Containers' => [ 'shape' => 'ContainerDefinitionList', ], 'InferenceExecutionConfig' => [ 'shape' => 'InferenceExecutionConfig', ], 'ExecutionRoleArn' => [ 'shape' => 'RoleArn', ], 'VpcConfig' => [ 'shape' => 'VpcConfig', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'ModelArn' => [ 'shape' => 'ModelArn', ], 'EnableNetworkIsolation' => [ 'shape' => 'Boolean', ], 'DeploymentRecommendation' => [ 'shape' => 'DeploymentRecommendation', ], ], ], 'DescribeModelPackageGroupInput' => [ 'type' => 'structure', 'required' => [ 'ModelPackageGroupName', ], 'members' => [ 'ModelPackageGroupName' => [ 'shape' => 'ArnOrName', ], ], ], 'DescribeModelPackageGroupOutput' => [ 'type' => 'structure', 'required' => [ 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'shape' => 'ModelPackageVersion', ], 'ModelPackageArn' => [ 'shape' => 'ModelPackageArn', ], 'ModelPackageDescription' => [ 'shape' => 'EntityDescription', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'InferenceSpecification' => [ 'shape' => 'InferenceSpecification', ], 'SourceAlgorithmSpecification' => [ 'shape' => 'SourceAlgorithmSpecification', ], 'ValidationSpecification' => [ 'shape' => 'ModelPackageValidationSpecification', ], 'ModelPackageStatus' => [ 'shape' => 'ModelPackageStatus', ], 'ModelPackageStatusDetails' => [ 'shape' => 'ModelPackageStatusDetails', ], 'CertifyForMarketplace' => [ 'shape' => 'CertifyForMarketplace', ], 'ModelApprovalStatus' => [ 'shape' => 'ModelApprovalStatus', ], 'CreatedBy' => [ 'shape' => 'UserContext', ], 'MetadataProperties' => [ 'shape' => 'MetadataProperties', ], 'ModelMetrics' => [ 'shape' => 'ModelMetrics', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedBy' => [ 'shape' => 'UserContext', ], 'ApprovalDescription' => [ 'shape' => 'ApprovalDescription', ], 'CustomerMetadataProperties' => [ 'shape' => 'CustomerMetadataMap', ], 'DriftCheckBaselines' => [ 'shape' => 'DriftCheckBaselines', ], 'Domain' => [ 'shape' => 'String', ], 'Task' => [ 'shape' => 'String', ], 'SamplePayloadUrl' => [ 'shape' => 'String', ], 'AdditionalInferenceSpecifications' => [ 'shape' => 'AdditionalInferenceSpecifications', ], 'SkipModelValidation' => [ 'shape' => 'SkipModelValidation', ], ], ], 'DescribeModelQualityJobDefinitionRequest' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionName', ], 'members' => [ 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], ], ], 'DescribeModelQualityJobDefinitionResponse' => [ 'type' => 'structure', 'required' => [ 'JobDefinitionArn', 'JobDefinitionName', 'CreationTime', 'ModelQualityAppSpecification', 'ModelQualityJobInput', 'ModelQualityJobOutputConfig', 'JobResources', 'RoleArn', ], 'members' => [ 'JobDefinitionArn' => [ 'shape' => 'MonitoringJobDefinitionArn', ], 'JobDefinitionName' => [ 'shape' => 'MonitoringJobDefinitionName', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'ModelQualityBaselineConfig' => [ 'shape' => 'ModelQualityBaselineConfig', ], 'ModelQualityAppSpecification' => [ 'shape' => 'ModelQualityAppSpecification', ], 'ModelQualityJobInput' => [ 'shape' => 'ModelQualityJobInput', ], 'ModelQualityJobOutputConfig' => [ 'shape' => 'MonitoringOutputConfig', ], 'JobResources' => [ 'shape' => 'MonitoringResources', ], 'NetworkConfig' => [ 'shape' => 'MonitoringNetworkConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'StoppingCondition' => [ 'shape' => 'MonitoringStoppingCondition', ], ], ], 'DescribeMonitoringScheduleRequest' => [ 'type' => 'structure', 'required' => [ 'MonitoringScheduleName', ], 'members' => [ 'MonitoringScheduleName' => [ 'shape' => 'MonitoringScheduleName', ], ], ], 'DescribeMonitoringScheduleResponse' => [ 'type' => 'structure', 'required' => [ 'MonitoringScheduleArn', 'MonitoringScheduleName', 'MonitoringScheduleStatus', 'CreationTime', 'LastModifiedTime', 'MonitoringScheduleConfig', ], 'members' => [ 'MonitoringScheduleArn' => [ 'shape' => 'MonitoringScheduleArn', ], 'MonitoringScheduleName' => [ 'shape' => 'MonitoringScheduleName', ], 'MonitoringScheduleStatus' => [ 'shape' => 'ScheduleStatus', ], 'MonitoringType' => [ 'shape' => 'MonitoringType', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'MonitoringScheduleConfig' => [ 'shape' => 'MonitoringScheduleConfig', ], 'EndpointName' => [ 'shape' => 'EndpointName', ], 'LastMonitoringExecutionSummary' => [ 'shape' => 'MonitoringExecutionSummary', ], ], ], 'DescribeNotebookInstanceInput' => [ 'type' => 'structure', 'required' => [ 'NotebookInstanceName', ], 'members' => [ 'NotebookInstanceName' => [ 'shape' => 'NotebookInstanceName', ], ], ], 'DescribeNotebookInstanceLifecycleConfigInput' => [ 'type' => 'structure', 'required' => [ 'NotebookInstanceLifecycleConfigName', ], 'members' => [ 'NotebookInstanceLifecycleConfigName' => [ 'shape' => 'NotebookInstanceLifecycleConfigName', ], ], ], 'DescribeNotebookInstanceLifecycleConfigOutput' => [ 'type' => 'structure', 'members' => [ 'NotebookInstanceLifecycleConfigArn' => [ 'shape' => 'NotebookInstanceLifecycleConfigArn', ], 'NotebookInstanceLifecycleConfigName' => [ 'shape' => 'NotebookInstanceLifecycleConfigName', ], 'OnCreate' => [ 'shape' => 'NotebookInstanceLifecycleConfigList', ], 'OnStart' => [ 'shape' => 'NotebookInstanceLifecycleConfigList', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], ], ], 'DescribeNotebookInstanceOutput' => [ 'type' => 'structure', 'members' => [ 'NotebookInstanceArn' => [ 'shape' => 'NotebookInstanceArn', ], 'NotebookInstanceName' => [ 'shape' => 'NotebookInstanceName', ], 'NotebookInstanceStatus' => [ 'shape' => 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'RootAccess' => [ 'shape' => 'RootAccess', ], 'PlatformIdentifier' => [ 'shape' => 'PlatformIdentifier', ], 'InstanceMetadataServiceConfiguration' => [ 'shape' => 'InstanceMetadataServiceConfiguration', ], ], ], 'DescribePipelineDefinitionForExecutionRequest' => [ 'type' => 'structure', 'required' => [ 'PipelineExecutionArn', ], 'members' => [ 'PipelineExecutionArn' => [ 'shape' => 'PipelineExecutionArn', ], ], ], 'DescribePipelineDefinitionForExecutionResponse' => [ 'type' => 'structure', 'members' => [ 'PipelineDefinition' => [ 'shape' => 'PipelineDefinition', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], ], ], 'DescribePipelineExecutionRequest' => [ 'type' => 'structure', 'required' => [ 'PipelineExecutionArn', ], 'members' => [ 'PipelineExecutionArn' => [ 'shape' => 'PipelineExecutionArn', ], ], ], 'DescribePipelineExecutionResponse' => [ 'type' => 'structure', 'members' => [ 'PipelineArn' => [ 'shape' => 'PipelineArn', ], 'PipelineExecutionArn' => [ 'shape' => 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[ 'shape' => 'PipelineArn', ], 'PipelineName' => [ 'shape' => 'PipelineName', ], 'PipelineDisplayName' => [ 'shape' => 'PipelineName', ], 'PipelineDefinition' => [ 'shape' => 'PipelineDefinition', ], 'PipelineDescription' => [ 'shape' => 'PipelineDescription', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'PipelineStatus' => [ 'shape' => 'PipelineStatus', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastRunTime' => [ 'shape' => 'Timestamp', ], 'CreatedBy' => [ 'shape' => 'UserContext', ], 'LastModifiedBy' => [ 'shape' => 'UserContext', ], 'ParallelismConfiguration' => [ 'shape' => 'ParallelismConfiguration', ], ], ], 'DescribeProcessingJobRequest' => [ 'type' => 'structure', 'required' => [ 'ProcessingJobName', ], 'members' => [ 'ProcessingJobName' => [ 'shape' => 'ProcessingJobName', ], ], ], 'DescribeProcessingJobResponse' => [ 'type' => 'structure', 'required' => [ 'ProcessingJobName', 'ProcessingResources', 'AppSpecification', 'ProcessingJobArn', 'ProcessingJobStatus', 'CreationTime', ], 'members' => [ 'ProcessingInputs' => [ 'shape' => 'ProcessingInputs', ], 'ProcessingOutputConfig' => [ 'shape' => 'ProcessingOutputConfig', ], 'ProcessingJobName' => [ 'shape' => 'ProcessingJobName', ], 'ProcessingResources' => [ 'shape' => 'ProcessingResources', ], 'StoppingCondition' => [ 'shape' => 'ProcessingStoppingCondition', ], 'AppSpecification' => [ 'shape' => 'AppSpecification', ], 'Environment' => [ 'shape' => 'ProcessingEnvironmentMap', ], 'NetworkConfig' => [ 'shape' => 'NetworkConfig', ], 'RoleArn' => [ 'shape' => 'RoleArn', ], 'ExperimentConfig' => [ 'shape' => 'ExperimentConfig', ], 'ProcessingJobArn' => [ 'shape' => 'ProcessingJobArn', ], 'ProcessingJobStatus' => [ 'shape' => 'ProcessingJobStatus', ], 'ExitMessage' => [ 'shape' => 'ExitMessage', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'ProcessingEndTime' => [ 'shape' => 'Timestamp', ], 'ProcessingStartTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'MonitoringScheduleArn' => [ 'shape' => 'MonitoringScheduleArn', ], 'AutoMLJobArn' => [ 'shape' => 'AutoMLJobArn', ], 'TrainingJobArn' => [ 'shape' => 'TrainingJobArn', ], ], ], 'DescribeProjectInput' => [ 'type' => 'structure', 'required' => [ 'ProjectName', ], 'members' => [ 'ProjectName' => [ 'shape' => 'ProjectEntityName', ], ], ], 'DescribeProjectOutput' => [ 'type' => 'structure', 'required' => [ 'ProjectArn', 'ProjectName', 'ProjectId', 'ServiceCatalogProvisioningDetails', 'ProjectStatus', 'CreationTime', ], 'members' => [ 'ProjectArn' => [ 'shape' => 'ProjectArn', ], 'ProjectName' => [ 'shape' => 'ProjectEntityName', ], 'ProjectId' => [ 'shape' => 'ProjectId', ], 'ProjectDescription' => [ 'shape' => 'EntityDescription', ], 'ServiceCatalogProvisioningDetails' => [ 'shape' => 'ServiceCatalogProvisioningDetails', ], 'ServiceCatalogProvisionedProductDetails' => [ 'shape' => 'ServiceCatalogProvisionedProductDetails', ], 'ProjectStatus' => [ 'shape' => 'ProjectStatus', ], 'CreatedBy' => [ 'shape' => 'UserContext', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedBy' => [ 'shape' => 'UserContext', ], ], ], 'DescribeSpaceRequest' => [ 'type' => 'structure', 'required' => [ 'DomainId', 'SpaceName', ], 'members' => [ 'DomainId' => [ 'shape' => 'DomainId', ], 'SpaceName' => [ 'shape' => 'SpaceName', ], ], ], 'DescribeSpaceResponse' => [ 'type' => 'structure', 'members' => [ 'DomainId' => [ 'shape' => 'DomainId', ], 'SpaceArn' => [ 'shape' => 'SpaceArn', ], 'SpaceName' => [ 'shape' => 'SpaceName', ], 'HomeEfsFileSystemUid' => [ 'shape' => 'EfsUid', ], 'Status' => [ 'shape' => 'SpaceStatus', ], 'LastModifiedTime' => [ 'shape' => 'LastModifiedTime', ], 'CreationTime' => [ 'shape' => 'CreationTime', ], 'FailureReason' => [ 'shape' => 'FailureReason', ], 'SpaceSettings' => [ 'shape' => 'SpaceSettings', ], ], ], 'DescribeStudioLifecycleConfigRequest' => [ 'type' => 'structure', 'required' => [ 'StudioLifecycleConfigName', ], 'members' => [ 'StudioLifecycleConfigName' => [ 'shape' => 'StudioLifecycleConfigName', ], ], ], 'DescribeStudioLifecycleConfigResponse' => [ 'type' => 'structure', 'members' => [ 'StudioLifecycleConfigArn' => [ 'shape' => 'StudioLifecycleConfigArn', ], 'StudioLifecycleConfigName' => [ 'shape' => 'StudioLifecycleConfigName', ], 'CreationTime' => [ 'shape' => 'Timestamp', ], 'LastModifiedTime' => [ 'shape' => 'Timestamp', ], 'StudioLifecycleConfigContent' => [ 'shape' => 'StudioLifecycleConfigContent', ], 'StudioLifecycleConfigAppType' => [ 'shape' => 'StudioLifecycleConfigAppType', ], ], ], 'DescribeSubscribedWorkteamRequest' => [ 'type' => 'structure', 'required' => [ 'WorkteamArn', ], 'members' => [ 'WorkteamArn' => [ 'shape' => 'WorkteamArn', ], ], ], 'DescribeSubscribedWorkteamResponse' => [ 'type' => 'structure', 'required' => [ 'SubscribedWorkteam', ], 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0, ], 'VariantName' => [ 'type' => 'string', 'max' => 63, 'pattern' => '^[a-zA-Z0-9](-*[a-zA-Z0-9]){0,62}', ], 'VariantProperty' => [ 'type' => 'structure', 'required' => [ 'VariantPropertyType', ], 'members' => [ 'VariantPropertyType' => [ 'shape' => 'VariantPropertyType', ], ], ], 'VariantPropertyList' => [ 'type' => 'list', 'member' => [ 'shape' => 'VariantProperty', ], 'max' => 3, 'min' => 0, ], 'VariantPropertyType' => [ 'type' => 'string', 'enum' => [ 'DesiredInstanceCount', 'DesiredWeight', 'DataCaptureConfig', ], ], 'VariantStatus' => [ 'type' => 'string', 'enum' => [ 'Creating', 'Updating', 'Deleting', 'ActivatingTraffic', 'Baking', ], ], 'VariantStatusMessage' => [ 'type' => 'string', 'max' => 1024, ], 'VariantWeight' => [ 'type' => 'float', 'min' => 0, ], 'VectorConfig' => [ 'type' => 'structure', 'required' => [ 'Dimension', ], 'members' => [ 'Dimension' => [ 'shape' => 'Dimension', ], ], ], 'VendorGuidance' => [ 'type' => 'string', 'enum' => [ 'NOT_PROVIDED', 'STABLE', 'TO_BE_ARCHIVED', 'ARCHIVED', ], ], 'VersionId' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, 'pattern' => '.+', ], 'VersionedArnOrName' => [ 'type' => 'string', 'max' => 176, 'min' => 1, 'pattern' => '(arn:aws[a-z\\-]*:sagemaker:[a-z0-9\\-]*:[0-9]{12}:[a-z\\-]*\\/)?([a-zA-Z0-9]([a-zA-Z0-9-]){0,62})(? [ 'type' => 'structure', 'members' => [ 'Arn' => [ 'shape' => 'AssociationEntityArn', ], 'Type' => [ 'shape' => 'String40', ], 'LineageType' => [ 'shape' => 'LineageType', ], ], ], 'Vertices' => [ 'type' => 'list', 'member' => [ 'shape' => 'Vertex', ], ], 'VolumeSizeInGB' => [ 'type' => 'integer', 'min' => 1, ], 'VpcConfig' => [ 'type' => 'structure', 'required' => [ 'SecurityGroupIds', 'Subnets', ], 'members' => [ 'SecurityGroupIds' => [ 'shape' => 'VpcSecurityGroupIds', ], 'Subnets' => [ 'shape' => 'Subnets', ], ], ], 'VpcId' => [ 'type' => 'string', 'max' => 32, 'pattern' => '[-0-9a-zA-Z]+', ], 'VpcSecurityGroupIds' => [ 'type' => 'list', 'member' => [ 'shape' => 'SecurityGroupId', ], 'max' => 5, 'min' => 1, ], 'WaitIntervalInSeconds' => [ 'type' => 'integer', 'max' => 3600, 'min' => 0, ], 'WarmPoolResourceStatus' => [ 'type' => 'string', 'enum' => [ 'Available', 'Terminated', 'Reused', 'InUse', ], ], 'WarmPoolStatus' => [ 'type' => 'structure', 'required' => [ 'Status', ], 'members' => [ 'Status' => [ 'shape' => 'WarmPoolResourceStatus', ], 'ResourceRetainedBillableTimeInSeconds' => [ 'shape' => 'ResourceRetainedBillableTimeInSeconds', ], 'ReusedByJob' => [ 'shape' => 'TrainingJobName', ], ], ], 'Workforce' => [ 'type' => 'structure', 'required' => [ 'WorkforceName', 'WorkforceArn', ], 'members' => [ 'WorkforceName' => [ 'shape' => 'WorkforceName', ], 'WorkforceArn' => [ 'shape' => 'WorkforceArn', ], 'LastUpdatedDate' => [ 'shape' => 'Timestamp', ], 'SourceIpConfig' => [ 'shape' => 'SourceIpConfig', ], 'SubDomain' => [ 'shape' => 'String', ], 'CognitoConfig' => [ 'shape' => 'CognitoConfig', ], 'OidcConfig' => [ 'shape' => 'OidcConfigForResponse', ], 'CreateDate' => [ 'shape' => 'Timestamp', ], 'WorkforceVpcConfig' => [ 'shape' => 'WorkforceVpcConfigResponse', ], 'Status' => [ 'shape' => 'WorkforceStatus', ], 'FailureReason' => [ 'shape' => 'WorkforceFailureReason', ], ], ], 'WorkforceArn' => [ 'type' => 'string', 'max' => 256, 'pattern' => 'arn:aws[a-z\\-]*:sagemaker:[a-z0-9\\-]*:[0-9]{12}:workforce/.*', ], 'WorkforceFailureReason' => [ 'type' => 'string', 'max' => 1024, 'min' => 1, 'pattern' => '.+', ], 'WorkforceName' => [ 'type' => 'string', 'max' => 63, 'min' => 1, 'pattern' => '^[a-zA-Z0-9]([a-zA-Z0-9\\-]){0,62}$', ], 'WorkforceSecurityGroupId' => [ 'type' => 'string', 'max' => 32, 'pattern' => '^sg-[0-9a-z]*$', ], 'WorkforceSecurityGroupIds' => [ 'type' => 'list', 'member' => [ 'shape' => 'WorkforceSecurityGroupId', ], 'max' => 5, 'min' => 1, ], 'WorkforceStatus' => [ 'type' => 'string', 'enum' => [ 'Initializing', 'Updating', 'Deleting', 'Failed', 'Active', ], ], 'WorkforceSubnetId' => [ 'type' => 'string', 'max' => 32, 'pattern' => '^subnet-[0-9a-z]*$', ], 'WorkforceSubnets' => [ 'type' => 'list', 'member' => [ 'shape' => 'WorkforceSubnetId', ], 'max' => 16, 'min' => 1, ], 'WorkforceVpcConfigRequest' => [ 'type' => 'structure', 'members' => [ 'VpcId' => [ 'shape' => 'WorkforceVpcId', ], 'SecurityGroupIds' => [ 'shape' => 'WorkforceSecurityGroupIds', ], 'Subnets' => [ 'shape' => 'WorkforceSubnets', ], ], ], 'WorkforceVpcConfigResponse' => [ 'type' => 'structure', 'required' => [ 'VpcId', 'SecurityGroupIds', 'Subnets', ], 'members' => [ 'VpcId' => [ 'shape' => 'WorkforceVpcId', ], 'SecurityGroupIds' => [ 'shape' => 'WorkforceSecurityGroupIds', ], 'Subnets' => [ 'shape' => 'WorkforceSubnets', ], 'VpcEndpointId' => [ 'shape' => 'WorkforceVpcEndpointId', ], ], ], 'WorkforceVpcEndpointId' => [ 'type' => 'string', 'max' => 255, 'min' => 1, 'pattern' => '^vpce-[0-9a-z]*$', ], 'WorkforceVpcId' => [ 'type' => 'string', 'max' => 32, 'pattern' => '^vpc-[0-9a-z]*$', ], 'Workforces' => [ 'type' => 'list', 'member' => [ 'shape' => 'Workforce', ], ], 'WorkspaceSettings' => [ 'type' => 'structure', 'members' => [ 'S3ArtifactPath' => [ 'shape' => 'S3Uri', ], 'S3KmsKeyId' => [ 'shape' => 'KmsKeyId', ], ], ], 'Workteam' => [ 'type' => 'structure', 'required' => [ 'WorkteamName', 'MemberDefinitions', 'WorkteamArn', 'Description', ], 'members' => [ 'WorkteamName' => [ 'shape' => 'WorkteamName', ], 'MemberDefinitions' => [ 'shape' => 'MemberDefinitions', ], 'WorkteamArn' => [ 'shape' => 'WorkteamArn', ], 'WorkforceArn' => [ 'shape' => 'WorkforceArn', ], 'ProductListingIds' => [ 'shape' => 'ProductListings', ], 'Description' => [ 'shape' => 'String200', ], 'SubDomain' => [ 'shape' => 'String', ], 'CreateDate' => [ 'shape' => 'Timestamp', ], 'LastUpdatedDate' => [ 'shape' => 'Timestamp', ], 'NotificationConfiguration' => [ 'shape' => 'NotificationConfiguration', ], ], ], 'WorkteamArn' => [ 'type' => 'string', 'max' => 256, 'pattern' => 'arn:aws[a-z\\-]*:sagemaker:[a-z0-9\\-]*:[0-9]{12}:workteam/.*', ], 'WorkteamName' => [ 'type' => 'string', 'max' => 63, 'min' => 1, 'pattern' => '^[a-zA-Z0-9](-*[a-zA-Z0-9]){0,62}', ], 'Workteams' => [ 'type' => 'list', 'member' => [ 'shape' => 'Workteam', ], ], ],]; diff --git a/src/data/sagemaker/2017-07-24/docs-2.json b/src/data/sagemaker/2017-07-24/docs-2.json index 19a932bd93..b1955e6a94 100644 --- a/src/data/sagemaker/2017-07-24/docs-2.json +++ b/src/data/sagemaker/2017-07-24/docs-2.json @@ -314,6 +314,12 @@ "TransformOutput$Accept": "The MIME type used to specify the output data. Amazon SageMaker uses the MIME type with each http call to transfer data from the transform job.
" } }, + "AcceptEula": { + "base": null, + "refs": { + "ModelAccessConfig$AcceptEula": "Specifies agreement to the model end-user license agreement (EULA). The AcceptEula value must be explicitly defined as True in order to accept the EULA that this model requires. You are responsible for reviewing and complying with any applicable license terms and making sure they are acceptable for your use case before downloading or using a model.
The maximum pending time in seconds.
" + "StoppingCondition$MaxPendingTimeInSeconds": "The maximum length of time, in seconds, that a training or compilation job can be pending before it is stopped.
" } }, "MaxPercentageOfInputDatasetLabeled": { @@ -8693,6 +8699,12 @@ "ModelDashboardModel$Model": "A model displayed in the Model Dashboard.
" } }, + "ModelAccessConfig": { + "base": "The access configuration file for the ML model. You can explicitly accept the model end-user license agreement (EULA) within the ModelAccessConfig. For more information, see End-user license agreements.
Specifies the access configuration file for the ML model. You can explicitly accept the model end-user license agreement (EULA) within the ModelAccessConfig. You are responsible for reviewing and complying with any applicable license terms and making sure they are acceptable for your use case before downloading or using a model.
The ARN of the associated Amazon Web Services Single Sign-On application for this Domain.
" + "DescribeDomainResponse$SingleSignOnApplicationArn": "The ARN of the application managed by SageMaker in IAM Identity Center. This value is only returned for domains created after September 19, 2023.
" } }, "SingleSignOnUserIdentifier": { diff --git a/src/data/sagemaker/2017-07-24/docs-2.json.php b/src/data/sagemaker/2017-07-24/docs-2.json.php index 25e38dfd89..23aa0b5543 100644 --- a/src/data/sagemaker/2017-07-24/docs-2.json.php +++ b/src/data/sagemaker/2017-07-24/docs-2.json.php @@ -1,3 +1,3 @@ '2.0', 'service' => 'Provides APIs for creating and managing SageMaker resources.
Other Resources:
', 'operations' => [ 'AddAssociation' => 'Creates an association between the source and the destination. A source can be associated with multiple destinations, and a destination can be associated with multiple sources. An association is a lineage tracking entity. For more information, see Amazon SageMaker ML Lineage Tracking.
', 'AddTags' => 'Adds or overwrites one or more tags for the specified SageMaker resource. You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints.
Each tag consists of a key and an optional value. Tag keys must be unique per resource. For more information about tags, see For more information, see Amazon Web Services Tagging Strategies.
Tags that you add to a hyperparameter tuning job by calling this API are also added to any training jobs that the hyperparameter tuning job launches after you call this API, but not to training jobs that the hyperparameter tuning job launched before you called this API. To make sure that the tags associated with a hyperparameter tuning job are also added to all training jobs that the hyperparameter tuning job launches, add the tags when you first create the tuning job by specifying them in the Tags parameter of CreateHyperParameterTuningJob
Tags that you add to a SageMaker Studio Domain or User Profile by calling this API are also added to any Apps that the Domain or User Profile launches after you call this API, but not to Apps that the Domain or User Profile launched before you called this API. To make sure that the tags associated with a Domain or User Profile are also added to all Apps that the Domain or User Profile launches, add the tags when you first create the Domain or User Profile by specifying them in the Tags parameter of CreateDomain or CreateUserProfile.
Associates a trial component with a trial. A trial component can be associated with multiple trials. To disassociate a trial component from a trial, call the DisassociateTrialComponent API.
', 'BatchDescribeModelPackage' => 'This action batch describes a list of versioned model packages
', 'CreateAction' => 'Creates an action. An action is a lineage tracking entity that represents an action or activity. For example, a model deployment or an HPO job. Generally, an action involves at least one input or output artifact. For more information, see Amazon SageMaker ML Lineage Tracking.
', 'CreateAlgorithm' => 'Create a machine learning algorithm that you can use in SageMaker and list in the Amazon Web Services Marketplace.
', 'CreateApp' => 'Creates a running app for the specified UserProfile. This operation is automatically invoked by Amazon SageMaker Studio upon access to the associated Domain, and when new kernel configurations are selected by the user. A user may have multiple Apps active simultaneously.
', 'CreateAppImageConfig' => 'Creates a configuration for running a SageMaker image as a KernelGateway app. The configuration specifies the Amazon Elastic File System (EFS) storage volume on the image, and a list of the kernels in the image.
', 'CreateArtifact' => 'Creates an artifact. An artifact is a lineage tracking entity that represents a URI addressable object or data. Some examples are the S3 URI of a dataset and the ECR registry path of an image. For more information, see Amazon SageMaker ML Lineage Tracking.
', 'CreateAutoMLJob' => 'Creates an Autopilot job also referred to as Autopilot experiment or AutoML job.
We recommend using the new versions CreateAutoMLJobV2 and DescribeAutoMLJobV2, which offer backward compatibility.
CreateAutoMLJobV2 can manage tabular problem types identical to those of its previous version CreateAutoMLJob, as well as time-series forecasting, non-tabular problem types such as image or text classification, and text generation (LLMs fine-tuning).
Find guidelines about how to migrate a CreateAutoMLJob to CreateAutoMLJobV2 in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.
You can find the best-performing model after you run an AutoML job by calling DescribeAutoMLJobV2 (recommended) or DescribeAutoMLJob.
', 'CreateAutoMLJobV2' => 'Creates an Autopilot job also referred to as Autopilot experiment or AutoML job V2.
CreateAutoMLJobV2 and DescribeAutoMLJobV2 are new versions of CreateAutoMLJob and DescribeAutoMLJob which offer backward compatibility.
CreateAutoMLJobV2 can manage tabular problem types identical to those of its previous version CreateAutoMLJob, as well as time-series forecasting, non-tabular problem types such as image or text classification, and text generation (LLMs fine-tuning).
Find guidelines about how to migrate a CreateAutoMLJob to CreateAutoMLJobV2 in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.
For the list of available problem types supported by CreateAutoMLJobV2, see AutoMLProblemTypeConfig.
You can find the best-performing model after you run an AutoML job V2 by calling DescribeAutoMLJobV2.
', 'CreateCodeRepository' => 'Creates a Git repository as a resource in your SageMaker account. You can associate the repository with notebook instances so that you can use Git source control for the notebooks you create. The Git repository is a resource in your SageMaker account, so it can be associated with more than one notebook instance, and it persists independently from the lifecycle of any notebook instances it is associated with.
The repository can be hosted either in Amazon Web Services CodeCommit or in any other Git repository.
', 'CreateCompilationJob' => 'Starts a model compilation job. After the model has been compiled, Amazon SageMaker saves the resulting model artifacts to an Amazon Simple Storage Service (Amazon S3) bucket that you specify.
If you choose to host your model using Amazon SageMaker hosting services, you can use the resulting model artifacts as part of the model. You can also use the artifacts with Amazon Web Services IoT Greengrass. In that case, deploy them as an ML resource.
In the request body, you provide the following:
A name for the compilation job
Information about the input model artifacts
The output location for the compiled model and the device (target) that the model runs on
The Amazon Resource Name (ARN) of the IAM role that Amazon SageMaker assumes to perform the model compilation job.
You can also provide a Tag to track the model compilation job\'s resource use and costs. The response body contains the CompilationJobArn for the compiled job.
To stop a model compilation job, use StopCompilationJob. To get information about a particular model compilation job, use DescribeCompilationJob. To get information about multiple model compilation jobs, use ListCompilationJobs.
', 'CreateContext' => 'Creates a context. A context is a lineage tracking entity that represents a logical grouping of other tracking or experiment entities. Some examples are an endpoint and a model package. For more information, see Amazon SageMaker ML Lineage Tracking.
', 'CreateDataQualityJobDefinition' => 'Creates a definition for a job that monitors data quality and drift. For information about model monitor, see Amazon SageMaker Model Monitor.
', 'CreateDeviceFleet' => 'Creates a device fleet.
', 'CreateDomain' => 'Creates a Domain used by Amazon SageMaker Studio. A domain consists of an associated Amazon Elastic File System (EFS) volume, a list of authorized users, and a variety of security, application, policy, and Amazon Virtual Private Cloud (VPC) configurations. Users within a domain can share notebook files and other artifacts with each other.
EFS storage
When a domain is created, an EFS volume is created for use by all of the users within the domain. Each user receives a private home directory within the EFS volume for notebooks, Git repositories, and data files.
SageMaker uses the Amazon Web Services Key Management Service (Amazon Web Services KMS) to encrypt the EFS volume attached to the domain with an Amazon Web Services managed key by default. For more control, you can specify a customer managed key. For more information, see Protect Data at Rest Using Encryption.
VPC configuration
All SageMaker Studio traffic between the domain and the EFS volume is through the specified VPC and subnets. For other Studio traffic, you can specify the AppNetworkAccessType parameter. AppNetworkAccessType corresponds to the network access type that you choose when you onboard to Studio. The following options are available:
PublicInternetOnly - Non-EFS traffic goes through a VPC managed by Amazon SageMaker, which allows internet access. This is the default value.
VpcOnly - All Studio traffic is through the specified VPC and subnets. Internet access is disabled by default. To allow internet access, you must specify a NAT gateway.
When internet access is disabled, you won\'t be able to run a Studio notebook or to train or host models unless your VPC has an interface endpoint to the SageMaker API and runtime or a NAT gateway and your security groups allow outbound connections.
NFS traffic over TCP on port 2049 needs to be allowed in both inbound and outbound rules in order to launch a SageMaker Studio app successfully.
For more information, see Connect SageMaker Studio Notebooks to Resources in a VPC.
', 'CreateEdgeDeploymentPlan' => 'Creates an edge deployment plan, consisting of multiple stages. Each stage may have a different deployment configuration and devices.
', 'CreateEdgeDeploymentStage' => 'Creates a new stage in an existing edge deployment plan.
', 'CreateEdgePackagingJob' => 'Starts a SageMaker Edge Manager model packaging job. Edge Manager will use the model artifacts from the Amazon Simple Storage Service bucket that you specify. After the model has been packaged, Amazon SageMaker saves the resulting artifacts to an S3 bucket that you specify.
', 'CreateEndpoint' => 'Creates an endpoint using the endpoint configuration specified in the request. SageMaker uses the endpoint to provision resources and deploy models. You create the endpoint configuration with the CreateEndpointConfig API.
Use this API to deploy models using SageMaker hosting services.
You must not delete an EndpointConfig that is in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. To update an endpoint, you must create a new EndpointConfig.
The endpoint name must be unique within an Amazon Web Services Region in your Amazon Web Services account.
When it receives the request, SageMaker creates the endpoint, launches the resources (ML compute instances), and deploys the model(s) on them.
When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads , the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read.
When SageMaker receives the request, it sets the endpoint status to Creating. After it creates the endpoint, it sets the status to InService. SageMaker can then process incoming requests for inferences. To check the status of an endpoint, use the DescribeEndpoint API.
If any of the models hosted at this endpoint get model data from an Amazon S3 location, SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you provided. Amazon Web Services STS is activated in your Amazon Web Services account by default. If you previously deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see Activating and Deactivating Amazon Web Services STS in an Amazon Web Services Region in the Amazon Web Services Identity and Access Management User Guide.
To add the IAM role policies for using this API operation, go to the IAM console, and choose Roles in the left navigation pane. Search the IAM role that you want to grant access to use the CreateEndpoint and CreateEndpointConfig API operations, add the following policies to the role.
Option 1: For a full SageMaker access, search and attach the AmazonSageMakerFullAccess policy.
Option 2: For granting a limited access to an IAM role, paste the following Action elements manually into the JSON file of the IAM role:
"Action": ["sagemaker:CreateEndpoint", "sagemaker:CreateEndpointConfig"]
"Resource": [
"arn:aws:sagemaker:region:account-id:endpoint/endpointName"
"arn:aws:sagemaker:region:account-id:endpoint-config/endpointConfigName"
]
For more information, see SageMaker API Permissions: Actions, Permissions, and Resources Reference.
Creates an endpoint configuration that SageMaker hosting services uses to deploy models. In the configuration, you identify one or more models, created using the CreateModel API, to deploy and the resources that you want SageMaker to provision. Then you call the CreateEndpoint API.
Use this API if you want to use SageMaker hosting services to deploy models into production.
In the request, you define a ProductionVariant, for each model that you want to deploy. Each ProductionVariant parameter also describes the resources that you want SageMaker to provision. This includes the number and type of ML compute instances to deploy.
If you are hosting multiple models, you also assign a VariantWeight to specify how much traffic you want to allocate to each model. For example, suppose that you want to host two models, A and B, and you assign traffic weight 2 for model A and 1 for model B. SageMaker distributes two-thirds of the traffic to Model A, and one-third to model B.
When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads , the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read.
Creates a SageMaker experiment. An experiment is a collection of trials that are observed, compared and evaluated as a group. A trial is a set of steps, called trial components, that produce a machine learning model.
In the Studio UI, trials are referred to as run groups and trial components are referred to as runs.
The goal of an experiment is to determine the components that produce the best model. Multiple trials are performed, each one isolating and measuring the impact of a change to one or more inputs, while keeping the remaining inputs constant.
When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided by the SDK.
You can add tags to experiments, trials, trial components and then use the Search API to search for the tags.
To add a description to an experiment, specify the optional Description parameter. To add a description later, or to change the description, call the UpdateExperiment API.
To get a list of all your experiments, call the ListExperiments API. To view an experiment\'s properties, call the DescribeExperiment API. To get a list of all the trials associated with an experiment, call the ListTrials API. To create a trial call the CreateTrial API.
', 'CreateFeatureGroup' => 'Create a new FeatureGroup. A FeatureGroup is a group of Features defined in the FeatureStore to describe a Record.
The FeatureGroup defines the schema and features contained in the FeatureGroup. A FeatureGroup definition is composed of a list of Features, a RecordIdentifierFeatureName, an EventTimeFeatureName and configurations for its OnlineStore and OfflineStore. Check Amazon Web Services service quotas to see the FeatureGroups quota for your Amazon Web Services account.
Note that it can take approximately 10-15 minutes to provision an OnlineStore FeatureGroup with the InMemory StorageType.
You must include at least one of OnlineStoreConfig and OfflineStoreConfig to create a FeatureGroup.
Creates a flow definition.
', 'CreateHub' => 'Create a hub.
Hub APIs are only callable through SageMaker Studio.
Defines the settings you will use for the human review workflow user interface. Reviewers will see a three-panel interface with an instruction area, the item to review, and an input area.
', 'CreateHyperParameterTuningJob' => 'Starts a hyperparameter tuning job. A hyperparameter tuning job finds the best version of a model by running many training jobs on your dataset using the algorithm you choose and values for hyperparameters within ranges that you specify. It then chooses the hyperparameter values that result in a model that performs the best, as measured by an objective metric that you choose.
A hyperparameter tuning job automatically creates Amazon SageMaker experiments, trials, and trial components for each training job that it runs. You can view these entities in Amazon SageMaker Studio. For more information, see View Experiments, Trials, and Trial Components.
Do not include any security-sensitive information including account access IDs, secrets or tokens in any hyperparameter field. If the use of security-sensitive credentials are detected, SageMaker will reject your training job request and return an exception error.
Creates a custom SageMaker image. A SageMaker image is a set of image versions. Each image version represents a container image stored in Amazon Elastic Container Registry (ECR). For more information, see Bring your own SageMaker image.
', 'CreateImageVersion' => 'Creates a version of the SageMaker image specified by ImageName. The version represents the Amazon Elastic Container Registry (ECR) container image specified by BaseImage.
Creates an inference experiment using the configurations specified in the request.
Use this API to setup and schedule an experiment to compare model variants on a Amazon SageMaker inference endpoint. For more information about inference experiments, see Shadow tests.
Amazon SageMaker begins your experiment at the scheduled time and routes traffic to your endpoint\'s model variants based on your specified configuration.
While the experiment is in progress or after it has concluded, you can view metrics that compare your model variants. For more information, see View, monitor, and edit shadow tests.
', 'CreateInferenceRecommendationsJob' => 'Starts a recommendation job. You can create either an instance recommendation or load test job.
', 'CreateLabelingJob' => 'Creates a job that uses workers to label the data objects in your input dataset. You can use the labeled data to train machine learning models.
You can select your workforce from one of three providers:
A private workforce that you create. It can include employees, contractors, and outside experts. Use a private workforce when want the data to stay within your organization or when a specific set of skills is required.
One or more vendors that you select from the Amazon Web Services Marketplace. Vendors provide expertise in specific areas.
The Amazon Mechanical Turk workforce. This is the largest workforce, but it should only be used for public data or data that has been stripped of any personally identifiable information.
You can also use automated data labeling to reduce the number of data objects that need to be labeled by a human. Automated data labeling uses active learning to determine if a data object can be labeled by machine or if it needs to be sent to a human worker. For more information, see Using Automated Data Labeling.
The data objects to be labeled are contained in an Amazon S3 bucket. You create a manifest file that describes the location of each object. For more information, see Using Input and Output Data.
The output can be used as the manifest file for another labeling job or as training data for your machine learning models.
You can use this operation to create a static labeling job or a streaming labeling job. A static labeling job stops if all data objects in the input manifest file identified in ManifestS3Uri have been labeled. A streaming labeling job runs perpetually until it is manually stopped, or remains idle for 10 days. You can send new data objects to an active (InProgress) streaming labeling job in real time. To learn how to create a static labeling job, see Create a Labeling Job (API) in the Amazon SageMaker Developer Guide. To learn how to create a streaming labeling job, see Create a Streaming Labeling Job.
Creates a model in SageMaker. In the request, you name the model and describe a primary container. For the primary container, you specify the Docker image that contains inference code, artifacts (from prior training), and a custom environment map that the inference code uses when you deploy the model for predictions.
Use this API to create a model if you want to use SageMaker hosting services or run a batch transform job.
To host your model, you create an endpoint configuration with the CreateEndpointConfig API, and then create an endpoint with the CreateEndpoint API. SageMaker then deploys all of the containers that you defined for the model in the hosting environment.
For an example that calls this method when deploying a model to SageMaker hosting services, see Create a Model (Amazon Web Services SDK for Python (Boto 3)).
To run a batch transform using your model, you start a job with the CreateTransformJob API. SageMaker uses your model and your dataset to get inferences which are then saved to a specified S3 location.
In the request, you also provide an IAM role that SageMaker can assume to access model artifacts and docker image for deployment on ML compute hosting instances or for batch transform jobs. In addition, you also use the IAM role to manage permissions the inference code needs. For example, if the inference code access any other Amazon Web Services resources, you grant necessary permissions via this role.
', 'CreateModelBiasJobDefinition' => 'Creates the definition for a model bias job.
', 'CreateModelCard' => 'Creates an Amazon SageMaker Model Card.
For information about how to use model cards, see Amazon SageMaker Model Card.
', 'CreateModelCardExportJob' => 'Creates an Amazon SageMaker Model Card export job.
', 'CreateModelExplainabilityJobDefinition' => 'Creates the definition for a model explainability job.
', 'CreateModelPackage' => 'Creates a model package that you can use to create SageMaker models or list on Amazon Web Services Marketplace, or a versioned model that is part of a model group. Buyers can subscribe to model packages listed on Amazon Web Services Marketplace to create models in SageMaker.
To create a model package by specifying a Docker container that contains your inference code and the Amazon S3 location of your model artifacts, provide values for InferenceSpecification. To create a model from an algorithm resource that you created or subscribed to in Amazon Web Services Marketplace, provide a value for SourceAlgorithmSpecification.
There are two types of model packages:
Versioned - a model that is part of a model group in the model registry.
Unversioned - a model package that is not part of a model group.
Creates a model group. A model group contains a group of model versions.
', 'CreateModelQualityJobDefinition' => 'Creates a definition for a job that monitors model quality and drift. For information about model monitor, see Amazon SageMaker Model Monitor.
', 'CreateMonitoringSchedule' => 'Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to monitor the data captured for an Amazon SageMaker Endpoint.
', 'CreateNotebookInstance' => 'Creates an SageMaker notebook instance. A notebook instance is a machine learning (ML) compute instance running on a Jupyter notebook.
In a CreateNotebookInstance request, specify the type of ML compute instance that you want to run. SageMaker launches the instance, installs common libraries that you can use to explore datasets for model training, and attaches an ML storage volume to the notebook instance.
SageMaker also provides a set of example notebooks. Each notebook demonstrates how to use SageMaker with a specific algorithm or with a machine learning framework.
After receiving the request, SageMaker does the following:
Creates a network interface in the SageMaker VPC.
(Option) If you specified SubnetId, SageMaker creates a network interface in your own VPC, which is inferred from the subnet ID that you provide in the input. When creating this network interface, SageMaker attaches the security group that you specified in the request to the network interface that it creates in your VPC.
Launches an EC2 instance of the type specified in the request in the SageMaker VPC. If you specified SubnetId of your VPC, SageMaker specifies both network interfaces when launching this instance. This enables inbound traffic from your own VPC to the notebook instance, assuming that the security groups allow it.
After creating the notebook instance, SageMaker returns its Amazon Resource Name (ARN). You can\'t change the name of a notebook instance after you create it.
After SageMaker creates the notebook instance, you can connect to the Jupyter server and work in Jupyter notebooks. For example, you can write code to explore a dataset that you can use for model training, train a model, host models by creating SageMaker endpoints, and validate hosted models.
For more information, see How It Works.
', 'CreateNotebookInstanceLifecycleConfig' => 'Creates a lifecycle configuration that you can associate with a notebook instance. A lifecycle configuration is a collection of shell scripts that run when you create or start a notebook instance.
Each lifecycle configuration script has a limit of 16384 characters.
The value of the $PATH environment variable that is available to both scripts is /sbin:bin:/usr/sbin:/usr/bin.
View CloudWatch Logs for notebook instance lifecycle configurations in log group /aws/sagemaker/NotebookInstances in log stream [notebook-instance-name]/[LifecycleConfigHook].
Lifecycle configuration scripts cannot run for longer than 5 minutes. If a script runs for longer than 5 minutes, it fails and the notebook instance is not created or started.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
', 'CreatePipeline' => 'Creates a pipeline using a JSON pipeline definition.
', 'CreatePresignedDomainUrl' => 'Creates a URL for a specified UserProfile in a Domain. When accessed in a web browser, the user will be automatically signed in to Amazon SageMaker Studio, and granted access to all of the Apps and files associated with the Domain\'s Amazon Elastic File System (EFS) volume. This operation can only be called when the authentication mode equals IAM.
The IAM role or user passed to this API defines the permissions to access the app. Once the presigned URL is created, no additional permission is required to access this URL. IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that attempts to connect to the app.
You can restrict access to this API and to the URL that it returns to a list of IP addresses, Amazon VPCs or Amazon VPC Endpoints that you specify. For more information, see Connect to SageMaker Studio Through an Interface VPC Endpoint .
The URL that you get from a call to CreatePresignedDomainUrl has a default timeout of 5 minutes. You can configure this value using ExpiresInSeconds. If you try to use the URL after the timeout limit expires, you are directed to the Amazon Web Services console sign-in page.
Returns a URL that you can use to connect to the Jupyter server from a notebook instance. In the SageMaker console, when you choose Open next to a notebook instance, SageMaker opens a new tab showing the Jupyter server home page from the notebook instance. The console uses this API to get the URL and show the page.
The IAM role or user used to call this API defines the permissions to access the notebook instance. Once the presigned URL is created, no additional permission is required to access this URL. IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that attempts to connect to the notebook instance.
You can restrict access to this API and to the URL that it returns to a list of IP addresses that you specify. Use the NotIpAddress condition operator and the aws:SourceIP condition context key to specify the list of IP addresses that you want to have access to the notebook instance. For more information, see Limit Access to a Notebook Instance by IP Address.
The URL that you get from a call to CreatePresignedNotebookInstanceUrl is valid only for 5 minutes. If you try to use the URL after the 5-minute limit expires, you are directed to the Amazon Web Services console sign-in page.
Creates a processing job.
', 'CreateProject' => 'Creates a machine learning (ML) project that can contain one or more templates that set up an ML pipeline from training to deploying an approved model.
', 'CreateSpace' => 'Creates a space used for real time collaboration in a Domain.
', 'CreateStudioLifecycleConfig' => 'Creates a new Studio Lifecycle Configuration.
', 'CreateTrainingJob' => 'Starts a model training job. After training completes, SageMaker saves the resulting model artifacts to an Amazon S3 location that you specify.
If you choose to host your model using SageMaker hosting services, you can use the resulting model artifacts as part of the model. You can also use the artifacts in a machine learning service other than SageMaker, provided that you know how to use them for inference.
In the request body, you provide the following:
AlgorithmSpecification - Identifies the training algorithm to use.
HyperParameters - Specify these algorithm-specific parameters to enable the estimation of model parameters during training. Hyperparameters can be tuned to optimize this learning process. For a list of hyperparameters for each training algorithm provided by SageMaker, see Algorithms.
Do not include any security-sensitive information including account access IDs, secrets or tokens in any hyperparameter field. If the use of security-sensitive credentials are detected, SageMaker will reject your training job request and return an exception error.
InputDataConfig - Describes the input required by the training job and the Amazon S3, EFS, or FSx location where it is stored.
OutputDataConfig - Identifies the Amazon S3 bucket where you want SageMaker to save the results of model training.
ResourceConfig - Identifies the resources, ML compute instances, and ML storage volumes to deploy for model training. In distributed training, you specify more than one instance.
EnableManagedSpotTraining - Optimize the cost of training machine learning models by up to 80% by using Amazon EC2 Spot instances. For more information, see Managed Spot Training.
RoleArn - The Amazon Resource Name (ARN) that SageMaker assumes to perform tasks on your behalf during model training. You must grant this role the necessary permissions so that SageMaker can successfully complete model training.
StoppingCondition - To help cap training costs, use MaxRuntimeInSeconds to set a time limit for training. Use MaxWaitTimeInSeconds to specify how long a managed spot training job has to complete.
Environment - The environment variables to set in the Docker container.
RetryStrategy - The number of times to retry the job when the job fails due to an InternalServerError.
For more information about SageMaker, see How It Works.
', 'CreateTransformJob' => 'Starts a transform job. A transform job uses a trained model to get inferences on a dataset and saves these results to an Amazon S3 location that you specify.
To perform batch transformations, you create a transform job and use the data that you have readily available.
In the request body, you provide the following:
TransformJobName - Identifies the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
ModelName - Identifies the model to use. ModelName must be the name of an existing Amazon SageMaker model in the same Amazon Web Services Region and Amazon Web Services account. For information on creating a model, see CreateModel.
TransformInput - Describes the dataset to be transformed and the Amazon S3 location where it is stored.
TransformOutput - Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
TransformResources - Identifies the ML compute instances for the transform job.
For more information about how batch transformation works, see Batch Transform.
', 'CreateTrial' => 'Creates an SageMaker trial. A trial is a set of steps called trial components that produce a machine learning model. A trial is part of a single SageMaker experiment.
When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided by the SDK.
You can add tags to a trial and then use the Search API to search for the tags.
To get a list of all your trials, call the ListTrials API. To view a trial\'s properties, call the DescribeTrial API. To create a trial component, call the CreateTrialComponent API.
', 'CreateTrialComponent' => 'Creates a trial component, which is a stage of a machine learning trial. A trial is composed of one or more trial components. A trial component can be used in multiple trials.
Trial components include pre-processing jobs, training jobs, and batch transform jobs.
When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided by the SDK.
You can add tags to a trial component and then use the Search API to search for the tags.
', 'CreateUserProfile' => 'Creates a user profile. A user profile represents a single user within a domain, and is the main way to reference a "person" for the purposes of sharing, reporting, and other user-oriented features. This entity is created when a user onboards to Amazon SageMaker Studio. If an administrator invites a person by email or imports them from IAM Identity Center, a user profile is automatically created. A user profile is the primary holder of settings for an individual user and has a reference to the user\'s private Amazon Elastic File System (EFS) home directory.
', 'CreateWorkforce' => 'Use this operation to create a workforce. This operation will return an error if a workforce already exists in the Amazon Web Services Region that you specify. You can only create one workforce in each Amazon Web Services Region per Amazon Web Services account.
If you want to create a new workforce in an Amazon Web Services Region where a workforce already exists, use the DeleteWorkforce API operation to delete the existing workforce and then use CreateWorkforce to create a new workforce.
To create a private workforce using Amazon Cognito, you must specify a Cognito user pool in CognitoConfig. You can also create an Amazon Cognito workforce using the Amazon SageMaker console. For more information, see Create a Private Workforce (Amazon Cognito).
To create a private workforce using your own OIDC Identity Provider (IdP), specify your IdP configuration in OidcConfig. Your OIDC IdP must support groups because groups are used by Ground Truth and Amazon A2I to create work teams. For more information, see Create a Private Workforce (OIDC IdP).
Creates a new work team for labeling your data. A work team is defined by one or more Amazon Cognito user pools. You must first create the user pools before you can create a work team.
You cannot create more than 25 work teams in an account and region.
', 'DeleteAction' => 'Deletes an action.
', 'DeleteAlgorithm' => 'Removes the specified algorithm from your account.
', 'DeleteApp' => 'Used to stop and delete an app.
', 'DeleteAppImageConfig' => 'Deletes an AppImageConfig.
', 'DeleteArtifact' => 'Deletes an artifact. Either ArtifactArn or Source must be specified.
Deletes an association.
', 'DeleteCodeRepository' => 'Deletes the specified Git repository from your account.
', 'DeleteContext' => 'Deletes an context.
', 'DeleteDataQualityJobDefinition' => 'Deletes a data quality monitoring job definition.
', 'DeleteDeviceFleet' => 'Deletes a fleet.
', 'DeleteDomain' => 'Used to delete a domain. If you onboarded with IAM mode, you will need to delete your domain to onboard again using IAM Identity Center. Use with caution. All of the members of the domain will lose access to their EFS volume, including data, notebooks, and other artifacts.
', 'DeleteEdgeDeploymentPlan' => 'Deletes an edge deployment plan if (and only if) all the stages in the plan are inactive or there are no stages in the plan.
', 'DeleteEdgeDeploymentStage' => 'Delete a stage in an edge deployment plan if (and only if) the stage is inactive.
', 'DeleteEndpoint' => 'Deletes an endpoint. SageMaker frees up all of the resources that were deployed when the endpoint was created.
SageMaker retires any custom KMS key grants associated with the endpoint, meaning you don\'t need to use the RevokeGrant API call.
When you delete your endpoint, SageMaker asynchronously deletes associated endpoint resources such as KMS key grants. You might still see these resources in your account for a few minutes after deleting your endpoint. Do not delete or revoke the permissions for your ExecutionRoleArn , otherwise SageMaker cannot delete these resources.
Deletes an endpoint configuration. The DeleteEndpointConfig API deletes only the specified configuration. It does not delete endpoints created using the configuration.
You must not delete an EndpointConfig in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. If you delete the EndpointConfig of an endpoint that is active or being created or updated you may lose visibility into the instance type the endpoint is using. The endpoint must be deleted in order to stop incurring charges.
Deletes an SageMaker experiment. All trials associated with the experiment must be deleted first. Use the ListTrials API to get a list of the trials associated with the experiment.
', 'DeleteFeatureGroup' => 'Delete the FeatureGroup and any data that was written to the OnlineStore of the FeatureGroup. Data cannot be accessed from the OnlineStore immediately after DeleteFeatureGroup is called.
Data written into the OfflineStore will not be deleted. The Amazon Web Services Glue database and tables that are automatically created for your OfflineStore are not deleted.
Note that it can take approximately 10-15 minutes to delete an OnlineStore FeatureGroup with the InMemory StorageType.
Deletes the specified flow definition.
', 'DeleteHub' => 'Delete a hub.
Hub APIs are only callable through SageMaker Studio.
Delete the contents of a hub.
Hub APIs are only callable through SageMaker Studio.
Use this operation to delete a human task user interface (worker task template).
To see a list of human task user interfaces (work task templates) in your account, use ListHumanTaskUis. When you delete a worker task template, it no longer appears when you call ListHumanTaskUis.
Deletes a SageMaker image and all versions of the image. The container images aren\'t deleted.
', 'DeleteImageVersion' => 'Deletes a version of a SageMaker image. The container image the version represents isn\'t deleted.
', 'DeleteInferenceExperiment' => 'Deletes an inference experiment.
This operation does not delete your endpoint, variants, or any underlying resources. This operation only deletes the metadata of your experiment.
Deletes a model. The DeleteModel API deletes only the model entry that was created in SageMaker when you called the CreateModel API. It does not delete model artifacts, inference code, or the IAM role that you specified when creating the model.
Deletes an Amazon SageMaker model bias job definition.
', 'DeleteModelCard' => 'Deletes an Amazon SageMaker Model Card.
', 'DeleteModelExplainabilityJobDefinition' => 'Deletes an Amazon SageMaker model explainability job definition.
', 'DeleteModelPackage' => 'Deletes a model package.
A model package is used to create SageMaker models or list on Amazon Web Services Marketplace. Buyers can subscribe to model packages listed on Amazon Web Services Marketplace to create models in SageMaker.
', 'DeleteModelPackageGroup' => 'Deletes the specified model group.
', 'DeleteModelPackageGroupPolicy' => 'Deletes a model group resource policy.
', 'DeleteModelQualityJobDefinition' => 'Deletes the secified model quality monitoring job definition.
', 'DeleteMonitoringSchedule' => 'Deletes a monitoring schedule. Also stops the schedule had not already been stopped. This does not delete the job execution history of the monitoring schedule.
', 'DeleteNotebookInstance' => ' Deletes an SageMaker notebook instance. Before you can delete a notebook instance, you must call the StopNotebookInstance API.
When you delete a notebook instance, you lose all of your data. SageMaker removes the ML compute instance, and deletes the ML storage volume and the network interface associated with the notebook instance.
Deletes a notebook instance lifecycle configuration.
', 'DeletePipeline' => 'Deletes a pipeline if there are no running instances of the pipeline. To delete a pipeline, you must stop all running instances of the pipeline using the StopPipelineExecution API. When you delete a pipeline, all instances of the pipeline are deleted.
Delete the specified project.
', 'DeleteSpace' => 'Used to delete a space.
', 'DeleteStudioLifecycleConfig' => 'Deletes the Studio Lifecycle Configuration. In order to delete the Lifecycle Configuration, there must be no running apps using the Lifecycle Configuration. You must also remove the Lifecycle Configuration from UserSettings in all Domains and UserProfiles.
', 'DeleteTags' => 'Deletes the specified tags from an SageMaker resource.
To list a resource\'s tags, use the ListTags API.
When you call this API to delete tags from a hyperparameter tuning job, the deleted tags are not removed from training jobs that the hyperparameter tuning job launched before you called this API.
When you call this API to delete tags from a SageMaker Studio Domain or User Profile, the deleted tags are not removed from Apps that the SageMaker Studio Domain or User Profile launched before you called this API.
Deletes the specified trial. All trial components that make up the trial must be deleted first. Use the DescribeTrialComponent API to get the list of trial components.
', 'DeleteTrialComponent' => 'Deletes the specified trial component. A trial component must be disassociated from all trials before the trial component can be deleted. To disassociate a trial component from a trial, call the DisassociateTrialComponent API.
', 'DeleteUserProfile' => 'Deletes a user profile. When a user profile is deleted, the user loses access to their EFS volume, including data, notebooks, and other artifacts.
', 'DeleteWorkforce' => 'Use this operation to delete a workforce.
If you want to create a new workforce in an Amazon Web Services Region where a workforce already exists, use this operation to delete the existing workforce and then use CreateWorkforce to create a new workforce.
If a private workforce contains one or more work teams, you must use the DeleteWorkteam operation to delete all work teams before you delete the workforce. If you try to delete a workforce that contains one or more work teams, you will recieve a ResourceInUse error.
Deletes an existing work team. This operation can\'t be undone.
', 'DeregisterDevices' => 'Deregisters the specified devices. After you deregister a device, you will need to re-register the devices.
', 'DescribeAction' => 'Describes an action.
', 'DescribeAlgorithm' => 'Returns a description of the specified algorithm that is in your account.
', 'DescribeApp' => 'Describes the app.
', 'DescribeAppImageConfig' => 'Describes an AppImageConfig.
', 'DescribeArtifact' => 'Describes an artifact.
', 'DescribeAutoMLJob' => 'Returns information about an AutoML job created by calling CreateAutoMLJob.
AutoML jobs created by calling CreateAutoMLJobV2 cannot be described by DescribeAutoMLJob.
Returns information about an AutoML job created by calling CreateAutoMLJobV2 or CreateAutoMLJob.
', 'DescribeCodeRepository' => 'Gets details about the specified Git repository.
', 'DescribeCompilationJob' => 'Returns information about a model compilation job.
To create a model compilation job, use CreateCompilationJob. To get information about multiple model compilation jobs, use ListCompilationJobs.
', 'DescribeContext' => 'Describes a context.
', 'DescribeDataQualityJobDefinition' => 'Gets the details of a data quality monitoring job definition.
', 'DescribeDevice' => 'Describes the device.
', 'DescribeDeviceFleet' => 'A description of the fleet the device belongs to.
', 'DescribeDomain' => 'The description of the domain.
', 'DescribeEdgeDeploymentPlan' => 'Describes an edge deployment plan with deployment status per stage.
', 'DescribeEdgePackagingJob' => 'A description of edge packaging jobs.
', 'DescribeEndpoint' => 'Returns the description of an endpoint.
', 'DescribeEndpointConfig' => 'Returns the description of an endpoint configuration created using the CreateEndpointConfig API.
Provides a list of an experiment\'s properties.
', 'DescribeFeatureGroup' => 'Use this operation to describe a FeatureGroup. The response includes information on the creation time, FeatureGroup name, the unique identifier for each FeatureGroup, and more.
Shows the metadata for a feature within a feature group.
', 'DescribeFlowDefinition' => 'Returns information about the specified flow definition.
', 'DescribeHub' => 'Describe a hub.
Hub APIs are only callable through SageMaker Studio.
Describe the content of a hub.
Hub APIs are only callable through SageMaker Studio.
Returns information about the requested human task user interface (worker task template).
', 'DescribeHyperParameterTuningJob' => 'Returns a description of a hyperparameter tuning job, depending on the fields selected. These fields can include the name, Amazon Resource Name (ARN), job status of your tuning job and more.
', 'DescribeImage' => 'Describes a SageMaker image.
', 'DescribeImageVersion' => 'Describes a version of a SageMaker image.
', 'DescribeInferenceExperiment' => 'Returns details about an inference experiment.
', 'DescribeInferenceRecommendationsJob' => 'Provides the results of the Inference Recommender job. One or more recommendation jobs are returned.
', 'DescribeLabelingJob' => 'Gets information about a labeling job.
', 'DescribeLineageGroup' => 'Provides a list of properties for the requested lineage group. For more information, see Cross-Account Lineage Tracking in the Amazon SageMaker Developer Guide.
', 'DescribeModel' => 'Describes a model that you created using the CreateModel API.
Returns a description of a model bias job definition.
', 'DescribeModelCard' => 'Describes the content, creation time, and security configuration of an Amazon SageMaker Model Card.
', 'DescribeModelCardExportJob' => 'Describes an Amazon SageMaker Model Card export job.
', 'DescribeModelExplainabilityJobDefinition' => 'Returns a description of a model explainability job definition.
', 'DescribeModelPackage' => 'Returns a description of the specified model package, which is used to create SageMaker models or list them on Amazon Web Services Marketplace.
To create models in SageMaker, buyers can subscribe to model packages listed on Amazon Web Services Marketplace.
', 'DescribeModelPackageGroup' => 'Gets a description for the specified model group.
', 'DescribeModelQualityJobDefinition' => 'Returns a description of a model quality job definition.
', 'DescribeMonitoringSchedule' => 'Describes the schedule for a monitoring job.
', 'DescribeNotebookInstance' => 'Returns information about a notebook instance.
', 'DescribeNotebookInstanceLifecycleConfig' => 'Returns a description of a notebook instance lifecycle configuration.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
', 'DescribePipeline' => 'Describes the details of a pipeline.
', 'DescribePipelineDefinitionForExecution' => 'Describes the details of an execution\'s pipeline definition.
', 'DescribePipelineExecution' => 'Describes the details of a pipeline execution.
', 'DescribeProcessingJob' => 'Returns a description of a processing job.
', 'DescribeProject' => 'Describes the details of a project.
', 'DescribeSpace' => 'Describes the space.
', 'DescribeStudioLifecycleConfig' => 'Describes the Studio Lifecycle Configuration.
', 'DescribeSubscribedWorkteam' => 'Gets information about a work team provided by a vendor. It returns details about the subscription with a vendor in the Amazon Web Services Marketplace.
', 'DescribeTrainingJob' => 'Returns information about a training job.
Some of the attributes below only appear if the training job successfully starts. If the training job fails, TrainingJobStatus is Failed and, depending on the FailureReason, attributes like TrainingStartTime, TrainingTimeInSeconds, TrainingEndTime, and BillableTimeInSeconds may not be present in the response.
Returns information about a transform job.
', 'DescribeTrial' => 'Provides a list of a trial\'s properties.
', 'DescribeTrialComponent' => 'Provides a list of a trials component\'s properties.
', 'DescribeUserProfile' => 'Describes a user profile. For more information, see CreateUserProfile.
Lists private workforce information, including workforce name, Amazon Resource Name (ARN), and, if applicable, allowed IP address ranges (CIDRs). Allowable IP address ranges are the IP addresses that workers can use to access tasks.
This operation applies only to private workforces.
Gets information about a specific work team. You can see information such as the create date, the last updated date, membership information, and the work team\'s Amazon Resource Name (ARN).
', 'DisableSagemakerServicecatalogPortfolio' => 'Disables using Service Catalog in SageMaker. Service Catalog is used to create SageMaker projects.
', 'DisassociateTrialComponent' => 'Disassociates a trial component from a trial. This doesn\'t effect other trials the component is associated with. Before you can delete a component, you must disassociate the component from all trials it is associated with. To associate a trial component with a trial, call the AssociateTrialComponent API.
To get a list of the trials a component is associated with, use the Search API. Specify ExperimentTrialComponent for the Resource parameter. The list appears in the response under Results.TrialComponent.Parents.
Enables using Service Catalog in SageMaker. Service Catalog is used to create SageMaker projects.
', 'GetDeviceFleetReport' => 'Describes a fleet.
', 'GetLineageGroupPolicy' => 'The resource policy for the lineage group.
', 'GetModelPackageGroupPolicy' => 'Gets a resource policy that manages access for a model group. For information about resource policies, see Identity-based policies and resource-based policies in the Amazon Web Services Identity and Access Management User Guide..
', 'GetSagemakerServicecatalogPortfolioStatus' => 'Gets the status of Service Catalog in SageMaker. Service Catalog is used to create SageMaker projects.
', 'GetScalingConfigurationRecommendation' => 'Starts an Amazon SageMaker Inference Recommender autoscaling recommendation job. Returns recommendations for autoscaling policies that you can apply to your SageMaker endpoint.
', 'GetSearchSuggestions' => 'An auto-complete API for the search functionality in the SageMaker console. It returns suggestions of possible matches for the property name to use in Search queries. Provides suggestions for HyperParameters, Tags, and Metrics.
Import hub content.
Hub APIs are only callable through SageMaker Studio.
Lists the actions in your account and their properties.
', 'ListAlgorithms' => 'Lists the machine learning algorithms that have been created.
', 'ListAliases' => 'Lists the aliases of a specified image or image version.
', 'ListAppImageConfigs' => 'Lists the AppImageConfigs in your account and their properties. The list can be filtered by creation time or modified time, and whether the AppImageConfig name contains a specified string.
', 'ListApps' => 'Lists apps.
', 'ListArtifacts' => 'Lists the artifacts in your account and their properties.
', 'ListAssociations' => 'Lists the associations in your account and their properties.
', 'ListAutoMLJobs' => 'Request a list of jobs.
', 'ListCandidatesForAutoMLJob' => 'List the candidates created for the job.
', 'ListCodeRepositories' => 'Gets a list of the Git repositories in your account.
', 'ListCompilationJobs' => 'Lists model compilation jobs that satisfy various filters.
To create a model compilation job, use CreateCompilationJob. To get information about a particular model compilation job you have created, use DescribeCompilationJob.
', 'ListContexts' => 'Lists the contexts in your account and their properties.
', 'ListDataQualityJobDefinitions' => 'Lists the data quality job definitions in your account.
', 'ListDeviceFleets' => 'Returns a list of devices in the fleet.
', 'ListDevices' => 'A list of devices.
', 'ListDomains' => 'Lists the domains.
', 'ListEdgeDeploymentPlans' => 'Lists all edge deployment plans.
', 'ListEdgePackagingJobs' => 'Returns a list of edge packaging jobs.
', 'ListEndpointConfigs' => 'Lists endpoint configurations.
', 'ListEndpoints' => 'Lists endpoints.
', 'ListExperiments' => 'Lists all the experiments in your account. The list can be filtered to show only experiments that were created in a specific time range. The list can be sorted by experiment name or creation time.
', 'ListFeatureGroups' => 'List FeatureGroups based on given filter and order.
Returns information about the flow definitions in your account.
', 'ListHubContentVersions' => 'List hub content versions.
Hub APIs are only callable through SageMaker Studio.
List the contents of a hub.
Hub APIs are only callable through SageMaker Studio.
List all existing hubs.
Hub APIs are only callable through SageMaker Studio.
Returns information about the human task user interfaces in your account.
', 'ListHyperParameterTuningJobs' => 'Gets a list of HyperParameterTuningJobSummary objects that describe the hyperparameter tuning jobs launched in your account.
', 'ListImageVersions' => 'Lists the versions of a specified image and their properties. The list can be filtered by creation time or modified time.
', 'ListImages' => 'Lists the images in your account and their properties. The list can be filtered by creation time or modified time, and whether the image name contains a specified string.
', 'ListInferenceExperiments' => 'Returns the list of all inference experiments.
', 'ListInferenceRecommendationsJobSteps' => 'Returns a list of the subtasks for an Inference Recommender job.
The supported subtasks are benchmarks, which evaluate the performance of your model on different instance types.
', 'ListInferenceRecommendationsJobs' => 'Lists recommendation jobs that satisfy various filters.
', 'ListLabelingJobs' => 'Gets a list of labeling jobs.
', 'ListLabelingJobsForWorkteam' => 'Gets a list of labeling jobs assigned to a specified work team.
', 'ListLineageGroups' => 'A list of lineage groups shared with your Amazon Web Services account. For more information, see Cross-Account Lineage Tracking in the Amazon SageMaker Developer Guide.
', 'ListModelBiasJobDefinitions' => 'Lists model bias jobs definitions that satisfy various filters.
', 'ListModelCardExportJobs' => 'List the export jobs for the Amazon SageMaker Model Card.
', 'ListModelCardVersions' => 'List existing versions of an Amazon SageMaker Model Card.
', 'ListModelCards' => 'List existing model cards.
', 'ListModelExplainabilityJobDefinitions' => 'Lists model explainability job definitions that satisfy various filters.
', 'ListModelMetadata' => 'Lists the domain, framework, task, and model name of standard machine learning models found in common model zoos.
', 'ListModelPackageGroups' => 'Gets a list of the model groups in your Amazon Web Services account.
', 'ListModelPackages' => 'Lists the model packages that have been created.
', 'ListModelQualityJobDefinitions' => 'Gets a list of model quality monitoring job definitions in your account.
', 'ListModels' => 'Lists models created with the CreateModel API.
Gets a list of past alerts in a model monitoring schedule.
', 'ListMonitoringAlerts' => 'Gets the alerts for a single monitoring schedule.
', 'ListMonitoringExecutions' => 'Returns list of all monitoring job executions.
', 'ListMonitoringSchedules' => 'Returns list of all monitoring schedules.
', 'ListNotebookInstanceLifecycleConfigs' => 'Lists notebook instance lifestyle configurations created with the CreateNotebookInstanceLifecycleConfig API.
', 'ListNotebookInstances' => 'Returns a list of the SageMaker notebook instances in the requester\'s account in an Amazon Web Services Region.
', 'ListPipelineExecutionSteps' => 'Gets a list of PipeLineExecutionStep objects.
Gets a list of the pipeline executions.
', 'ListPipelineParametersForExecution' => 'Gets a list of parameters for a pipeline execution.
', 'ListPipelines' => 'Gets a list of pipelines.
', 'ListProcessingJobs' => 'Lists processing jobs that satisfy various filters.
', 'ListProjects' => 'Gets a list of the projects in an Amazon Web Services account.
', 'ListResourceCatalogs' => ' Lists Amazon SageMaker Catalogs based on given filters and orders. The maximum number of ResourceCatalogs viewable is 1000.
Lists spaces.
', 'ListStageDevices' => 'Lists devices allocated to the stage, containing detailed device information and deployment status.
', 'ListStudioLifecycleConfigs' => 'Lists the Studio Lifecycle Configurations in your Amazon Web Services Account.
', 'ListSubscribedWorkteams' => 'Gets a list of the work teams that you are subscribed to in the Amazon Web Services Marketplace. The list may be empty if no work team satisfies the filter specified in the NameContains parameter.
Returns the tags for the specified SageMaker resource.
', 'ListTrainingJobs' => 'Lists training jobs.
When StatusEquals and MaxResults are set at the same time, the MaxResults number of training jobs are first retrieved ignoring the StatusEquals parameter and then they are filtered by the StatusEquals parameter, which is returned as a response.
For example, if ListTrainingJobs is invoked with the following parameters:
{ ... MaxResults: 100, StatusEquals: InProgress ... }
First, 100 trainings jobs with any status, including those other than InProgress, are selected (sorted according to the creation time, from the most current to the oldest). Next, those with a status of InProgress are returned.
You can quickly test the API using the following Amazon Web Services CLI code.
aws sagemaker list-training-jobs --max-results 100 --status-equals InProgress
Gets a list of TrainingJobSummary objects that describe the training jobs that a hyperparameter tuning job launched.
', 'ListTransformJobs' => 'Lists transform jobs.
', 'ListTrialComponents' => 'Lists the trial components in your account. You can sort the list by trial component name or creation time. You can filter the list to show only components that were created in a specific time range. You can also filter on one of the following:
ExperimentName
SourceArn
TrialName
Lists the trials in your account. Specify an experiment name to limit the list to the trials that are part of that experiment. Specify a trial component name to limit the list to the trials that associated with that trial component. The list can be filtered to show only trials that were created in a specific time range. The list can be sorted by trial name or creation time.
', 'ListUserProfiles' => 'Lists user profiles.
', 'ListWorkforces' => 'Use this operation to list all private and vendor workforces in an Amazon Web Services Region. Note that you can only have one private workforce per Amazon Web Services Region.
', 'ListWorkteams' => 'Gets a list of private work teams that you have defined in a region. The list may be empty if no work team satisfies the filter specified in the NameContains parameter.
Adds a resouce policy to control access to a model group. For information about resoure policies, see Identity-based policies and resource-based policies in the Amazon Web Services Identity and Access Management User Guide..
', 'QueryLineage' => 'Use this action to inspect your lineage and discover relationships between entities. For more information, see Querying Lineage Entities in the Amazon SageMaker Developer Guide.
', 'RegisterDevices' => 'Register devices.
', 'RenderUiTemplate' => 'Renders the UI template so that you can preview the worker\'s experience.
', 'RetryPipelineExecution' => 'Retry the execution of the pipeline.
', 'Search' => 'Finds SageMaker resources that match a search query. Matching resources are returned as a list of SearchRecord objects in the response. You can sort the search results by any resource property in a ascending or descending order.
You can query against the following value types: numeric, text, Boolean, and timestamp.
The Search API may provide access to otherwise restricted data. See Amazon SageMaker API Permissions: Actions, Permissions, and Resources Reference for more information.
Notifies the pipeline that the execution of a callback step failed, along with a message describing why. When a callback step is run, the pipeline generates a callback token and includes the token in a message sent to Amazon Simple Queue Service (Amazon SQS).
', 'SendPipelineExecutionStepSuccess' => 'Notifies the pipeline that the execution of a callback step succeeded and provides a list of the step\'s output parameters. When a callback step is run, the pipeline generates a callback token and includes the token in a message sent to Amazon Simple Queue Service (Amazon SQS).
', 'StartEdgeDeploymentStage' => 'Starts a stage in an edge deployment plan.
', 'StartInferenceExperiment' => 'Starts an inference experiment.
', 'StartMonitoringSchedule' => 'Starts a previously stopped monitoring schedule.
By default, when you successfully create a new schedule, the status of a monitoring schedule is scheduled.
Launches an ML compute instance with the latest version of the libraries and attaches your ML storage volume. After configuring the notebook instance, SageMaker sets the notebook instance status to InService. A notebook instance\'s status must be InService before you can connect to your Jupyter notebook.
Starts a pipeline execution.
', 'StopAutoMLJob' => 'A method for forcing a running job to shut down.
', 'StopCompilationJob' => 'Stops a model compilation job.
To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal. This gracefully shuts the job down. If the job hasn\'t stopped, it sends the SIGKILL signal.
When it receives a StopCompilationJob request, Amazon SageMaker changes the CompilationJobStatus of the job to Stopping. After Amazon SageMaker stops the job, it sets the CompilationJobStatus to Stopped.
Stops a stage in an edge deployment plan.
', 'StopEdgePackagingJob' => 'Request to stop an edge packaging job.
', 'StopHyperParameterTuningJob' => 'Stops a running hyperparameter tuning job and all running training jobs that the tuning job launched.
All model artifacts output from the training jobs are stored in Amazon Simple Storage Service (Amazon S3). All data that the training jobs write to Amazon CloudWatch Logs are still available in CloudWatch. After the tuning job moves to the Stopped state, it releases all reserved resources for the tuning job.
Stops an inference experiment.
', 'StopInferenceRecommendationsJob' => 'Stops an Inference Recommender job.
', 'StopLabelingJob' => 'Stops a running labeling job. A job that is stopped cannot be restarted. Any results obtained before the job is stopped are placed in the Amazon S3 output bucket.
', 'StopMonitoringSchedule' => 'Stops a previously started monitoring schedule.
', 'StopNotebookInstance' => 'Terminates the ML compute instance. Before terminating the instance, SageMaker disconnects the ML storage volume from it. SageMaker preserves the ML storage volume. SageMaker stops charging you for the ML compute instance when you call StopNotebookInstance.
To access data on the ML storage volume for a notebook instance that has been terminated, call the StartNotebookInstance API. StartNotebookInstance launches another ML compute instance, configures it, and attaches the preserved ML storage volume so you can continue your work.
Stops a pipeline execution.
Callback Step
A pipeline execution won\'t stop while a callback step is running. When you call StopPipelineExecution on a pipeline execution with a running callback step, SageMaker Pipelines sends an additional Amazon SQS message to the specified SQS queue. The body of the SQS message contains a "Status" field which is set to "Stopping".
You should add logic to your Amazon SQS message consumer to take any needed action (for example, resource cleanup) upon receipt of the message followed by a call to SendPipelineExecutionStepSuccess or SendPipelineExecutionStepFailure.
Only when SageMaker Pipelines receives one of these calls will it stop the pipeline execution.
Lambda Step
A pipeline execution can\'t be stopped while a lambda step is running because the Lambda function invoked by the lambda step can\'t be stopped. If you attempt to stop the execution while the Lambda function is running, the pipeline waits for the Lambda function to finish or until the timeout is hit, whichever occurs first, and then stops. If the Lambda function finishes, the pipeline execution status is Stopped. If the timeout is hit the pipeline execution status is Failed.
Stops a processing job.
', 'StopTrainingJob' => 'Stops a training job. To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms might use this 120-second window to save the model artifacts, so the results of the training is not lost.
When it receives a StopTrainingJob request, SageMaker changes the status of the job to Stopping. After SageMaker stops the job, it sets the status to Stopped.
Stops a batch transform job.
When Amazon SageMaker receives a StopTransformJob request, the status of the job changes to Stopping. After Amazon SageMaker stops the job, the status is set to Stopped. When you stop a batch transform job before it is completed, Amazon SageMaker doesn\'t store the job\'s output in Amazon S3.
Updates an action.
', 'UpdateAppImageConfig' => 'Updates the properties of an AppImageConfig.
', 'UpdateArtifact' => 'Updates an artifact.
', 'UpdateCodeRepository' => 'Updates the specified Git repository with the specified values.
', 'UpdateContext' => 'Updates a context.
', 'UpdateDeviceFleet' => 'Updates a fleet of devices.
', 'UpdateDevices' => 'Updates one or more devices in a fleet.
', 'UpdateDomain' => 'Updates the default settings for new user profiles in the domain.
', 'UpdateEndpoint' => 'Deploys the new EndpointConfig specified in the request, switches to using newly created endpoint, and then deletes resources provisioned for the endpoint using the previous EndpointConfig (there is no availability loss).
When SageMaker receives the request, it sets the endpoint status to Updating. After updating the endpoint, it sets the status to InService. To check the status of an endpoint, use the DescribeEndpoint API.
You must not delete an EndpointConfig in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. To update an endpoint, you must create a new EndpointConfig.
If you delete the EndpointConfig of an endpoint that is active or being created or updated you may lose visibility into the instance type the endpoint is using. The endpoint must be deleted in order to stop incurring charges.
Updates variant weight of one or more variants associated with an existing endpoint, or capacity of one variant associated with an existing endpoint. When it receives the request, SageMaker sets the endpoint status to Updating. After updating the endpoint, it sets the status to InService. To check the status of an endpoint, use the DescribeEndpoint API.
Adds, updates, or removes the description of an experiment. Updates the display name of an experiment.
', 'UpdateFeatureGroup' => 'Updates the feature group by either adding features or updating the online store configuration. Use one of the following request parameters at a time while using the UpdateFeatureGroup API.
You can add features for your feature group using the FeatureAdditions request parameter. Features cannot be removed from a feature group.
You can update the online store configuration by using the OnlineStoreConfig request parameter. If a TtlDuration is specified, the default TtlDuration applies for all records added to the feature group after the feature group is updated. If a record level TtlDuration exists from using the PutRecord API, the record level TtlDuration applies to that record instead of the default TtlDuration.
Updates the description and parameters of the feature group.
', 'UpdateHub' => 'Update a hub.
Hub APIs are only callable through SageMaker Studio.
Updates the properties of a SageMaker image. To change the image\'s tags, use the AddTags and DeleteTags APIs.
', 'UpdateImageVersion' => 'Updates the properties of a SageMaker image version.
', 'UpdateInferenceExperiment' => ' Updates an inference experiment that you created. The status of the inference experiment has to be either Created, Running. For more information on the status of an inference experiment, see DescribeInferenceExperiment.
Update an Amazon SageMaker Model Card.
You cannot update both model card content and model card status in a single call.
Updates a versioned model.
', 'UpdateMonitoringAlert' => 'Update the parameters of a model monitor alert.
', 'UpdateMonitoringSchedule' => 'Updates a previously created schedule.
', 'UpdateNotebookInstance' => 'Updates a notebook instance. NotebookInstance updates include upgrading or downgrading the ML compute instance used for your notebook instance to accommodate changes in your workload requirements.
', 'UpdateNotebookInstanceLifecycleConfig' => 'Updates a notebook instance lifecycle configuration created with the CreateNotebookInstanceLifecycleConfig API.
', 'UpdatePipeline' => 'Updates a pipeline.
', 'UpdatePipelineExecution' => 'Updates a pipeline execution.
', 'UpdateProject' => 'Updates a machine learning (ML) project that is created from a template that sets up an ML pipeline from training to deploying an approved model.
You must not update a project that is in use. If you update the ServiceCatalogProvisioningUpdateDetails of a project that is active or being created, or updated, you may lose resources already created by the project.
Updates the settings of a space.
', 'UpdateTrainingJob' => 'Update a model training job to request a new Debugger profiling configuration or to change warm pool retention length.
', 'UpdateTrial' => 'Updates the display name of a trial.
', 'UpdateTrialComponent' => 'Updates one or more properties of a trial component.
', 'UpdateUserProfile' => 'Updates a user profile.
', 'UpdateWorkforce' => 'Use this operation to update your workforce. You can use this operation to require that workers use specific IP addresses to work on tasks and to update your OpenID Connect (OIDC) Identity Provider (IdP) workforce configuration.
The worker portal is now supported in VPC and public internet.
Use SourceIpConfig to restrict worker access to tasks to a specific range of IP addresses. You specify allowed IP addresses by creating a list of up to ten CIDRs. By default, a workforce isn\'t restricted to specific IP addresses. If you specify a range of IP addresses, workers who attempt to access tasks using any IP address outside the specified range are denied and get a Not Found error message on the worker portal.
To restrict access to all the workers in public internet, add the SourceIpConfig CIDR value as "10.0.0.0/16".
Amazon SageMaker does not support Source Ip restriction for worker portals in VPC.
Use OidcConfig to update the configuration of a workforce created using your own OIDC IdP.
You can only update your OIDC IdP configuration when there are no work teams associated with your workforce. You can delete work teams using the DeleteWorkteam operation.
After restricting access to a range of IP addresses or updating your OIDC IdP configuration with this operation, you can view details about your update workforce using the DescribeWorkforce operation.
This operation only applies to private workforces.
Updates an existing work team with new member definitions or description.
', ], 'shapes' => [ 'Accept' => [ 'base' => NULL, 'refs' => [ 'TransformOutput$Accept' => 'The MIME type used to specify the output data. Amazon SageMaker uses the MIME type with each http call to transfer data from the transform job.
', ], ], 'AccountId' => [ 'base' => NULL, 'refs' => [ 'LabelingJobForWorkteamSummary$WorkRequesterAccountId' => 'The Amazon Web Services account ID of the account used to start the labeling job.
', ], ], 'ActionArn' => [ 'base' => NULL, 'refs' => [ 'ActionSummary$ActionArn' => 'The Amazon Resource Name (ARN) of the action.
', 'CreateActionResponse$ActionArn' => 'The Amazon Resource Name (ARN) of the action.
', 'DeleteActionResponse$ActionArn' => 'The Amazon Resource Name (ARN) of the action.
', 'DescribeActionResponse$ActionArn' => 'The Amazon Resource Name (ARN) of the action.
', 'UpdateActionResponse$ActionArn' => 'The Amazon Resource Name (ARN) of the action.
', ], ], 'ActionSource' => [ 'base' => 'A structure describing the source of an action.
', 'refs' => [ 'ActionSummary$Source' => 'The source of the action.
', 'CreateActionRequest$Source' => 'The source type, ID, and URI.
', 'DescribeActionResponse$Source' => 'The source of the action.
', ], ], 'ActionStatus' => [ 'base' => NULL, 'refs' => [ 'ActionSummary$Status' => 'The status of the action.
', 'CreateActionRequest$Status' => 'The status of the action.
', 'DescribeActionResponse$Status' => 'The status of the action.
', 'UpdateActionRequest$Status' => 'The new status for the action.
', ], ], 'ActionSummaries' => [ 'base' => NULL, 'refs' => [ 'ListActionsResponse$ActionSummaries' => 'A list of actions and their properties.
', ], ], 'ActionSummary' => [ 'base' => 'Lists the properties of an action. An action represents an action or activity. Some examples are a workflow step and a model deployment. Generally, an action involves at least one input artifact or output artifact.
', 'refs' => [ 'ActionSummaries$member' => NULL, ], ], 'AddAssociationRequest' => [ 'base' => NULL, 'refs' => [], ], 'AddAssociationResponse' => [ 'base' => NULL, 'refs' => [], ], 'AddTagsInput' => [ 'base' => NULL, 'refs' => [], ], 'AddTagsOutput' => [ 'base' => NULL, 'refs' => [], ], 'AdditionalCodeRepositoryNamesOrUrls' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$AdditionalCodeRepositories' => 'An array of up to three Git repositories to associate with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', 'DescribeNotebookInstanceOutput$AdditionalCodeRepositories' => 'An array of up to three Git repositories associated with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', 'NotebookInstanceSummary$AdditionalCodeRepositories' => 'An array of up to three Git repositories associated with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', 'UpdateNotebookInstanceInput$AdditionalCodeRepositories' => 'An array of up to three Git repositories to associate with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', ], ], 'AdditionalInferenceSpecificationDefinition' => [ 'base' => 'A structure of additional Inference Specification. Additional Inference Specification specifies details about inference jobs that can be run with models based on this model package
', 'refs' => [ 'AdditionalInferenceSpecifications$member' => NULL, ], ], 'AdditionalInferenceSpecifications' => [ 'base' => NULL, 'refs' => [ 'CreateModelPackageInput$AdditionalInferenceSpecifications' => 'An array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
', 'DescribeModelPackageOutput$AdditionalInferenceSpecifications' => 'An array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
', 'ModelPackage$AdditionalInferenceSpecifications' => 'An array of additional Inference Specification objects.
', 'UpdateModelPackageInput$AdditionalInferenceSpecificationsToAdd' => 'An array of additional Inference Specification objects to be added to the existing array additional Inference Specification. Total number of additional Inference Specifications can not exceed 15. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
', ], ], 'AdditionalS3DataSource' => [ 'base' => 'A data source used for training or inference that is in addition to the input dataset or model data.
', 'refs' => [ 'ModelPackageContainerDefinition$AdditionalS3DataSource' => 'The additional data source that is used during inference in the Docker container for your model package.
', 'TrainingSpecification$AdditionalS3DataSource' => 'The additional data source used during the training job.
', ], ], 'AdditionalS3DataSourceDataType' => [ 'base' => NULL, 'refs' => [ 'AdditionalS3DataSource$S3DataType' => 'The data type of the additional data source that you specify for use in inference or training.
', ], ], 'AgentVersion' => [ 'base' => 'Edge Manager agent version.
', 'refs' => [ 'AgentVersions$member' => NULL, ], ], 'AgentVersions' => [ 'base' => NULL, 'refs' => [ 'GetDeviceFleetReportResponse$AgentVersions' => 'The versions of Edge Manager agent deployed on the fleet.
', ], ], 'AggregationTransformationValue' => [ 'base' => NULL, 'refs' => [ 'AggregationTransformations$value' => NULL, ], ], 'AggregationTransformations' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesTransformations$Aggregation' => 'A key value pair defining the aggregation method for a column, where the key is the column name and the value is the aggregation method.
The supported aggregation methods are sum (default), avg, first, min, max.
Aggregation is only supported for the target column.
An Amazon CloudWatch alarm configured to monitor metrics on an endpoint.
', 'refs' => [ 'AlarmList$member' => NULL, ], ], 'AlarmList' => [ 'base' => NULL, 'refs' => [ 'AutoRollbackConfig$Alarms' => 'List of CloudWatch alarms in your account that are configured to monitor metrics on an endpoint. If any alarms are tripped during a deployment, SageMaker rolls back the deployment.
', ], ], 'AlarmName' => [ 'base' => NULL, 'refs' => [ 'Alarm$AlarmName' => 'The name of a CloudWatch alarm in your account.
', ], ], 'AlgorithmArn' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSummary$AlgorithmArn' => 'The Amazon Resource Name (ARN) of the algorithm.
', 'CreateAlgorithmOutput$AlgorithmArn' => 'The Amazon Resource Name (ARN) of the new algorithm.
', 'DescribeAlgorithmOutput$AlgorithmArn' => 'The Amazon Resource Name (ARN) of the algorithm.
', ], ], 'AlgorithmImage' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSpecification$TrainingImage' => 'The registry path of the Docker image that contains the training algorithm. For information about docker registry paths for SageMaker built-in algorithms, see Docker Registry Paths and Example Code in the Amazon SageMaker developer guide. SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information about using your custom training container, see Using Your Own Algorithms with Amazon SageMaker.
You must specify either the algorithm name to the AlgorithmName parameter or the image URI of the algorithm container to the TrainingImage parameter.
For more information, see the note in the AlgorithmName parameter description.
The Amazon Elastic Container (ECR) Image for the managed rule evaluation.
', 'HyperParameterAlgorithmSpecification$TrainingImage' => ' The registry path of the Docker image that contains the training algorithm. For information about Docker registry paths for built-in algorithms, see Algorithms Provided by Amazon SageMaker: Common Parameters. SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.
The Amazon Elastic Container Registry Image for the managed rule evaluation.
', ], ], 'AlgorithmSortBy' => [ 'base' => NULL, 'refs' => [ 'ListAlgorithmsInput$SortBy' => 'The parameter by which to sort the results. The default is CreationTime.
Specifies the training algorithm to use in a CreateTrainingJob request.
For more information about algorithms provided by SageMaker, see Algorithms. For information about using your own algorithms, see Using Your Own Algorithms with Amazon SageMaker.
', 'refs' => [ 'CreateTrainingJobRequest$AlgorithmSpecification' => 'The registry path of the Docker image that contains the training algorithm and algorithm-specific metadata, including the input mode. For more information about algorithms provided by SageMaker, see Algorithms. For information about providing your own algorithms, see Using Your Own Algorithms with Amazon SageMaker.
', 'DescribeTrainingJobResponse$AlgorithmSpecification' => 'Information about the algorithm used for training, and algorithm metadata.
', 'TrainingJob$AlgorithmSpecification' => 'Information about the algorithm used for training, and algorithm metadata.
', ], ], 'AlgorithmStatus' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSummary$AlgorithmStatus' => 'The overall status of the algorithm.
', 'DescribeAlgorithmOutput$AlgorithmStatus' => 'The current status of the algorithm.
', ], ], 'AlgorithmStatusDetails' => [ 'base' => 'Specifies the validation and image scan statuses of the algorithm.
', 'refs' => [ 'DescribeAlgorithmOutput$AlgorithmStatusDetails' => 'Details about the current status of the algorithm.
', ], ], 'AlgorithmStatusItem' => [ 'base' => 'Represents the overall status of an algorithm.
', 'refs' => [ 'AlgorithmStatusItemList$member' => NULL, ], ], 'AlgorithmStatusItemList' => [ 'base' => NULL, 'refs' => [ 'AlgorithmStatusDetails$ValidationStatuses' => 'The status of algorithm validation.
', 'AlgorithmStatusDetails$ImageScanStatuses' => 'The status of the scan of the algorithm\'s Docker image container.
', ], ], 'AlgorithmSummary' => [ 'base' => 'Provides summary information about an algorithm.
', 'refs' => [ 'AlgorithmSummaryList$member' => NULL, ], ], 'AlgorithmSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListAlgorithmsOutput$AlgorithmSummaryList' => '>An array of AlgorithmSummary objects, each of which lists an algorithm.
Defines a training job and a batch transform job that SageMaker runs to validate your algorithm.
The data provided in the validation profile is made available to your buyers on Amazon Web Services Marketplace.
', 'refs' => [ 'AlgorithmValidationProfiles$member' => NULL, ], ], 'AlgorithmValidationProfiles' => [ 'base' => NULL, 'refs' => [ 'AlgorithmValidationSpecification$ValidationProfiles' => 'An array of AlgorithmValidationProfile objects, each of which specifies a training job and batch transform job that SageMaker runs to validate your algorithm.
Specifies configurations for one or more training jobs that SageMaker runs to test the algorithm.
', 'refs' => [ 'CreateAlgorithmInput$ValidationSpecification' => 'Specifies configurations for one or more training jobs and that SageMaker runs to test the algorithm\'s training code and, optionally, one or more batch transform jobs that SageMaker runs to test the algorithm\'s inference code.
', 'DescribeAlgorithmOutput$ValidationSpecification' => 'Details about configurations for one or more training jobs that SageMaker runs to test the algorithm.
', ], ], 'AnnotationConsolidationConfig' => [ 'base' => 'Configures how labels are consolidated across human workers and processes output data.
', 'refs' => [ 'HumanTaskConfig$AnnotationConsolidationConfig' => 'Configures how labels are consolidated across human workers.
', ], ], 'AppArn' => [ 'base' => NULL, 'refs' => [ 'CreateAppResponse$AppArn' => 'The Amazon Resource Name (ARN) of the app.
', 'DescribeAppResponse$AppArn' => 'The Amazon Resource Name (ARN) of the app.
', ], ], 'AppDetails' => [ 'base' => 'Details about an Amazon SageMaker app.
', 'refs' => [ 'AppList$member' => NULL, ], ], 'AppImageConfigArn' => [ 'base' => NULL, 'refs' => [ 'AppImageConfigDetails$AppImageConfigArn' => 'The Amazon Resource Name (ARN) of the AppImageConfig.
', 'CreateAppImageConfigResponse$AppImageConfigArn' => 'The Amazon Resource Name (ARN) of the AppImageConfig.
', 'DescribeAppImageConfigResponse$AppImageConfigArn' => 'The Amazon Resource Name (ARN) of the AppImageConfig.
', 'UpdateAppImageConfigResponse$AppImageConfigArn' => 'The Amazon Resource Name (ARN) for the AppImageConfig.
', ], ], 'AppImageConfigDetails' => [ 'base' => 'The configuration for running a SageMaker image as a KernelGateway app.
', 'refs' => [ 'AppImageConfigList$member' => NULL, ], ], 'AppImageConfigList' => [ 'base' => NULL, 'refs' => [ 'ListAppImageConfigsResponse$AppImageConfigs' => 'A list of AppImageConfigs and their properties.
', ], ], 'AppImageConfigName' => [ 'base' => NULL, 'refs' => [ 'AppImageConfigDetails$AppImageConfigName' => 'The name of the AppImageConfig. Must be unique to your account.
', 'CreateAppImageConfigRequest$AppImageConfigName' => 'The name of the AppImageConfig. Must be unique to your account.
', 'CustomImage$AppImageConfigName' => 'The name of the AppImageConfig.
', 'DeleteAppImageConfigRequest$AppImageConfigName' => 'The name of the AppImageConfig to delete.
', 'DescribeAppImageConfigRequest$AppImageConfigName' => 'The name of the AppImageConfig to describe.
', 'DescribeAppImageConfigResponse$AppImageConfigName' => 'The name of the AppImageConfig.
', 'ListAppImageConfigsRequest$NameContains' => 'A filter that returns only AppImageConfigs whose name contains the specified string.
', 'UpdateAppImageConfigRequest$AppImageConfigName' => 'The name of the AppImageConfig to update.
', ], ], 'AppImageConfigSortKey' => [ 'base' => NULL, 'refs' => [ 'ListAppImageConfigsRequest$SortBy' => 'The property used to sort results. The default value is CreationTime.
The instance type that the image version runs on.
JupyterServer apps only support the system value.
For KernelGateway apps, the system value is translated to ml.t3.medium. KernelGateway apps also support all other values for available instance types.
The list of apps.
', ], ], 'AppManaged' => [ 'base' => NULL, 'refs' => [ 'ProcessingInput$AppManaged' => 'When True, input operations such as data download are managed natively by the processing job application. When False (default), input operations are managed by Amazon SageMaker.
When True, output operations such as data upload are managed natively by the processing job application. When False (default), output operations are managed by Amazon SageMaker.
The name of the app.
', 'CreateAppRequest$AppName' => 'The name of the app.
', 'DeleteAppRequest$AppName' => 'The name of the app.
', 'DescribeAppRequest$AppName' => 'The name of the app.
', 'DescribeAppResponse$AppName' => 'The name of the app.
', ], ], 'AppNetworkAccessType' => [ 'base' => NULL, 'refs' => [ 'CreateDomainRequest$AppNetworkAccessType' => 'Specifies the VPC used for non-EFS traffic. The default value is PublicInternetOnly.
PublicInternetOnly - Non-EFS traffic is through a VPC managed by Amazon SageMaker, which allows direct internet access
VpcOnly - All Studio traffic is through the specified VPC and subnets
Specifies the VPC used for non-EFS traffic. The default value is PublicInternetOnly.
PublicInternetOnly - Non-EFS traffic is through a VPC managed by Amazon SageMaker, which allows direct internet access
VpcOnly - All Studio traffic is through the specified VPC and subnets
The entity that creates and manages the required security groups for inter-app communication in VPCOnly mode. Required when CreateDomain.AppNetworkAccessType is VPCOnly and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided. If setting up the domain for use with RStudio, this value must be set to Service.
The entity that creates and manages the required security groups for inter-app communication in VPCOnly mode. Required when CreateDomain.AppNetworkAccessType is VPCOnly and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided.
The entity that creates and manages the required security groups for inter-app communication in VPCOnly mode. Required when CreateDomain.AppNetworkAccessType is VPCOnly and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided. If setting up the domain for use with RStudio, this value must be set to Service.
The parameter by which to sort the results. The default is CreationTime.
', ], ], 'AppSpecification' => [ 'base' => 'Configuration to run a processing job in a specified container image.
', 'refs' => [ 'CreateProcessingJobRequest$AppSpecification' => 'Configures the processing job to run a specified Docker container image.
', 'DescribeProcessingJobResponse$AppSpecification' => 'Configures the processing job to run a specified container image.
', 'ProcessingJob$AppSpecification' => NULL, ], ], 'AppStatus' => [ 'base' => NULL, 'refs' => [ 'AppDetails$Status' => 'The status.
', 'DescribeAppResponse$Status' => 'The status.
', ], ], 'AppType' => [ 'base' => NULL, 'refs' => [ 'AppDetails$AppType' => 'The type of app.
', 'CreateAppRequest$AppType' => 'The type of app.
', 'DeleteAppRequest$AppType' => 'The type of app.
', 'DescribeAppRequest$AppType' => 'The type of app.
', 'DescribeAppResponse$AppType' => 'The type of app.
', ], ], 'ApprovalDescription' => [ 'base' => NULL, 'refs' => [ 'DescribeModelPackageOutput$ApprovalDescription' => 'A description provided for the model approval.
', 'ModelPackage$ApprovalDescription' => 'A description provided when the model approval is set.
', 'UpdateModelPackageInput$ApprovalDescription' => 'A description for the approval status of the model.
', ], ], 'ArnOrName' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSpecification$AlgorithmName' => 'The name of the algorithm resource to use for the training job. This must be an algorithm resource that you created or subscribe to on Amazon Web Services Marketplace.
You must specify either the algorithm name to the AlgorithmName parameter or the image URI of the algorithm container to the TrainingImage parameter.
Note that the AlgorithmName parameter is mutually exclusive with the TrainingImage parameter. If you specify a value for the AlgorithmName parameter, you can\'t specify a value for TrainingImage, and vice versa.
If you specify values for both parameters, the training job might break; if you don\'t specify any value for both parameters, the training job might raise a null error.
The name or Amazon Resource Name (ARN) of the model package group that this model version belongs to.
This parameter is required for versioned models, and does not apply to unversioned models.
', 'DeleteModelPackageGroupInput$ModelPackageGroupName' => 'The name of the model group to delete.
', 'DescribeAlgorithmInput$AlgorithmName' => 'The name of the algorithm to describe.
', 'DescribeModelPackageGroupInput$ModelPackageGroupName' => 'The name of gthe model group to describe.
', 'HyperParameterAlgorithmSpecification$AlgorithmName' => 'The name of the resource algorithm to use for the hyperparameter tuning job. If you specify a value for this parameter, do not specify a value for TrainingImage.
A filter that returns only model versions that belong to the specified model group.
', 'SourceAlgorithm$AlgorithmName' => 'The name of an algorithm that was used to create the model package. The algorithm must be either an algorithm resource in your SageMaker account or an algorithm in Amazon Web Services Marketplace that you are subscribed to.
', ], ], 'ArtifactArn' => [ 'base' => NULL, 'refs' => [ 'ArtifactSummary$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact.
', 'CreateArtifactResponse$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact.
', 'DeleteArtifactRequest$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact to delete.
', 'DeleteArtifactResponse$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact.
', 'DescribeArtifactRequest$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact to describe.
', 'DescribeArtifactResponse$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact.
', 'UpdateArtifactRequest$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact to update.
', 'UpdateArtifactResponse$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact.
', ], ], 'ArtifactDigest' => [ 'base' => NULL, 'refs' => [ 'ModelDigests$ArtifactDigest' => 'Provides a hash value that uniquely identifies the stored model artifacts.
', ], ], 'ArtifactSource' => [ 'base' => 'A structure describing the source of an artifact.
', 'refs' => [ 'ArtifactSummary$Source' => 'The source of the artifact.
', 'CreateArtifactRequest$Source' => 'The ID, ID type, and URI of the source.
', 'DeleteArtifactRequest$Source' => 'The URI of the source.
', 'DescribeArtifactResponse$Source' => 'The source of the artifact.
', ], ], 'ArtifactSourceIdType' => [ 'base' => NULL, 'refs' => [ 'ArtifactSourceType$SourceIdType' => 'The type of ID.
', ], ], 'ArtifactSourceType' => [ 'base' => 'The ID and ID type of an artifact source.
', 'refs' => [ 'ArtifactSourceTypes$member' => NULL, ], ], 'ArtifactSourceTypes' => [ 'base' => NULL, 'refs' => [ 'ArtifactSource$SourceTypes' => 'A list of source types.
', ], ], 'ArtifactSummaries' => [ 'base' => NULL, 'refs' => [ 'ListArtifactsResponse$ArtifactSummaries' => 'A list of artifacts and their properties.
', ], ], 'ArtifactSummary' => [ 'base' => 'Lists a summary of the properties of an artifact. An artifact represents a URI addressable object or data. Some examples are a dataset and a model.
', 'refs' => [ 'ArtifactSummaries$member' => NULL, ], ], 'AssemblyType' => [ 'base' => NULL, 'refs' => [ 'TransformOutput$AssembleWith' => 'Defines how to assemble the results of the transform job as a single S3 object. Choose a format that is most convenient to you. To concatenate the results in binary format, specify None. To add a newline character at the end of every transformed record, specify Line.
The type of association. The following are suggested uses for each type. Amazon SageMaker places no restrictions on their use.
ContributedTo - The source contributed to the destination or had a part in enabling the destination. For example, the training data contributed to the training job.
AssociatedWith - The source is connected to the destination. For example, an approval workflow is associated with a model deployment.
DerivedFrom - The destination is a modification of the source. For example, a digest output of a channel input for a processing job is derived from the original inputs.
Produced - The source generated the destination. For example, a training job produced a model artifact.
The type of the association.
', 'Edge$AssociationType' => 'The type of the Association(Edge) between the source and destination. For example ContributedTo, Produced, or DerivedFrom.
A filter that returns only associations of the specified type.
', ], ], 'AssociationEntityArn' => [ 'base' => NULL, 'refs' => [ 'AddAssociationRequest$SourceArn' => 'The ARN of the source.
', 'AddAssociationRequest$DestinationArn' => 'The Amazon Resource Name (ARN) of the destination.
', 'AddAssociationResponse$SourceArn' => 'The ARN of the source.
', 'AddAssociationResponse$DestinationArn' => 'The Amazon Resource Name (ARN) of the destination.
', 'AssociationSummary$SourceArn' => 'The ARN of the source.
', 'AssociationSummary$DestinationArn' => 'The Amazon Resource Name (ARN) of the destination.
', 'DeleteAssociationRequest$SourceArn' => 'The ARN of the source.
', 'DeleteAssociationRequest$DestinationArn' => 'The Amazon Resource Name (ARN) of the destination.
', 'DeleteAssociationResponse$SourceArn' => 'The ARN of the source.
', 'DeleteAssociationResponse$DestinationArn' => 'The Amazon Resource Name (ARN) of the destination.
', 'Edge$SourceArn' => 'The Amazon Resource Name (ARN) of the source lineage entity of the directed edge.
', 'Edge$DestinationArn' => 'The Amazon Resource Name (ARN) of the destination lineage entity of the directed edge.
', 'ListAssociationsRequest$SourceArn' => 'A filter that returns only associations with the specified source ARN.
', 'ListAssociationsRequest$DestinationArn' => 'A filter that returns only associations with the specified destination Amazon Resource Name (ARN).
', 'QueryLineageStartArns$member' => NULL, 'Vertex$Arn' => 'The Amazon Resource Name (ARN) of the lineage entity resource.
', ], ], 'AssociationSummaries' => [ 'base' => NULL, 'refs' => [ 'ListAssociationsResponse$AssociationSummaries' => 'A list of associations and their properties.
', ], ], 'AssociationSummary' => [ 'base' => 'Lists a summary of the properties of an association. An association is an entity that links other lineage or experiment entities. An example would be an association between a training job and a model.
', 'refs' => [ 'AssociationSummaries$member' => NULL, ], ], 'AsyncInferenceClientConfig' => [ 'base' => 'Configures the behavior of the client used by SageMaker to interact with the model container during asynchronous inference.
', 'refs' => [ 'AsyncInferenceConfig$ClientConfig' => 'Configures the behavior of the client used by SageMaker to interact with the model container during asynchronous inference.
', ], ], 'AsyncInferenceConfig' => [ 'base' => 'Specifies configuration for how an endpoint performs asynchronous inference.
', 'refs' => [ 'CreateEndpointConfigInput$AsyncInferenceConfig' => 'Specifies configuration for how an endpoint performs asynchronous inference. This is a required field in order for your Endpoint to be invoked using InvokeEndpointAsync.
', 'DescribeEndpointConfigOutput$AsyncInferenceConfig' => 'Returns the description of an endpoint configuration created using the CreateEndpointConfig API.
Returns the description of an endpoint configuration created using the CreateEndpointConfig API.
Specifies the configuration for notifications of inference results for asynchronous inference.
', 'refs' => [ 'AsyncInferenceOutputConfig$NotificationConfig' => 'Specifies the configuration for notifications of inference results for asynchronous inference.
', ], ], 'AsyncInferenceOutputConfig' => [ 'base' => 'Specifies the configuration for asynchronous inference invocation outputs.
', 'refs' => [ 'AsyncInferenceConfig$OutputConfig' => 'Specifies the configuration for asynchronous inference invocation outputs.
', ], ], 'AsyncNotificationTopicTypeList' => [ 'base' => NULL, 'refs' => [ 'AsyncInferenceNotificationConfig$IncludeInferenceResponseIn' => 'The Amazon SNS topics where you want the inference response to be included.
The inference response is included only if the response size is less than or equal to 128 KB.
The name of the data catalog used in Athena query execution.
', 'refs' => [ 'AthenaDatasetDefinition$Catalog' => NULL, ], ], 'AthenaDatabase' => [ 'base' => 'The name of the database used in the Athena query execution.
', 'refs' => [ 'AthenaDatasetDefinition$Database' => NULL, ], ], 'AthenaDatasetDefinition' => [ 'base' => 'Configuration for Athena Dataset Definition input.
', 'refs' => [ 'DatasetDefinition$AthenaDatasetDefinition' => NULL, ], ], 'AthenaQueryString' => [ 'base' => 'The SQL query statements, to be executed.
', 'refs' => [ 'AthenaDatasetDefinition$QueryString' => NULL, ], ], 'AthenaResultCompressionType' => [ 'base' => 'The compression used for Athena query results.
', 'refs' => [ 'AthenaDatasetDefinition$OutputCompression' => NULL, ], ], 'AthenaResultFormat' => [ 'base' => 'The data storage format for Athena query results.
', 'refs' => [ 'AthenaDatasetDefinition$OutputFormat' => NULL, ], ], 'AthenaWorkGroup' => [ 'base' => 'The name of the workgroup in which the Athena query is being started.
', 'refs' => [ 'AthenaDatasetDefinition$WorkGroup' => NULL, ], ], 'AttributeName' => [ 'base' => NULL, 'refs' => [ 'AttributeNames$member' => NULL, ], ], 'AttributeNames' => [ 'base' => NULL, 'refs' => [ 'S3DataSource$AttributeNames' => 'A list of one or more attribute names to use that are found in a specified augmented manifest file.
', ], ], 'AuthMode' => [ 'base' => NULL, 'refs' => [ 'CreateDomainRequest$AuthMode' => 'The mode of authentication that members use to access the domain.
', 'DescribeDomainResponse$AuthMode' => 'The domain\'s authentication mode.
', ], ], 'AutoGenerateEndpointName' => [ 'base' => NULL, 'refs' => [ 'ModelDeployConfig$AutoGenerateEndpointName' => 'Set to True to automatically generate an endpoint name for a one-click Autopilot model deployment; set to False otherwise. The default value is False.
If you set AutoGenerateEndpointName to True, do not specify the EndpointName; otherwise a 400 error is thrown.
The collection of algorithms run on a dataset for training the model candidates of an Autopilot job.
', 'refs' => [ 'AutoMLAlgorithmsConfig$member' => NULL, ], ], 'AutoMLAlgorithms' => [ 'base' => NULL, 'refs' => [ 'AutoMLAlgorithmConfig$AutoMLAlgorithms' => 'The selection of algorithms run on a dataset to train the model candidates of an Autopilot job.
Selected algorithms must belong to the list corresponding to the training mode set in AutoMLJobConfig.Mode (ENSEMBLING or HYPERPARAMETER_TUNING). Choose a minimum of 1 algorithm.
In ENSEMBLING mode:
"catboost"
"extra-trees"
"fastai"
"lightgbm"
"linear-learner"
"nn-torch"
"randomforest"
"xgboost"
In HYPERPARAMETER_TUNING mode:
"linear-learner"
"mlp"
"xgboost"
Stores the configuration information for the selection of algorithms used to train the model candidates.
The list of available algorithms to choose from depends on the training mode set in AutoMLJobConfig.Mode .
AlgorithmsConfig should not be set in AUTO training mode.
When AlgorithmsConfig is provided, one AutoMLAlgorithms attribute must be set and one only.
If the list of algorithms provided as values for AutoMLAlgorithms is empty, AutoMLCandidateGenerationConfig uses the full set of algorithms for the given training mode.
When AlgorithmsConfig is not provided, AutoMLCandidateGenerationConfig uses the full set of algorithms for the given training mode.
For the list of all algorithms per training mode, see AutoMLAlgorithmConfig.
For more information on each algorithm, see the Algorithm support section in Autopilot developer guide.
', 'CandidateGenerationConfig$AlgorithmsConfig' => 'Stores the configuration information for the selection of algorithms used to train model candidates on tabular data.
The list of available algorithms to choose from depends on the training mode set in TabularJobConfig.Mode .
AlgorithmsConfig should not be set in AUTO training mode.
When AlgorithmsConfig is provided, one AutoMLAlgorithms attribute must be set and one only.
If the list of algorithms provided as values for AutoMLAlgorithms is empty, CandidateGenerationConfig uses the full set of algorithms for the given training mode.
When AlgorithmsConfig is not provided, CandidateGenerationConfig uses the full set of algorithms for the given training mode.
For the list of all algorithms per problem type and training mode, see AutoMLAlgorithmConfig.
For more information on each algorithm, see the Algorithm support section in Autopilot developer guide.
', ], ], 'AutoMLCandidate' => [ 'base' => 'Information about a candidate produced by an AutoML training job, including its status, steps, and other properties.
', 'refs' => [ 'AutoMLCandidates$member' => NULL, 'DescribeAutoMLJobResponse$BestCandidate' => 'The best model candidate selected by SageMaker Autopilot using both the best objective metric and lowest InferenceLatency for an experiment.
', 'DescribeAutoMLJobV2Response$BestCandidate' => 'Information about the candidate produced by an AutoML training job V2, including its status, steps, and other properties.
', ], ], 'AutoMLCandidateGenerationConfig' => [ 'base' => 'Stores the configuration information for how a candidate is generated (optional).
', 'refs' => [ 'AutoMLJobConfig$CandidateGenerationConfig' => 'The configuration for generating a candidate for an AutoML job (optional).
', ], ], 'AutoMLCandidateStep' => [ 'base' => 'Information about the steps for a candidate and what step it is working on.
', 'refs' => [ 'CandidateSteps$member' => NULL, ], ], 'AutoMLCandidates' => [ 'base' => NULL, 'refs' => [ 'ListCandidatesForAutoMLJobResponse$Candidates' => 'Summaries about the AutoMLCandidates.
A channel is a named input source that training algorithms can consume. The validation dataset size is limited to less than 2 GB. The training dataset size must be less than 100 GB. For more information, see Channel.
A validation dataset must contain the same headers as the training dataset.
The channel type (optional) is an enum string. The default value is training. Channels for training and validation must share the same ContentType and TargetAttributeName. For information on specifying training and validation channel types, see How to specify training and validation datasets.
The type of channel. Defines whether the data are used for training or validation. The default value is training. Channels for training and validation must share the same ContentType
The type of channel defaults to training for the time-series forecasting problem type.
A list of container definitions that describe the different containers that make up an AutoML candidate. For more information, see ContainerDefinition.
', 'refs' => [ 'AutoMLContainerDefinitions$member' => NULL, ], ], 'AutoMLContainerDefinitions' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidate$InferenceContainers' => 'Information about the recommended inference container definitions.
', 'AutoMLInferenceContainerDefinitions$value' => 'Information about the recommended inference container definitions.
', ], ], 'AutoMLDataSource' => [ 'base' => 'The data source for the Autopilot job.
', 'refs' => [ 'AutoMLChannel$DataSource' => 'The data source for an AutoML channel.
', 'AutoMLJobChannel$DataSource' => 'The data source for an AutoML channel (Required).
', ], ], 'AutoMLDataSplitConfig' => [ 'base' => 'This structure specifies how to split the data into train and validation datasets.
The validation and training datasets must contain the same headers. For jobs created by calling CreateAutoMLJob, the validation dataset must be less than 2 GB in size.
The configuration for splitting the input training dataset.
Type: AutoMLDataSplitConfig
', 'CreateAutoMLJobV2Request$DataSplitConfig' => 'This structure specifies how to split the data into train and validation datasets.
The validation and training datasets must contain the same headers. For jobs created by calling CreateAutoMLJob, the validation dataset must be less than 2 GB in size.
This attribute must not be set for the time-series forecasting problem type, as Autopilot automatically splits the input dataset into training and validation sets.
Returns the configuration settings of how the data are split into train and validation datasets.
', ], ], 'AutoMLFailureReason' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidate$FailureReason' => 'The failure reason.
', 'AutoMLJobSummary$FailureReason' => 'The failure reason of an AutoML job.
', 'AutoMLPartialFailureReason$PartialFailureMessage' => 'The message containing the reason for a partial failure of an AutoML job.
', 'DescribeAutoMLJobResponse$FailureReason' => 'Returns the failure reason for an AutoML job, when applicable.
', 'DescribeAutoMLJobV2Response$FailureReason' => 'Returns the reason for the failure of the AutoML job V2, when applicable.
', ], ], 'AutoMLInferenceContainerDefinitions' => [ 'base' => 'The mapping of all supported processing unit (CPU, GPU, etc...) to inference container definitions for the candidate. This field is populated for the V2 API only (for example, for jobs created by calling CreateAutoMLJobV2).
The mapping of all supported processing unit (CPU, GPU, etc...) to inference container definitions for the candidate. This field is populated for the AutoML jobs V2 (for example, for jobs created by calling CreateAutoMLJobV2) related to image or text classification problem types only.
An array of channel objects that describes the input data and its location. Each channel is a named input source. Similar to InputDataConfig supported by HyperParameterTrainingJobDefinition. Format(s) supported: CSV, Parquet. A minimum of 500 rows is required for the training dataset. There is not a minimum number of rows required for the validation dataset.
Returns the input data configuration for the AutoML job.
', ], ], 'AutoMLJobArn' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the AutoML job.
', 'AutoMLJobSummary$AutoMLJobArn' => 'The ARN of the AutoML job.
', 'CreateAutoMLJobResponse$AutoMLJobArn' => 'The unique ARN assigned to the AutoML job when it is created.
', 'CreateAutoMLJobV2Response$AutoMLJobArn' => 'The unique ARN assigned to the AutoMLJob when it is created.
', 'DescribeAutoMLJobResponse$AutoMLJobArn' => 'Returns the ARN of the AutoML job.
', 'DescribeAutoMLJobV2Response$AutoMLJobArn' => 'Returns the Amazon Resource Name (ARN) of the AutoML job V2.
', 'DescribeProcessingJobResponse$AutoMLJobArn' => 'The ARN of an AutoML job associated with this processing job.
', 'DescribeTrainingJobResponse$AutoMLJobArn' => 'The Amazon Resource Name (ARN) of an AutoML job.
', 'DescribeTransformJobResponse$AutoMLJobArn' => 'The Amazon Resource Name (ARN) of the AutoML transform job.
', 'ProcessingJob$AutoMLJobArn' => 'The Amazon Resource Name (ARN) of the AutoML job associated with this processing job.
', 'TrainingJob$AutoMLJobArn' => 'The Amazon Resource Name (ARN) of the job.
', 'TransformJob$AutoMLJobArn' => 'The Amazon Resource Name (ARN) of the AutoML job that created the transform job.
', ], ], 'AutoMLJobArtifacts' => [ 'base' => 'The artifacts that are generated during an AutoML job.
', 'refs' => [ 'DescribeAutoMLJobResponse$AutoMLJobArtifacts' => 'Returns information on the job\'s artifacts found in AutoMLJobArtifacts.
A channel is a named input source that training algorithms can consume. This channel is used for AutoML jobs V2 (jobs created by calling CreateAutoMLJobV2).
', 'refs' => [ 'AutoMLJobInputDataConfig$member' => NULL, ], ], 'AutoMLJobCompletionCriteria' => [ 'base' => 'How long a job is allowed to run, or how many candidates a job is allowed to generate.
', 'refs' => [ 'AutoMLJobConfig$CompletionCriteria' => 'How long an AutoML job is allowed to run, or how many candidates a job is allowed to generate.
', 'AutoMLResolvedAttributes$CompletionCriteria' => NULL, 'ImageClassificationJobConfig$CompletionCriteria' => 'How long a job is allowed to run, or how many candidates a job is allowed to generate.
', 'ResolvedAttributes$CompletionCriteria' => NULL, 'TabularJobConfig$CompletionCriteria' => NULL, 'TextClassificationJobConfig$CompletionCriteria' => 'How long a job is allowed to run, or how many candidates a job is allowed to generate.
', 'TextGenerationJobConfig$CompletionCriteria' => NULL, 'TimeSeriesForecastingJobConfig$CompletionCriteria' => NULL, ], ], 'AutoMLJobConfig' => [ 'base' => 'A collection of settings used for an AutoML job.
', 'refs' => [ 'CreateAutoMLJobRequest$AutoMLJobConfig' => 'A collection of settings used to configure an AutoML job.
', 'DescribeAutoMLJobResponse$AutoMLJobConfig' => 'Returns the configuration for the AutoML job.
', ], ], 'AutoMLJobInputDataConfig' => [ 'base' => NULL, 'refs' => [ 'CreateAutoMLJobV2Request$AutoMLJobInputDataConfig' => 'An array of channel objects describing the input data and their location. Each channel is a named input source. Similar to the InputDataConfig attribute in the CreateAutoMLJob input parameters. The supported formats depend on the problem type:
For tabular problem types: S3Prefix, ManifestFile.
For image classification: S3Prefix, ManifestFile, AugmentedManifestFile.
For text classification: S3Prefix.
For time-series forecasting: S3Prefix.
For text generation (LLMs fine-tuning): S3Prefix.
Returns an array of channel objects describing the input data and their location.
', ], ], 'AutoMLJobName' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobSummary$AutoMLJobName' => 'The name of the AutoML job you are requesting.
', 'CreateAutoMLJobRequest$AutoMLJobName' => 'Identifies an Autopilot job. The name must be unique to your account and is case insensitive.
', 'CreateAutoMLJobV2Request$AutoMLJobName' => 'Identifies an Autopilot job. The name must be unique to your account and is case insensitive.
', 'DescribeAutoMLJobRequest$AutoMLJobName' => 'Requests information about an AutoML job using its unique name.
', 'DescribeAutoMLJobResponse$AutoMLJobName' => 'Returns the name of the AutoML job.
', 'DescribeAutoMLJobV2Request$AutoMLJobName' => 'Requests information about an AutoML job V2 using its unique name.
', 'DescribeAutoMLJobV2Response$AutoMLJobName' => 'Returns the name of the AutoML job V2.
', 'ListCandidatesForAutoMLJobRequest$AutoMLJobName' => 'List the candidates created for the job by providing the job\'s name.
', 'StopAutoMLJobRequest$AutoMLJobName' => 'The name of the object you are requesting.
', ], ], 'AutoMLJobObjective' => [ 'base' => 'Specifies a metric to minimize or maximize as the objective of an AutoML job.
', 'refs' => [ 'AutoMLResolvedAttributes$AutoMLJobObjective' => NULL, 'CreateAutoMLJobRequest$AutoMLJobObjective' => 'Specifies a metric to minimize or maximize as the objective of a job. If not specified, the default objective metric depends on the problem type. See AutoMLJobObjective for the default values.
', 'CreateAutoMLJobV2Request$AutoMLJobObjective' => 'Specifies a metric to minimize or maximize as the objective of a job. If not specified, the default objective metric depends on the problem type. For the list of default values per problem type, see AutoMLJobObjective.
For tabular problem types: You must either provide both the AutoMLJobObjective and indicate the type of supervised learning problem in AutoMLProblemTypeConfig (TabularJobConfig.ProblemType), or none at all.
For text generation problem types (LLMs fine-tuning): Fine-tuning language models in Autopilot does not require setting the AutoMLJobObjective field. Autopilot fine-tunes LLMs without requiring multiple candidates to be trained and evaluated. Instead, using your dataset, Autopilot directly fine-tunes your target model to enhance a default objective metric, the cross-entropy loss. After fine-tuning a language model, you can evaluate the quality of its generated text using different metrics. For a list of the available metrics, see Metrics for fine-tuning LLMs in Autopilot.
Returns the job\'s objective.
', 'DescribeAutoMLJobV2Response$AutoMLJobObjective' => 'Returns the job\'s objective.
', 'ResolvedAttributes$AutoMLJobObjective' => NULL, ], ], 'AutoMLJobObjectiveType' => [ 'base' => NULL, 'refs' => [ 'FinalAutoMLJobObjectiveMetric$Type' => 'The type of metric with the best result.
', ], ], 'AutoMLJobSecondaryStatus' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobSummary$AutoMLJobSecondaryStatus' => 'The secondary status of the AutoML job.
', 'DescribeAutoMLJobResponse$AutoMLJobSecondaryStatus' => 'Returns the secondary status of the AutoML job.
', 'DescribeAutoMLJobV2Response$AutoMLJobSecondaryStatus' => 'Returns the secondary status of the AutoML job V2.
', ], ], 'AutoMLJobStatus' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobSummary$AutoMLJobStatus' => 'The status of the AutoML job.
', 'DescribeAutoMLJobResponse$AutoMLJobStatus' => 'Returns the status of the AutoML job.
', 'DescribeAutoMLJobV2Response$AutoMLJobStatus' => 'Returns the status of the AutoML job V2.
', 'ListAutoMLJobsRequest$StatusEquals' => 'Request a list of jobs, using a filter for status.
', ], ], 'AutoMLJobStepMetadata' => [ 'base' => 'Metadata for an AutoML job step.
', 'refs' => [ 'PipelineExecutionStepMetadata$AutoMLJob' => 'The Amazon Resource Name (ARN) of the AutoML job that was run by this step.
', ], ], 'AutoMLJobSummaries' => [ 'base' => NULL, 'refs' => [ 'ListAutoMLJobsResponse$AutoMLJobSummaries' => 'Returns a summary list of jobs.
', ], ], 'AutoMLJobSummary' => [ 'base' => 'Provides a summary about an AutoML job.
', 'refs' => [ 'AutoMLJobSummaries$member' => NULL, ], ], 'AutoMLMaxResults' => [ 'base' => NULL, 'refs' => [ 'ListAutoMLJobsRequest$MaxResults' => 'Request a list of jobs up to a specified limit.
', 'ListCandidatesForAutoMLJobRequest$MaxResults' => 'List the job\'s candidates up to a specified limit.
', ], ], 'AutoMLMetricEnum' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobObjective$MetricName' => 'The name of the objective metric used to measure the predictive quality of a machine learning system. During training, the model\'s parameters are updated iteratively to optimize its performance based on the feedback provided by the objective metric when evaluating the model on the validation dataset.
The list of available metrics supported by Autopilot and the default metric applied when you do not specify a metric name explicitly depend on the problem type.
For tabular problem types:
List of available metrics:
Regression: InferenceLatency, MAE, MSE, R2, RMSE
Binary classification: Accuracy, AUC, BalancedAccuracy, F1, InferenceLatency, LogLoss, Precision, Recall
Multiclass classification: Accuracy, BalancedAccuracy, F1macro, InferenceLatency, LogLoss, PrecisionMacro, RecallMacro
For a description of each metric, see Autopilot metrics for classification and regression.
Default objective metrics:
Regression: MSE.
Binary classification: F1.
Multiclass classification: Accuracy.
For image or text classification problem types:
List of available metrics: Accuracy
For a description of each metric, see Autopilot metrics for text and image classification.
Default objective metrics: Accuracy
For time-series forecasting problem types:
List of available metrics: RMSE, wQL, Average wQL, MASE, MAPE, WAPE
For a description of each metric, see Autopilot metrics for time-series forecasting.
Default objective metrics: AverageWeightedQuantileLoss
For text generation problem types (LLMs fine-tuning): Fine-tuning language models in Autopilot does not require setting the AutoMLJobObjective field. Autopilot fine-tunes LLMs without requiring multiple candidates to be trained and evaluated. Instead, using your dataset, Autopilot directly fine-tunes your target model to enhance a default objective metric, the cross-entropy loss. After fine-tuning a language model, you can evaluate the quality of its generated text using different metrics. For a list of the available metrics, see Metrics for fine-tuning LLMs in Autopilot.
The name of the metric with the best result. For a description of the possible objective metrics, see AutoMLJobObjective$MetricName.
', 'FinalAutoMLJobObjectiveMetric$StandardMetricName' => 'The name of the standard metric. For a description of the standard metrics, see Autopilot candidate metrics.
', 'MetricDatum$MetricName' => 'The name of the metric.
', ], ], 'AutoMLMetricExtendedEnum' => [ 'base' => NULL, 'refs' => [ 'MetricDatum$StandardMetricName' => 'The name of the standard metric.
For definitions of the standard metrics, see Autopilot candidate metrics .
The method that Autopilot uses to train the data. You can either specify the mode manually or let Autopilot choose for you based on the dataset size by selecting AUTO. In AUTO mode, Autopilot chooses ENSEMBLING for datasets smaller than 100 MB, and HYPERPARAMETER_TUNING for larger ones.
The ENSEMBLING mode uses a multi-stack ensemble model to predict classification and regression tasks directly from your dataset. This machine learning mode combines several base models to produce an optimal predictive model. It then uses a stacking ensemble method to combine predictions from contributing members. A multi-stack ensemble model can provide better performance over a single model by combining the predictive capabilities of multiple models. See Autopilot algorithm support for a list of algorithms supported by ENSEMBLING mode.
The HYPERPARAMETER_TUNING (HPO) mode uses the best hyperparameters to train the best version of a model. HPO automatically selects an algorithm for the type of problem you want to solve. Then HPO finds the best hyperparameters according to your objective metric. See Autopilot algorithm support for a list of algorithms supported by HYPERPARAMETER_TUNING mode.
The method that Autopilot uses to train the data. You can either specify the mode manually or let Autopilot choose for you based on the dataset size by selecting AUTO. In AUTO mode, Autopilot chooses ENSEMBLING for datasets smaller than 100 MB, and HYPERPARAMETER_TUNING for larger ones.
The ENSEMBLING mode uses a multi-stack ensemble model to predict classification and regression tasks directly from your dataset. This machine learning mode combines several base models to produce an optimal predictive model. It then uses a stacking ensemble method to combine predictions from contributing members. A multi-stack ensemble model can provide better performance over a single model by combining the predictive capabilities of multiple models. See Autopilot algorithm support for a list of algorithms supported by ENSEMBLING mode.
The HYPERPARAMETER_TUNING (HPO) mode uses the best hyperparameters to train the best version of a model. HPO automatically selects an algorithm for the type of problem you want to solve. Then HPO finds the best hyperparameters according to your objective metric. See Autopilot algorithm support for a list of algorithms supported by HYPERPARAMETER_TUNING mode.
Request a list of jobs, using a search filter for name.
', ], ], 'AutoMLOutputDataConfig' => [ 'base' => 'The output data configuration.
', 'refs' => [ 'CreateAutoMLJobRequest$OutputDataConfig' => 'Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job. Format(s) supported: CSV.
', 'CreateAutoMLJobV2Request$OutputDataConfig' => 'Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job.
', 'DescribeAutoMLJobResponse$OutputDataConfig' => 'Returns the job\'s output data config.
', 'DescribeAutoMLJobV2Response$OutputDataConfig' => 'Returns the job\'s output data config.
', ], ], 'AutoMLPartialFailureReason' => [ 'base' => 'The reason for a partial failure of an AutoML job.
', 'refs' => [ 'AutoMLPartialFailureReasons$member' => NULL, ], ], 'AutoMLPartialFailureReasons' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobSummary$PartialFailureReasons' => 'The list of reasons for partial failures within an AutoML job.
', 'DescribeAutoMLJobResponse$PartialFailureReasons' => 'Returns a list of reasons for partial failures within an AutoML job.
', 'DescribeAutoMLJobV2Response$PartialFailureReasons' => 'Returns a list of reasons for partial failures within an AutoML job V2.
', ], ], 'AutoMLProblemTypeConfig' => [ 'base' => 'A collection of settings specific to the problem type used to configure an AutoML job V2. There must be one and only one config of the following type.
', 'refs' => [ 'CreateAutoMLJobV2Request$AutoMLProblemTypeConfig' => 'Defines the configuration settings of one of the supported problem types.
', 'DescribeAutoMLJobV2Response$AutoMLProblemTypeConfig' => 'Returns the configuration settings of the problem type set for the AutoML job V2.
', ], ], 'AutoMLProblemTypeConfigName' => [ 'base' => NULL, 'refs' => [ 'DescribeAutoMLJobV2Response$AutoMLProblemTypeConfigName' => 'Returns the name of the problem type configuration set for the AutoML job V2.
', ], ], 'AutoMLProblemTypeResolvedAttributes' => [ 'base' => 'Stores resolved attributes specific to the problem type of an AutoML job V2.
', 'refs' => [ 'AutoMLResolvedAttributes$AutoMLProblemTypeResolvedAttributes' => 'Defines the resolved attributes specific to a problem type.
', ], ], 'AutoMLProcessingUnit' => [ 'base' => NULL, 'refs' => [ 'AutoMLInferenceContainerDefinitions$key' => 'Processing unit for an inference container. Currently Autopilot only supports CPU or GPU.
The resolved attributes used to configure an AutoML job V2.
', 'refs' => [ 'DescribeAutoMLJobV2Response$ResolvedAttributes' => 'Returns the resolved attributes used by the AutoML job V2.
', ], ], 'AutoMLS3DataSource' => [ 'base' => 'Describes the Amazon S3 data source.
', 'refs' => [ 'AutoMLDataSource$S3DataSource' => 'The Amazon S3 location of the input data.
', ], ], 'AutoMLS3DataType' => [ 'base' => NULL, 'refs' => [ 'AutoMLS3DataSource$S3DataType' => 'The data type.
If you choose S3Prefix, S3Uri identifies a key name prefix. SageMaker uses all objects that match the specified key name prefix for model training.
The S3Prefix should have the following format:
s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER-OR-FILE
If you choose ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want SageMaker to use for model training.
A ManifestFile should have the format shown below:
[ {"prefix": "s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER/DOC-EXAMPLE-PREFIX/"},
"DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-1",
"DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-2",
... "DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-N" ]
If you choose AugmentedManifestFile, S3Uri identifies an object that is an augmented manifest file in JSON lines format. This file contains the data you want to use for model training. AugmentedManifestFile is available for V2 API jobs only (for example, for jobs created by calling CreateAutoMLJobV2).
Here is a minimal, single-record example of an AugmentedManifestFile:
{"source-ref": "s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER/cats/cat.jpg",
"label-metadata": {"class-name": "cat" }
For more information on AugmentedManifestFile, see Provide Dataset Metadata to Training Jobs with an Augmented Manifest File.
Security options.
', 'refs' => [ 'AutoMLJobConfig$SecurityConfig' => 'The security configuration for traffic encryption or Amazon VPC settings.
', 'CreateAutoMLJobV2Request$SecurityConfig' => 'The security configuration for traffic encryption or Amazon VPC settings.
', 'DescribeAutoMLJobV2Response$SecurityConfig' => 'Returns the security configuration for traffic encryption or Amazon VPC settings.
', ], ], 'AutoMLSortBy' => [ 'base' => NULL, 'refs' => [ 'ListAutoMLJobsRequest$SortBy' => 'The parameter by which to sort the results. The default is Name.
The sort order for the results. The default is Descending.
The sort order for the results. The default is Ascending.
The name and an example value of the hyperparameter that you want to use in Autotune. If Automatic model tuning (AMT) determines that your hyperparameter is eligible for Autotune, an optimal hyperparameter range is selected for you.
', 'refs' => [ 'AutoParameters$member' => NULL, ], ], 'AutoParameters' => [ 'base' => NULL, 'refs' => [ 'ParameterRanges$AutoParameters' => 'A list containing hyperparameter names and example values to be used by Autotune to determine optimal ranges for your tuning job.
', ], ], 'AutoRollbackConfig' => [ 'base' => 'Automatic rollback configuration for handling endpoint deployment failures and recovery.
', 'refs' => [ 'DeploymentConfig$AutoRollbackConfiguration' => 'Automatic rollback configuration for handling endpoint deployment failures and recovery.
', ], ], 'Autotune' => [ 'base' => 'A flag to indicate if you want to use Autotune to automatically find optimal values for the following fields:
ParameterRanges: The names and ranges of parameters that a hyperparameter tuning job can optimize.
ResourceLimits: The maximum resources that can be used for a training job. These resources include the maximum number of training jobs, the maximum runtime of a tuning job, and the maximum number of training jobs to run at the same time.
TrainingJobEarlyStoppingType: A flag that specifies whether or not to use early stopping for training jobs launched by a hyperparameter tuning job.
RetryStrategy: The number of times to retry a training job.
Strategy: Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training jobs that it launches.
ConvergenceDetected: A flag to indicate that Automatic model tuning (AMT) has detected model convergence.
Configures SageMaker Automatic model tuning (AMT) to automatically find optimal parameters for the following fields:
ParameterRanges: The names and ranges of parameters that a hyperparameter tuning job can optimize.
ResourceLimits: The maximum resources that can be used for a training job. These resources include the maximum number of training jobs, the maximum runtime of a tuning job, and the maximum number of training jobs to run at the same time.
TrainingJobEarlyStoppingType: A flag that specifies whether or not to use early stopping for training jobs launched by a hyperparameter tuning job.
RetryStrategy: The number of times to retry a training job.
Strategy: Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training jobs that it launches.
ConvergenceDetected: A flag to indicate that Automatic model tuning (AMT) has detected model convergence.
A flag to indicate if autotune is enabled for the hyperparameter tuning job.
', ], ], 'AutotuneMode' => [ 'base' => NULL, 'refs' => [ 'Autotune$Mode' => 'Set Mode to Enabled if you want to use Autotune.
Specifies whether Amazon Rekognition or Amazon Textract are used as the integration source. The default field settings and JSON parsing rules are different based on the integration source. Valid values:
', ], ], 'BacktestResultsLocation' => [ 'base' => NULL, 'refs' => [ 'CandidateArtifactLocations$BacktestResults' => 'The Amazon S3 prefix to the accuracy metrics and the inference results observed over the testing window. Available only for the time-series forecasting problem type.
', ], ], 'BaseModelName' => [ 'base' => NULL, 'refs' => [ 'TextGenerationJobConfig$BaseModelName' => 'The name of the base model to fine-tune. Autopilot supports fine-tuning a variety of large language models. For information on the list of supported models, see Text generation models supporting fine-tuning in Autopilot. If no BaseModelName is provided, the default model used is Falcon-7B-Instruct.
The name of the base model to fine-tune.
', ], ], 'BatchDataCaptureConfig' => [ 'base' => 'Configuration to control how SageMaker captures inference data for batch transform jobs.
', 'refs' => [ 'CreateTransformJobRequest$DataCaptureConfig' => 'Configuration to control how SageMaker captures inference data.
', 'DescribeTransformJobResponse$DataCaptureConfig' => 'Configuration to control how SageMaker captures inference data.
', 'TransformJob$DataCaptureConfig' => NULL, ], ], 'BatchDescribeModelPackageError' => [ 'base' => 'The error code and error description associated with the resource.
', 'refs' => [ 'BatchDescribeModelPackageErrorMap$value' => NULL, ], ], 'BatchDescribeModelPackageErrorMap' => [ 'base' => NULL, 'refs' => [ 'BatchDescribeModelPackageOutput$BatchDescribeModelPackageErrorMap' => 'A map of the resource and BatchDescribeModelPackageError objects reporting the error associated with describing the model package.
', ], ], 'BatchDescribeModelPackageInput' => [ 'base' => NULL, 'refs' => [], ], 'BatchDescribeModelPackageOutput' => [ 'base' => NULL, 'refs' => [], ], 'BatchDescribeModelPackageSummary' => [ 'base' => 'Provides summary information about the model package.
', 'refs' => [ 'ModelPackageSummaries$value' => NULL, ], ], 'BatchStrategy' => [ 'base' => NULL, 'refs' => [ 'CreateTransformJobRequest$BatchStrategy' => 'Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.
To enable the batch strategy, you must set the SplitType property to Line, RecordIO, or TFRecord.
To use only one record when making an HTTP invocation request to a container, set BatchStrategy to SingleRecord and SplitType to Line.
To fit as many records in a mini-batch as can fit within the MaxPayloadInMB limit, set BatchStrategy to MultiRecord and SplitType to Line.
Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.
To enable the batch strategy, you must set SplitType to Line, RecordIO, or TFRecord.
Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.
', 'TransformJobDefinition$BatchStrategy' => 'A string that determines the number of records included in a single mini-batch.
SingleRecord means only one record is used per mini-batch. MultiRecord means a mini-batch is set to contain as many records that can fit within the MaxPayloadInMB limit.
Input object for the batch transform job.
', 'refs' => [ 'DataQualityJobInput$BatchTransformInput' => 'Input object for the batch transform job.
', 'ModelBiasJobInput$BatchTransformInput' => 'Input object for the batch transform job.
', 'ModelDashboardMonitoringSchedule$BatchTransformInput' => NULL, 'ModelExplainabilityJobInput$BatchTransformInput' => 'Input object for the batch transform job.
', 'ModelQualityJobInput$BatchTransformInput' => 'Input object for the batch transform job.
', 'MonitoringInput$BatchTransformInput' => 'Input object for the batch transform job.
', ], ], 'BestObjectiveNotImproving' => [ 'base' => 'A structure that keeps track of which training jobs launched by your hyperparameter tuning job are not improving model performance as evaluated against an objective function.
', 'refs' => [ 'TuningJobCompletionCriteria$BestObjectiveNotImproving' => 'A flag to stop your hyperparameter tuning job if model performance fails to improve as evaluated against an objective function.
', ], ], 'Bias' => [ 'base' => 'Contains bias metrics for a model.
', 'refs' => [ 'ModelMetrics$Bias' => 'Metrics that measure bais in a model.
', ], ], 'BillableTimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'DescribeTrainingJobResponse$BillableTimeInSeconds' => 'The billable time in seconds. Billable time refers to the absolute wall-clock time.
Multiply BillableTimeInSeconds by the number of instances (InstanceCount) in your training cluster to get the total compute time SageMaker bills you if you run distributed training. The formula is as follows: BillableTimeInSeconds * InstanceCount .
You can calculate the savings from using managed spot training using the formula (1 - BillableTimeInSeconds / TrainingTimeInSeconds) * 100. For example, if BillableTimeInSeconds is 100 and TrainingTimeInSeconds is 500, the savings is 80%.
The billable time in seconds.
', ], ], 'BlockedReason' => [ 'base' => NULL, 'refs' => [ 'OfflineStoreStatus$BlockedReason' => 'The justification for why the OfflineStoreStatus is Blocked (if applicable).
', ], ], 'BlueGreenUpdatePolicy' => [ 'base' => 'Update policy for a blue/green deployment. If this update policy is specified, SageMaker creates a new fleet during the deployment while maintaining the old fleet. SageMaker flips traffic to the new fleet according to the specified traffic routing configuration. Only one update policy should be used in the deployment configuration. If no update policy is specified, SageMaker uses a blue/green deployment strategy with all at once traffic shifting by default.
', 'refs' => [ 'DeploymentConfig$BlueGreenUpdatePolicy' => 'Update policy for a blue/green deployment. If this update policy is specified, SageMaker creates a new fleet during the deployment while maintaining the old fleet. SageMaker flips traffic to the new fleet according to the specified traffic routing configuration. Only one update policy should be used in the deployment configuration. If no update policy is specified, SageMaker uses a blue/green deployment strategy with all at once traffic shifting by default.
', ], ], 'Boolean' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSpecification$EnableSageMakerMetricsTimeSeries' => 'To generate and save time-series metrics during training, set to true. The default is false and time-series metrics aren\'t generated except in the following cases:
You use one of the SageMaker built-in algorithms
You use one of the following Prebuilt SageMaker Docker Images:
Tensorflow (version >= 1.15)
MXNet (version >= 1.6)
PyTorch (version >= 1.3)
You specify at least one MetricDefinition
Whether to use traffic encryption between the container layers.
', 'BatchDataCaptureConfig$GenerateInferenceId' => 'Flag that indicates whether to append inference id to the output.
', 'ChannelSpecification$IsRequired' => 'Indicates whether the channel is required by the algorithm.
', 'ClarifyCheckStepMetadata$SkipCheck' => 'This flag indicates if the drift check against the previous baseline will be skipped or not. If it is set to False, the previous baseline of the configured check type must be available.
This flag indicates if a newly calculated baseline can be accessed through step properties BaselineUsedForDriftCheckConstraints and BaselineUsedForDriftCheckStatistics. If it is set to False, the previous baseline of the configured check type must also be available. These can be accessed through the BaselineUsedForDriftCheckConstraints property.
Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
', 'CreateTrainingJobRequest$EnableNetworkIsolation' => 'Isolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If you enable network isolation for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.
', 'CreateTrainingJobRequest$EnableInterContainerTrafficEncryption' => 'To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training. For more information, see Protect Communications Between ML Compute Instances in a Distributed Training Job.
To train models using managed spot training, choose True. Managed spot training provides a fully managed and scalable infrastructure for training machine learning models. this option is useful when training jobs can be interrupted and when there is flexibility when the training job is run.
The complete and intermediate results of jobs are stored in an Amazon S3 bucket, and can be used as a starting point to train models incrementally. Amazon SageMaker provides metrics and logs in CloudWatch. They can be used to see when managed spot training jobs are running, interrupted, resumed, or completed.
', 'DescribeModelOutput$EnableNetworkIsolation' => 'If True, no inbound or outbound network calls can be made to or from the model container.
If you want to allow inbound or outbound network calls, except for calls between peers within a training cluster for distributed training, choose True. If you enable network isolation for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.
To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithms in distributed training.
A Boolean indicating whether managed spot training is enabled (True) or not (False).
Indicates whether this hyperparameter is tunable in a hyperparameter tuning job.
', 'HyperParameterSpecification$IsRequired' => 'Indicates whether this hyperparameter is required.
', 'HyperParameterTrainingJobDefinition$EnableNetworkIsolation' => 'Isolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If network isolation is used for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.
', 'HyperParameterTrainingJobDefinition$EnableInterContainerTrafficEncryption' => 'To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training.
A Boolean indicating whether managed spot training is enabled (True) or not (False).
Toggle for excluding devices deployed in other stages.
', 'Model$EnableNetworkIsolation' => 'Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
', 'ModelDashboardIndicatorAction$Enabled' => 'Indicates whether the alert action is turned on.
', 'MonitoringCsvDatasetFormat$Header' => 'Indicates if the CSV data has a header.
', 'MonitoringJsonDatasetFormat$Line' => 'Indicates if the file should be read as a JSON object per line.
', 'MonitoringNetworkConfig$EnableInterContainerTrafficEncryption' => 'Whether to encrypt all communications between the instances used for the monitoring jobs. Choose True to encrypt communications. Encryption provides greater security for distributed jobs, but the processing might take longer.
Whether to allow inbound and outbound network calls to and from the containers used for the monitoring job.
', 'NetworkConfig$EnableInterContainerTrafficEncryption' => 'Whether to encrypt all communications between distributed processing jobs. Choose True to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.
Whether to allow inbound and outbound network calls to and from the containers used for the processing job.
', 'OfflineStoreConfig$DisableGlueTableCreation' => 'Set to True to disable the automatic creation of an Amazon Web Services Glue table when configuring an OfflineStore. If set to False, Feature Store will name the OfflineStore Glue table following Athena\'s naming recommendations.
The default value is False.
Turn OnlineStore off by specifying False for the EnableOnlineStore flag. Turn OnlineStore on by specifying True for the EnableOnlineStore flag.
The default value is False.
This flag indicates if the drift check against the previous baseline will be skipped or not. If it is set to False, the previous baseline of the configured check type must be available.
This flag indicates if a newly calculated baseline can be accessed through step properties BaselineUsedForDriftCheckConstraints and BaselineUsedForDriftCheckStatistics. If it is set to False, the previous baseline of the configured check type must also be available. These can be accessed through the BaselineUsedForDriftCheckConstraints and BaselineUsedForDriftCheckStatistics properties.
Setting this value to True retrieves not only the entities of interest but also the Associations and lineage entities on the path. Set to False to only return lineage entities that match your query.
If the TrainingJob was created with network isolation, the value is set to true. If network isolation is enabled, nodes can\'t communicate beyond the VPC they run in.
To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training.
When true, enables managed spot training using Amazon EC2 Spot instances to run training jobs instead of on-demand instances. For more information, see Managed Spot Training.
', 'TrainingSpecification$SupportsDistributedTraining' => 'Indicates whether the algorithm supports distributed training. If set to false, buyers can\'t request more than one instance during training.
', 'UpdateEndpointInput$RetainAllVariantProperties' => 'When updating endpoint resources, enables or disables the retention of variant properties, such as the instance count or the variant weight. To retain the variant properties of an endpoint when updating it, set RetainAllVariantProperties to true. To use the variant properties specified in a new EndpointConfig call when updating an endpoint, set RetainAllVariantProperties to false. The default is false.
Specifies whether to reuse the last deployment configuration. The default value is false (the configuration is not reused).
', ], ], 'BooleanOperator' => [ 'base' => NULL, 'refs' => [ 'SearchExpression$Operator' => 'A Boolean operator used to evaluate the search expression. If you want every conditional statement in all lists to be satisfied for the entire search expression to be true, specify And. If only a single conditional statement needs to be true for the entire search expression to be true, specify Or. The default value is And.
The default branch for the Git repository.
', ], ], 'BucketName' => [ 'base' => NULL, 'refs' => [ 'PipelineDefinitionS3Location$Bucket' => 'Name of the S3 bucket.
', ], ], 'CacheHitResult' => [ 'base' => 'Details on the cache hit of a pipeline execution step.
', 'refs' => [ 'PipelineExecutionStep$CacheHitResult' => 'If this pipeline execution step was cached, details on the cache hit.
', ], ], 'CallbackStepMetadata' => [ 'base' => 'Metadata about a callback step.
', 'refs' => [ 'PipelineExecutionStepMetadata$Callback' => 'The URL of the Amazon SQS queue used by this step execution, the pipeline generated token, and a list of output parameters.
', ], ], 'CallbackToken' => [ 'base' => NULL, 'refs' => [ 'CallbackStepMetadata$CallbackToken' => 'The pipeline generated token from the Amazon SQS queue.
', 'SendPipelineExecutionStepFailureRequest$CallbackToken' => 'The pipeline generated token from the Amazon SQS queue.
', 'SendPipelineExecutionStepSuccessRequest$CallbackToken' => 'The pipeline generated token from the Amazon SQS queue.
', ], ], 'CandidateArtifactLocations' => [ 'base' => 'The location of artifacts for an AutoML candidate job.
', 'refs' => [ 'CandidateProperties$CandidateArtifactLocations' => 'The Amazon S3 prefix to the artifacts generated for an AutoML candidate.
', ], ], 'CandidateDefinitionNotebookLocation' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobArtifacts$CandidateDefinitionNotebookLocation' => 'The URL of the notebook location.
', ], ], 'CandidateGenerationConfig' => [ 'base' => 'Stores the configuration information for how model candidates are generated using an AutoML job V2.
', 'refs' => [ 'TabularJobConfig$CandidateGenerationConfig' => 'The configuration information of how model candidates are generated.
', ], ], 'CandidateName' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidate$CandidateName' => 'The name of the candidate.
', 'ListCandidatesForAutoMLJobRequest$CandidateNameEquals' => 'List the candidates for the job and filter by candidate name.
', ], ], 'CandidateProperties' => [ 'base' => 'The properties of an AutoML candidate job.
', 'refs' => [ 'AutoMLCandidate$CandidateProperties' => 'The properties of an AutoML candidate job.
', ], ], 'CandidateSortBy' => [ 'base' => NULL, 'refs' => [ 'ListCandidatesForAutoMLJobRequest$SortBy' => 'The parameter by which to sort the results. The default is Descending.
The candidate\'s status.
', 'ListCandidatesForAutoMLJobRequest$StatusEquals' => 'List the candidates for the job and filter by status.
', ], ], 'CandidateStepArn' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidateStep$CandidateStepArn' => 'The ARN for the candidate\'s step.
', ], ], 'CandidateStepName' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidateStep$CandidateStepName' => 'The name for the candidate\'s step.
', ], ], 'CandidateStepType' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidateStep$CandidateStepType' => 'Whether the candidate is at the transform, training, or processing step.
', ], ], 'CandidateSteps' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidate$CandidateSteps' => 'Information about the candidate\'s steps.
', ], ], 'CanvasAppSettings' => [ 'base' => 'The SageMaker Canvas application settings.
', 'refs' => [ 'UserSettings$CanvasAppSettings' => 'The Canvas app settings.
', ], ], 'CapacitySize' => [ 'base' => 'Specifies the type and size of the endpoint capacity to activate for a blue/green deployment, a rolling deployment, or a rollback strategy. You can specify your batches as either instance count or the overall percentage or your fleet.
For a rollback strategy, if you don\'t specify the fields in this object, or if you set the Value to 100%, then SageMaker uses a blue/green rollback strategy and rolls all traffic back to the blue fleet.
Batch size for each rolling step to provision capacity and turn on traffic on the new endpoint fleet, and terminate capacity on the old endpoint fleet. Value must be between 5% to 50% of the variant\'s total instance count.
', 'RollingUpdatePolicy$RollbackMaximumBatchSize' => 'Batch size for rollback to the old endpoint fleet. Each rolling step to provision capacity and turn on traffic on the old endpoint fleet, and terminate capacity on the new endpoint fleet. If this field is absent, the default value will be set to 100% of total capacity which means to bring up the whole capacity of the old fleet at once during rollback.
', 'TrafficRoutingConfig$CanarySize' => 'Batch size for the first step to turn on traffic on the new endpoint fleet. Value must be less than or equal to 50% of the variant\'s total instance count.
Batch size for each step to turn on traffic on the new endpoint fleet. Value must be 10-50% of the variant\'s total instance count.
Specifies the endpoint capacity type.
INSTANCE_COUNT: The endpoint activates based on the number of instances.
CAPACITY_PERCENT: The endpoint activates based on the specified percentage of capacity.
Defines the capacity size, either as a number of instances or a capacity percentage.
', ], ], 'CaptureContentTypeHeader' => [ 'base' => 'Configuration specifying how to treat different headers. If no headers are specified Amazon SageMaker will by default base64 encode when capturing the data.
', 'refs' => [ 'DataCaptureConfig$CaptureContentTypeHeader' => 'Configuration specifying how to treat different headers. If no headers are specified SageMaker will by default base64 encode when capturing the data.
', 'InferenceExperimentDataStorageConfig$ContentType' => NULL, ], ], 'CaptureMode' => [ 'base' => NULL, 'refs' => [ 'CaptureOption$CaptureMode' => 'Specify the boundary of data to capture.
', ], ], 'CaptureOption' => [ 'base' => 'Specifies data Model Monitor will capture.
', 'refs' => [ 'CaptureOptionList$member' => NULL, ], ], 'CaptureOptionList' => [ 'base' => NULL, 'refs' => [ 'DataCaptureConfig$CaptureOptions' => 'Specifies data Model Monitor will capture. You can configure whether to collect only input, only output, or both
', ], ], 'CaptureStatus' => [ 'base' => NULL, 'refs' => [ 'DataCaptureConfigSummary$CaptureStatus' => 'Whether data capture is currently functional.
', ], ], 'Catalog' => [ 'base' => NULL, 'refs' => [ 'DataCatalogConfig$Catalog' => 'The name of the Glue table catalog.
', ], ], 'CategoricalParameter' => [ 'base' => 'Environment parameters you want to benchmark your load test against.
', 'refs' => [ 'CategoricalParameters$member' => NULL, ], ], 'CategoricalParameterRange' => [ 'base' => 'A list of categorical hyperparameters to tune.
', 'refs' => [ 'CategoricalParameterRanges$member' => NULL, ], ], 'CategoricalParameterRangeSpecification' => [ 'base' => 'Defines the possible values for a categorical hyperparameter.
', 'refs' => [ 'ParameterRange$CategoricalParameterRangeSpecification' => 'A CategoricalParameterRangeSpecification object that defines the possible values for a categorical hyperparameter.
The list of values you can pass.
', ], ], 'CategoricalParameterRanges' => [ 'base' => NULL, 'refs' => [ 'ParameterRanges$CategoricalParameterRanges' => 'The array of CategoricalParameterRange objects that specify ranges of categorical hyperparameters that a hyperparameter tuning job searches.
', ], ], 'CategoricalParameters' => [ 'base' => NULL, 'refs' => [ 'EnvironmentParameterRanges$CategoricalParameterRanges' => 'Specified a list of parameters for each category.
', ], ], 'Cents' => [ 'base' => NULL, 'refs' => [ 'USD$Cents' => 'The fractional portion, in cents, of the amount.
', ], ], 'CertifyForMarketplace' => [ 'base' => NULL, 'refs' => [ 'CreateAlgorithmInput$CertifyForMarketplace' => 'Whether to certify the algorithm so that it can be listed in Amazon Web Services Marketplace.
', 'CreateModelPackageInput$CertifyForMarketplace' => 'Whether to certify the model package for listing on Amazon Web Services Marketplace.
This parameter is optional for unversioned models, and does not apply to versioned models.
', 'DescribeAlgorithmOutput$CertifyForMarketplace' => 'Whether the algorithm is certified to be listed in Amazon Web Services Marketplace.
', 'DescribeModelPackageOutput$CertifyForMarketplace' => 'Whether the model package is certified for listing on Amazon Web Services Marketplace.
', 'ModelPackage$CertifyForMarketplace' => 'Whether the model package is to be certified to be listed on Amazon Web Services Marketplace. For information about listing model packages on Amazon Web Services Marketplace, see List Your Algorithm or Model Package on Amazon Web Services Marketplace.
', ], ], 'Channel' => [ 'base' => 'A channel is a named input source that training algorithms can consume.
', 'refs' => [ 'InputDataConfig$member' => NULL, ], ], 'ChannelName' => [ 'base' => NULL, 'refs' => [ 'Channel$ChannelName' => 'The name of the channel.
', 'ChannelSpecification$Name' => 'The name of the channel.
', ], ], 'ChannelSpecification' => [ 'base' => 'Defines a named input source, called a channel, to be used by an algorithm.
', 'refs' => [ 'ChannelSpecifications$member' => NULL, ], ], 'ChannelSpecifications' => [ 'base' => NULL, 'refs' => [ 'TrainingSpecification$TrainingChannels' => 'A list of ChannelSpecification objects, which specify the input sources to be used by the algorithm.
Contains information about the output location for managed spot training checkpoint data.
', 'refs' => [ 'CreateTrainingJobRequest$CheckpointConfig' => 'Contains information about the output location for managed spot training checkpoint data.
', 'DescribeTrainingJobResponse$CheckpointConfig' => NULL, 'HyperParameterTrainingJobDefinition$CheckpointConfig' => NULL, 'TrainingJob$CheckpointConfig' => NULL, ], ], 'Cidr' => [ 'base' => NULL, 'refs' => [ 'Cidrs$member' => NULL, ], ], 'Cidrs' => [ 'base' => NULL, 'refs' => [ 'SourceIpConfig$Cidrs' => 'A list of one to ten Classless Inter-Domain Routing (CIDR) values.
Maximum: Ten CIDR values
The following Length Constraints apply to individual CIDR values in the CIDR value list.
The container for the metadata for the ClarifyCheck step. For more information, see the topic on ClarifyCheck step in the Amazon SageMaker Developer Guide.
', 'refs' => [ 'PipelineExecutionStepMetadata$ClarifyCheck' => 'Container for the metadata for a Clarify check step. The configurations and outcomes of the check step execution. This includes:
The type of the check conducted,
The Amazon S3 URIs of baseline constraints and statistics files to be used for the drift check.
The Amazon S3 URIs of newly calculated baseline constraints and statistics.
The model package group name provided.
The Amazon S3 URI of the violation report if violations detected.
The Amazon Resource Name (ARN) of check processing job initiated by the step execution.
The boolean flags indicating if the drift check is skipped.
If step property BaselineUsedForDriftCheck is set the same as CalculatedBaseline.
A template string used to format a JSON record into an acceptable model container input. For example, a ContentTemplate string \'{"myfeatures":$features}\' will format a list of features [1,2,3] into the record string \'{"myfeatures":[1,2,3]}\'. Required only when the model container input is in JSON Lines format.
A JMESPath boolean expression used to filter which records to explain. Explanations are activated by default. See EnableExplanations for additional information.
The configuration parameters for the SageMaker Clarify explainer.
', 'refs' => [ 'ExplainerConfig$ClarifyExplainerConfig' => 'A member of ExplainerConfig that contains configuration parameters for the SageMaker Clarify explainer.
The names of the features. If provided, these are included in the endpoint response payload to help readability of the InvokeEndpoint output. See the Response section under Invoke the endpoint in the Developer Guide for more information.
A list of data types of the features (optional). Applicable only to NLP explainability. If provided, FeatureTypes must have at least one \'text\' string (for example, [\'text\']). If FeatureTypes is not provided, the explainer infers the feature types based on the baseline data. The feature types are included in the endpoint response payload. For additional information see the response section under Invoke the endpoint in the Developer Guide for more information.
Provides the JMESPath expression to extract the features from a model container input in JSON Lines format. For example, if FeaturesAttribute is the JMESPath expression \'myfeatures\', it extracts a list of features [1,2,3] from request data \'{"myfeatures":[1,2,3]}\'.
The inference configuration parameter for the model container.
', 'refs' => [ 'ClarifyExplainerConfig$InferenceConfig' => 'The inference configuration parameter for the model container.
', ], ], 'ClarifyLabelAttribute' => [ 'base' => NULL, 'refs' => [ 'ClarifyInferenceConfig$LabelAttribute' => 'A JMESPath expression used to locate the list of label headers in the model container output.
Example: If the model container output of a batch request is \'{"labels":["cat","dog","fish"],"probability":[0.6,0.3,0.1]}\', then set LabelAttribute to \'labels\' to extract the list of label headers ["cat","dog","fish"]
For multiclass classification problems, the label headers are the names of the classes. Otherwise, the label header is the name of the predicted label. These are used to help readability for the output of the InvokeEndpoint API. See the response section under Invoke the endpoint in the Developer Guide for more information. If there are no label headers in the model container output, provide them manually using this parameter.
A zero-based index used to extract a label header or list of label headers from model container output in CSV format.
Example for a multiclass model: If the model container output consists of label headers followed by probabilities: \'"[\\\'cat\\\',\\\'dog\\\',\\\'fish\\\']","[0.1,0.6,0.3]"\', set LabelIndex to 0 to select the label headers [\'cat\',\'dog\',\'fish\'].
The maximum payload size (MB) allowed of a request from the explainer to the model container. Defaults to 6 MB.
The maximum number of records in a request that the model container can process when querying the model container for the predictions of a synthetic dataset. A record is a unit of input data that inference can be made on, for example, a single line in CSV data. If MaxRecordCount is 1, the model container expects one record per request. A value of 2 or greater means that the model expects batch requests, which can reduce overhead and speed up the inferencing process. If this parameter is not provided, the explainer will tune the record count per request according to the model container\'s capacity at runtime.
The MIME type of the baseline data. Choose from \'text/csv\' or \'application/jsonlines\'. Defaults to \'text/csv\'.
A JMESPath expression used to extract the probability (or score) from the model container output if the model container is in JSON Lines format.
Example: If the model container output of a single request is \'{"predicted_label":1,"probability":0.6}\', then set ProbabilityAttribute to \'probability\'.
A zero-based index used to extract a probability value (score) or list from model container output in CSV format. If this value is not provided, the entire model container output will be treated as a probability value (score) or list.
Example for a single class model: If the model container output consists of a string-formatted prediction label followed by its probability: \'1,0.6\', set ProbabilityIndex to 1 to select the probability value 0.6.
Example for a multiclass model: If the model container output consists of a string-formatted prediction label followed by its probability: \'"[\\\'cat\\\',\\\'dog\\\',\\\'fish\\\']","[0.1,0.6,0.3]"\', set ProbabilityIndex to 1 to select the probability values [0.1,0.6,0.3].
The inline SHAP baseline data in string format. ShapBaseline can have one or multiple records to be used as the baseline dataset. The format of the SHAP baseline file should be the same format as the training dataset. For example, if the training dataset is in CSV format and each record contains four features, and all features are numerical, then the format of the baseline data should also share these characteristics. For natural language processing (NLP) of text columns, the baseline value should be the value used to replace the unit of text specified by the Granularity of the TextConfig parameter. The size limit for ShapBasline is 4 KB. Use the ShapBaselineUri parameter if you want to provide more than 4 KB of baseline data.
The configuration for the SHAP baseline (also called the background or reference dataset) of the Kernal SHAP algorithm.
The number of records in the baseline data determines the size of the synthetic dataset, which has an impact on latency of explainability requests. For more information, see the Synthetic data of Configure and create an endpoint.
ShapBaseline and ShapBaselineUri are mutually exclusive parameters. One or the either is required to configure a SHAP baseline.
The configuration for the SHAP baseline of the Kernal SHAP algorithm.
', ], ], 'ClarifyShapConfig' => [ 'base' => 'The configuration for SHAP analysis using SageMaker Clarify Explainer.
', 'refs' => [ 'ClarifyExplainerConfig$ShapConfig' => 'The configuration for SHAP analysis.
', ], ], 'ClarifyShapNumberOfSamples' => [ 'base' => NULL, 'refs' => [ 'ClarifyShapConfig$NumberOfSamples' => 'The number of samples to be used for analysis by the Kernal SHAP algorithm.
The number of samples determines the size of the synthetic dataset, which has an impact on latency of explainability requests. For more information, see the Synthetic data of Configure and create an endpoint.
The starting value used to initialize the random number generator in the explainer. Provide a value for this parameter to obtain a deterministic SHAP result.
', ], ], 'ClarifyShapUseLogit' => [ 'base' => NULL, 'refs' => [ 'ClarifyShapConfig$UseLogit' => 'A Boolean toggle to indicate if you want to use the logit function (true) or log-odds units (false) for model predictions. Defaults to false.
', ], ], 'ClarifyTextConfig' => [ 'base' => 'A parameter used to configure the SageMaker Clarify explainer to treat text features as text so that explanations are provided for individual units of text. Required only for natural language processing (NLP) explainability.
', 'refs' => [ 'ClarifyShapConfig$TextConfig' => 'A parameter that indicates if text features are treated as text and explanations are provided for individual units of text. Required for natural language processing (NLP) explainability only.
', ], ], 'ClarifyTextGranularity' => [ 'base' => NULL, 'refs' => [ 'ClarifyTextConfig$Granularity' => 'The unit of granularity for the analysis of text features. For example, if the unit is \'token\', then each token (like a word in English) of the text is treated as a feature. SHAP values are computed for each unit/feature.
Specifies the language of the text features in ISO 639-1 or ISO 639-3 code of a supported language.
For a mix of multiple languages, use code \'xx\'.
The client ID for your Amazon Cognito user pool.
', 'CognitoMemberDefinition$ClientId' => 'An identifier for an application client. You must create the app client ID using Amazon Cognito.
', 'OidcConfig$ClientId' => 'The OIDC IdP client ID used to configure your private workforce.
', 'OidcConfigForResponse$ClientId' => 'The OIDC IdP client ID used to configure your private workforce.
', ], ], 'ClientSecret' => [ 'base' => NULL, 'refs' => [ 'OidcConfig$ClientSecret' => 'The OIDC IdP client secret used to configure your private workforce.
', ], ], 'ClientToken' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$ClientToken' => 'A unique ID. If not specified, the Amazon Web Services CLI and Amazon Web Services SDKs, such as the SDK for Python (Boto3), add a unique value to the call.
', 'CreateModelPackageInput$ClientToken' => 'A unique token that guarantees that the call to this API is idempotent.
', ], ], 'CodeRepositories' => [ 'base' => NULL, 'refs' => [ 'JupyterServerAppSettings$CodeRepositories' => 'A list of Git repositories that SageMaker automatically displays to users for cloning in the JupyterServer application.
', ], ], 'CodeRepository' => [ 'base' => 'A Git repository that SageMaker automatically displays to users for cloning in the JupyterServer application.
', 'refs' => [ 'CodeRepositories$member' => NULL, ], ], 'CodeRepositoryArn' => [ 'base' => NULL, 'refs' => [ 'CodeRepositorySummary$CodeRepositoryArn' => 'The Amazon Resource Name (ARN) of the Git repository.
', 'CreateCodeRepositoryOutput$CodeRepositoryArn' => 'The Amazon Resource Name (ARN) of the new repository.
', 'DescribeCodeRepositoryOutput$CodeRepositoryArn' => 'The Amazon Resource Name (ARN) of the Git repository.
', 'UpdateCodeRepositoryOutput$CodeRepositoryArn' => 'The ARN of the Git repository.
', ], ], 'CodeRepositoryContains' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstancesInput$DefaultCodeRepositoryContains' => 'A string in the name or URL of a Git repository associated with this notebook instance. This filter returns only notebook instances associated with a git repository with a name that contains the specified string.
', ], ], 'CodeRepositoryNameContains' => [ 'base' => NULL, 'refs' => [ 'ListCodeRepositoriesInput$NameContains' => 'A string in the Git repositories name. This filter returns only repositories whose name contains the specified string.
', ], ], 'CodeRepositoryNameOrUrl' => [ 'base' => NULL, 'refs' => [ 'AdditionalCodeRepositoryNamesOrUrls$member' => NULL, 'CreateNotebookInstanceInput$DefaultCodeRepository' => 'A Git repository to associate with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', 'DescribeNotebookInstanceOutput$DefaultCodeRepository' => 'The Git repository associated with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', 'ListNotebookInstancesInput$AdditionalCodeRepositoryEquals' => 'A filter that returns only notebook instances with associated with the specified git repository.
', 'NotebookInstanceSummary$DefaultCodeRepository' => 'The Git repository associated with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', 'UpdateNotebookInstanceInput$DefaultCodeRepository' => 'The Git repository to associate with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', ], ], 'CodeRepositorySortBy' => [ 'base' => NULL, 'refs' => [ 'ListCodeRepositoriesInput$SortBy' => 'The field to sort results by. The default is Name.
The sort order for results. The default is Ascending.
Specifies summary information about a Git repository.
', 'refs' => [ 'CodeRepositorySummaryList$member' => NULL, ], ], 'CodeRepositorySummaryList' => [ 'base' => NULL, 'refs' => [ 'ListCodeRepositoriesOutput$CodeRepositorySummaryList' => 'Gets a list of summaries of the Git repositories. Each summary specifies the following values for the repository:
Name
Amazon Resource Name (ARN)
Creation time
Last modified time
Configuration information, including the URL location of the repository and the ARN of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository.
Use this parameter to configure your Amazon Cognito workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.
', 'refs' => [ 'CreateWorkforceRequest$CognitoConfig' => 'Use this parameter to configure an Amazon Cognito private workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.
Do not use OidcConfig if you specify values for CognitoConfig.
The configuration of an Amazon Cognito workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.
', ], ], 'CognitoMemberDefinition' => [ 'base' => 'Identifies a Amazon Cognito user group. A user group can be used in on or more work teams.
', 'refs' => [ 'MemberDefinition$CognitoMemberDefinition' => 'The Amazon Cognito user group that is part of the work team.
', ], ], 'CognitoUserGroup' => [ 'base' => NULL, 'refs' => [ 'CognitoMemberDefinition$UserGroup' => 'An identifier for a user group.
', ], ], 'CognitoUserPool' => [ 'base' => NULL, 'refs' => [ 'CognitoConfig$UserPool' => 'A user pool is a user directory in Amazon Cognito. With a user pool, your users can sign in to your web or mobile app through Amazon Cognito. Your users can also sign in through social identity providers like Google, Facebook, Amazon, or Apple, and through SAML identity providers.
', 'CognitoMemberDefinition$UserPool' => 'An identifier for a user pool. The user pool must be in the same region as the service that you are calling.
', ], ], 'CollectionConfig' => [ 'base' => 'Configuration for your collection.
', 'refs' => [ 'FeatureDefinition$CollectionConfig' => 'Configuration for your collection.
', ], ], 'CollectionConfiguration' => [ 'base' => 'Configuration information for the Amazon SageMaker Debugger output tensor collections.
', 'refs' => [ 'CollectionConfigurations$member' => NULL, ], ], 'CollectionConfigurations' => [ 'base' => NULL, 'refs' => [ 'DebugHookConfig$CollectionConfigurations' => 'Configuration information for Amazon SageMaker Debugger tensor collections. To learn more about how to configure the CollectionConfiguration parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
The name of the tensor collection. The name must be unique relative to other rule configuration names.
', ], ], 'CollectionParameters' => [ 'base' => NULL, 'refs' => [ 'CollectionConfiguration$CollectionParameters' => 'Parameter values for the tensor collection. The allowed parameters are "name", "include_regex", "reduction_config", "save_config", "tensor_names", and "save_histogram".
A grouping of elements where each element within the collection must have the same feature type (String, Integral, or Fractional).
List: An ordered collection of elements.
Set: An unordered collection of unique elements.
Vector: A specialized list that represents a fixed-size array of elements. The vector dimension is determined by you. Must have elements with fractional feature types.
The Amazon Resource Name (ARN) of the model compilation job.
', 'CreateCompilationJobResponse$CompilationJobArn' => 'If the action is successful, the service sends back an HTTP 200 response. Amazon SageMaker returns the following data in JSON format:
CompilationJobArn: The Amazon Resource Name (ARN) of the compiled job.
The Amazon Resource Name (ARN) of the model compilation job.
', ], ], 'CompilationJobStatus' => [ 'base' => NULL, 'refs' => [ 'CompilationJobSummary$CompilationJobStatus' => 'The status of the model compilation job.
', 'DescribeCompilationJobResponse$CompilationJobStatus' => 'The status of the model compilation job.
', 'ListCompilationJobsRequest$StatusEquals' => 'A filter that retrieves model compilation jobs with a specific CompilationJobStatus status.
An array of CompilationJobSummary objects, each describing a model compilation job.
', ], ], 'CompilationJobSummary' => [ 'base' => 'A summary of a model compilation job.
', 'refs' => [ 'CompilationJobSummaries$member' => NULL, ], ], 'CompilerOptions' => [ 'base' => NULL, 'refs' => [ 'OutputConfig$CompilerOptions' => 'Specifies additional parameters for compiler options in JSON format. The compiler options are TargetPlatform specific. It is required for NVIDIA accelerators and highly recommended for CPU compilations. For any other cases, it is optional to specify CompilerOptions.
DTYPE: Specifies the data type for the input. When compiling for ml_* (except for ml_inf) instances using PyTorch framework, provide the data type (dtype) of the model\'s input. "float32" is used if "DTYPE" is not specified. Options for data type are:
float32: Use either "float" or "float32".
int64: Use either "int64" or "long".
For example, {"dtype" : "float32"}.
CPU: Compilation for CPU supports the following compiler options.
mcpu: CPU micro-architecture. For example, {\'mcpu\': \'skylake-avx512\'}
mattr: CPU flags. For example, {\'mattr\': [\'+neon\', \'+vfpv4\']}
ARM: Details of ARM CPU compilations.
NEON: NEON is an implementation of the Advanced SIMD extension used in ARMv7 processors.
For example, add {\'mattr\': [\'+neon\']} to the compiler options if compiling for ARM 32-bit platform with the NEON support.
NVIDIA: Compilation for NVIDIA GPU supports the following compiler options.
gpu_code: Specifies the targeted architecture.
trt-ver: Specifies the TensorRT versions in x.y.z. format.
cuda-ver: Specifies the CUDA version in x.y format.
For example, {\'gpu-code\': \'sm_72\', \'trt-ver\': \'6.0.1\', \'cuda-ver\': \'10.1\'}
ANDROID: Compilation for the Android OS supports the following compiler options:
ANDROID_PLATFORM: Specifies the Android API levels. Available levels range from 21 to 29. For example, {\'ANDROID_PLATFORM\': 28}.
mattr: Add {\'mattr\': [\'+neon\']} to compiler options if compiling for ARM 32-bit platform with NEON support.
INFERENTIA: Compilation for target ml_inf1 uses compiler options passed in as a JSON string. For example, "CompilerOptions": "\\"--verbose 1 --num-neuroncores 2 -O2\\"".
For information about supported compiler options, see Neuron Compiler CLI Reference Guide.
CoreML: Compilation for the CoreML OutputConfig TargetDevice supports the following compiler options:
class_labels: Specifies the classification labels file name inside input tar.gz file. For example, {"class_labels": "imagenet_labels_1000.txt"}. Labels inside the txt file should be separated by newlines.
EIA: Compilation for the Elastic Inference Accelerator supports the following compiler options:
precision_mode: Specifies the precision of compiled artifacts. Supported values are "FP16" and "FP32". Default is "FP32".
signature_def_key: Specifies the signature to use for models in SavedModel format. Defaults is TensorFlow\'s default signature def key.
output_names: Specifies a list of output tensor names for models in FrozenGraph format. Set at most one API field, either: signature_def_key or output_names.
For example: {"precision_mode": "FP32", "output_names": ["output:0"]}
A flag to stop a tuning job once AMT has detected that the job has converged.
', ], ], 'CompressionType' => [ 'base' => NULL, 'refs' => [ 'AdditionalS3DataSource$CompressionType' => 'The type of compression used for an additional data source used in inference or training. Specify None if your additional data source is not compressed.
You can use Gzip or None. The default value is None.
The allowed compression types depend on the input format and problem type. We allow the compression type Gzip for S3Prefix inputs on tabular data only. For all other inputs, the compression type should be None. If no compression type is provided, we default to None.
If training data is compressed, the compression type. The default value is None. CompressionType is used only in Pipe input mode. In File mode, leave this field unset or set it to None.
If your transform data is compressed, specify the compression type. Amazon SageMaker automatically decompresses the data for the transform job accordingly. The default value is None.
The allowed compression types, if data compression is used.
', ], ], 'ConditionOutcome' => [ 'base' => NULL, 'refs' => [ 'ConditionStepMetadata$Outcome' => 'The outcome of the Condition step evaluation.
', ], ], 'ConditionStepMetadata' => [ 'base' => 'Metadata for a Condition step.
', 'refs' => [ 'PipelineExecutionStepMetadata$Condition' => 'The outcome of the condition evaluation that was run by this step execution.
', ], ], 'ConfigKey' => [ 'base' => NULL, 'refs' => [ 'CollectionParameters$key' => NULL, 'HookParameters$key' => NULL, 'ProfilingParameters$key' => NULL, 'RuleParameters$key' => NULL, ], ], 'ConfigValue' => [ 'base' => NULL, 'refs' => [ 'CollectionParameters$value' => NULL, 'HookParameters$value' => NULL, 'ProfilingParameters$value' => NULL, 'RuleParameters$value' => NULL, ], ], 'ConflictException' => [ 'base' => 'There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
The arguments for a container used to run a processing job.
', ], ], 'ContainerDefinition' => [ 'base' => 'Describes the container, as part of model definition.
', 'refs' => [ 'ContainerDefinitionList$member' => NULL, 'CreateModelInput$PrimaryContainer' => 'The location of the primary docker image containing inference code, associated artifacts, and custom environment map that the inference code uses when the model is deployed for predictions.
', 'DescribeModelOutput$PrimaryContainer' => 'The location of the primary inference code, associated artifacts, and custom environment map that the inference code uses when it is deployed in production.
', 'Model$PrimaryContainer' => NULL, ], ], 'ContainerDefinitionList' => [ 'base' => NULL, 'refs' => [ 'CreateModelInput$Containers' => 'Specifies the containers in the inference pipeline.
', 'DescribeModelOutput$Containers' => 'The containers in the inference pipeline.
', 'Model$Containers' => 'The containers in the inference pipeline.
', ], ], 'ContainerEntrypoint' => [ 'base' => NULL, 'refs' => [ 'AppSpecification$ContainerEntrypoint' => 'The entrypoint for a container used to run a processing job.
', 'DataQualityAppSpecification$ContainerEntrypoint' => 'The entrypoint for a container used to run a monitoring job.
', 'ModelQualityAppSpecification$ContainerEntrypoint' => 'Specifies the entrypoint for a container that the monitoring job runs.
', 'MonitoringAppSpecification$ContainerEntrypoint' => 'Specifies the entrypoint for a container used to run the monitoring job.
', ], ], 'ContainerEntrypointString' => [ 'base' => NULL, 'refs' => [ 'ContainerEntrypoint$member' => NULL, ], ], 'ContainerHostname' => [ 'base' => NULL, 'refs' => [ 'ContainerDefinition$ContainerHostname' => 'This parameter is ignored for models that contain only a PrimaryContainer.
When a ContainerDefinition is part of an inference pipeline, the value of the parameter uniquely identifies the container for the purposes of logging and metrics. For information, see Use Logs and Metrics to Monitor an Inference Pipeline. If you don\'t specify a value for this parameter for a ContainerDefinition that is part of an inference pipeline, a unique name is automatically assigned based on the position of the ContainerDefinition in the pipeline. If you specify a value for the ContainerHostName for any ContainerDefinition that is part of an inference pipeline, you must specify a value for the ContainerHostName parameter of every ContainerDefinition in that pipeline.
The DNS host name for the Docker container.
', ], ], 'ContainerImage' => [ 'base' => NULL, 'refs' => [ 'AutoMLContainerDefinition$Image' => 'The Amazon Elastic Container Registry (Amazon ECR) path of the container. For more information, see ContainerDefinition.
', 'ContainerDefinition$Image' => 'The path where inference code is stored. This can be either in Amazon EC2 Container Registry or in a Docker registry that is accessible from the same VPC that you configure for your endpoint. If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference code must meet SageMaker requirements. SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.
The model artifacts in an Amazon S3 bucket and the Docker image for inference container in Amazon EC2 Container Registry must be in the same region as the model or endpoint you are creating.
The image path you specified when you created the model.
', 'DeployedImage$ResolvedImage' => 'The specific digest path of the image hosted in this ProductionVariant.
The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.
If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference code must meet SageMaker requirements. SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.
The Amazon ECR registry path of the Docker image that contains the training algorithm.
', ], ], 'ContainerMode' => [ 'base' => NULL, 'refs' => [ 'ContainerDefinition$Mode' => 'Whether the container hosts a single model or multiple models.
', ], ], 'ContentClassifier' => [ 'base' => NULL, 'refs' => [ 'ContentClassifiers$member' => NULL, ], ], 'ContentClassifiers' => [ 'base' => NULL, 'refs' => [ 'LabelingJobDataAttributes$ContentClassifiers' => 'Declares that your content is free of personally identifiable information or adult content. SageMaker may restrict the Amazon Mechanical Turk workers that can view your task based on this information.
', ], ], 'ContentColumn' => [ 'base' => NULL, 'refs' => [ 'TextClassificationJobConfig$ContentColumn' => 'The name of the column used to provide the sentences to be classified. It should not be the same as the target column.
', ], ], 'ContentDigest' => [ 'base' => NULL, 'refs' => [ 'FileSource$ContentDigest' => 'The digest of the file source.
', 'MetricsSource$ContentDigest' => 'The hash key used for the metrics source.
', ], ], 'ContentType' => [ 'base' => NULL, 'refs' => [ 'AutoMLChannel$ContentType' => 'The content type of the data from the input source. You can use text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
The content type of the data from the input source. The following are the allowed content types for different problems:
For tabular problem types: text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
For image classification: image/png, image/jpeg, or image/*. The default value is image/*.
For text classification: text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
For time-series forecasting: text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
For text generation (LLMs fine-tuning): text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
The MIME type of the data.
', 'ContentTypes$member' => NULL, 'FileSource$ContentType' => 'The type of content stored in the file source.
', 'MetricsSource$ContentType' => 'The metric source content type.
', 'TransformInput$ContentType' => 'The multipurpose internet mail extension (MIME) type of the data. Amazon SageMaker uses the MIME type with each http call to transfer data to the transform job.
', ], ], 'ContentTypes' => [ 'base' => NULL, 'refs' => [ 'AdditionalInferenceSpecificationDefinition$SupportedContentTypes' => 'The supported MIME types for the input data.
', 'ChannelSpecification$SupportedContentTypes' => 'The supported MIME types for the data.
', 'InferenceSpecification$SupportedContentTypes' => 'The supported MIME types for the input data.
', ], ], 'ContextArn' => [ 'base' => NULL, 'refs' => [ 'ContextSummary$ContextArn' => 'The Amazon Resource Name (ARN) of the context.
', 'CreateContextResponse$ContextArn' => 'The Amazon Resource Name (ARN) of the context.
', 'DeleteContextResponse$ContextArn' => 'The Amazon Resource Name (ARN) of the context.
', 'DescribeContextResponse$ContextArn' => 'The Amazon Resource Name (ARN) of the context.
', 'UpdateContextResponse$ContextArn' => 'The Amazon Resource Name (ARN) of the context.
', ], ], 'ContextSource' => [ 'base' => 'A structure describing the source of a context.
', 'refs' => [ 'ContextSummary$Source' => 'The source of the context.
', 'CreateContextRequest$Source' => 'The source type, ID, and URI.
', 'DescribeContextResponse$Source' => 'The source of the context.
', ], ], 'ContextSummaries' => [ 'base' => NULL, 'refs' => [ 'ListContextsResponse$ContextSummaries' => 'A list of contexts and their properties.
', ], ], 'ContextSummary' => [ 'base' => 'Lists a summary of the properties of a context. A context provides a logical grouping of other entities.
', 'refs' => [ 'ContextSummaries$member' => NULL, ], ], 'ContinuousParameterRange' => [ 'base' => 'A list of continuous hyperparameters to tune.
', 'refs' => [ 'ContinuousParameterRanges$member' => NULL, ], ], 'ContinuousParameterRangeSpecification' => [ 'base' => 'Defines the possible values for a continuous hyperparameter.
', 'refs' => [ 'ParameterRange$ContinuousParameterRangeSpecification' => 'A ContinuousParameterRangeSpecification object that defines the possible values for a continuous hyperparameter.
The array of ContinuousParameterRange objects that specify ranges of continuous hyperparameters that a hyperparameter tuning job searches.
', ], ], 'ConvergenceDetected' => [ 'base' => 'A flag to indicating that automatic model tuning (AMT) has detected model convergence, defined as a lack of significant improvement (1% or less) against an objective metric.
', 'refs' => [ 'TuningJobCompletionCriteria$ConvergenceDetected' => 'A flag to top your hyperparameter tuning job if automatic model tuning (AMT) has detected that your model has converged as evaluated against your objective function.
', ], ], 'CountryCode' => [ 'base' => NULL, 'refs' => [ 'HolidayConfigAttributes$CountryCode' => 'The country code for the holiday calendar.
For the list of public holiday calendars supported by AutoML job V2, see Country Codes. Use the country code corresponding to the country of your choice.
', ], ], 'CreateActionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateActionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateAlgorithmInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateAlgorithmOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateAppImageConfigRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateAppImageConfigResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateAppRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateAppResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateArtifactRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateArtifactResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateAutoMLJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateAutoMLJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateAutoMLJobV2Request' => [ 'base' => NULL, 'refs' => [], ], 'CreateAutoMLJobV2Response' => [ 'base' => NULL, 'refs' => [], ], 'CreateCodeRepositoryInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateCodeRepositoryOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateCompilationJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateCompilationJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateContextRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateContextResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateDataQualityJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateDataQualityJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateDeviceFleetRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateDomainRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateDomainResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateEdgeDeploymentPlanRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateEdgeDeploymentPlanResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateEdgeDeploymentStageRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateEdgePackagingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateEndpointConfigInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateEndpointConfigOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateEndpointInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateEndpointOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateFeatureGroupRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateFeatureGroupResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateFlowDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateFlowDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateHubRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateHubResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateHumanTaskUiRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateHumanTaskUiResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateHyperParameterTuningJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateHyperParameterTuningJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateImageRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateImageResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateImageVersionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateImageVersionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateInferenceExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateInferenceExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateInferenceRecommendationsJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateInferenceRecommendationsJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateLabelingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateLabelingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelBiasJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelBiasJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelCardExportJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelCardExportJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelCardRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelCardResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelExplainabilityJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelExplainabilityJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelPackageGroupInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelPackageGroupOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelPackageInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelPackageOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelQualityJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelQualityJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateMonitoringScheduleRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateMonitoringScheduleResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateNotebookInstanceInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateNotebookInstanceLifecycleConfigInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateNotebookInstanceLifecycleConfigOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateNotebookInstanceOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreatePipelineRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreatePipelineResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreatePresignedDomainUrlRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreatePresignedDomainUrlResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreatePresignedNotebookInstanceUrlInput' => [ 'base' => NULL, 'refs' => [], ], 'CreatePresignedNotebookInstanceUrlOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateProcessingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateProcessingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateProjectInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateProjectOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateSpaceRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateSpaceResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateStudioLifecycleConfigRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateStudioLifecycleConfigResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateTrainingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateTrainingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateTransformJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateTransformJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateTrialComponentRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateTrialComponentResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateTrialRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateTrialResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateUserProfileRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateUserProfileResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateWorkforceRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateWorkforceResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateWorkteamRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateWorkteamResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreationTime' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSummary$CreationTime' => 'A timestamp that shows when the algorithm was created.
', 'AppDetails$CreationTime' => 'The creation time.
', 'BatchDescribeModelPackageSummary$CreationTime' => 'The creation time of the mortgage package summary.
', 'CodeRepositorySummary$CreationTime' => 'The date and time that the Git repository was created.
', 'CompilationJobSummary$CreationTime' => 'The time when the model compilation job was created.
', 'DescribeAlgorithmOutput$CreationTime' => 'A timestamp specifying when the algorithm was created.
', 'DescribeAppResponse$CreationTime' => 'The creation time.
', 'DescribeCodeRepositoryOutput$CreationTime' => 'The date and time that the repository was created.
', 'DescribeCompilationJobResponse$CreationTime' => 'The time that the model compilation job was created.
', 'DescribeDomainResponse$CreationTime' => 'The creation time.
', 'DescribeFeatureGroupResponse$CreationTime' => 'A timestamp indicating when SageMaker created the FeatureGroup.
A timestamp indicating when the feature was created.
', 'DescribeInferenceRecommendationsJobResponse$CreationTime' => 'A timestamp that shows when the job was created.
', 'DescribeModelPackageGroupOutput$CreationTime' => 'The time that the model group was created.
', 'DescribeModelPackageOutput$CreationTime' => 'A timestamp specifying when the model package was created.
', 'DescribeNotebookInstanceLifecycleConfigOutput$CreationTime' => 'A timestamp that tells when the lifecycle configuration was created.
', 'DescribeNotebookInstanceOutput$CreationTime' => 'A timestamp. Use this parameter to return the time when the notebook instance was created
', 'DescribeSpaceResponse$CreationTime' => 'The creation time.
', 'DescribeUserProfileResponse$CreationTime' => 'The creation time.
', 'DomainDetails$CreationTime' => 'The creation time.
', 'FeatureGroup$CreationTime' => 'The time a FeatureGroup was created.
A timestamp indicating when the feature was created.
', 'InferenceRecommendationsJob$CreationTime' => 'A timestamp that shows when the job was created.
', 'ListAlgorithmsInput$CreationTimeAfter' => 'A filter that returns only algorithms created after the specified time (timestamp).
', 'ListAlgorithmsInput$CreationTimeBefore' => 'A filter that returns only algorithms created before the specified time (timestamp).
', 'ListCodeRepositoriesInput$CreationTimeAfter' => 'A filter that returns only Git repositories that were created after the specified time.
', 'ListCodeRepositoriesInput$CreationTimeBefore' => 'A filter that returns only Git repositories that were created before the specified time.
', 'ListCompilationJobsRequest$CreationTimeAfter' => 'A filter that returns the model compilation jobs that were created after a specified time.
', 'ListCompilationJobsRequest$CreationTimeBefore' => 'A filter that returns the model compilation jobs that were created before a specified time.
', 'ListFeatureGroupsRequest$CreationTimeAfter' => 'Use this parameter to search for FeatureGroupss created after a specific date and time.
Use this parameter to search for FeatureGroupss created before a specific date and time.
A filter that returns only jobs created after the specified time (timestamp).
', 'ListInferenceRecommendationsJobsRequest$CreationTimeBefore' => 'A filter that returns only jobs created before the specified time (timestamp).
', 'ListModelPackageGroupsInput$CreationTimeAfter' => 'A filter that returns only model groups created after the specified time.
', 'ListModelPackageGroupsInput$CreationTimeBefore' => 'A filter that returns only model groups created before the specified time.
', 'ListModelPackagesInput$CreationTimeAfter' => 'A filter that returns only model packages created after the specified time (timestamp).
', 'ListModelPackagesInput$CreationTimeBefore' => 'A filter that returns only model packages created before the specified time (timestamp).
', 'ListNotebookInstanceLifecycleConfigsInput$CreationTimeBefore' => 'A filter that returns only lifecycle configurations that were created before the specified time (timestamp).
', 'ListNotebookInstanceLifecycleConfigsInput$CreationTimeAfter' => 'A filter that returns only lifecycle configurations that were created after the specified time (timestamp).
', 'ListNotebookInstancesInput$CreationTimeBefore' => 'A filter that returns only notebook instances that were created before the specified time (timestamp).
', 'ListNotebookInstancesInput$CreationTimeAfter' => 'A filter that returns only notebook instances that were created after the specified time (timestamp).
', 'ModelPackage$CreationTime' => 'The time that the model package was created.
', 'ModelPackageGroup$CreationTime' => 'The time that the model group was created.
', 'ModelPackageGroupSummary$CreationTime' => 'The time that the model group was created.
', 'ModelPackageSummary$CreationTime' => 'A timestamp that shows when the model package was created.
', 'NotebookInstanceLifecycleConfigSummary$CreationTime' => 'A timestamp that tells when the lifecycle configuration was created.
', 'NotebookInstanceSummary$CreationTime' => 'A timestamp that shows when the notebook instance was created.
', 'SpaceDetails$CreationTime' => 'The creation time.
', 'UserProfileDetails$CreationTime' => 'The creation time.
', ], ], 'CrossAccountFilterOption' => [ 'base' => NULL, 'refs' => [ 'SearchRequest$CrossAccountFilterOption' => ' A cross account filter option. When the value is "CrossAccount" the search results will only include resources made discoverable to you from other accounts. When the value is "SameAccount" or null the search results will only include resources from your account. Default is null. For more information on searching for resources made discoverable to your account, see Search discoverable resources in the SageMaker Developer Guide. The maximum number of ResourceCatalogs viewable is 1000.
The list of all content type headers that Amazon SageMaker will treat as CSV and capture accordingly.
', ], ], 'CustomImage' => [ 'base' => 'A custom SageMaker image. For more information, see Bring your own SageMaker image.
', 'refs' => [ 'CustomImages$member' => NULL, ], ], 'CustomImages' => [ 'base' => NULL, 'refs' => [ 'KernelGatewayAppSettings$CustomImages' => 'A list of custom SageMaker images that are configured to run as a KernelGateway app.
', 'RSessionAppSettings$CustomImages' => 'A list of custom SageMaker images that are configured to run as a RSession app.
', ], ], 'CustomerMetadataKey' => [ 'base' => NULL, 'refs' => [ 'CustomerMetadataKeyList$member' => NULL, 'CustomerMetadataMap$key' => NULL, ], ], 'CustomerMetadataKeyList' => [ 'base' => NULL, 'refs' => [ 'UpdateModelPackageInput$CustomerMetadataPropertiesToRemove' => 'The metadata properties associated with the model package versions to remove.
', ], ], 'CustomerMetadataMap' => [ 'base' => NULL, 'refs' => [ 'CreateModelPackageInput$CustomerMetadataProperties' => 'The metadata properties associated with the model package versions.
', 'DescribeModelPackageOutput$CustomerMetadataProperties' => 'The metadata properties associated with the model package versions.
', 'ModelPackage$CustomerMetadataProperties' => 'The metadata properties for the model package.
', 'UpdateModelPackageInput$CustomerMetadataProperties' => 'The metadata properties associated with the model package versions.
', ], ], 'CustomerMetadataValue' => [ 'base' => NULL, 'refs' => [ 'CustomerMetadataMap$value' => NULL, ], ], 'CustomizedMetricSpecification' => [ 'base' => 'A customized metric.
', 'refs' => [ 'MetricSpecification$Customized' => 'Information about a customized metric.
', ], ], 'DataCaptureConfig' => [ 'base' => 'Configuration to control how SageMaker captures inference data.
', 'refs' => [ 'CreateEndpointConfigInput$DataCaptureConfig' => NULL, 'DescribeEndpointConfigOutput$DataCaptureConfig' => NULL, ], ], 'DataCaptureConfigSummary' => [ 'base' => 'The currently active data capture configuration used by your Endpoint.
', 'refs' => [ 'DescribeEndpointOutput$DataCaptureConfig' => NULL, 'Endpoint$DataCaptureConfig' => NULL, ], ], 'DataCatalogConfig' => [ 'base' => 'The meta data of the Glue table which serves as data catalog for the OfflineStore.
The meta data of the Glue table that is autogenerated when an OfflineStore is created.
Whether the generated dataset is FullyReplicated or ShardedByS3Key (default).
The URL of the notebook location.
', ], ], 'DataInputConfig' => [ 'base' => NULL, 'refs' => [ 'DerivedInformation$DerivedDataInputConfig' => 'The data input configuration that SageMaker Neo automatically derived for the model. When SageMaker Neo derives this information, you don\'t need to specify the data input configuration when you create a compilation job.
', 'InputConfig$DataInputConfig' => 'Specifies the name and shape of the expected data inputs for your trained model with a JSON dictionary form. The data inputs are Framework specific.
TensorFlow: You must specify the name and shape (NHWC format) of the expected data inputs using a dictionary format for your trained model. The dictionary formats required for the console and CLI are different.
Examples for one input:
If using the console, {"input":[1,1024,1024,3]}
If using the CLI, {\\"input\\":[1,1024,1024,3]}
Examples for two inputs:
If using the console, {"data1": [1,28,28,1], "data2":[1,28,28,1]}
If using the CLI, {\\"data1\\": [1,28,28,1], \\"data2\\":[1,28,28,1]}
KERAS: You must specify the name and shape (NCHW format) of expected data inputs using a dictionary format for your trained model. Note that while Keras model artifacts should be uploaded in NHWC (channel-last) format, DataInputConfig should be specified in NCHW (channel-first) format. The dictionary formats required for the console and CLI are different.
Examples for one input:
If using the console, {"input_1":[1,3,224,224]}
If using the CLI, {\\"input_1\\":[1,3,224,224]}
Examples for two inputs:
If using the console, {"input_1": [1,3,224,224], "input_2":[1,3,224,224]}
If using the CLI, {\\"input_1\\": [1,3,224,224], \\"input_2\\":[1,3,224,224]}
MXNET/ONNX/DARKNET: You must specify the name and shape (NCHW format) of the expected data inputs in order using a dictionary format for your trained model. The dictionary formats required for the console and CLI are different.
Examples for one input:
If using the console, {"data":[1,3,1024,1024]}
If using the CLI, {\\"data\\":[1,3,1024,1024]}
Examples for two inputs:
If using the console, {"var1": [1,1,28,28], "var2":[1,1,28,28]}
If using the CLI, {\\"var1\\": [1,1,28,28], \\"var2\\":[1,1,28,28]}
PyTorch: You can either specify the name and shape (NCHW format) of expected data inputs in order using a dictionary format for your trained model or you can specify the shape only using a list format. The dictionary formats required for the console and CLI are different. The list formats for the console and CLI are the same.
Examples for one input in dictionary format:
If using the console, {"input0":[1,3,224,224]}
If using the CLI, {\\"input0\\":[1,3,224,224]}
Example for one input in list format: [[1,3,224,224]]
Examples for two inputs in dictionary format:
If using the console, {"input0":[1,3,224,224], "input1":[1,3,224,224]}
If using the CLI, {\\"input0\\":[1,3,224,224], \\"input1\\":[1,3,224,224]}
Example for two inputs in list format: [[1,3,224,224], [1,3,224,224]]
XGBOOST: input data name and shape are not needed.
DataInputConfig supports the following parameters for CoreML TargetDevice (ML Model format):
shape: Input shape, for example {"input_1": {"shape": [1,224,224,3]}}. In addition to static input shapes, CoreML converter supports Flexible input shapes:
Range Dimension. You can use the Range Dimension feature if you know the input shape will be within some specific interval in that dimension, for example: {"input_1": {"shape": ["1..10", 224, 224, 3]}}
Enumerated shapes. Sometimes, the models are trained to work only on a select set of inputs. You can enumerate all supported input shapes, for example: {"input_1": {"shape": [[1, 224, 224, 3], [1, 160, 160, 3]]}}
default_shape: Default input shape. You can set a default shape during conversion for both Range Dimension and Enumerated Shapes. For example {"input_1": {"shape": ["1..10", 224, 224, 3], "default_shape": [1, 224, 224, 3]}}
type: Input type. Allowed values: Image and Tensor. By default, the converter generates an ML Model with inputs of type Tensor (MultiArray). User can set input type to be Image. Image input type requires additional input parameters such as bias and scale.
bias: If the input type is an Image, you need to provide the bias vector.
scale: If the input type is an Image, you need to provide a scale factor.
CoreML ClassifierConfig parameters can be specified using OutputConfig CompilerOptions. CoreML converter supports Tensorflow and PyTorch models. CoreML conversion examples:
Tensor type input:
"DataInputConfig": {"input_1": {"shape": [[1,224,224,3], [1,160,160,3]], "default_shape": [1,224,224,3]}}
Tensor type input without input name (PyTorch):
"DataInputConfig": [{"shape": [[1,3,224,224], [1,3,160,160]], "default_shape": [1,3,224,224]}]
Image type input:
"DataInputConfig": {"input_1": {"shape": [[1,224,224,3], [1,160,160,3]], "default_shape": [1,224,224,3], "type": "Image", "bias": [-1,-1,-1], "scale": 0.007843137255}}
"CompilerOptions": {"class_labels": "imagenet_labels_1000.txt"}
Image type input without input name (PyTorch):
"DataInputConfig": [{"shape": [[1,3,224,224], [1,3,160,160]], "default_shape": [1,3,224,224], "type": "Image", "bias": [-1,-1,-1], "scale": 0.007843137255}]
"CompilerOptions": {"class_labels": "imagenet_labels_1000.txt"}
Depending on the model format, DataInputConfig requires the following parameters for ml_eia2 OutputConfig:TargetDevice.
For TensorFlow models saved in the SavedModel format, specify the input names from signature_def_key and the input model shapes for DataInputConfig. Specify the signature_def_key in OutputConfig:CompilerOptions if the model does not use TensorFlow\'s default signature def key. For example:
"DataInputConfig": {"inputs": [1, 224, 224, 3]}
"CompilerOptions": {"signature_def_key": "serving_custom"}
For TensorFlow models saved as a frozen graph, specify the input tensor names and shapes in DataInputConfig and the output tensor names for output_names in OutputConfig:CompilerOptions . For example:
"DataInputConfig": {"input_tensor:0": [1, 224, 224, 3]}
"CompilerOptions": {"output_names": ["output_tensor:0"]}
The input configuration object for the model.
', ], ], 'DataProcessing' => [ 'base' => 'The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see Associate Prediction Results with their Corresponding Input Records.
', 'refs' => [ 'CreateTransformJobRequest$DataProcessing' => 'The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see Associate Prediction Results with their Corresponding Input Records.
', 'DescribeTransformJobResponse$DataProcessing' => NULL, 'TransformJob$DataProcessing' => NULL, ], ], 'DataQualityAppSpecification' => [ 'base' => 'Information about the container that a data quality monitoring job runs.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$DataQualityAppSpecification' => 'Specifies the container that runs the monitoring job.
', 'DescribeDataQualityJobDefinitionResponse$DataQualityAppSpecification' => 'Information about the container that runs the data quality monitoring job.
', ], ], 'DataQualityBaselineConfig' => [ 'base' => 'Configuration for monitoring constraints and monitoring statistics. These baseline resources are compared against the results of the current job from the series of jobs scheduled to collect data periodically.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$DataQualityBaselineConfig' => 'Configures the constraints and baselines for the monitoring job.
', 'DescribeDataQualityJobDefinitionResponse$DataQualityBaselineConfig' => 'The constraints and baselines for the data quality monitoring job definition.
', ], ], 'DataQualityJobInput' => [ 'base' => 'The input for the data quality monitoring job. Currently endpoints are supported for input.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$DataQualityJobInput' => 'A list of inputs for the monitoring job. Currently endpoints are supported as monitoring inputs.
', 'DescribeDataQualityJobDefinitionResponse$DataQualityJobInput' => 'The list of inputs for the data quality monitoring job. Currently endpoints are supported.
', ], ], 'DataSource' => [ 'base' => 'Describes the location of the channel data.
', 'refs' => [ 'Channel$DataSource' => 'The location of the channel data.
', ], ], 'DataSourceName' => [ 'base' => NULL, 'refs' => [ 'IdentityProviderOAuthSetting$DataSourceName' => 'The name of the data source that you\'re connecting to. Canvas currently supports OAuth for Snowflake and Salesforce Data Cloud.
', ], ], 'Database' => [ 'base' => NULL, 'refs' => [ 'DataCatalogConfig$Database' => 'The name of the Glue table database.
', ], ], 'DatasetDefinition' => [ 'base' => 'Configuration for Dataset Definition inputs. The Dataset Definition input must specify exactly one of either AthenaDatasetDefinition or RedshiftDatasetDefinition types.
Configuration for a Dataset Definition input.
', ], ], 'DebugHookConfig' => [ 'base' => 'Configuration information for the Amazon SageMaker Debugger hook parameters, metric and tensor collections, and storage paths. To learn more about how to configure the DebugHookConfig parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Configuration information for SageMaker Debugger rules for debugging. To learn more about how to configure the DebugRuleConfiguration parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.
', 'DescribeTrainingJobResponse$DebugRuleConfigurations' => 'Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.
', 'TrainingJob$DebugRuleConfigurations' => 'Information about the debug rule configuration.
', ], ], 'DebugRuleEvaluationStatus' => [ 'base' => 'Information about the status of the rule evaluation.
', 'refs' => [ 'DebugRuleEvaluationStatuses$member' => NULL, ], ], 'DebugRuleEvaluationStatuses' => [ 'base' => NULL, 'refs' => [ 'DescribeTrainingJobResponse$DebugRuleEvaluationStatuses' => 'Evaluation status of Amazon SageMaker Debugger rules for debugging on a training job.
', 'TrainingJob$DebugRuleEvaluationStatuses' => 'Information about the evaluation status of the rules for the training job.
', ], ], 'DefaultGid' => [ 'base' => NULL, 'refs' => [ 'FileSystemConfig$DefaultGid' => 'The default POSIX group ID (GID). If not specified, defaults to 100.
A collection of settings that apply to spaces created in the Domain.
', 'refs' => [ 'CreateDomainRequest$DefaultSpaceSettings' => 'The default settings used to create a space.
', 'DescribeDomainResponse$DefaultSpaceSettings' => 'The default settings used to create a space.
', 'UpdateDomainRequest$DefaultSpaceSettings' => 'The default settings used to create a space within the Domain.
', ], ], 'DefaultUid' => [ 'base' => NULL, 'refs' => [ 'FileSystemConfig$DefaultUid' => 'The default POSIX user ID (UID). If not specified, defaults to 1000.
The hub content dependency copy path.
', ], ], 'DependencyOriginPath' => [ 'base' => NULL, 'refs' => [ 'HubContentDependency$DependencyOriginPath' => 'The hub content dependency origin path.
', ], ], 'DeployedImage' => [ 'base' => 'Gets the Amazon EC2 Container Registry path of the docker image of the model that is hosted in this ProductionVariant.
If you used the registry/repository[:tag] form to specify the image path of the primary container when you created the model hosted in this ProductionVariant, the path resolves to a path of the form registry/repository[@digest]. A digest is a hash value that identifies a specific version of an image. For information about Amazon ECR paths, see Pulling an Image in the Amazon ECR User Guide.
An array of DeployedImage objects that specify the Amazon EC2 Container Registry paths of the inference images deployed on instances of this ProductionVariant.
An array of DeployedImage objects that specify the Amazon EC2 Container Registry paths of the inference images deployed on instances of this ProductionVariant.
The deployment configuration for an endpoint, which contains the desired deployment strategy and rollback configurations.
', 'refs' => [ 'CreateEndpointInput$DeploymentConfig' => NULL, 'DescribeEndpointOutput$LastDeploymentConfig' => 'The most recent deployment configuration for the endpoint.
', 'UpdateEndpointInput$DeploymentConfig' => 'The deployment configuration for an endpoint, which contains the desired deployment strategy and rollback configurations.
', ], ], 'DeploymentRecommendation' => [ 'base' => 'A set of recommended deployment configurations for the model. To get more advanced recommendations, see CreateInferenceRecommendationsJob to create an inference recommendation job.
', 'refs' => [ 'DescribeModelOutput$DeploymentRecommendation' => 'A set of recommended deployment configurations for the model.
', 'Model$DeploymentRecommendation' => 'A set of recommended deployment configurations for the model.
', ], ], 'DeploymentStage' => [ 'base' => 'Contains information about a stage in an edge deployment plan.
', 'refs' => [ 'DeploymentStages$member' => NULL, ], ], 'DeploymentStageMaxResults' => [ 'base' => NULL, 'refs' => [ 'DescribeEdgeDeploymentPlanRequest$MaxResults' => 'The maximum number of results to select (50 by default).
', ], ], 'DeploymentStageStatusSummaries' => [ 'base' => NULL, 'refs' => [ 'DescribeEdgeDeploymentPlanResponse$Stages' => 'List of stages in the edge deployment plan.
', ], ], 'DeploymentStageStatusSummary' => [ 'base' => 'Contains information summarizing the deployment stage results.
', 'refs' => [ 'DeploymentStageStatusSummaries$member' => NULL, ], ], 'DeploymentStages' => [ 'base' => NULL, 'refs' => [ 'CreateEdgeDeploymentPlanRequest$Stages' => 'List of stages of the edge deployment plan. The number of stages is limited to 10 per deployment.
', 'CreateEdgeDeploymentStageRequest$Stages' => 'List of stages to be added to the edge deployment plan.
', ], ], 'DeregisterDevicesRequest' => [ 'base' => NULL, 'refs' => [], ], 'DerivedInformation' => [ 'base' => 'Information that SageMaker Neo automatically derived about the model.
', 'refs' => [ 'DescribeCompilationJobResponse$DerivedInformation' => 'Information that SageMaker Neo automatically derived about the model.
', ], ], 'DescribeActionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeActionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAlgorithmInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAlgorithmOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAppImageConfigRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAppImageConfigResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAppRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAppResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeArtifactRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeArtifactResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAutoMLJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAutoMLJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAutoMLJobV2Request' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAutoMLJobV2Response' => [ 'base' => NULL, 'refs' => [], ], 'DescribeCodeRepositoryInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeCodeRepositoryOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeCompilationJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeCompilationJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeContextRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeContextResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDataQualityJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDataQualityJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDeviceFleetRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDeviceFleetResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDeviceRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDeviceResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDomainRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDomainResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEdgeDeploymentPlanRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEdgeDeploymentPlanResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEdgePackagingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEdgePackagingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEndpointConfigInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEndpointConfigOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEndpointInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEndpointOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeFeatureGroupRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeFeatureGroupResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeFeatureMetadataRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeFeatureMetadataResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeFlowDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeFlowDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHubContentRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHubContentResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHubRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHubResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHumanTaskUiRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHumanTaskUiResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHyperParameterTuningJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHyperParameterTuningJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeImageRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeImageResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeImageVersionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeImageVersionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeInferenceExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeInferenceExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeInferenceRecommendationsJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeInferenceRecommendationsJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeLabelingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeLabelingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeLineageGroupRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeLineageGroupResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelBiasJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelBiasJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelCardExportJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelCardExportJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelCardRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelCardResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelExplainabilityJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelExplainabilityJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelPackageGroupInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelPackageGroupOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelPackageInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelPackageOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelQualityJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelQualityJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeMonitoringScheduleRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeMonitoringScheduleResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeNotebookInstanceInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeNotebookInstanceLifecycleConfigInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeNotebookInstanceLifecycleConfigOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeNotebookInstanceOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribePipelineDefinitionForExecutionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribePipelineDefinitionForExecutionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribePipelineExecutionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribePipelineExecutionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribePipelineRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribePipelineResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeProcessingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeProcessingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeProjectInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeProjectOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeSpaceRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeSpaceResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeStudioLifecycleConfigRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeStudioLifecycleConfigResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeSubscribedWorkteamRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeSubscribedWorkteamResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTrainingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTrainingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTransformJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTransformJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTrialComponentRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTrialComponentResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTrialRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTrialResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeUserProfileRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeUserProfileResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeWorkforceRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeWorkforceResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeWorkteamRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeWorkteamResponse' => [ 'base' => NULL, 'refs' => [], ], 'Description' => [ 'base' => NULL, 'refs' => [ 'CreateFeatureGroupRequest$Description' => 'A free-form description of a FeatureGroup.
A free form description of the feature group.
', 'FeatureGroup$Description' => 'A free form description of a FeatureGroup.
Specifies weight and capacity values for a production variant.
', 'refs' => [ 'DesiredWeightAndCapacityList$member' => NULL, ], ], 'DesiredWeightAndCapacityList' => [ 'base' => NULL, 'refs' => [ 'UpdateEndpointWeightsAndCapacitiesInput$DesiredWeightsAndCapacities' => 'An object that provides new capacity and weight values for a variant.
', ], ], 'DestinationS3Uri' => [ 'base' => NULL, 'refs' => [ 'AsyncInferenceOutputConfig$S3OutputPath' => 'The Amazon S3 location to upload inference responses to.
', 'AsyncInferenceOutputConfig$S3FailurePath' => 'The Amazon S3 location to upload failure inference responses to.
', 'BatchTransformInput$DataCapturedDestinationS3Uri' => 'The Amazon S3 location being used to capture the data.
', 'DataCaptureConfig$DestinationS3Uri' => 'The Amazon S3 location used to capture the data.
', 'DataCaptureConfigSummary$DestinationS3Uri' => 'The Amazon S3 location being used to capture the data.
', 'InferenceExperimentDataStorageConfig$Destination' => 'The Amazon S3 bucket where the inference request and response data is stored.
', 'ProductionVariantCoreDumpConfig$DestinationS3Uri' => 'The Amazon S3 bucket to send the core dump to.
', ], ], 'DetailedAlgorithmStatus' => [ 'base' => NULL, 'refs' => [ 'AlgorithmStatusItem$Status' => 'The current status.
', ], ], 'DetailedModelPackageStatus' => [ 'base' => NULL, 'refs' => [ 'ModelPackageStatusItem$Status' => 'The current status.
', ], ], 'Device' => [ 'base' => 'Information of a particular device.
', 'refs' => [ 'Devices$member' => NULL, ], ], 'DeviceArn' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceResponse$DeviceArn' => 'The Amazon Resource Name (ARN) of the device.
', 'DeviceDeploymentSummary$DeviceArn' => 'The ARN of the device.
', 'DeviceSummary$DeviceArn' => 'Amazon Resource Name (ARN) of the device.
', ], ], 'DeviceDeploymentStatus' => [ 'base' => NULL, 'refs' => [ 'DeviceDeploymentSummary$DeviceDeploymentStatus' => 'The deployment status of the device.
', ], ], 'DeviceDeploymentSummaries' => [ 'base' => NULL, 'refs' => [ 'ListStageDevicesResponse$DeviceDeploymentSummaries' => 'List of summaries of devices allocated to the stage.
', ], ], 'DeviceDeploymentSummary' => [ 'base' => 'Contains information summarizing device details and deployment status.
', 'refs' => [ 'DeviceDeploymentSummaries$member' => NULL, ], ], 'DeviceDescription' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceResponse$Description' => 'A description of the device.
', 'Device$Description' => 'Description of the device.
', 'DeviceDeploymentSummary$Description' => 'The description of the device.
', 'DeviceSummary$Description' => 'A description of the device.
', ], ], 'DeviceFleetArn' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceFleetResponse$DeviceFleetArn' => 'The The Amazon Resource Name (ARN) of the fleet.
', 'DeviceFleetSummary$DeviceFleetArn' => 'Amazon Resource Name (ARN) of the device fleet.
', 'GetDeviceFleetReportResponse$DeviceFleetArn' => 'The Amazon Resource Name (ARN) of the device.
', ], ], 'DeviceFleetDescription' => [ 'base' => NULL, 'refs' => [ 'CreateDeviceFleetRequest$Description' => 'A description of the fleet.
', 'DescribeDeviceFleetResponse$Description' => 'A description of the fleet.
', 'GetDeviceFleetReportResponse$Description' => 'Description of the fleet.
', 'UpdateDeviceFleetRequest$Description' => 'Description of the fleet.
', ], ], 'DeviceFleetSummaries' => [ 'base' => NULL, 'refs' => [ 'ListDeviceFleetsResponse$DeviceFleetSummaries' => 'Summary of the device fleet.
', ], ], 'DeviceFleetSummary' => [ 'base' => 'Summary of the device fleet.
', 'refs' => [ 'DeviceFleetSummaries$member' => NULL, ], ], 'DeviceName' => [ 'base' => NULL, 'refs' => [ 'Device$DeviceName' => 'The name of the device.
', 'DeviceDeploymentSummary$DeviceName' => 'The name of the device.
', 'DeviceNames$member' => NULL, 'DeviceSelectionConfig$DeviceNameContains' => 'A filter to select devices with names containing this name.
', ], ], 'DeviceNames' => [ 'base' => NULL, 'refs' => [ 'DeregisterDevicesRequest$DeviceNames' => 'The unique IDs of the devices.
', 'DeviceSelectionConfig$DeviceNames' => 'List of devices chosen to deploy.
', ], ], 'DeviceSelectionConfig' => [ 'base' => 'Contains information about the configurations of selected devices.
', 'refs' => [ 'DeploymentStage$DeviceSelectionConfig' => 'Configuration of the devices in the stage.
', 'DeploymentStageStatusSummary$DeviceSelectionConfig' => 'Configuration of the devices in the stage.
', ], ], 'DeviceStats' => [ 'base' => 'Status of devices.
', 'refs' => [ 'GetDeviceFleetReportResponse$DeviceStats' => 'Status of devices.
', ], ], 'DeviceSubsetType' => [ 'base' => NULL, 'refs' => [ 'DeviceSelectionConfig$DeviceSubsetType' => 'Type of device subsets to deploy to the current stage.
', ], ], 'DeviceSummaries' => [ 'base' => NULL, 'refs' => [ 'ListDevicesResponse$DeviceSummaries' => 'Summary of devices.
', ], ], 'DeviceSummary' => [ 'base' => 'Summary of the device.
', 'refs' => [ 'DeviceSummaries$member' => NULL, ], ], 'Devices' => [ 'base' => NULL, 'refs' => [ 'RegisterDevicesRequest$Devices' => 'A list of devices to register with SageMaker Edge Manager.
', 'UpdateDevicesRequest$Devices' => 'List of devices to register with Edge Manager agent.
', ], ], 'Dimension' => [ 'base' => NULL, 'refs' => [ 'VectorConfig$Dimension' => 'The number of elements in your vector.
', ], ], 'DirectDeploySettings' => [ 'base' => 'The model deployment settings for the SageMaker Canvas application.
In order to enable model deployment for Canvas, the SageMaker Domain\'s or user profile\'s Amazon Web Services IAM execution role must have the AmazonSageMakerCanvasDirectDeployAccess policy attached. You can also turn on model deployment permissions through the SageMaker Domain\'s or user profile\'s settings in the SageMaker console.
The model deployment settings for the SageMaker Canvas application.
', ], ], 'DirectInternetAccess' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$DirectInternetAccess' => 'Sets whether SageMaker provides internet access to the notebook instance. If you set this to Disabled this notebook instance is able to access resources only in your VPC, and is not be able to connect to SageMaker training and endpoint services unless you configure a NAT Gateway in your VPC.
For more information, see Notebook Instances Are Internet-Enabled by Default. You can set the value of this parameter to Disabled only if you set a value for the SubnetId parameter.
Describes whether SageMaker provides internet access to the notebook instance. If this value is set to Disabled, the notebook instance does not have internet access, and cannot connect to SageMaker training and endpoint services.
For more information, see Notebook Instances Are Internet-Enabled by Default.
', ], ], 'Direction' => [ 'base' => NULL, 'refs' => [ 'QueryLineageRequest$Direction' => 'Associations between lineage entities have a direction. This parameter determines the direction from the StartArn(s) that the query traverses.
', ], ], 'DirectoryPath' => [ 'base' => NULL, 'refs' => [ 'CheckpointConfig$LocalPath' => '(Optional) The local directory where checkpoints are written. The default directory is /opt/ml/checkpoints/.
Path to local storage location for metrics and tensors. Defaults to /opt/ml/output/tensors/.
Path to local storage location for output of rules. Defaults to /opt/ml/processing/output/rule/.
The full path to the directory to associate with the channel.
', 'ProfilerRuleConfiguration$LocalPath' => 'Path to local storage location for output of rules. Defaults to /opt/ml/processing/output/rule/.
Path to local storage location for tensorBoard output. Defaults to /opt/ml/output/tensorboard.
Configuration to turn off Amazon SageMaker Debugger\'s system monitoring and profiling functionality. To turn it off, set to True.
To turn off Amazon SageMaker Debugger monitoring and profiling while a training job is in progress, set to True.
A list of names or URLs of the default Git repositories to remove from this notebook instance. This operation is idempotent. If you specify a Git repository that is not associated with the notebook instance when you call this method, it does not throw an error.
', ], ], 'DisassociateDefaultCodeRepository' => [ 'base' => NULL, 'refs' => [ 'UpdateNotebookInstanceInput$DisassociateDefaultCodeRepository' => 'The name or URL of the default Git repository to remove from this notebook instance. This operation is idempotent. If you specify a Git repository that is not associated with the notebook instance when you call this method, it does not throw an error.
', ], ], 'DisassociateNotebookInstanceAcceleratorTypes' => [ 'base' => NULL, 'refs' => [ 'UpdateNotebookInstanceInput$DisassociateAcceleratorTypes' => 'A list of the Elastic Inference (EI) instance types to remove from this notebook instance. This operation is idempotent. If you specify an accelerator type that is not associated with the notebook instance when you call this method, it does not throw an error.
', ], ], 'DisassociateNotebookInstanceLifecycleConfig' => [ 'base' => NULL, 'refs' => [ 'UpdateNotebookInstanceInput$DisassociateLifecycleConfig' => 'Set to true to remove the notebook instance lifecycle configuration currently associated with the notebook instance. This operation is idempotent. If you specify a lifecycle configuration that is not associated with the notebook instance when you call this method, it does not throw an error.
The document schema version for the hub content.
', 'HubContentInfo$DocumentSchemaVersion' => 'The version of the hub content document schema.
', 'ImportHubContentRequest$DocumentSchemaVersion' => 'The version of the hub content schema to import.
', 'ListHubContentVersionsRequest$MaxSchemaVersion' => 'The upper bound of the hub content schema version.
', 'ListHubContentsRequest$MaxSchemaVersion' => 'The upper bound of the hub content schema verion.
', ], ], 'Dollars' => [ 'base' => NULL, 'refs' => [ 'USD$Dollars' => 'The whole number of dollars in the amount.
', ], ], 'DomainArn' => [ 'base' => NULL, 'refs' => [ 'CreateDomainResponse$DomainArn' => 'The Amazon Resource Name (ARN) of the created domain.
', 'DescribeDomainResponse$DomainArn' => 'The domain\'s Amazon Resource Name (ARN).
', 'DomainDetails$DomainArn' => 'The domain\'s Amazon Resource Name (ARN).
', 'UpdateDomainResponse$DomainArn' => 'The Amazon Resource Name (ARN) of the domain.
', ], ], 'DomainDetails' => [ 'base' => 'The domain\'s details.
', 'refs' => [ 'DomainList$member' => NULL, ], ], 'DomainId' => [ 'base' => NULL, 'refs' => [ 'AppDetails$DomainId' => 'The domain ID.
', 'CreateAppRequest$DomainId' => 'The domain ID.
', 'CreatePresignedDomainUrlRequest$DomainId' => 'The domain ID.
', 'CreateSpaceRequest$DomainId' => 'The ID of the associated Domain.
', 'CreateUserProfileRequest$DomainId' => 'The ID of the associated Domain.
', 'DeleteAppRequest$DomainId' => 'The domain ID.
', 'DeleteDomainRequest$DomainId' => 'The domain ID.
', 'DeleteSpaceRequest$DomainId' => 'The ID of the associated Domain.
', 'DeleteUserProfileRequest$DomainId' => 'The domain ID.
', 'DescribeAppRequest$DomainId' => 'The domain ID.
', 'DescribeAppResponse$DomainId' => 'The domain ID.
', 'DescribeDomainRequest$DomainId' => 'The domain ID.
', 'DescribeDomainResponse$DomainId' => 'The domain ID.
', 'DescribeSpaceRequest$DomainId' => 'The ID of the associated Domain.
', 'DescribeSpaceResponse$DomainId' => 'The ID of the associated Domain.
', 'DescribeUserProfileRequest$DomainId' => 'The domain ID.
', 'DescribeUserProfileResponse$DomainId' => 'The ID of the domain that contains the profile.
', 'DomainDetails$DomainId' => 'The domain ID.
', 'ListAppsRequest$DomainIdEquals' => 'A parameter to search for the domain ID.
', 'ListSpacesRequest$DomainIdEquals' => 'A parameter to search for the Domain ID.
', 'ListUserProfilesRequest$DomainIdEquals' => 'A parameter by which to filter the results.
', 'SpaceDetails$DomainId' => 'The ID of the associated Domain.
', 'UpdateDomainRequest$DomainId' => 'The ID of the domain to be updated.
', 'UpdateSpaceRequest$DomainId' => 'The ID of the associated Domain.
', 'UpdateUserProfileRequest$DomainId' => 'The domain ID.
', 'UserProfileDetails$DomainId' => 'The domain ID.
', ], ], 'DomainList' => [ 'base' => NULL, 'refs' => [ 'ListDomainsResponse$Domains' => 'The list of domains.
', ], ], 'DomainName' => [ 'base' => NULL, 'refs' => [ 'CreateDomainRequest$DomainName' => 'A name for the domain.
', 'DescribeDomainResponse$DomainName' => 'The domain name.
', 'DomainDetails$DomainName' => 'The domain name.
', ], ], 'DomainSecurityGroupIds' => [ 'base' => NULL, 'refs' => [ 'DomainSettings$SecurityGroupIds' => 'The security groups for the Amazon Virtual Private Cloud that the Domain uses for communication between Domain-level apps and user apps.
The security groups for the Amazon Virtual Private Cloud that the Domain uses for communication between Domain-level apps and user apps.
A collection of settings that apply to the SageMaker Domain. These settings are specified through the CreateDomain API call.
A collection of Domain settings.
A collection of Domain settings.
A collection of Domain configuration settings to update.
A collection of DomainSettings configuration values to update.
The status.
', 'DomainDetails$Status' => 'The status.
', ], ], 'Double' => [ 'base' => NULL, 'refs' => [ 'TargetTrackingScalingPolicyConfiguration$TargetValue' => 'The recommended target value to specify for the metric when creating a scaling policy.
', ], ], 'DoubleParameterValue' => [ 'base' => NULL, 'refs' => [ 'TrialComponentParameterValue$NumberValue' => 'The numeric value of a numeric hyperparameter. If you specify a value for this parameter, you can\'t specify the StringValue parameter.
Represents the drift check baselines that can be used when the model monitor is set using the model package.
', 'refs' => [ 'CreateModelPackageInput$DriftCheckBaselines' => 'Represents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on Drift Detection against Previous Baselines in SageMaker Pipelines in the Amazon SageMaker Developer Guide.
', 'DescribeModelPackageOutput$DriftCheckBaselines' => 'Represents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on Drift Detection against Previous Baselines in SageMaker Pipelines in the Amazon SageMaker Developer Guide.
', 'ModelPackage$DriftCheckBaselines' => 'Represents the drift check baselines that can be used when the model monitor is set using the model package.
', ], ], 'DriftCheckBias' => [ 'base' => 'Represents the drift check bias baselines that can be used when the model monitor is set using the model package.
', 'refs' => [ 'DriftCheckBaselines$Bias' => 'Represents the drift check bias baselines that can be used when the model monitor is set using the model package.
', ], ], 'DriftCheckExplainability' => [ 'base' => 'Represents the drift check explainability baselines that can be used when the model monitor is set using the model package.
', 'refs' => [ 'DriftCheckBaselines$Explainability' => 'Represents the drift check explainability baselines that can be used when the model monitor is set using the model package.
', ], ], 'DriftCheckModelDataQuality' => [ 'base' => 'Represents the drift check data quality baselines that can be used when the model monitor is set using the model package.
', 'refs' => [ 'DriftCheckBaselines$ModelDataQuality' => 'Represents the drift check model data quality baselines that can be used when the model monitor is set using the model package.
', ], ], 'DriftCheckModelQuality' => [ 'base' => 'Represents the drift check model quality baselines that can be used when the model monitor is set using the model package.
', 'refs' => [ 'DriftCheckBaselines$ModelQuality' => 'Represents the drift check model quality baselines that can be used when the model monitor is set using the model package.
', ], ], 'DynamicScalingConfiguration' => [ 'base' => 'An object with the recommended values for you to specify when creating an autoscaling policy.
', 'refs' => [ 'GetScalingConfigurationRecommendationResponse$DynamicScalingConfiguration' => 'An object with the recommended values for you to specify when creating an autoscaling policy.
', ], ], 'EMRStepMetadata' => [ 'base' => 'The configurations and outcomes of an Amazon EMR step execution.
', 'refs' => [ 'PipelineExecutionStepMetadata$EMR' => 'The configurations and outcomes of an Amazon EMR step execution.
', ], ], 'Edge' => [ 'base' => 'A directed edge connecting two lineage entities.
', 'refs' => [ 'Edges$member' => NULL, ], ], 'EdgeDeploymentConfig' => [ 'base' => 'Contains information about the configuration of a deployment.
', 'refs' => [ 'DeploymentStage$DeploymentConfig' => 'Configuration of the deployment details.
', 'DeploymentStageStatusSummary$DeploymentConfig' => 'Configuration of the deployment details.
', ], ], 'EdgeDeploymentModelConfig' => [ 'base' => 'Contains information about the configuration of a model in a deployment.
', 'refs' => [ 'EdgeDeploymentModelConfigs$member' => NULL, ], ], 'EdgeDeploymentModelConfigs' => [ 'base' => NULL, 'refs' => [ 'CreateEdgeDeploymentPlanRequest$ModelConfigs' => 'List of models associated with the edge deployment plan.
', 'DescribeEdgeDeploymentPlanResponse$ModelConfigs' => 'List of models associated with the edge deployment plan.
', ], ], 'EdgeDeploymentPlanArn' => [ 'base' => NULL, 'refs' => [ 'CreateEdgeDeploymentPlanResponse$EdgeDeploymentPlanArn' => 'The ARN of the edge deployment plan.
', 'DescribeEdgeDeploymentPlanResponse$EdgeDeploymentPlanArn' => 'The ARN of edge deployment plan.
', 'DeviceDeploymentSummary$EdgeDeploymentPlanArn' => 'The ARN of the edge deployment plan.
', 'EdgeDeploymentPlanSummary$EdgeDeploymentPlanArn' => 'The ARN of the edge deployment plan.
', ], ], 'EdgeDeploymentPlanSummaries' => [ 'base' => NULL, 'refs' => [ 'ListEdgeDeploymentPlansResponse$EdgeDeploymentPlanSummaries' => 'List of summaries of edge deployment plans.
', ], ], 'EdgeDeploymentPlanSummary' => [ 'base' => 'Contains information summarizing an edge deployment plan.
', 'refs' => [ 'EdgeDeploymentPlanSummaries$member' => NULL, ], ], 'EdgeDeploymentStatus' => [ 'base' => 'Contains information summarizing the deployment stage results.
', 'refs' => [ 'DeploymentStageStatusSummary$DeploymentStatus' => 'General status of the current state.
', ], ], 'EdgeModel' => [ 'base' => 'The model on the edge device.
', 'refs' => [ 'EdgeModels$member' => NULL, ], ], 'EdgeModelStat' => [ 'base' => 'Status of edge devices with this model.
', 'refs' => [ 'EdgeModelStats$member' => NULL, ], ], 'EdgeModelStats' => [ 'base' => NULL, 'refs' => [ 'GetDeviceFleetReportResponse$ModelStats' => 'Status of model on device.
', ], ], 'EdgeModelSummaries' => [ 'base' => NULL, 'refs' => [ 'DeviceSummary$Models' => 'Models on the device.
', ], ], 'EdgeModelSummary' => [ 'base' => 'Summary of model on edge device.
', 'refs' => [ 'EdgeModelSummaries$member' => NULL, ], ], 'EdgeModels' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceResponse$Models' => 'Models on the device.
', ], ], 'EdgeOutputConfig' => [ 'base' => 'The output configuration.
', 'refs' => [ 'CreateDeviceFleetRequest$OutputConfig' => 'The output configuration for storing sample data collected by the fleet.
', 'CreateEdgePackagingJobRequest$OutputConfig' => 'Provides information about the output location for the packaged model.
', 'DescribeDeviceFleetResponse$OutputConfig' => 'The output configuration for storing sampled data.
', 'DescribeEdgePackagingJobResponse$OutputConfig' => 'The output configuration for the edge packaging job.
', 'GetDeviceFleetReportResponse$OutputConfig' => 'The output configuration for storing sample data collected by the fleet.
', 'UpdateDeviceFleetRequest$OutputConfig' => 'Output configuration for storing sample data collected by the fleet.
', ], ], 'EdgePackagingJobArn' => [ 'base' => NULL, 'refs' => [ 'DescribeEdgePackagingJobResponse$EdgePackagingJobArn' => 'The Amazon Resource Name (ARN) of the edge packaging job.
', 'EdgePackagingJobSummary$EdgePackagingJobArn' => 'The Amazon Resource Name (ARN) of the edge packaging job.
', ], ], 'EdgePackagingJobStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeEdgePackagingJobResponse$EdgePackagingJobStatus' => 'The current status of the packaging job.
', 'EdgePackagingJobSummary$EdgePackagingJobStatus' => 'The status of the edge packaging job.
', 'ListEdgePackagingJobsRequest$StatusEquals' => 'The job status to filter for.
', ], ], 'EdgePackagingJobSummaries' => [ 'base' => NULL, 'refs' => [ 'ListEdgePackagingJobsResponse$EdgePackagingJobSummaries' => 'Summaries of edge packaging jobs.
', ], ], 'EdgePackagingJobSummary' => [ 'base' => 'Summary of edge packaging job.
', 'refs' => [ 'EdgePackagingJobSummaries$member' => NULL, ], ], 'EdgePresetDeploymentArtifact' => [ 'base' => NULL, 'refs' => [ 'EdgePresetDeploymentOutput$Artifact' => 'The Amazon Resource Name (ARN) of the generated deployable resource.
', ], ], 'EdgePresetDeploymentOutput' => [ 'base' => 'The output of a SageMaker Edge Manager deployable resource.
', 'refs' => [ 'DescribeEdgePackagingJobResponse$PresetDeploymentOutput' => 'The output of a SageMaker Edge Manager deployable resource.
', ], ], 'EdgePresetDeploymentStatus' => [ 'base' => NULL, 'refs' => [ 'EdgePresetDeploymentOutput$Status' => 'The status of the deployable resource.
', ], ], 'EdgePresetDeploymentType' => [ 'base' => NULL, 'refs' => [ 'EdgeOutputConfig$PresetDeploymentType' => 'The deployment type SageMaker Edge Manager will create. Currently only supports Amazon Web Services IoT Greengrass Version 2 components.
', 'EdgePresetDeploymentOutput$Type' => 'The deployment type created by SageMaker Edge Manager. Currently only supports Amazon Web Services IoT Greengrass Version 2 components.
', ], ], 'EdgeVersion' => [ 'base' => NULL, 'refs' => [ 'AgentVersion$Version' => 'Version of the agent.
', 'CreateEdgePackagingJobRequest$ModelVersion' => 'The version of the model.
', 'DescribeDeviceResponse$AgentVersion' => 'Edge Manager agent version.
', 'DescribeEdgePackagingJobResponse$ModelVersion' => 'The version of the model.
', 'DeviceSummary$AgentVersion' => 'Edge Manager agent version.
', 'EdgeModel$ModelVersion' => 'The model version.
', 'EdgeModelStat$ModelVersion' => 'The model version.
', 'EdgeModelSummary$ModelVersion' => 'The version model.
', 'EdgePackagingJobSummary$ModelVersion' => 'The version of the model.
', ], ], 'Edges' => [ 'base' => NULL, 'refs' => [ 'QueryLineageResponse$Edges' => 'A list of edges that connect vertices in the response.
', ], ], 'EfsUid' => [ 'base' => NULL, 'refs' => [ 'DescribeSpaceResponse$HomeEfsFileSystemUid' => 'The ID of the space\'s profile in the Amazon Elastic File System volume.
', 'DescribeUserProfileResponse$HomeEfsFileSystemUid' => 'The ID of the user\'s profile in the Amazon Elastic File System (EFS) volume.
', ], ], 'EnableCapture' => [ 'base' => NULL, 'refs' => [ 'DataCaptureConfig$EnableCapture' => 'Whether data capture should be enabled or disabled (defaults to enabled).
', 'DataCaptureConfigSummary$EnableCapture' => 'Whether data capture is enabled or disabled.
', ], ], 'EnableIotRoleAlias' => [ 'base' => NULL, 'refs' => [ 'CreateDeviceFleetRequest$EnableIotRoleAlias' => 'Whether to create an Amazon Web Services IoT Role Alias during device fleet creation. The name of the role alias generated will match this pattern: "SageMakerEdge-{DeviceFleetName}".
For example, if your device fleet is called "demo-fleet", the name of the role alias will be "SageMakerEdge-demo-fleet".
', 'UpdateDeviceFleetRequest$EnableIotRoleAlias' => 'Whether to create an Amazon Web Services IoT Role Alias during device fleet creation. The name of the role alias generated will match this pattern: "SageMakerEdge-{DeviceFleetName}".
For example, if your device fleet is called "demo-fleet", the name of the role alias will be "SageMakerEdge-demo-fleet".
', ], ], 'EnableSagemakerServicecatalogPortfolioInput' => [ 'base' => NULL, 'refs' => [], ], 'EnableSagemakerServicecatalogPortfolioOutput' => [ 'base' => NULL, 'refs' => [], ], 'Endpoint' => [ 'base' => 'A hosted endpoint for real-time inference.
', 'refs' => [ 'SearchRecord$Endpoint' => NULL, ], ], 'EndpointArn' => [ 'base' => NULL, 'refs' => [ 'CreateEndpointOutput$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint.
', 'DescribeEndpointOutput$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint.
', 'Endpoint$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint.
', 'EndpointSummary$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint.
', 'ModelDashboardEndpoint$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint.
', 'UpdateEndpointOutput$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint.
', 'UpdateEndpointWeightsAndCapacitiesOutput$EndpointArn' => 'The Amazon Resource Name (ARN) of the updated endpoint.
', ], ], 'EndpointConfigArn' => [ 'base' => NULL, 'refs' => [ 'CreateEndpointConfigOutput$EndpointConfigArn' => 'The Amazon Resource Name (ARN) of the endpoint configuration.
', 'DescribeEndpointConfigOutput$EndpointConfigArn' => 'The Amazon Resource Name (ARN) of the endpoint configuration.
', 'EndpointConfigSummary$EndpointConfigArn' => 'The Amazon Resource Name (ARN) of the endpoint configuration.
', ], ], 'EndpointConfigName' => [ 'base' => NULL, 'refs' => [ 'CreateEndpointConfigInput$EndpointConfigName' => 'The name of the endpoint configuration. You specify this name in a CreateEndpoint request.
', 'CreateEndpointInput$EndpointConfigName' => 'The name of an endpoint configuration. For more information, see CreateEndpointConfig.
', 'DeleteEndpointConfigInput$EndpointConfigName' => 'The name of the endpoint configuration that you want to delete.
', 'DescribeEndpointConfigInput$EndpointConfigName' => 'The name of the endpoint configuration.
', 'DescribeEndpointConfigOutput$EndpointConfigName' => 'Name of the SageMaker endpoint configuration.
', 'DescribeEndpointOutput$EndpointConfigName' => 'The name of the endpoint configuration associated with this endpoint.
', 'Endpoint$EndpointConfigName' => 'The endpoint configuration associated with the endpoint.
', 'EndpointConfigSummary$EndpointConfigName' => 'The name of the endpoint configuration.
', 'EndpointMetadata$EndpointConfigName' => 'The name of the endpoint configuration.
', 'PendingDeploymentSummary$EndpointConfigName' => 'The name of the endpoint configuration used in the deployment.
', 'UpdateEndpointInput$EndpointConfigName' => 'The name of the new endpoint configuration.
', ], ], 'EndpointConfigNameContains' => [ 'base' => NULL, 'refs' => [ 'ListEndpointConfigsInput$NameContains' => 'A string in the endpoint configuration name. This filter returns only endpoint configurations whose name contains the specified string.
', ], ], 'EndpointConfigSortKey' => [ 'base' => NULL, 'refs' => [ 'ListEndpointConfigsInput$SortBy' => 'The field to sort results by. The default is CreationTime.
Provides summary information for an endpoint configuration.
', 'refs' => [ 'EndpointConfigSummaryList$member' => NULL, ], ], 'EndpointConfigSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListEndpointConfigsOutput$EndpointConfigs' => 'An array of endpoint configurations.
', ], ], 'EndpointInfo' => [ 'base' => 'Details about a customer endpoint that was compared in an Inference Recommender job.
', 'refs' => [ 'EndpointPerformance$EndpointInfo' => NULL, 'Endpoints$member' => NULL, ], ], 'EndpointInput' => [ 'base' => 'Input object for the endpoint
', 'refs' => [ 'DataQualityJobInput$EndpointInput' => NULL, 'ModelBiasJobInput$EndpointInput' => NULL, 'ModelExplainabilityJobInput$EndpointInput' => NULL, 'ModelQualityJobInput$EndpointInput' => NULL, 'MonitoringInput$EndpointInput' => 'The endpoint for a monitoring job.
', ], ], 'EndpointInputConfiguration' => [ 'base' => 'The endpoint configuration for the load test.
', 'refs' => [ 'EndpointInputConfigurations$member' => NULL, ], ], 'EndpointInputConfigurations' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobInputConfig$EndpointConfigurations' => 'Specifies the endpoint configuration to use for a job.
', ], ], 'EndpointMetadata' => [ 'base' => 'The metadata of the endpoint.
', 'refs' => [ 'DescribeInferenceExperimentResponse$EndpointMetadata' => 'The metadata of the endpoint on which the inference experiment ran.
', ], ], 'EndpointName' => [ 'base' => NULL, 'refs' => [ 'CreateEndpointInput$EndpointName' => 'The name of the endpoint.The name must be unique within an Amazon Web Services Region in your Amazon Web Services account. The name is case-insensitive in CreateEndpoint, but the case is preserved and must be matched in InvokeEndpoint.
The name of the Amazon SageMaker endpoint on which you want to run the inference experiment.
', 'DeleteEndpointInput$EndpointName' => 'The name of the endpoint that you want to delete.
', 'DescribeEndpointInput$EndpointName' => 'The name of the endpoint.
', 'DescribeEndpointOutput$EndpointName' => 'Name of the endpoint.
', 'DescribeMonitoringScheduleResponse$EndpointName' => 'The name of the endpoint for the monitoring job.
', 'Endpoint$EndpointName' => 'The name of the endpoint.
', 'EndpointInfo$EndpointName' => 'The name of a customer\'s endpoint.
', 'EndpointInput$EndpointName' => 'An endpoint in customer\'s account which has enabled DataCaptureConfig enabled.
The name of the endpoint.
', 'EndpointSummary$EndpointName' => 'The name of the endpoint.
', 'GetScalingConfigurationRecommendationRequest$EndpointName' => 'The name of an endpoint benchmarked during a previously completed inference recommendation job. This name should come from one of the recommendations returned by the job specified in the InferenceRecommendationsJobName field.
Specify either this field or the RecommendationId field.
The name of an endpoint benchmarked during a previously completed Inference Recommender job.
', 'ListDataQualityJobDefinitionsRequest$EndpointName' => 'A filter that lists the data quality job definitions associated with the specified endpoint.
', 'ListModelBiasJobDefinitionsRequest$EndpointName' => 'Name of the endpoint to monitor for model bias.
', 'ListModelExplainabilityJobDefinitionsRequest$EndpointName' => 'Name of the endpoint to monitor for model explainability.
', 'ListModelQualityJobDefinitionsRequest$EndpointName' => 'A filter that returns only model quality monitoring job definitions that are associated with the specified endpoint.
', 'ListMonitoringExecutionsRequest$EndpointName' => 'Name of a specific endpoint to fetch jobs for.
', 'ListMonitoringSchedulesRequest$EndpointName' => 'Name of a specific endpoint to fetch schedules for.
', 'ModelDashboardEndpoint$EndpointName' => 'The endpoint name.
', 'ModelDashboardMonitoringSchedule$EndpointName' => 'The endpoint which is monitored.
', 'ModelDeployConfig$EndpointName' => 'Specifies the endpoint name to use for a one-click Autopilot model deployment if the endpoint name is not generated automatically.
Specify the EndpointName if and only if you set AutoGenerateEndpointName to False; otherwise a 400 error is thrown.
The name of the endpoint to which the model has been deployed.
If model deployment fails, this field is omitted from the response.
The name of the endpoint used to run the monitoring job.
', 'MonitoringJobDefinitionSummary$EndpointName' => 'The name of the endpoint that the job monitors.
', 'MonitoringSchedule$EndpointName' => 'The endpoint that hosts the model being monitored.
', 'MonitoringScheduleSummary$EndpointName' => 'The name of the endpoint using the monitoring schedule.
', 'UpdateEndpointInput$EndpointName' => 'The name of the endpoint whose configuration you want to update.
', 'UpdateEndpointWeightsAndCapacitiesInput$EndpointName' => 'The name of an existing SageMaker endpoint.
', ], ], 'EndpointNameContains' => [ 'base' => NULL, 'refs' => [ 'ListEndpointsInput$NameContains' => 'A string in endpoint names. This filter returns only endpoints whose name contains the specified string.
', ], ], 'EndpointOutputConfiguration' => [ 'base' => 'The endpoint configuration made by Inference Recommender during a recommendation job.
', 'refs' => [ 'InferenceRecommendation$EndpointConfiguration' => 'Defines the endpoint configuration parameters.
', 'RecommendationJobInferenceBenchmark$EndpointConfiguration' => NULL, ], ], 'EndpointPerformance' => [ 'base' => 'The performance results from running an Inference Recommender job on an existing endpoint.
', 'refs' => [ 'EndpointPerformances$member' => NULL, ], ], 'EndpointPerformances' => [ 'base' => NULL, 'refs' => [ 'DescribeInferenceRecommendationsJobResponse$EndpointPerformances' => 'The performance results from running an Inference Recommender job on an existing endpoint.
', ], ], 'EndpointSortKey' => [ 'base' => NULL, 'refs' => [ 'ListEndpointsInput$SortBy' => 'Sorts the list of results. The default is CreationTime.
The status of the endpoint.
OutOfService: Endpoint is not available to take incoming requests.
Creating: CreateEndpoint is executing.
Updating: UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing.
SystemUpdating: Endpoint is undergoing maintenance and cannot be updated or deleted or re-scaled until it has completed. This maintenance operation does not change any customer-specified values such as VPC config, KMS encryption, model, instance type, or instance count.
RollingBack: Endpoint fails to scale up or down or change its variant weight and is in the process of rolling back to its previous configuration. Once the rollback completes, endpoint returns to an InService status. This transitional status only applies to an endpoint that has autoscaling enabled and is undergoing variant weight or capacity changes as part of an UpdateEndpointWeightsAndCapacities call or when the UpdateEndpointWeightsAndCapacities operation is called explicitly.
InService: Endpoint is available to process incoming requests.
Deleting: DeleteEndpoint is executing.
Failed: Endpoint could not be created, updated, or re-scaled. Use the FailureReason value returned by DescribeEndpoint for information about the failure. DeleteEndpoint is the only operation that can be performed on a failed endpoint.
UpdateRollbackFailed: Both the rolling deployment and auto-rollback failed. Your endpoint is in service with a mix of the old and new endpoint configurations. For information about how to remedy this issue and restore the endpoint\'s status to InService, see Rolling Deployments.
The status of the endpoint.
', 'EndpointMetadata$EndpointStatus' => 'The status of the endpoint. For possible values of the status of an endpoint, see EndpointSummary.
', 'EndpointSummary$EndpointStatus' => 'The status of the endpoint.
OutOfService: Endpoint is not available to take incoming requests.
Creating: CreateEndpoint is executing.
Updating: UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing.
SystemUpdating: Endpoint is undergoing maintenance and cannot be updated or deleted or re-scaled until it has completed. This maintenance operation does not change any customer-specified values such as VPC config, KMS encryption, model, instance type, or instance count.
RollingBack: Endpoint fails to scale up or down or change its variant weight and is in the process of rolling back to its previous configuration. Once the rollback completes, endpoint returns to an InService status. This transitional status only applies to an endpoint that has autoscaling enabled and is undergoing variant weight or capacity changes as part of an UpdateEndpointWeightsAndCapacities call or when the UpdateEndpointWeightsAndCapacities operation is called explicitly.
InService: Endpoint is available to process incoming requests.
Deleting: DeleteEndpoint is executing.
Failed: Endpoint could not be created, updated, or re-scaled. Use DescribeEndpointOutput$FailureReason for information about the failure. DeleteEndpoint is the only operation that can be performed on a failed endpoint.
To get a list of endpoints with a specified status, use the StatusEquals filter with a call to ListEndpoints.
A filter that returns only endpoints with the specified status.
', 'ModelDashboardEndpoint$EndpointStatus' => 'The endpoint status.
', ], ], 'EndpointSummary' => [ 'base' => 'Provides summary information for an endpoint.
', 'refs' => [ 'EndpointSummaryList$member' => NULL, ], ], 'EndpointSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListEndpointsOutput$Endpoints' => 'An array or endpoint objects.
', ], ], 'Endpoints' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobInputConfig$Endpoints' => 'Existing customer endpoints on which to run an Inference Recommender job.
', ], ], 'EntityDescription' => [ 'base' => NULL, 'refs' => [ 'AdditionalInferenceSpecificationDefinition$Description' => 'A description of the additional Inference specification
', 'AlgorithmSummary$AlgorithmDescription' => 'A brief description of the algorithm.
', 'BatchDescribeModelPackageSummary$ModelPackageDescription' => 'The description of the model package.
', 'ChannelSpecification$Description' => 'A brief description of the channel.
', 'CreateAlgorithmInput$AlgorithmDescription' => 'A description of the algorithm.
', 'CreateModelPackageGroupInput$ModelPackageGroupDescription' => 'A description for the model group.
', 'CreateModelPackageInput$ModelPackageDescription' => 'A description of the model package.
', 'CreateProjectInput$ProjectDescription' => 'A description for the project.
', 'DescribeAlgorithmOutput$AlgorithmDescription' => 'A brief summary about the algorithm.
', 'DescribeModelPackageGroupOutput$ModelPackageGroupDescription' => 'A description of the model group.
', 'DescribeModelPackageOutput$ModelPackageDescription' => 'A brief summary of the model package.
', 'DescribeProjectOutput$ProjectDescription' => 'The description of the project.
', 'HyperParameterSpecification$Description' => 'A brief description of the hyperparameter.
', 'ModelPackage$ModelPackageDescription' => 'The description of the model package.
', 'ModelPackageGroup$ModelPackageGroupDescription' => 'The description for the model group.
', 'ModelPackageGroupSummary$ModelPackageGroupDescription' => 'A description of the model group.
', 'ModelPackageSummary$ModelPackageDescription' => 'A brief description of the model package.
', 'Project$ProjectDescription' => 'The description of the project.
', 'ProjectSummary$ProjectDescription' => 'The description of the project.
', 'UpdateProjectInput$ProjectDescription' => 'The description for the project.
', ], ], 'EntityName' => [ 'base' => NULL, 'refs' => [ 'AdditionalInferenceSpecificationDefinition$Name' => 'A unique name to identify the additional inference specification. The name must be unique within the list of your additional inference specifications for a particular model package.
', 'AlgorithmStatusItem$Name' => 'The name of the algorithm for which the overall status is being reported.
', 'AlgorithmSummary$AlgorithmName' => 'The name of the algorithm that is described by the summary.
', 'AlgorithmValidationProfile$ProfileName' => 'The name of the profile for the algorithm. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
', 'BatchDescribeModelPackageSummary$ModelPackageGroupName' => 'The group name for the model package
', 'CodeRepositorySummary$CodeRepositoryName' => 'The name of the Git repository.
', 'CompilationJobSummary$CompilationJobName' => 'The name of the model compilation job that you want a summary for.
', 'CreateAlgorithmInput$AlgorithmName' => 'The name of the algorithm.
', 'CreateCodeRepositoryInput$CodeRepositoryName' => 'The name of the Git repository. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
', 'CreateCompilationJobRequest$CompilationJobName' => 'A name for the model compilation job. The name must be unique within the Amazon Web Services Region and within your Amazon Web Services account.
', 'CreateDeviceFleetRequest$DeviceFleetName' => 'The name of the fleet that the device belongs to.
', 'CreateEdgeDeploymentPlanRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan.
', 'CreateEdgeDeploymentPlanRequest$DeviceFleetName' => 'The device fleet used for this edge deployment plan.
', 'CreateEdgeDeploymentStageRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan.
', 'CreateEdgePackagingJobRequest$EdgePackagingJobName' => 'The name of the edge packaging job.
', 'CreateEdgePackagingJobRequest$CompilationJobName' => 'The name of the SageMaker Neo compilation job that will be used to locate model artifacts for packaging.
', 'CreateEdgePackagingJobRequest$ModelName' => 'The name of the model.
', 'CreateModelCardExportJobRequest$ModelCardExportJobName' => 'The name of the model card export job.
', 'CreateModelCardRequest$ModelCardName' => 'The unique name of the model card.
', 'CreateModelPackageGroupInput$ModelPackageGroupName' => 'The name of the model group.
', 'CreateModelPackageInput$ModelPackageName' => 'The name of the model package. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
This parameter is required for unversioned models. It is not applicable to versioned models.
', 'DeleteAlgorithmInput$AlgorithmName' => 'The name of the algorithm to delete.
', 'DeleteCodeRepositoryInput$CodeRepositoryName' => 'The name of the Git repository to delete.
', 'DeleteDeviceFleetRequest$DeviceFleetName' => 'The name of the fleet to delete.
', 'DeleteEdgeDeploymentPlanRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan to delete.
', 'DeleteEdgeDeploymentStageRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan from which the stage will be deleted.
', 'DeleteEdgeDeploymentStageRequest$StageName' => 'The name of the stage.
', 'DeleteModelCardRequest$ModelCardName' => 'The name of the model card to delete.
', 'DeleteModelPackageGroupPolicyInput$ModelPackageGroupName' => 'The name of the model group for which to delete the policy.
', 'DeploymentStage$StageName' => 'The name of the stage.
', 'DeploymentStageStatusSummary$StageName' => 'The name of the stage.
', 'DeregisterDevicesRequest$DeviceFleetName' => 'The name of the fleet the devices belong to.
', 'DescribeAlgorithmOutput$AlgorithmName' => 'The name of the algorithm being described.
', 'DescribeCodeRepositoryInput$CodeRepositoryName' => 'The name of the Git repository to describe.
', 'DescribeCodeRepositoryOutput$CodeRepositoryName' => 'The name of the Git repository.
', 'DescribeCompilationJobRequest$CompilationJobName' => 'The name of the model compilation job that you want information about.
', 'DescribeCompilationJobResponse$CompilationJobName' => 'The name of the model compilation job.
', 'DescribeDeviceFleetRequest$DeviceFleetName' => 'The name of the fleet.
', 'DescribeDeviceFleetResponse$DeviceFleetName' => 'The name of the fleet.
', 'DescribeDeviceRequest$DeviceName' => 'The unique ID of the device.
', 'DescribeDeviceRequest$DeviceFleetName' => 'The name of the fleet the devices belong to.
', 'DescribeDeviceResponse$DeviceName' => 'The unique identifier of the device.
', 'DescribeDeviceResponse$DeviceFleetName' => 'The name of the fleet the device belongs to.
', 'DescribeEdgeDeploymentPlanRequest$EdgeDeploymentPlanName' => 'The name of the deployment plan to describe.
', 'DescribeEdgeDeploymentPlanResponse$EdgeDeploymentPlanName' => 'The name of the edge deployment plan.
', 'DescribeEdgeDeploymentPlanResponse$DeviceFleetName' => 'The device fleet used for this edge deployment plan.
', 'DescribeEdgePackagingJobRequest$EdgePackagingJobName' => 'The name of the edge packaging job.
', 'DescribeEdgePackagingJobResponse$EdgePackagingJobName' => 'The name of the edge packaging job.
', 'DescribeEdgePackagingJobResponse$CompilationJobName' => 'The name of the SageMaker Neo compilation job that is used to locate model artifacts that are being packaged.
', 'DescribeEdgePackagingJobResponse$ModelName' => 'The name of the model.
', 'DescribeModelCardExportJobResponse$ModelCardExportJobName' => 'The name of the model card export job to describe.
', 'DescribeModelCardExportJobResponse$ModelCardName' => 'The name or Amazon Resource Name (ARN) of the model card that the model export job exports.
', 'DescribeModelCardResponse$ModelCardName' => 'The name of the model card.
', 'DescribeModelPackageGroupOutput$ModelPackageGroupName' => 'The name of the model group.
', 'DescribeModelPackageOutput$ModelPackageName' => 'The name of the model package being described.
', 'DescribeModelPackageOutput$ModelPackageGroupName' => 'If the model is a versioned model, the name of the model group that the versioned model belongs to.
', 'DeviceDeploymentSummary$EdgeDeploymentPlanName' => 'The name of the edge deployment plan.
', 'DeviceDeploymentSummary$StageName' => 'The name of the stage in the edge deployment plan.
', 'DeviceDeploymentSummary$DeployedStageName' => 'The name of the deployed stage.
', 'DeviceDeploymentSummary$DeviceFleetName' => 'The name of the fleet to which the device belongs to.
', 'DeviceFleetSummary$DeviceFleetName' => 'Name of the device fleet.
', 'DeviceSummary$DeviceName' => 'The unique identifier of the device.
', 'DeviceSummary$DeviceFleetName' => 'The name of the fleet the device belongs to.
', 'EdgeDeploymentModelConfig$ModelHandle' => 'The name the device application uses to reference this model.
', 'EdgeDeploymentModelConfig$EdgePackagingJobName' => 'The edge packaging job associated with this deployment.
', 'EdgeDeploymentPlanSummary$EdgeDeploymentPlanName' => 'The name of the edge deployment plan.
', 'EdgeDeploymentPlanSummary$DeviceFleetName' => 'The name of the device fleet used for the deployment.
', 'EdgeModel$ModelName' => 'The name of the model.
', 'EdgeModelStat$ModelName' => 'The name of the model.
', 'EdgeModelSummary$ModelName' => 'The name of the model.
', 'EdgePackagingJobSummary$EdgePackagingJobName' => 'The name of the edge packaging job.
', 'EdgePackagingJobSummary$CompilationJobName' => 'The name of the SageMaker Neo compilation job.
', 'EdgePackagingJobSummary$ModelName' => 'The name of the model.
', 'GetDeviceFleetReportRequest$DeviceFleetName' => 'The name of the fleet.
', 'GetDeviceFleetReportResponse$DeviceFleetName' => 'The name of the fleet.
', 'GetModelPackageGroupPolicyInput$ModelPackageGroupName' => 'The name of the model group for which to get the resource policy.
', 'ListDevicesRequest$ModelName' => 'A filter that searches devices that contains this name in any of their models.
', 'ListDevicesRequest$DeviceFleetName' => 'Filter for fleets containing this name in their device fleet name.
', 'ListModelCardExportJobsRequest$ModelCardName' => 'List export jobs for the model card with the specified name.
', 'ListModelCardExportJobsRequest$ModelCardExportJobNameContains' => 'Only list model card export jobs with names that contain the specified string.
', 'ListModelCardsRequest$NameContains' => 'Only list model cards with names that contain the specified string.
', 'ListStageDevicesRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan.
', 'ListStageDevicesRequest$StageName' => 'The name of the stage in the deployment.
', 'ModelCard$ModelCardName' => 'The unique name of the model card.
', 'ModelCardExportJobSummary$ModelCardExportJobName' => 'The name of the model card export job.
', 'ModelCardExportJobSummary$ModelCardName' => 'The name of the model card that the export job exports.
', 'ModelCardSummary$ModelCardName' => 'The name of the model card.
', 'ModelCardVersionSummary$ModelCardName' => 'The name of the model card.
', 'ModelDashboardModelCard$ModelCardName' => 'The name of a model card.
', 'ModelPackage$ModelPackageName' => 'The name of the model.
', 'ModelPackage$ModelPackageGroupName' => 'The model group to which the model belongs.
', 'ModelPackageGroup$ModelPackageGroupName' => 'The name of the model group.
', 'ModelPackageGroupSummary$ModelPackageGroupName' => 'The name of the model group.
', 'ModelPackageStatusItem$Name' => 'The name of the model package for which the overall status is being reported.
', 'ModelPackageSummary$ModelPackageName' => 'The name of the model package.
', 'ModelPackageSummary$ModelPackageGroupName' => 'If the model package is a versioned model, the model group that the versioned model belongs to.
', 'ModelPackageValidationProfile$ProfileName' => 'The name of the profile for the model package.
', 'PutModelPackageGroupPolicyInput$ModelPackageGroupName' => 'The name of the model group to add a resource policy to.
', 'RegisterDevicesRequest$DeviceFleetName' => 'The name of the fleet.
', 'StartEdgeDeploymentStageRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan to start.
', 'StartEdgeDeploymentStageRequest$StageName' => 'The name of the stage to start.
', 'StopCompilationJobRequest$CompilationJobName' => 'The name of the model compilation job to stop.
', 'StopEdgeDeploymentStageRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan to stop.
', 'StopEdgeDeploymentStageRequest$StageName' => 'The name of the stage to stop.
', 'StopEdgePackagingJobRequest$EdgePackagingJobName' => 'The name of the edge packaging job.
', 'UpdateCodeRepositoryInput$CodeRepositoryName' => 'The name of the Git repository to update.
', 'UpdateDeviceFleetRequest$DeviceFleetName' => 'The name of the fleet.
', 'UpdateDevicesRequest$DeviceFleetName' => 'The name of the fleet the devices belong to.
', ], ], 'EnvironmentKey' => [ 'base' => NULL, 'refs' => [ 'EnvironmentMap$key' => NULL, ], ], 'EnvironmentMap' => [ 'base' => NULL, 'refs' => [ 'AutoMLContainerDefinition$Environment' => 'The environment variables to set in the container. For more information, see ContainerDefinition.
', 'ContainerDefinition$Environment' => 'The environment variables to set in the Docker container. Each key and value in the Environment string to string map can have length of up to 1024. We support up to 16 entries in the map.
The environment variables to set in the Docker container. Each key and value in the Environment string to string map can have length of up to 1024. We support up to 16 entries in the map.
The recommended environment variables to set in the model container for Real-Time Inference.
', ], ], 'EnvironmentParameter' => [ 'base' => 'A list of environment parameters suggested by the Amazon SageMaker Inference Recommender.
', 'refs' => [ 'EnvironmentParameters$member' => NULL, ], ], 'EnvironmentParameterRanges' => [ 'base' => 'Specifies the range of environment parameters
', 'refs' => [ 'EndpointInputConfiguration$EnvironmentParameterRanges' => 'The parameter you want to benchmark against.
', ], ], 'EnvironmentParameters' => [ 'base' => NULL, 'refs' => [ 'ModelConfiguration$EnvironmentParameters' => 'Defines the environment parameters that includes key, value types, and values.
', ], ], 'EnvironmentValue' => [ 'base' => NULL, 'refs' => [ 'EnvironmentMap$value' => NULL, ], ], 'ExcludeFeaturesAttribute' => [ 'base' => NULL, 'refs' => [ 'BatchTransformInput$ExcludeFeaturesAttribute' => 'The attributes of the input data to exclude from the analysis.
', 'EndpointInput$ExcludeFeaturesAttribute' => 'The attributes of the input data to exclude from the analysis.
', ], ], 'ExecutionRoleIdentityConfig' => [ 'base' => NULL, 'refs' => [ 'DomainSettings$ExecutionRoleIdentityConfig' => 'The configuration for attaching a SageMaker user profile name to the execution role as a sts:SourceIdentity key.
', 'DomainSettingsForUpdate$ExecutionRoleIdentityConfig' => 'The configuration for attaching a SageMaker user profile name to the execution role as a sts:SourceIdentity key. This configuration can only be modified if there are no apps in the InService or Pending state.
A filter that retrieves only jobs with a specific status.
', 'MonitoringExecutionSummary$MonitoringExecutionStatus' => 'The status of the monitoring job.
', ], ], 'ExitMessage' => [ 'base' => NULL, 'refs' => [ 'DescribeProcessingJobResponse$ExitMessage' => 'An optional string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
', 'ProcessingJob$ExitMessage' => 'A string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
', 'ProcessingJobSummary$ExitMessage' => 'An optional string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
', ], ], 'Experiment' => [ 'base' => 'The properties of an experiment as returned by the Search API.
', 'refs' => [ 'SearchRecord$Experiment' => 'The properties of an experiment.
', ], ], 'ExperimentArn' => [ 'base' => NULL, 'refs' => [ 'CreateExperimentResponse$ExperimentArn' => 'The Amazon Resource Name (ARN) of the experiment.
', 'DeleteExperimentResponse$ExperimentArn' => 'The Amazon Resource Name (ARN) of the experiment that is being deleted.
', 'DescribeExperimentResponse$ExperimentArn' => 'The Amazon Resource Name (ARN) of the experiment.
', 'Experiment$ExperimentArn' => 'The Amazon Resource Name (ARN) of the experiment.
', 'ExperimentSummary$ExperimentArn' => 'The Amazon Resource Name (ARN) of the experiment.
', 'UpdateExperimentResponse$ExperimentArn' => 'The Amazon Resource Name (ARN) of the experiment.
', ], ], 'ExperimentConfig' => [ 'base' => 'Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
', 'refs' => [ 'CreateProcessingJobRequest$ExperimentConfig' => NULL, 'CreateTrainingJobRequest$ExperimentConfig' => NULL, 'CreateTransformJobRequest$ExperimentConfig' => NULL, 'DescribeProcessingJobResponse$ExperimentConfig' => 'The configuration information used to create an experiment.
', 'DescribeTrainingJobResponse$ExperimentConfig' => NULL, 'DescribeTransformJobResponse$ExperimentConfig' => NULL, 'ProcessingJob$ExperimentConfig' => NULL, 'TrainingJob$ExperimentConfig' => NULL, 'TransformJob$ExperimentConfig' => NULL, ], ], 'ExperimentDescription' => [ 'base' => NULL, 'refs' => [ 'CreateActionRequest$Description' => 'The description of the action.
', 'CreateContextRequest$Description' => 'The description of the context.
', 'CreateExperimentRequest$Description' => 'The description of the experiment.
', 'DescribeActionResponse$Description' => 'The description of the action.
', 'DescribeContextResponse$Description' => 'The description of the context.
', 'DescribeExperimentResponse$Description' => 'The description of the experiment.
', 'DescribeLineageGroupResponse$Description' => 'The description of the lineage group.
', 'Experiment$Description' => 'The description of the experiment.
', 'UpdateActionRequest$Description' => 'The new description for the action.
', 'UpdateContextRequest$Description' => 'The new description for the context.
', 'UpdateExperimentRequest$Description' => 'The description of the experiment.
', ], ], 'ExperimentEntityName' => [ 'base' => NULL, 'refs' => [ 'ActionSummary$ActionName' => 'The name of the action.
', 'ArtifactSummary$ArtifactName' => 'The name of the artifact.
', 'AssociateTrialComponentRequest$TrialComponentName' => 'The name of the component to associated with the trial.
', 'AssociateTrialComponentRequest$TrialName' => 'The name of the trial to associate with.
', 'AssociationSummary$SourceName' => 'The name of the source.
', 'AssociationSummary$DestinationName' => 'The name of the destination.
', 'ContextSummary$ContextName' => 'The name of the context.
', 'CreateActionRequest$ActionName' => 'The name of the action. Must be unique to your account in an Amazon Web Services Region.
', 'CreateArtifactRequest$ArtifactName' => 'The name of the artifact. Must be unique to your account in an Amazon Web Services Region.
', 'CreateContextRequest$ContextName' => 'The name of the context. Must be unique to your account in an Amazon Web Services Region.
', 'CreateExperimentRequest$ExperimentName' => 'The name of the experiment. The name must be unique in your Amazon Web Services account and is not case-sensitive.
', 'CreateExperimentRequest$DisplayName' => 'The name of the experiment as displayed. The name doesn\'t need to be unique. If you don\'t specify DisplayName, the value in ExperimentName is displayed.
The name of the component. The name must be unique in your Amazon Web Services account and is not case-sensitive.
', 'CreateTrialComponentRequest$DisplayName' => 'The name of the component as displayed. The name doesn\'t need to be unique. If DisplayName isn\'t specified, TrialComponentName is displayed.
The name of the trial. The name must be unique in your Amazon Web Services account and is not case-sensitive.
', 'CreateTrialRequest$DisplayName' => 'The name of the trial as displayed. The name doesn\'t need to be unique. If DisplayName isn\'t specified, TrialName is displayed.
The name of the experiment to associate the trial with.
', 'DeleteActionRequest$ActionName' => 'The name of the action to delete.
', 'DeleteContextRequest$ContextName' => 'The name of the context to delete.
', 'DeleteExperimentRequest$ExperimentName' => 'The name of the experiment to delete.
', 'DeleteTrialComponentRequest$TrialComponentName' => 'The name of the component to delete.
', 'DeleteTrialRequest$TrialName' => 'The name of the trial to delete.
', 'DescribeActionRequest$ActionName' => 'The name of the action to describe.
', 'DescribeContextResponse$ContextName' => 'The name of the context.
', 'DescribeExperimentRequest$ExperimentName' => 'The name of the experiment to describe.
', 'DescribeExperimentResponse$ExperimentName' => 'The name of the experiment.
', 'DescribeExperimentResponse$DisplayName' => 'The name of the experiment as displayed. If DisplayName isn\'t specified, ExperimentName is displayed.
The name of the lineage group.
', 'DescribeLineageGroupResponse$LineageGroupName' => 'The name of the lineage group.
', 'DescribeLineageGroupResponse$DisplayName' => 'The display name of the lineage group.
', 'DescribeTrialComponentResponse$TrialComponentName' => 'The name of the trial component.
', 'DescribeTrialComponentResponse$DisplayName' => 'The name of the component as displayed. If DisplayName isn\'t specified, TrialComponentName is displayed.
The name of the trial to describe.
', 'DescribeTrialResponse$TrialName' => 'The name of the trial.
', 'DescribeTrialResponse$DisplayName' => 'The name of the trial as displayed. If DisplayName isn\'t specified, TrialName is displayed.
The name of the experiment the trial is part of.
', 'DisassociateTrialComponentRequest$TrialComponentName' => 'The name of the component to disassociate from the trial.
', 'DisassociateTrialComponentRequest$TrialName' => 'The name of the trial to disassociate from.
', 'Experiment$ExperimentName' => 'The name of the experiment.
', 'Experiment$DisplayName' => 'The name of the experiment as displayed. If DisplayName isn\'t specified, ExperimentName is displayed.
The name of an existing experiment to associate with the trial component.
', 'ExperimentConfig$TrialName' => 'The name of an existing trial to associate the trial component with. If not specified, a new trial is created.
', 'ExperimentConfig$TrialComponentDisplayName' => 'The display name for the trial component. If this key isn\'t specified, the display name is the trial component name.
', 'ExperimentConfig$RunName' => 'The name of the experiment run to associate with the trial component.
', 'ExperimentSummary$ExperimentName' => 'The name of the experiment.
', 'ExperimentSummary$DisplayName' => 'The name of the experiment as displayed. If DisplayName isn\'t specified, ExperimentName is displayed.
The name or Amazon Resource Name (ARN) of the lineage group.
', 'LineageGroupSummary$DisplayName' => 'The display name of the lineage group summary.
', 'ListTrialComponentsRequest$ExperimentName' => 'A filter that returns only components that are part of the specified experiment. If you specify ExperimentName, you can\'t filter by SourceArn or TrialName.
A filter that returns only components that are part of the specified trial. If you specify TrialName, you can\'t filter by ExperimentName or SourceArn.
A filter that returns only trials that are part of the specified experiment.
', 'ListTrialsRequest$TrialComponentName' => 'A filter that returns only trials that are associated with the specified trial component.
', 'Parent$TrialName' => 'The name of the trial.
', 'Parent$ExperimentName' => 'The name of the experiment.
', 'PipelineExperimentConfig$ExperimentName' => 'The name of the experiment.
', 'PipelineExperimentConfig$TrialName' => 'The name of the trial.
', 'Trial$TrialName' => 'The name of the trial.
', 'Trial$DisplayName' => 'The name of the trial as displayed. If DisplayName isn\'t specified, TrialName is displayed.
The name of the experiment the trial is part of.
', 'TrialComponent$TrialComponentName' => 'The name of the trial component.
', 'TrialComponent$DisplayName' => 'The name of the component as displayed. If DisplayName isn\'t specified, TrialComponentName is displayed.
The name of the experiment run.
', 'TrialComponentSimpleSummary$TrialComponentName' => 'The name of the trial component.
', 'TrialComponentSummary$TrialComponentName' => 'The name of the trial component.
', 'TrialComponentSummary$DisplayName' => 'The name of the component as displayed. If DisplayName isn\'t specified, TrialComponentName is displayed.
The name of the trial.
', 'TrialSummary$DisplayName' => 'The name of the trial as displayed. If DisplayName isn\'t specified, TrialName is displayed.
The name of the action to update.
', 'UpdateArtifactRequest$ArtifactName' => 'The new name for the artifact.
', 'UpdateContextRequest$ContextName' => 'The name of the context to update.
', 'UpdateExperimentRequest$ExperimentName' => 'The name of the experiment to update.
', 'UpdateExperimentRequest$DisplayName' => 'The name of the experiment as displayed. The name doesn\'t need to be unique. If DisplayName isn\'t specified, ExperimentName is displayed.
The name of the component to update.
', 'UpdateTrialComponentRequest$DisplayName' => 'The name of the component as displayed. The name doesn\'t need to be unique. If DisplayName isn\'t specified, TrialComponentName is displayed.
The name of the trial to update.
', 'UpdateTrialRequest$DisplayName' => 'The name of the trial as displayed. The name doesn\'t need to be unique. If DisplayName isn\'t specified, TrialName is displayed.
The name of the action.
', 'DescribeArtifactResponse$ArtifactName' => 'The name of the artifact.
', 'DescribeContextRequest$ContextName' => 'The name of the context to describe.
', 'DescribeTrialComponentRequest$TrialComponentName' => 'The name of the trial component to describe.
', ], ], 'ExperimentSource' => [ 'base' => 'The source of the experiment.
', 'refs' => [ 'DescribeExperimentResponse$Source' => 'The Amazon Resource Name (ARN) of the source and, optionally, the type.
', 'Experiment$Source' => NULL, 'ExperimentSummary$ExperimentSource' => NULL, ], ], 'ExperimentSourceArn' => [ 'base' => NULL, 'refs' => [ 'ExperimentSource$SourceArn' => 'The Amazon Resource Name (ARN) of the source.
', ], ], 'ExperimentSummaries' => [ 'base' => NULL, 'refs' => [ 'ListExperimentsResponse$ExperimentSummaries' => 'A list of the summaries of your experiments.
', ], ], 'ExperimentSummary' => [ 'base' => 'A summary of the properties of an experiment. To get the complete set of properties, call the DescribeExperiment API and provide the ExperimentName.
The number of seconds until the pre-signed URL expires. This value defaults to 300.
', ], ], 'Explainability' => [ 'base' => 'Contains explainability metrics for a model.
', 'refs' => [ 'ModelMetrics$Explainability' => 'Metrics that help explain a model.
', ], ], 'ExplainabilityLocation' => [ 'base' => NULL, 'refs' => [ 'CandidateArtifactLocations$Explainability' => 'The Amazon S3 prefix to the explainability artifacts generated for the AutoML candidate.
', ], ], 'ExplainerConfig' => [ 'base' => 'A parameter to activate explainers.
', 'refs' => [ 'CreateEndpointConfigInput$ExplainerConfig' => 'A member of CreateEndpointConfig that enables explainers.
The configuration parameters for an explainer.
', 'DescribeEndpointOutput$ExplainerConfig' => 'The configuration parameters for an explainer.
', ], ], 'FailStepMetadata' => [ 'base' => 'The container for the metadata for Fail step.
', 'refs' => [ 'PipelineExecutionStepMetadata$Fail' => 'The configurations and outcomes of a Fail step execution.
', ], ], 'FailureHandlingPolicy' => [ 'base' => NULL, 'refs' => [ 'EdgeDeploymentConfig$FailureHandlingPolicy' => 'Toggle that determines whether to rollback to previous configuration if the current deployment fails. By default this is turned on. You may turn this off if you want to investigate the errors yourself.
', ], ], 'FailureReason' => [ 'base' => NULL, 'refs' => [ 'ConflictException$Message' => NULL, 'DescribeAppResponse$FailureReason' => 'The failure reason.
', 'DescribeCompilationJobResponse$FailureReason' => 'If a model compilation job failed, the reason it failed.
', 'DescribeDomainResponse$FailureReason' => 'The failure reason.
', 'DescribeEndpointOutput$FailureReason' => 'If the status of the endpoint is Failed, the reason why it failed.
The reason that the FeatureGroup failed to be replicated in the OfflineStore. This is failure can occur because:
The FeatureGroup could not be created in the OfflineStore.
The FeatureGroup could not be deleted from the OfflineStore.
The reason your flow definition failed.
', 'DescribeHubContentResponse$FailureReason' => 'The failure reason if importing hub content failed.
', 'DescribeHubResponse$FailureReason' => 'The failure reason if importing hub content failed.
', 'DescribeHyperParameterTuningJobResponse$FailureReason' => 'If the tuning job failed, the reason it failed.
', 'DescribeImageResponse$FailureReason' => 'When a create, update, or delete operation fails, the reason for the failure.
', 'DescribeImageVersionResponse$FailureReason' => 'When a create or delete operation fails, the reason for the failure.
', 'DescribeInferenceRecommendationsJobResponse$FailureReason' => 'If the job fails, provides information why the job failed.
', 'DescribeLabelingJobResponse$FailureReason' => 'If the job failed, the reason that it failed.
', 'DescribeModelCardExportJobResponse$FailureReason' => 'The failure reason if the model export job fails.
', 'DescribeMonitoringScheduleResponse$FailureReason' => 'A string, up to one KB in size, that contains the reason a monitoring job failed, if it failed.
', 'DescribeNotebookInstanceOutput$FailureReason' => 'If status is Failed, the reason it failed.
A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
', 'DescribeSpaceResponse$FailureReason' => 'The failure reason.
', 'DescribeTrainingJobResponse$FailureReason' => 'If the training job failed, the reason it failed.
', 'DescribeTransformJobResponse$FailureReason' => 'If the transform job failed, FailureReason describes why it failed. A transform job creates a log file, which includes error messages, and stores it as an Amazon S3 object. For more information, see Log Amazon SageMaker Events with Amazon CloudWatch.
The failure reason.
', 'Endpoint$FailureReason' => 'If the endpoint failed, the reason it failed.
', 'EndpointMetadata$FailureReason' => ' If the status of the endpoint is Failed, or the status is InService but update operation fails, this provides the reason why it failed.
The reason that the FeatureGroup failed to be replicated in the OfflineStore. This is failure may be due to a failure to create a FeatureGroup in or delete a FeatureGroup from the OfflineStore.
The reason why the flow definition creation failed. A failure reason is returned only when the flow definition status is Failed.
The reason that the training job failed.
', 'HyperParameterTuningJobSearchEntity$FailureReason' => 'The error that was created when a hyperparameter tuning job failed.
', 'Image$FailureReason' => 'When a create, update, or delete operation fails, the reason for the failure.
', 'ImageVersion$FailureReason' => 'When a create or delete operation fails, the reason for the failure.
', 'InferenceRecommendationsJob$FailureReason' => 'If the job fails, provides information why the job failed.
', 'LabelingJobSummary$FailureReason' => 'If the LabelingJobStatus field is Failed, this field contains a description of the error.
If the update wasn\'t successful, indicates the reason why it failed.
', 'ModelDashboardMonitoringSchedule$FailureReason' => 'If a monitoring job failed, provides the reason.
', 'MonitoringExecutionSummary$FailureReason' => 'Contains the reason a monitoring job failed, if it failed.
', 'MonitoringSchedule$FailureReason' => 'If the monitoring schedule failed, the reason it failed.
', 'PipelineExecutionStep$FailureReason' => 'The reason why the step failed execution. This is only returned if the step failed its execution.
', 'ProcessingJob$FailureReason' => 'A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
', 'ProcessingJobSummary$FailureReason' => 'A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
', 'ResourceInUse$Message' => NULL, 'ResourceLimitExceeded$Message' => NULL, 'ResourceNotFound$Message' => NULL, 'TrainingJob$FailureReason' => 'If the training job failed, the reason it failed.
', 'TransformJob$FailureReason' => 'If the transform job failed, the reason it failed.
', 'TransformJobSummary$FailureReason' => 'If the transform job failed, the reason it failed.
', ], ], 'FeatureAdditions' => [ 'base' => NULL, 'refs' => [ 'UpdateFeatureGroupRequest$FeatureAdditions' => 'Updates the feature group. Updating a feature group is an asynchronous operation. When you get an HTTP 200 response, you\'ve made a valid request. It takes some time after you\'ve made a valid request for Feature Store to update the feature group.
', ], ], 'FeatureDefinition' => [ 'base' => 'A list of features. You must include FeatureName and FeatureType. Valid feature FeatureTypes are Integral, Fractional and String.
A list of Feature names and types. Name and Type is compulsory per Feature.
Valid feature FeatureTypes are Integral, Fractional and String.
FeatureNames cannot be any of the following: is_deleted, write_time, api_invocation_time
You can create up to 2,500 FeatureDefinitions per FeatureGroup.
A list of the Features in the FeatureGroup. Each feature is defined by a FeatureName and FeatureType.
A list of Features. Each Feature must include a FeatureName and a FeatureType.
Valid FeatureTypes are Integral, Fractional and String.
FeatureNames cannot be any of the following: is_deleted, write_time, api_invocation_time.
You can create up to 2,500 FeatureDefinitions per FeatureGroup.
The description you added to describe the feature.
', 'FeatureMetadata$Description' => 'An optional description that you specify to better describe the feature.
', 'UpdateFeatureMetadataRequest$Description' => 'A description that you can write to better describe the feature.
', ], ], 'FeatureGroup' => [ 'base' => 'Amazon SageMaker Feature Store stores features in a collection called Feature Group. A Feature Group can be visualized as a table which has rows, with a unique identifier for each row where each column in the table is a feature. In principle, a Feature Group is composed of features and values per features.
', 'refs' => [ 'SearchRecord$FeatureGroup' => NULL, ], ], 'FeatureGroupArn' => [ 'base' => NULL, 'refs' => [ 'CreateFeatureGroupResponse$FeatureGroupArn' => 'The Amazon Resource Name (ARN) of the FeatureGroup. This is a unique identifier for the feature group.
The Amazon Resource Name (ARN) of the FeatureGroup.
The Amazon Resource Number (ARN) of the feature group that contains the feature.
', 'FeatureGroup$FeatureGroupArn' => 'The Amazon Resource Name (ARN) of a FeatureGroup.
Unique identifier for the FeatureGroup.
The Amazon Resource Number (ARN) of the feature group.
', 'UpdateFeatureGroupResponse$FeatureGroupArn' => 'The Amazon Resource Number (ARN) of the feature group that you\'re updating.
', ], ], 'FeatureGroupMaxResults' => [ 'base' => NULL, 'refs' => [ 'ListFeatureGroupsRequest$MaxResults' => 'The maximum number of results returned by ListFeatureGroups.
The name of the FeatureGroup. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account. The name:
Must start and end with an alphanumeric character.
Can only contain alphanumeric character and hyphens. Spaces are not allowed.
The name of the FeatureGroup you want to delete. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
he name of the FeatureGroup.
The name of the feature group that you\'ve specified.
', 'FeatureGroup$FeatureGroupName' => 'The name of the FeatureGroup.
The name of FeatureGroup.
The name of the feature group containing the feature.
', 'ProcessingFeatureStoreOutput$FeatureGroupName' => 'The name of the Amazon SageMaker FeatureGroup to use as the destination for processing job output. Note that your processing script is responsible for putting records into your Feature Store.
', ], ], 'FeatureGroupNameContains' => [ 'base' => NULL, 'refs' => [ 'ListFeatureGroupsRequest$NameContains' => 'A string that partially matches one or more FeatureGroups names. Filters FeatureGroups by name.
The name or Amazon Resource Name (ARN) of the FeatureGroup you want described.
The name or Amazon Resource Name (ARN) of the feature group containing the feature.
', 'UpdateFeatureGroupRequest$FeatureGroupName' => 'The name or Amazon Resource Name (ARN) of the feature group that you\'re updating.
', 'UpdateFeatureMetadataRequest$FeatureGroupName' => 'The name or Amazon Resource Name (ARN) of the feature group containing the feature that you\'re updating.
', ], ], 'FeatureGroupSortBy' => [ 'base' => NULL, 'refs' => [ 'ListFeatureGroupsRequest$SortBy' => 'The value on which the feature group list is sorted.
', ], ], 'FeatureGroupSortOrder' => [ 'base' => NULL, 'refs' => [ 'ListFeatureGroupsRequest$SortOrder' => 'The order in which feature groups are listed.
', ], ], 'FeatureGroupStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeFeatureGroupResponse$FeatureGroupStatus' => 'The status of the feature group.
', 'FeatureGroup$FeatureGroupStatus' => 'A FeatureGroup status.
The status of a FeatureGroup. The status can be any of the following: Creating, Created, CreateFail, Deleting or DetailFail.
A FeatureGroup status. Filters by FeatureGroup status.
A summary of feature groups.
', ], ], 'FeatureGroupSummary' => [ 'base' => 'The name, ARN, CreationTime, FeatureGroup values, LastUpdatedTime and EnableOnlineStorage status of a FeatureGroup.
The metadata for a feature. It can either be metadata that you specify, or metadata that is updated automatically.
', 'refs' => [ 'SearchRecord$FeatureMetadata' => 'The feature metadata used to search through the features.
', ], ], 'FeatureName' => [ 'base' => NULL, 'refs' => [ 'CreateFeatureGroupRequest$RecordIdentifierFeatureName' => 'The name of the Feature whose value uniquely identifies a Record defined in the FeatureStore. Only the latest record per identifier value will be stored in the OnlineStore. RecordIdentifierFeatureName must be one of feature definitions\' names.
You use the RecordIdentifierFeatureName to access data in a FeatureStore.
This name:
Must start and end with an alphanumeric character.
Can only contains alphanumeric characters, hyphens, underscores. Spaces are not allowed.
The name of the feature that stores the EventTime of a Record in a FeatureGroup.
An EventTime is a point in time when a new event occurs that corresponds to the creation or update of a Record in a FeatureGroup. All Records in the FeatureGroup must have a corresponding EventTime.
An EventTime can be a String or Fractional.
Fractional: EventTime feature values must be a Unix timestamp in seconds.
String: EventTime feature values must be an ISO-8601 string in the format. The following formats are supported yyyy-MM-dd\'T\'HH:mm:ssZ and yyyy-MM-dd\'T\'HH:mm:ss.SSSZ where yyyy, MM, and dd represent the year, month, and day respectively and HH, mm, ss, and if applicable, SSS represent the hour, month, second and milliseconds respsectively. \'T\' and Z are constants.
The name of the Feature used for RecordIdentifier, whose value uniquely identifies a record stored in the feature store.
The name of the feature that stores the EventTime of a Record in a FeatureGroup.
An EventTime is a point in time when a new event occurs that corresponds to the creation or update of a Record in a FeatureGroup. All Records in the FeatureGroup have a corresponding EventTime.
The name of the feature.
', 'DescribeFeatureMetadataResponse$FeatureName' => 'The name of the feature that you\'ve specified.
', 'FeatureDefinition$FeatureName' => 'The name of a feature. The type must be a string. FeatureName cannot be any of the following: is_deleted, write_time, api_invocation_time.
The name of the Feature whose value uniquely identifies a Record defined in the FeatureGroup FeatureDefinitions.
The name of the feature that stores the EventTime of a Record in a FeatureGroup.
A EventTime is point in time when a new event occurs that corresponds to the creation or update of a Record in FeatureGroup. All Records in the FeatureGroup must have a corresponding EventTime.
The name of feature.
', 'UpdateFeatureMetadataRequest$FeatureName' => 'The name of the feature that you\'re updating.
', ], ], 'FeatureParameter' => [ 'base' => 'A key-value pair that you specify to describe the feature.
', 'refs' => [ 'FeatureParameterAdditions$member' => NULL, 'FeatureParameters$member' => NULL, ], ], 'FeatureParameterAdditions' => [ 'base' => NULL, 'refs' => [ 'UpdateFeatureMetadataRequest$ParameterAdditions' => 'A list of key-value pairs that you can add to better describe the feature.
', ], ], 'FeatureParameterKey' => [ 'base' => NULL, 'refs' => [ 'FeatureParameter$Key' => 'A key that must contain a value to describe the feature.
', 'FeatureParameterRemovals$member' => NULL, ], ], 'FeatureParameterRemovals' => [ 'base' => NULL, 'refs' => [ 'UpdateFeatureMetadataRequest$ParameterRemovals' => 'A list of parameter keys that you can specify to remove parameters that describe your feature.
', ], ], 'FeatureParameterValue' => [ 'base' => NULL, 'refs' => [ 'FeatureParameter$Value' => 'The value that belongs to a key.
', ], ], 'FeatureParameters' => [ 'base' => NULL, 'refs' => [ 'DescribeFeatureMetadataResponse$Parameters' => 'The key-value pairs that you added to describe the feature.
', 'FeatureMetadata$Parameters' => 'Optional key-value pairs that you specify to better describe the feature.
', ], ], 'FeatureStatus' => [ 'base' => NULL, 'refs' => [ 'DirectDeploySettings$Status' => 'Describes whether model deployment permissions are enabled or disabled in the Canvas application.
', 'IdentityProviderOAuthSetting$Status' => 'Describes whether OAuth for a data source is enabled or disabled in the Canvas application.
', 'KendraSettings$Status' => 'Describes whether the document querying feature is enabled or disabled in the Canvas application.
', 'ModelRegisterSettings$Status' => 'Describes whether the integration to the model registry is enabled or disabled in the Canvas application.
', 'TimeSeriesForecastingSettings$Status' => 'Describes whether time series forecasting is enabled or disabled in the Canvas application.
', ], ], 'FeatureType' => [ 'base' => NULL, 'refs' => [ 'DescribeFeatureMetadataResponse$FeatureType' => 'The data type of the feature.
', 'FeatureDefinition$FeatureType' => 'The value type of a feature. Valid values are Integral, Fractional, or String.
', 'FeatureMetadata$FeatureType' => 'The data type of the feature.
', ], ], 'FileSource' => [ 'base' => 'Contains details regarding the file source.
', 'refs' => [ 'DriftCheckBias$ConfigFile' => 'The bias config file for a model.
', 'DriftCheckExplainability$ConfigFile' => 'The explainability config file for the model.
', ], ], 'FileSystemAccessMode' => [ 'base' => NULL, 'refs' => [ 'FileSystemDataSource$FileSystemAccessMode' => 'The access mode of the mount of the directory associated with the channel. A directory can be mounted either in ro (read-only) or rw (read-write) mode.
The Amazon Elastic File System (EFS) storage configuration for a SageMaker image.
', 'refs' => [ 'KernelGatewayImageConfig$FileSystemConfig' => 'The Amazon Elastic File System (EFS) storage configuration for a SageMaker image.
', ], ], 'FileSystemDataSource' => [ 'base' => 'Specifies a file system data source for a channel.
', 'refs' => [ 'DataSource$FileSystemDataSource' => 'The file system that is associated with a channel.
', ], ], 'FileSystemId' => [ 'base' => NULL, 'refs' => [ 'FileSystemDataSource$FileSystemId' => 'The file system id.
', ], ], 'FileSystemType' => [ 'base' => NULL, 'refs' => [ 'FileSystemDataSource$FileSystemType' => 'The file system type.
', ], ], 'FillingTransformationMap' => [ 'base' => NULL, 'refs' => [ 'FillingTransformations$value' => NULL, ], ], 'FillingTransformationValue' => [ 'base' => NULL, 'refs' => [ 'FillingTransformationMap$value' => NULL, ], ], 'FillingTransformations' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesTransformations$Filling' => 'A key value pair defining the filling method for a column, where the key is the column name and the value is an object which defines the filling logic. You can specify multiple filling methods for a single column.
The supported filling methods and their corresponding options are:
frontfill: none (Supported only for target column)
middlefill: zero, value, median, mean, min, max
backfill: zero, value, median, mean, min, max
futurefill: zero, value, median, mean, min, max
To set a filling method to a specific value, set the fill parameter to the chosen filling method value (for example "backfill" : "value"), and define the filling value in an additional parameter prefixed with "_value". For example, to set backfill to a value of 2, you must include two parameters: "backfill": "value" and "backfill_value":"2".
A conditional statement for a search expression that includes a resource property, a Boolean operator, and a value. Resources that match the statement are returned in the results from the Search API.
If you specify a Value, but not an Operator, SageMaker uses the equals operator.
In search, there are several property types:
To define a metric filter, enter a value using the form "Metrics.<name>", where <name> is a metric name. For example, the following filter searches for training jobs with an "accuracy" metric greater than "0.9":
{
"Name": "Metrics.accuracy",
"Operator": "GreaterThan",
"Value": "0.9"
}
To define a hyperparameter filter, enter a value with the form "HyperParameters.<name>". Decimal hyperparameter values are treated as a decimal in a comparison if the specified Value is also a decimal value. If the specified Value is an integer, the decimal hyperparameter values are treated as integers. For example, the following filter is satisfied by training jobs with a "learning_rate" hyperparameter that is less than "0.5":
{
"Name": "HyperParameters.learning_rate",
"Operator": "LessThan",
"Value": "0.5"
}
To define a tag filter, enter a value with the form Tags.<key>.
A list of filters. Each filter acts on a property. Filters must contain at least one Filters value. For example, a NestedFilters call might include a filter on the PropertyName parameter of the InputDataConfig property: InputDataConfig.DataSource.S3DataSource.S3Uri.
A list of filter objects.
', ], ], 'FilterValue' => [ 'base' => NULL, 'refs' => [ 'Filter$Value' => 'A value used with Name and Operator to determine which resources satisfy the filter\'s condition. For numerical properties, Value must be an integer or floating-point decimal. For timestamp properties, Value must be an ISO 8601 date-time string of the following format: YYYY-mm-dd\'T\'HH:MM:SS.
The best candidate result from an AutoML training job.
', 'refs' => [ 'AutoMLCandidate$FinalAutoMLJobObjectiveMetric' => NULL, ], ], 'FinalHyperParameterTuningJobObjectiveMetric' => [ 'base' => 'Shows the latest objective metric emitted by a training job that was launched by a hyperparameter tuning job. You define the objective metric in the HyperParameterTuningJobObjective parameter of HyperParameterTuningJobConfig.
The FinalHyperParameterTuningJobObjectiveMetric object that specifies the value of the objective metric of the tuning job that launched this training job.
', ], ], 'FinalMetricDataList' => [ 'base' => NULL, 'refs' => [ 'DescribeTrainingJobResponse$FinalMetricDataList' => 'A collection of MetricData objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.
A list of final metric values that are set when the training job completes. Used only if the training job was configured to use metrics.
', ], ], 'FlatInvocations' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobStoppingConditions$FlatInvocations' => 'Stops a load test when the number of invocations (TPS) peaks and flattens, which means that the instance has reached capacity. The default value is Stop. If you want the load test to continue after invocations have flattened, set the value to Continue.
The value of the metric.
', 'MetricDatum$Value' => 'The value of the metric.
', 'RecommendationMetrics$CostPerHour' => 'Defines the cost per hour for the instance.
', 'RecommendationMetrics$CostPerInference' => 'Defines the cost per inference for the instance .
', ], ], 'FlowDefinitionArn' => [ 'base' => NULL, 'refs' => [ 'CreateFlowDefinitionResponse$FlowDefinitionArn' => 'The Amazon Resource Name (ARN) of the flow definition you create.
', 'DescribeFlowDefinitionResponse$FlowDefinitionArn' => 'The Amazon Resource Name (ARN) of the flow defintion.
', 'FlowDefinitionSummary$FlowDefinitionArn' => 'The Amazon Resource Name (ARN) of the flow definition.
', ], ], 'FlowDefinitionName' => [ 'base' => NULL, 'refs' => [ 'CreateFlowDefinitionRequest$FlowDefinitionName' => 'The name of your flow definition.
', 'DeleteFlowDefinitionRequest$FlowDefinitionName' => 'The name of the flow definition you are deleting.
', 'DescribeFlowDefinitionRequest$FlowDefinitionName' => 'The name of the flow definition.
', 'DescribeFlowDefinitionResponse$FlowDefinitionName' => 'The Amazon Resource Name (ARN) of the flow definition.
', 'FlowDefinitionSummary$FlowDefinitionName' => 'The name of the flow definition.
', ], ], 'FlowDefinitionOutputConfig' => [ 'base' => 'Contains information about where human output will be stored.
', 'refs' => [ 'CreateFlowDefinitionRequest$OutputConfig' => 'An object containing information about where the human review results will be uploaded.
', 'DescribeFlowDefinitionResponse$OutputConfig' => 'An object containing information about the output file.
', ], ], 'FlowDefinitionStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeFlowDefinitionResponse$FlowDefinitionStatus' => 'The status of the flow definition. Valid values are listed below.
', 'FlowDefinitionSummary$FlowDefinitionStatus' => 'The status of the flow definition. Valid values:
', ], ], 'FlowDefinitionSummaries' => [ 'base' => NULL, 'refs' => [ 'ListFlowDefinitionsResponse$FlowDefinitionSummaries' => 'An array of objects describing the flow definitions.
', ], ], 'FlowDefinitionSummary' => [ 'base' => 'Contains summary information about the flow definition.
', 'refs' => [ 'FlowDefinitionSummaries$member' => NULL, ], ], 'FlowDefinitionTaskAvailabilityLifetimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'HumanLoopConfig$TaskAvailabilityLifetimeInSeconds' => 'The length of time that a task remains available for review by human workers.
', ], ], 'FlowDefinitionTaskCount' => [ 'base' => NULL, 'refs' => [ 'HumanLoopConfig$TaskCount' => 'The number of distinct workers who will perform the same task on each object. For example, if TaskCount is set to 3 for an image classification labeling job, three workers will classify each input image. Increasing TaskCount can improve label accuracy.
A description for the human worker task.
', ], ], 'FlowDefinitionTaskKeyword' => [ 'base' => NULL, 'refs' => [ 'FlowDefinitionTaskKeywords$member' => NULL, ], ], 'FlowDefinitionTaskKeywords' => [ 'base' => NULL, 'refs' => [ 'HumanLoopConfig$TaskKeywords' => 'Keywords used to describe the task so that workers can discover the task.
', ], ], 'FlowDefinitionTaskTimeLimitInSeconds' => [ 'base' => NULL, 'refs' => [ 'HumanLoopConfig$TaskTimeLimitInSeconds' => 'The amount of time that a worker has to complete a task. The default value is 3,600 seconds (1 hour).
', ], ], 'FlowDefinitionTaskTitle' => [ 'base' => NULL, 'refs' => [ 'HumanLoopConfig$TaskTitle' => 'A title for the human worker task.
', ], ], 'ForecastFrequency' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesForecastingJobConfig$ForecastFrequency' => 'The frequency of predictions in a forecast.
Valid intervals are an integer followed by Y (Year), M (Month), W (Week), D (Day), H (Hour), and min (Minute). For example, 1D indicates every day and 15min indicates every 15 minutes. The value of a frequency must not overlap with the next larger frequency. For example, you must use a frequency of 1H instead of 60min.
The valid values for each frequency are the following:
Minute - 1-59
Hour - 1-23
Day - 1-6
Week - 1-4
Month - 1-11
Year - 1
The number of time-steps that the model predicts. The forecast horizon is also called the prediction length. The maximum forecast horizon is the lesser of 500 time-steps or 1/4 of the time-steps in the dataset.
', ], ], 'ForecastQuantile' => [ 'base' => NULL, 'refs' => [ 'ForecastQuantiles$member' => NULL, ], ], 'ForecastQuantiles' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesForecastingJobConfig$ForecastQuantiles' => 'The quantiles used to train the model for forecasts at a specified quantile. You can specify quantiles from 0.01 (p1) to 0.99 (p99), by increments of 0.01 or higher. Up to five forecast quantiles can be specified. When ForecastQuantiles is not provided, the AutoML job uses the quantiles p10, p50, and p90 as default.
Identifies the framework in which the model was trained. For example: TENSORFLOW.
', ], ], 'FrameworkVersion' => [ 'base' => NULL, 'refs' => [ 'InputConfig$FrameworkVersion' => 'Specifies the framework version to use. This API field is only supported for the MXNet, PyTorch, TensorFlow and TensorFlow Lite frameworks.
For information about framework versions supported for cloud targets and edge devices, see Cloud Supported Instance Types and Frameworks and Edge Supported Frameworks.
', ], ], 'GenerateCandidateDefinitionsOnly' => [ 'base' => NULL, 'refs' => [ 'CreateAutoMLJobRequest$GenerateCandidateDefinitionsOnly' => 'Generates possible candidates without training the models. A candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings.
', 'DescribeAutoMLJobResponse$GenerateCandidateDefinitionsOnly' => 'Indicates whether the output for an AutoML job generates candidate definitions only.
', 'TabularJobConfig$GenerateCandidateDefinitionsOnly' => 'Generates possible candidates without training the models. A model candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings.
', ], ], 'GetDeviceFleetReportRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetDeviceFleetReportResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetLineageGroupPolicyRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetLineageGroupPolicyResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetModelPackageGroupPolicyInput' => [ 'base' => NULL, 'refs' => [], ], 'GetModelPackageGroupPolicyOutput' => [ 'base' => NULL, 'refs' => [], ], 'GetSagemakerServicecatalogPortfolioStatusInput' => [ 'base' => NULL, 'refs' => [], ], 'GetSagemakerServicecatalogPortfolioStatusOutput' => [ 'base' => NULL, 'refs' => [], ], 'GetScalingConfigurationRecommendationRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetScalingConfigurationRecommendationResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetSearchSuggestionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetSearchSuggestionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'GitConfig' => [ 'base' => 'Specifies configuration details for a Git repository in your Amazon Web Services account.
', 'refs' => [ 'CodeRepositorySummary$GitConfig' => 'Configuration details for the Git repository, including the URL where it is located and the ARN of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository.
', 'CreateCodeRepositoryInput$GitConfig' => 'Specifies details about the repository, including the URL where the repository is located, the default branch, and credentials to use to access the repository.
', 'DescribeCodeRepositoryOutput$GitConfig' => 'Configuration details about the repository, including the URL where the repository is located, the default branch, and the Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository.
', ], ], 'GitConfigForUpdate' => [ 'base' => 'Specifies configuration details for a Git repository when the repository is updated.
', 'refs' => [ 'UpdateCodeRepositoryInput$GitConfig' => 'The configuration of the git repository, including the URL and the Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository. The secret must have a staging label of AWSCURRENT and must be in the following format:
{"username": UserName, "password": Password}
The URL where the Git repository is located.
', ], ], 'Group' => [ 'base' => NULL, 'refs' => [ 'Groups$member' => NULL, ], ], 'GroupingAttributeName' => [ 'base' => NULL, 'refs' => [ 'GroupingAttributeNames$member' => NULL, ], ], 'GroupingAttributeNames' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesConfig$GroupingAttributeNames' => 'A set of columns names that can be grouped with the item identifier column to create a composite key for which a target value is predicted.
', ], ], 'Groups' => [ 'base' => NULL, 'refs' => [ 'OidcMemberDefinition$Groups' => 'A list of comma seperated strings that identifies user groups in your OIDC IdP. Each user group is made up of a group of private workers.
', ], ], 'HolidayConfig' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesForecastingJobConfig$HolidayConfig' => 'The collection of holiday featurization attributes used to incorporate national holiday information into your forecasting model.
', ], ], 'HolidayConfigAttributes' => [ 'base' => 'Stores the holiday featurization attributes applicable to each item of time-series datasets during the training of a forecasting model. This allows the model to identify patterns associated with specific holidays.
', 'refs' => [ 'HolidayConfig$member' => NULL, ], ], 'HookParameters' => [ 'base' => NULL, 'refs' => [ 'DebugHookConfig$HookParameters' => 'Configuration information for the Amazon SageMaker Debugger hook parameters.
', ], ], 'Horovod' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$Horovod' => 'Indicates Horovod compatibility.
', 'DescribeImageVersionResponse$Horovod' => 'Indicates Horovod compatibility.
', 'UpdateImageVersionRequest$Horovod' => 'Indicates Horovod compatibility.
', ], ], 'HubArn' => [ 'base' => NULL, 'refs' => [ 'CreateHubResponse$HubArn' => 'The Amazon Resource Name (ARN) of the hub.
', 'DescribeHubContentResponse$HubArn' => 'The Amazon Resource Name (ARN) of the hub that contains the content.
', 'DescribeHubResponse$HubArn' => 'The Amazon Resource Name (ARN) of the hub.
', 'HubInfo$HubArn' => 'The Amazon Resource Name (ARN) of the hub.
', 'ImportHubContentResponse$HubArn' => 'The ARN of the hub that the content was imported into.
', 'UpdateHubResponse$HubArn' => 'The Amazon Resource Name (ARN) of the updated hub.
', ], ], 'HubContentArn' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentArn' => 'The Amazon Resource Name (ARN) of the hub content.
', 'HubContentInfo$HubContentArn' => 'The Amazon Resource Name (ARN) of the hub content.
', 'ImportHubContentResponse$HubContentArn' => 'The ARN of the hub content that was imported.
', ], ], 'HubContentDependency' => [ 'base' => 'Any dependencies related to hub content, such as scripts, model artifacts, datasets, or notebooks.
', 'refs' => [ 'HubContentDependencyList$member' => NULL, ], ], 'HubContentDependencyList' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentDependencies' => 'The location of any dependencies that the hub content has, such as scripts, model artifacts, datasets, or notebooks.
', ], ], 'HubContentDescription' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentDescription' => 'A description of the hub content.
', 'HubContentInfo$HubContentDescription' => 'A description of the hub content.
', 'ImportHubContentRequest$HubContentDescription' => 'A description of the hub content to import.
', ], ], 'HubContentDisplayName' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentDisplayName' => 'The display name of the hub content.
', 'HubContentInfo$HubContentDisplayName' => 'The display name of the hub content.
', 'ImportHubContentRequest$HubContentDisplayName' => 'The display name of the hub content to import.
', ], ], 'HubContentDocument' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentDocument' => 'The hub content document that describes information about the hub content such as type, associated containers, scripts, and more.
', 'ImportHubContentRequest$HubContentDocument' => 'The hub content document that describes information about the hub content such as type, associated containers, scripts, and more.
', ], ], 'HubContentInfo' => [ 'base' => 'Information about hub content.
', 'refs' => [ 'HubContentInfoList$member' => NULL, ], ], 'HubContentInfoList' => [ 'base' => NULL, 'refs' => [ 'ListHubContentVersionsResponse$HubContentSummaries' => 'The summaries of the listed hub content versions.
', 'ListHubContentsResponse$HubContentSummaries' => 'The summaries of the listed hub content.
', ], ], 'HubContentMarkdown' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentMarkdown' => 'A string that provides a description of the hub content. This string can include links, tables, and standard markdown formating.
', 'ImportHubContentRequest$HubContentMarkdown' => 'A string that provides a description of the hub content. This string can include links, tables, and standard markdown formating.
', ], ], 'HubContentName' => [ 'base' => NULL, 'refs' => [ 'DeleteHubContentRequest$HubContentName' => 'The name of the content that you want to delete from a hub.
', 'DescribeHubContentRequest$HubContentName' => 'The name of the content to describe.
', 'DescribeHubContentResponse$HubContentName' => 'The name of the hub content.
', 'HubContentInfo$HubContentName' => 'The name of the hub content.
', 'ImportHubContentRequest$HubContentName' => 'The name of the hub content to import.
', 'ListHubContentVersionsRequest$HubContentName' => 'The name of the hub content.
', ], ], 'HubContentSearchKeywordList' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentSearchKeywords' => 'The searchable keywords for the hub content.
', 'HubContentInfo$HubContentSearchKeywords' => 'The searchable keywords for the hub content.
', 'ImportHubContentRequest$HubContentSearchKeywords' => 'The searchable keywords of the hub content.
', ], ], 'HubContentSortBy' => [ 'base' => NULL, 'refs' => [ 'ListHubContentVersionsRequest$SortBy' => 'Sort hub content versions by either name or creation time.
', 'ListHubContentsRequest$SortBy' => 'Sort hub content versions by either name or creation time.
', ], ], 'HubContentStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentStatus' => 'The status of the hub content.
', 'HubContentInfo$HubContentStatus' => 'The status of the hub content.
', ], ], 'HubContentType' => [ 'base' => NULL, 'refs' => [ 'DeleteHubContentRequest$HubContentType' => 'The type of content that you want to delete from a hub.
', 'DescribeHubContentRequest$HubContentType' => 'The type of content in the hub.
', 'DescribeHubContentResponse$HubContentType' => 'The type of hub content.
', 'HubContentInfo$HubContentType' => 'The type of hub content.
', 'ImportHubContentRequest$HubContentType' => 'The type of hub content to import.
', 'ListHubContentVersionsRequest$HubContentType' => 'The type of hub content to list versions of.
', 'ListHubContentsRequest$HubContentType' => 'The type of hub content to list.
', ], ], 'HubContentVersion' => [ 'base' => NULL, 'refs' => [ 'DeleteHubContentRequest$HubContentVersion' => 'The version of the content that you want to delete from a hub.
', 'DescribeHubContentRequest$HubContentVersion' => 'The version of the content to describe.
', 'DescribeHubContentResponse$HubContentVersion' => 'The version of the hub content.
', 'HubContentInfo$HubContentVersion' => 'The version of the hub content.
', 'ImportHubContentRequest$HubContentVersion' => 'The version of the hub content to import.
', 'ListHubContentVersionsRequest$MinVersion' => 'The lower bound of the hub content versions to list.
', ], ], 'HubDescription' => [ 'base' => NULL, 'refs' => [ 'CreateHubRequest$HubDescription' => 'A description of the hub.
', 'DescribeHubResponse$HubDescription' => 'A description of the hub.
', 'HubInfo$HubDescription' => 'A description of the hub.
', 'UpdateHubRequest$HubDescription' => 'A description of the updated hub.
', ], ], 'HubDisplayName' => [ 'base' => NULL, 'refs' => [ 'CreateHubRequest$HubDisplayName' => 'The display name of the hub.
', 'DescribeHubResponse$HubDisplayName' => 'The display name of the hub.
', 'HubInfo$HubDisplayName' => 'The display name of the hub.
', 'UpdateHubRequest$HubDisplayName' => 'The display name of the hub.
', ], ], 'HubInfo' => [ 'base' => 'Information about a hub.
', 'refs' => [ 'HubInfoList$member' => NULL, ], ], 'HubInfoList' => [ 'base' => NULL, 'refs' => [ 'ListHubsResponse$HubSummaries' => 'The summaries of the listed hubs.
', ], ], 'HubName' => [ 'base' => NULL, 'refs' => [ 'CreateHubRequest$HubName' => 'The name of the hub to create.
', 'DeleteHubContentRequest$HubName' => 'The name of the hub that you want to delete content in.
', 'DeleteHubRequest$HubName' => 'The name of the hub to delete.
', 'DescribeHubContentRequest$HubName' => 'The name of the hub that contains the content to describe.
', 'DescribeHubContentResponse$HubName' => 'The name of the hub that contains the content.
', 'DescribeHubRequest$HubName' => 'The name of the hub to describe.
', 'DescribeHubResponse$HubName' => 'The name of the hub.
', 'HubInfo$HubName' => 'The name of the hub.
', 'ImportHubContentRequest$HubName' => 'The name of the hub to import content into.
', 'ListHubContentVersionsRequest$HubName' => 'The name of the hub to list the content versions of.
', 'ListHubContentsRequest$HubName' => 'The name of the hub to list the contents of.
', 'UpdateHubRequest$HubName' => 'The name of the hub to update.
', ], ], 'HubS3StorageConfig' => [ 'base' => 'The Amazon S3 storage configuration of a hub.
', 'refs' => [ 'CreateHubRequest$S3StorageConfig' => 'The Amazon S3 storage configuration for the hub.
', 'DescribeHubResponse$S3StorageConfig' => 'The Amazon S3 storage configuration for the hub.
', ], ], 'HubSearchKeyword' => [ 'base' => NULL, 'refs' => [ 'HubContentSearchKeywordList$member' => NULL, 'HubSearchKeywordList$member' => NULL, ], ], 'HubSearchKeywordList' => [ 'base' => NULL, 'refs' => [ 'CreateHubRequest$HubSearchKeywords' => 'The searchable keywords for the hub.
', 'DescribeHubResponse$HubSearchKeywords' => 'The searchable keywords for the hub.
', 'HubInfo$HubSearchKeywords' => 'The searchable keywords for the hub.
', 'UpdateHubRequest$HubSearchKeywords' => 'The searchable keywords for the hub.
', ], ], 'HubSortBy' => [ 'base' => NULL, 'refs' => [ 'ListHubsRequest$SortBy' => 'Sort hubs by either name or creation time.
', ], ], 'HubStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeHubResponse$HubStatus' => 'The status of the hub.
', 'HubInfo$HubStatus' => 'The status of the hub.
', ], ], 'HumanLoopActivationConditions' => [ 'base' => NULL, 'refs' => [ 'HumanLoopActivationConditionsConfig$HumanLoopActivationConditions' => 'JSON expressing use-case specific conditions declaratively. If any condition is matched, atomic tasks are created against the configured work team. The set of conditions is different for Rekognition and Textract. For more information about how to structure the JSON, see JSON Schema for Human Loop Activation Conditions in Amazon Augmented AI in the Amazon SageMaker Developer Guide.
', ], ], 'HumanLoopActivationConditionsConfig' => [ 'base' => 'Defines under what conditions SageMaker creates a human loop. Used within CreateFlowDefinition. See HumanLoopActivationConditionsConfig for the required format of activation conditions.
', 'refs' => [ 'HumanLoopActivationConfig$HumanLoopActivationConditionsConfig' => 'Container structure for defining under what conditions SageMaker creates a human loop.
', ], ], 'HumanLoopActivationConfig' => [ 'base' => 'Provides information about how and under what conditions SageMaker creates a human loop. If HumanLoopActivationConfig is not given, then all requests go to humans.
An object containing information about the events that trigger a human workflow.
', 'DescribeFlowDefinitionResponse$HumanLoopActivationConfig' => 'An object containing information about what triggers a human review workflow.
', ], ], 'HumanLoopConfig' => [ 'base' => 'Describes the work to be performed by human workers.
', 'refs' => [ 'CreateFlowDefinitionRequest$HumanLoopConfig' => 'An object containing information about the tasks the human reviewers will perform.
', 'DescribeFlowDefinitionResponse$HumanLoopConfig' => 'An object containing information about who works on the task, the workforce task price, and other task details.
', ], ], 'HumanLoopRequestSource' => [ 'base' => 'Container for configuring the source of human task requests.
', 'refs' => [ 'CreateFlowDefinitionRequest$HumanLoopRequestSource' => 'Container for configuring the source of human task requests. Use to specify if Amazon Rekognition or Amazon Textract is used as an integration source.
', 'DescribeFlowDefinitionResponse$HumanLoopRequestSource' => 'Container for configuring the source of human task requests. Used to specify if Amazon Rekognition or Amazon Textract is used as an integration source.
', ], ], 'HumanTaskConfig' => [ 'base' => 'Information required for human workers to complete a labeling task.
', 'refs' => [ 'CreateLabelingJobRequest$HumanTaskConfig' => 'Configures the labeling task and how it is presented to workers; including, but not limited to price, keywords, and batch size (task count).
', 'DescribeLabelingJobResponse$HumanTaskConfig' => 'Configuration information required for human workers to complete a labeling task.
', ], ], 'HumanTaskUiArn' => [ 'base' => NULL, 'refs' => [ 'CreateHumanTaskUiResponse$HumanTaskUiArn' => 'The Amazon Resource Name (ARN) of the human review workflow user interface you create.
', 'DescribeHumanTaskUiResponse$HumanTaskUiArn' => 'The Amazon Resource Name (ARN) of the human task user interface (worker task template).
', 'HumanLoopConfig$HumanTaskUiArn' => 'The Amazon Resource Name (ARN) of the human task user interface.
You can use standard HTML and Crowd HTML Elements to create a custom worker task template. You use this template to create a human task UI.
To learn how to create a custom HTML template, see Create Custom Worker Task Template.
To learn how to create a human task UI, which is a worker task template that can be used in a flow definition, see Create and Delete a Worker Task Templates.
', 'HumanTaskUiSummary$HumanTaskUiArn' => 'The Amazon Resource Name (ARN) of the human task user interface.
', 'RenderUiTemplateRequest$HumanTaskUiArn' => 'The HumanTaskUiArn of the worker UI that you want to render. Do not provide a HumanTaskUiArn if you use the UiTemplate parameter.
See a list of available Human Ui Amazon Resource Names (ARNs) in UiConfig.
', 'UiConfig$HumanTaskUiArn' => 'The ARN of the worker task template used to render the worker UI and tools for labeling job tasks.
Use this parameter when you are creating a labeling job for named entity recognition, 3D point cloud and video frame labeling jobs. Use your labeling job task type to select one of the following ARNs and use it with this parameter when you create a labeling job. Replace aws-region with the Amazon Web Services Region you are creating your labeling job in. For example, replace aws-region with us-west-1 if you create a labeling job in US West (N. California).
Named Entity Recognition
Use the following HumanTaskUiArn for named entity recognition labeling jobs:
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/NamedEntityRecognition
3D Point Cloud HumanTaskUiArns
Use this HumanTaskUiArn for 3D point cloud object detection and 3D point cloud object detection adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectDetection
Use this HumanTaskUiArn for 3D point cloud object tracking and 3D point cloud object tracking adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectTracking
Use this HumanTaskUiArn for 3D point cloud semantic segmentation and 3D point cloud semantic segmentation adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudSemanticSegmentation
Video Frame HumanTaskUiArns
Use this HumanTaskUiArn for video frame object detection and video frame object detection adjustment labeling jobs.
arn:aws:sagemaker:region:394669845002:human-task-ui/VideoObjectDetection
Use this HumanTaskUiArn for video frame object tracking and video frame object tracking adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/VideoObjectTracking
The name of the user interface you are creating.
', 'DeleteHumanTaskUiRequest$HumanTaskUiName' => 'The name of the human task user interface (work task template) you want to delete.
', 'DescribeHumanTaskUiRequest$HumanTaskUiName' => 'The name of the human task user interface (worker task template) you want information about.
', 'DescribeHumanTaskUiResponse$HumanTaskUiName' => 'The name of the human task user interface (worker task template).
', 'HumanTaskUiSummary$HumanTaskUiName' => 'The name of the human task user interface.
', ], ], 'HumanTaskUiStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeHumanTaskUiResponse$HumanTaskUiStatus' => 'The status of the human task user interface (worker task template). Valid values are listed below.
', ], ], 'HumanTaskUiSummaries' => [ 'base' => NULL, 'refs' => [ 'ListHumanTaskUisResponse$HumanTaskUiSummaries' => 'An array of objects describing the human task user interfaces.
', ], ], 'HumanTaskUiSummary' => [ 'base' => 'Container for human task user interface information.
', 'refs' => [ 'HumanTaskUiSummaries$member' => NULL, ], ], 'HyperParameterAlgorithmSpecification' => [ 'base' => 'Specifies which training algorithm to use for training jobs that a hyperparameter tuning job launches and the metrics to monitor.
', 'refs' => [ 'HyperParameterTrainingJobDefinition$AlgorithmSpecification' => 'The HyperParameterAlgorithmSpecification object that specifies the resource algorithm to use for the training jobs that the tuning job launches.
', ], ], 'HyperParameterKey' => [ 'base' => NULL, 'refs' => [ 'HyperParameters$key' => NULL, ], ], 'HyperParameterScalingType' => [ 'base' => NULL, 'refs' => [ 'ContinuousParameterRange$ScalingType' => 'The scale that hyperparameter tuning uses to search the hyperparameter range. For information about choosing a hyperparameter scale, see Hyperparameter Scaling. One of the following values:
SageMaker hyperparameter tuning chooses the best scale for the hyperparameter.
Hyperparameter tuning searches the values in the hyperparameter range by using a linear scale.
Hyperparameter tuning searches the values in the hyperparameter range by using a logarithmic scale.
Logarithmic scaling works only for ranges that have only values greater than 0.
Hyperparameter tuning searches the values in the hyperparameter range by using a reverse logarithmic scale.
Reverse logarithmic scaling works only for ranges that are entirely within the range 0<=x<1.0.
The scale that hyperparameter tuning uses to search the hyperparameter range. For information about choosing a hyperparameter scale, see Hyperparameter Scaling. One of the following values:
SageMaker hyperparameter tuning chooses the best scale for the hyperparameter.
Hyperparameter tuning searches the values in the hyperparameter range by using a linear scale.
Hyperparameter tuning searches the values in the hyperparameter range by using a logarithmic scale.
Logarithmic scaling works only for ranges that have only values greater than 0.
Defines a hyperparameter to be used by an algorithm.
', 'refs' => [ 'HyperParameterSpecifications$member' => NULL, ], ], 'HyperParameterSpecifications' => [ 'base' => NULL, 'refs' => [ 'TrainingSpecification$SupportedHyperParameters' => 'A list of the HyperParameterSpecification objects, that define the supported hyperparameters. This is required if the algorithm supports automatic model tuning.>
Defines the training jobs launched by a hyperparameter tuning job.
', 'refs' => [ 'CreateHyperParameterTuningJobRequest$TrainingJobDefinition' => 'The HyperParameterTrainingJobDefinition object that describes the training jobs that this tuning job launches, including static hyperparameters, input data configuration, output data configuration, resource configuration, and stopping condition.
', 'DescribeHyperParameterTuningJobResponse$TrainingJobDefinition' => 'The HyperParameterTrainingJobDefinition object that specifies the definition of the training jobs that this tuning job launches.
', 'HyperParameterTrainingJobDefinitions$member' => NULL, 'HyperParameterTuningJobSearchEntity$TrainingJobDefinition' => NULL, ], ], 'HyperParameterTrainingJobDefinitionName' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTrainingJobDefinition$DefinitionName' => 'The job definition name.
', 'HyperParameterTrainingJobSummary$TrainingJobDefinitionName' => 'The training job definition name.
', ], ], 'HyperParameterTrainingJobDefinitions' => [ 'base' => NULL, 'refs' => [ 'CreateHyperParameterTuningJobRequest$TrainingJobDefinitions' => 'A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.
', 'DescribeHyperParameterTuningJobResponse$TrainingJobDefinitions' => 'A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.
', 'HyperParameterTuningJobSearchEntity$TrainingJobDefinitions' => 'The job definitions included in a hyperparameter tuning job.
', ], ], 'HyperParameterTrainingJobEnvironmentKey' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTrainingJobEnvironmentMap$key' => NULL, ], ], 'HyperParameterTrainingJobEnvironmentMap' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTrainingJobDefinition$Environment' => 'An environment variable that you can pass into the SageMaker CreateTrainingJob API. You can use an existing environment variable from the training container or use your own. See Define metrics and variables for more information.
The maximum number of items specified for Map Entries refers to the maximum number of environment variables for each TrainingJobDefinition and also the maximum for the hyperparameter tuning job itself. That is, the sum of the number of environment variables for all the training job definitions can\'t exceed the maximum number specified.
A list of TrainingJobSummary objects that describe the training jobs that the ListTrainingJobsForHyperParameterTuningJob request returned.
The container for the summary information about a training job.
', 'refs' => [ 'DescribeHyperParameterTuningJobResponse$BestTrainingJob' => 'A TrainingJobSummary object that describes the training job that completed with the best current HyperParameterTuningJobObjective.
', 'DescribeHyperParameterTuningJobResponse$OverallBestTrainingJob' => 'If the hyperparameter tuning job is an warm start tuning job with a WarmStartType of IDENTICAL_DATA_AND_ALGORITHM, this is the TrainingJobSummary for the training job with the best objective metric value of all training jobs launched by this tuning job and all parent jobs specified for the warm start tuning job.
The strategy that determines the order of preference for resources specified in InstanceConfigs used in hyperparameter optimization.
The configuration for hyperparameter tuning resources for use in training jobs launched by the tuning job. These resources include compute instances and storage volumes. Specify one or more compute instance configurations and allocation strategies to select resources (optional).
', 'refs' => [ 'HyperParameterTuningInstanceConfigs$member' => NULL, ], ], 'HyperParameterTuningInstanceConfigs' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTuningResourceConfig$InstanceConfigs' => 'A list containing the configuration(s) for one or more resources for processing hyperparameter jobs. These resources include compute instances and storage volumes to use in model training jobs launched by hyperparameter tuning jobs. The AllocationStrategy controls the order in which multiple configurations provided in InstanceConfigs are used.
If you only want to use a single instance configuration inside the HyperParameterTuningResourceConfig API, do not provide a value for InstanceConfigs. Instead, use InstanceType, VolumeSizeInGB and InstanceCount. If you use InstanceConfigs, do not provide values for InstanceType, VolumeSizeInGB or InstanceCount.
The Amazon Resource Name (ARN) of the tuning job. SageMaker assigns an ARN to a hyperparameter tuning job when you create it.
', 'DescribeHyperParameterTuningJobResponse$HyperParameterTuningJobArn' => 'The Amazon Resource Name (ARN) of the tuning job.
', 'DescribeTrainingJobResponse$TuningJobArn' => 'The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.
', 'HyperParameterTuningJobSearchEntity$HyperParameterTuningJobArn' => 'The Amazon Resource Name (ARN) of a hyperparameter tuning job.
', 'HyperParameterTuningJobSummary$HyperParameterTuningJobArn' => 'The Amazon Resource Name (ARN) of the tuning job.
', 'TrainingJob$TuningJobArn' => 'The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.
', 'TuningJobStepMetaData$Arn' => 'The Amazon Resource Name (ARN) of the tuning job that was run by this step execution.
', ], ], 'HyperParameterTuningJobCompletionDetails' => [ 'base' => 'A structure that contains runtime information about both current and completed hyperparameter tuning jobs.
', 'refs' => [ 'DescribeHyperParameterTuningJobResponse$TuningJobCompletionDetails' => 'Tuning job completion information returned as the response from a hyperparameter tuning job. This information tells if your tuning job has or has not converged. It also includes the number of training jobs that have not improved model performance as evaluated against the objective function.
', 'HyperParameterTuningJobSearchEntity$TuningJobCompletionDetails' => 'Information about either a current or completed hyperparameter tuning job.
', ], ], 'HyperParameterTuningJobConfig' => [ 'base' => 'Configures a hyperparameter tuning job.
', 'refs' => [ 'CreateHyperParameterTuningJobRequest$HyperParameterTuningJobConfig' => 'The HyperParameterTuningJobConfig object that describes the tuning job, including the search strategy, the objective metric used to evaluate training jobs, ranges of parameters to search, and resource limits for the tuning job. For more information, see How Hyperparameter Tuning Works.
', 'DescribeHyperParameterTuningJobResponse$HyperParameterTuningJobConfig' => 'The HyperParameterTuningJobConfig object that specifies the configuration of the tuning job.
', 'HyperParameterTuningJobSearchEntity$HyperParameterTuningJobConfig' => NULL, ], ], 'HyperParameterTuningJobConsumedResources' => [ 'base' => 'The total resources consumed by your hyperparameter tuning job.
', 'refs' => [ 'DescribeHyperParameterTuningJobResponse$ConsumedResources' => NULL, 'HyperParameterTuningJobSearchEntity$ConsumedResources' => 'The total amount of resources consumed by a hyperparameter tuning job.
', ], ], 'HyperParameterTuningJobName' => [ 'base' => NULL, 'refs' => [ 'CreateHyperParameterTuningJobRequest$HyperParameterTuningJobName' => 'The name of the tuning job. This name is the prefix for the names of all training jobs that this tuning job launches. The name must be unique within the same Amazon Web Services account and Amazon Web Services Region. The name must have 1 to 32 characters. Valid characters are a-z, A-Z, 0-9, and : + = @ _ % - (hyphen). The name is not case sensitive.
', 'DescribeHyperParameterTuningJobRequest$HyperParameterTuningJobName' => 'The name of the tuning job.
', 'DescribeHyperParameterTuningJobResponse$HyperParameterTuningJobName' => 'The name of the hyperparameter tuning job.
', 'HyperParameterTrainingJobSummary$TuningJobName' => 'The HyperParameter tuning job that launched the training job.
', 'HyperParameterTuningJobSearchEntity$HyperParameterTuningJobName' => 'The name of a hyperparameter tuning job.
', 'HyperParameterTuningJobSummary$HyperParameterTuningJobName' => 'The name of the tuning job.
', 'ListTrainingJobsForHyperParameterTuningJobRequest$HyperParameterTuningJobName' => 'The name of the tuning job whose training jobs you want to list.
', 'ParentHyperParameterTuningJob$HyperParameterTuningJobName' => 'The name of the hyperparameter tuning job to be used as a starting point for a new hyperparameter tuning job.
', 'StopHyperParameterTuningJobRequest$HyperParameterTuningJobName' => 'The name of the tuning job to stop.
', ], ], 'HyperParameterTuningJobObjective' => [ 'base' => 'Defines the objective metric for a hyperparameter tuning job. Hyperparameter tuning uses the value of this metric to evaluate the training jobs it launches, and returns the training job that results in either the highest or lowest value for this metric, depending on the value you specify for the Type parameter. If you want to define a custom objective metric, see Define metrics and environment variables.
The HyperParameterTuningJobObjective specifies the objective metric used to evaluate the performance of training jobs launched by this tuning job.
', 'HyperParameterTuningJobObjectives$member' => NULL, ], ], 'HyperParameterTuningJobObjectiveType' => [ 'base' => NULL, 'refs' => [ 'FinalHyperParameterTuningJobObjectiveMetric$Type' => 'Select if you want to minimize or maximize the objective metric during hyperparameter tuning.
', 'HyperParameterTuningJobObjective$Type' => 'Whether to minimize or maximize the objective metric.
', ], ], 'HyperParameterTuningJobObjectives' => [ 'base' => NULL, 'refs' => [ 'TrainingSpecification$SupportedTuningJobObjectiveMetrics' => 'A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.
', ], ], 'HyperParameterTuningJobSearchEntity' => [ 'base' => 'An entity returned by the SearchRecord API containing the properties of a hyperparameter tuning job.
', 'refs' => [ 'SearchRecord$HyperParameterTuningJob' => 'The properties of a hyperparameter tuning job.
', ], ], 'HyperParameterTuningJobSortByOptions' => [ 'base' => NULL, 'refs' => [ 'ListHyperParameterTuningJobsRequest$SortBy' => 'The field to sort results by. The default is Name.
The status of the tuning job: InProgress, Completed, Failed, Stopping, or Stopped.
', 'HyperParameterTuningJobSearchEntity$HyperParameterTuningJobStatus' => 'The status of a hyperparameter tuning job.
', 'HyperParameterTuningJobSummary$HyperParameterTuningJobStatus' => 'The status of the tuning job.
', 'ListHyperParameterTuningJobsRequest$StatusEquals' => 'A filter that returns only tuning jobs with the specified status.
', ], ], 'HyperParameterTuningJobStrategyConfig' => [ 'base' => 'The configuration for a training job launched by a hyperparameter tuning job. Choose Bayesian for Bayesian optimization, and Random for random search optimization. For more advanced use cases, use Hyperband, which evaluates objective metrics for training jobs after every epoch. For more information about strategies, see How Hyperparameter Tuning Works.
The configuration for the Hyperband optimization strategy. This parameter should be provided only if Hyperband is selected as the strategy for HyperParameterTuningJobConfig.
The strategy hyperparameter tuning uses to find the best combination of hyperparameters for your model.
', 'refs' => [ 'HyperParameterTuningJobConfig$Strategy' => 'Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training job it launches. For information about search strategies, see How Hyperparameter Tuning Works.
', 'HyperParameterTuningJobSummary$Strategy' => 'Specifies the search strategy hyperparameter tuning uses to choose which hyperparameters to evaluate at each iteration.
', ], ], 'HyperParameterTuningJobSummaries' => [ 'base' => NULL, 'refs' => [ 'ListHyperParameterTuningJobsResponse$HyperParameterTuningJobSummaries' => 'A list of HyperParameterTuningJobSummary objects that describe the tuning jobs that the ListHyperParameterTuningJobs request returned.
Provides summary information about a hyperparameter tuning job.
', 'refs' => [ 'HyperParameterTuningJobSummaries$member' => NULL, ], ], 'HyperParameterTuningJobWarmStartConfig' => [ 'base' => 'Specifies the configuration for a hyperparameter tuning job that uses one or more previous hyperparameter tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.
All training jobs launched by the new hyperparameter tuning job are evaluated by using the objective metric, and the training job that performs the best is compared to the best training jobs from the parent tuning jobs. From these, the training job that performs the best as measured by the objective metric is returned as the overall best training job.
All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.
Specifies the configuration for starting the hyperparameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.
All training jobs launched by the new hyperparameter tuning job are evaluated by using the objective metric. If you specify IDENTICAL_DATA_AND_ALGORITHM as the WarmStartType value for the warm start configuration, the training job that performs the best in the new tuning job is compared to the best training jobs from the parent tuning jobs. From these, the training job that performs the best as measured by the objective metric is returned as the overall best training job.
All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.
The configuration for starting the hyperparameter parameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.
', 'HyperParameterTuningJobSearchEntity$WarmStartConfig' => NULL, ], ], 'HyperParameterTuningJobWarmStartType' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTuningJobWarmStartConfig$WarmStartType' => 'Specifies one of the following:
The new hyperparameter tuning job uses the same input data and training image as the parent tuning jobs. You can change the hyperparameter ranges to search and the maximum number of training jobs that the hyperparameter tuning job launches. You cannot use a new version of the training algorithm, unless the changes in the new version do not affect the algorithm itself. For example, changes that improve logging or adding support for a different data format are allowed. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.
The new hyperparameter tuning job can include input data, hyperparameter ranges, maximum number of concurrent training jobs, and maximum number of training jobs that are different than those of its parent hyperparameter tuning jobs. The training image can also be a different version from the version used in the parent hyperparameter tuning job. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.
The maximum time in seconds that a hyperparameter tuning job can run.
', ], ], 'HyperParameterTuningResourceConfig' => [ 'base' => 'The configuration of resources, including compute instances and storage volumes for use in training jobs launched by hyperparameter tuning jobs. HyperParameterTuningResourceConfig is similar to ResourceConfig, but has the additional InstanceConfigs and AllocationStrategy fields to allow for flexible instance management. Specify one or more instance types, count, and the allocation strategy for instance selection.
HyperParameterTuningResourceConfig supports the capabilities of ResourceConfig with the exception of KeepAlivePeriodInSeconds. Hyperparameter tuning jobs use warm pools by default, which reuse clusters between training jobs.
The configuration for the hyperparameter tuning resources, including the compute instances and storage volumes, used for training jobs launched by the tuning job. By default, storage volumes hold model artifacts and incremental states. Choose File for TrainingInputMode in the AlgorithmSpecification parameter to additionally store training data in the storage volume (optional).
The default value for this hyperparameter. If a default value is specified, a hyperparameter cannot be required.
', 'HyperParameters$value' => NULL, ], ], 'HyperParameters' => [ 'base' => NULL, 'refs' => [ 'CreateTrainingJobRequest$HyperParameters' => 'Algorithm-specific parameters that influence the quality of the model. You set hyperparameters before you start the learning process. For a list of hyperparameters for each training algorithm provided by SageMaker, see Algorithms.
You can specify a maximum of 100 hyperparameters. Each hyperparameter is a key-value pair. Each key and value is limited to 256 characters, as specified by the Length Constraint.
Do not include any security-sensitive information including account access IDs, secrets or tokens in any hyperparameter field. If the use of security-sensitive credentials are detected, SageMaker will reject your training job request and return an exception error.
Algorithm-specific parameters.
', 'HyperParameterTrainingJobDefinition$StaticHyperParameters' => 'Specifies the values of hyperparameters that do not change for the tuning job.
', 'HyperParameterTrainingJobSummary$TunedHyperParameters' => 'A list of the hyperparameters for which you specified ranges to search.
', 'TrainingJob$HyperParameters' => 'Algorithm-specific parameters.
', 'TrainingJobDefinition$HyperParameters' => 'The hyperparameters used for the training job.
', ], ], 'HyperbandStrategyConfig' => [ 'base' => 'The configuration for Hyperband, a multi-fidelity based hyperparameter tuning strategy. Hyperband uses the final and intermediate results of a training job to dynamically allocate resources to utilized hyperparameter configurations while automatically stopping under-performing configurations. This parameter should be provided only if Hyperband is selected as the StrategyConfig under the HyperParameterTuningJobConfig API.
The configuration for the object that specifies the Hyperband strategy. This parameter is only supported for the Hyperband selection for Strategy within the HyperParameterTuningJobConfig API.
The maximum number of resources (such as epochs) that can be used by a training job launched by a hyperparameter tuning job. Once a job reaches the MaxResource value, it is stopped. If a value for MaxResource is not provided, and Hyperband is selected as the hyperparameter tuning strategy, HyperbandTrainingJ attempts to infer MaxResource from the following keys (if present) in StaticsHyperParameters:
epochs
numepochs
n-epochs
n_epochs
num_epochs
If HyperbandStrategyConfig is unable to infer a value for MaxResource, it generates a validation error. The maximum value is 20,000 epochs. All metrics that correspond to an objective metric are used to derive early stopping decisions. For distributive training jobs, ensure that duplicate metrics are not printed in the logs across the individual nodes in a training job. If multiple nodes are publishing duplicate or incorrect metrics, training jobs may make an incorrect stopping decision and stop the job prematurely.
The minimum number of resources (such as epochs) that can be used by a training job launched by a hyperparameter tuning job. If the value for MinResource has not been reached, the training job is not stopped by Hyperband.
The IAM Identity details associated with the user. These details are associated with model package groups, model packages and project entities only.
', 'refs' => [ 'UserContext$IamIdentity' => 'The IAM Identity details associated with the user. These details are associated with model package groups, model packages, and project entities only.
', ], ], 'IdempotencyToken' => [ 'base' => NULL, 'refs' => [ 'CreatePipelineRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
', 'DeletePipelineRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
', 'RetryPipelineExecutionRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.
', 'SendPipelineExecutionStepFailureRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
', 'SendPipelineExecutionStepSuccessRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
', 'StartPipelineExecutionRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.
', 'StopPipelineExecutionRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.
', ], ], 'IdentityProviderOAuthSetting' => [ 'base' => 'The Amazon SageMaker Canvas application setting where you configure OAuth for connecting to an external data source, such as Snowflake.
', 'refs' => [ 'IdentityProviderOAuthSettings$member' => NULL, ], ], 'IdentityProviderOAuthSettings' => [ 'base' => NULL, 'refs' => [ 'CanvasAppSettings$IdentityProviderOAuthSettings' => 'The settings for connecting to an external data source with OAuth.
', ], ], 'Image' => [ 'base' => 'A SageMaker image. A SageMaker image represents a set of container images that are derived from a common base container image. Each of these container images is represented by a SageMaker ImageVersion.
The ARN of the image.
', 'DescribeImageResponse$ImageArn' => 'The ARN of the image.
', 'DescribeImageVersionResponse$ImageArn' => 'The ARN of the image the version is based on.
', 'Image$ImageArn' => 'The ARN of the image.
', 'ImageVersion$ImageArn' => 'The ARN of the image the version is based on.
', 'ResourceSpec$SageMakerImageArn' => 'The ARN of the SageMaker image that the image version belongs to.
', 'UpdateImageResponse$ImageArn' => 'The ARN of the image.
', ], ], 'ImageBaseImage' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$BaseImage' => 'The registry path of the container image to use as the starting point for this version. The path is an Amazon Elastic Container Registry (ECR) URI in the following format:
<acct-id>.dkr.ecr.<region>.amazonaws.com/<repo-name[:tag] or [@digest]>
The registry path of the container image on which this image version is based.
', ], ], 'ImageClassificationJobConfig' => [ 'base' => 'The collection of settings used by an AutoML job V2 for the image classification problem type.
', 'refs' => [ 'AutoMLProblemTypeConfig$ImageClassificationJobConfig' => 'Settings used to configure an AutoML job V2 for the image classification problem type.
', ], ], 'ImageConfig' => [ 'base' => 'Specifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon Virtual Private Cloud (VPC).
', 'refs' => [ 'ContainerDefinition$ImageConfig' => 'Specifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon Virtual Private Cloud (VPC). For information about storing containers in a private Docker registry, see Use a Private Docker Registry for Real-Time Inference Containers.
The model artifacts in an Amazon S3 bucket and the Docker image for inference container in Amazon EC2 Container Registry must be in the same region as the model or endpoint you are creating.
The registry path of the container image that contains this image version.
', ], ], 'ImageDeleteProperty' => [ 'base' => NULL, 'refs' => [ 'ImageDeletePropertyList$member' => NULL, ], ], 'ImageDeletePropertyList' => [ 'base' => NULL, 'refs' => [ 'UpdateImageRequest$DeleteProperties' => 'A list of properties to delete. Only the Description and DisplayName properties can be deleted.
The description of the image.
', 'DescribeImageResponse$Description' => 'The description of the image.
', 'Image$Description' => 'The description of the image.
', 'UpdateImageRequest$Description' => 'The new description for the image.
', ], ], 'ImageDigest' => [ 'base' => NULL, 'refs' => [ 'ModelPackageContainerDefinition$ImageDigest' => 'An MD5 hash of the training algorithm that identifies the Docker image used for training.
', 'TrainingSpecification$TrainingImageDigest' => 'An MD5 hash of the training algorithm that identifies the Docker image used for training.
', ], ], 'ImageDisplayName' => [ 'base' => NULL, 'refs' => [ 'CreateImageRequest$DisplayName' => 'The display name of the image. If not provided, ImageName is displayed.
The name of the image as displayed.
', 'Image$DisplayName' => 'The name of the image as displayed.
', 'UpdateImageRequest$DisplayName' => 'The new display name for the image.
', ], ], 'ImageName' => [ 'base' => NULL, 'refs' => [ 'CreateImageRequest$ImageName' => 'The name of the image. Must be unique to your account.
', 'CreateImageVersionRequest$ImageName' => 'The ImageName of the Image to create a version of.
The name of the CustomImage. Must be unique to your account.
', 'DeleteImageRequest$ImageName' => 'The name of the image to delete.
', 'DeleteImageVersionRequest$ImageName' => 'The name of the image to delete.
', 'DescribeImageRequest$ImageName' => 'The name of the image to describe.
', 'DescribeImageResponse$ImageName' => 'The name of the image.
', 'DescribeImageVersionRequest$ImageName' => 'The name of the image.
', 'Image$ImageName' => 'The name of the image.
', 'ListAliasesRequest$ImageName' => 'The name of the image.
', 'ListImageVersionsRequest$ImageName' => 'The name of the image to list the versions of.
', 'UpdateImageRequest$ImageName' => 'The name of the image to update.
', 'UpdateImageVersionRequest$ImageName' => 'The name of the image.
', ], ], 'ImageNameContains' => [ 'base' => NULL, 'refs' => [ 'ListImagesRequest$NameContains' => 'A filter that returns only images whose name contains the specified string.
', ], ], 'ImageSortBy' => [ 'base' => NULL, 'refs' => [ 'ListImagesRequest$SortBy' => 'The property used to sort results. The default value is CREATION_TIME.
The sort order. The default value is DESCENDING.
The status of the image.
', 'Image$ImageStatus' => 'The status of the image.
', ], ], 'ImageUri' => [ 'base' => NULL, 'refs' => [ 'AppSpecification$ImageUri' => 'The container image to be run by the processing job.
', 'DataQualityAppSpecification$ImageUri' => 'The container image that the data quality monitoring job runs.
', 'ModelBiasAppSpecification$ImageUri' => 'The container image to be run by the model bias job.
', 'ModelExplainabilityAppSpecification$ImageUri' => 'The container image to be run by the model explainability job.
', 'ModelQualityAppSpecification$ImageUri' => 'The address of the container image that the monitoring job runs.
', 'MonitoringAppSpecification$ImageUri' => 'The container image to be run by the monitoring job.
', ], ], 'ImageVersion' => [ 'base' => 'A version of a SageMaker Image. A version represents an existing container image.
The ARN of the image version.
', 'DescribeImageVersionResponse$ImageVersionArn' => 'The ARN of the version.
', 'ImageVersion$ImageVersionArn' => 'The ARN of the version.
', 'ResourceSpec$SageMakerImageVersionArn' => 'The ARN of the image version created on the instance.
', 'UpdateImageVersionResponse$ImageVersionArn' => 'The ARN of the image version.
', ], ], 'ImageVersionNumber' => [ 'base' => NULL, 'refs' => [ 'CustomImage$ImageVersionNumber' => 'The version number of the CustomImage.
', 'DeleteImageVersionRequest$Version' => 'The version to delete.
', 'DescribeImageVersionRequest$Version' => 'The version of the image. If not specified, the latest version is described.
', 'DescribeImageVersionResponse$Version' => 'The version number.
', 'ImageVersion$Version' => 'The version number.
', 'ListAliasesRequest$Version' => 'The version of the image. If image version is not specified, the aliases of all versions of the image are listed.
', 'UpdateImageVersionRequest$Version' => 'The version of the image.
', ], ], 'ImageVersionSortBy' => [ 'base' => NULL, 'refs' => [ 'ListImageVersionsRequest$SortBy' => 'The property used to sort results. The default value is CREATION_TIME.
The sort order. The default value is DESCENDING.
The status of the version.
', 'ImageVersion$ImageVersionStatus' => 'The status of the version.
', ], ], 'ImageVersions' => [ 'base' => NULL, 'refs' => [ 'ListImageVersionsResponse$ImageVersions' => 'A list of versions and their properties.
', ], ], 'Images' => [ 'base' => NULL, 'refs' => [ 'ListImagesResponse$Images' => 'A list of images and their properties.
', ], ], 'ImportHubContentRequest' => [ 'base' => NULL, 'refs' => [], ], 'ImportHubContentResponse' => [ 'base' => NULL, 'refs' => [], ], 'InferenceExecutionConfig' => [ 'base' => 'Specifies details about how containers in a multi-container endpoint are run.
', 'refs' => [ 'CreateModelInput$InferenceExecutionConfig' => 'Specifies details of how containers in a multi-container endpoint are called.
', 'DescribeModelOutput$InferenceExecutionConfig' => 'Specifies details of how containers in a multi-container endpoint are called.
', 'Model$InferenceExecutionConfig' => NULL, ], ], 'InferenceExecutionMode' => [ 'base' => NULL, 'refs' => [ 'InferenceExecutionConfig$Mode' => 'How containers in a multi-container are run. The following values are valid.
SERIAL - Containers run as a serial pipeline.
DIRECT - Only the individual container that you specify is run.
The ARN for your inference experiment.
', 'DeleteInferenceExperimentResponse$InferenceExperimentArn' => 'The ARN of the deleted inference experiment.
', 'DescribeInferenceExperimentResponse$Arn' => 'The ARN of the inference experiment being described.
', 'StartInferenceExperimentResponse$InferenceExperimentArn' => 'The ARN of the started inference experiment to start.
', 'StopInferenceExperimentResponse$InferenceExperimentArn' => 'The ARN of the stopped inference experiment.
', 'UpdateInferenceExperimentResponse$InferenceExperimentArn' => 'The ARN of the updated inference experiment.
', ], ], 'InferenceExperimentDataStorageConfig' => [ 'base' => 'The Amazon S3 location and configuration for storing inference request and response data.
', 'refs' => [ 'CreateInferenceExperimentRequest$DataStorageConfig' => 'The Amazon S3 location and configuration for storing inference request and response data.
This is an optional parameter that you can use for data capture. For more information, see Capture data.
', 'DescribeInferenceExperimentResponse$DataStorageConfig' => 'The Amazon S3 location and configuration for storing inference request and response data.
', 'UpdateInferenceExperimentRequest$DataStorageConfig' => 'The Amazon S3 location and configuration for storing inference request and response data.
', ], ], 'InferenceExperimentDescription' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceExperimentRequest$Description' => 'A description for the inference experiment.
', 'DescribeInferenceExperimentResponse$Description' => 'The description of the inference experiment.
', 'InferenceExperimentSummary$Description' => 'The description of the inference experiment.
', 'UpdateInferenceExperimentRequest$Description' => 'The description of the inference experiment.
', ], ], 'InferenceExperimentList' => [ 'base' => NULL, 'refs' => [ 'ListInferenceExperimentsResponse$InferenceExperiments' => 'List of inference experiments.
', ], ], 'InferenceExperimentName' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceExperimentRequest$Name' => 'The name for the inference experiment.
', 'DeleteInferenceExperimentRequest$Name' => 'The name of the inference experiment you want to delete.
', 'DescribeInferenceExperimentRequest$Name' => 'The name of the inference experiment to describe.
', 'DescribeInferenceExperimentResponse$Name' => 'The name of the inference experiment.
', 'InferenceExperimentSummary$Name' => 'The name of the inference experiment.
', 'StartInferenceExperimentRequest$Name' => 'The name of the inference experiment to start.
', 'StopInferenceExperimentRequest$Name' => 'The name of the inference experiment to stop.
', 'UpdateInferenceExperimentRequest$Name' => 'The name of the inference experiment to be updated.
', ], ], 'InferenceExperimentSchedule' => [ 'base' => 'The start and end times of an inference experiment.
The maximum duration that you can set for an inference experiment is 30 days.
', 'refs' => [ 'CreateInferenceExperimentRequest$Schedule' => 'The duration for which you want the inference experiment to run. If you don\'t specify this field, the experiment automatically starts immediately upon creation and concludes after 7 days.
', 'DescribeInferenceExperimentResponse$Schedule' => 'The duration for which the inference experiment ran or will run.
', 'InferenceExperimentSummary$Schedule' => 'The duration for which the inference experiment ran or will run.
The maximum duration that you can set for an inference experiment is 30 days.
', 'UpdateInferenceExperimentRequest$Schedule' => ' The duration for which the inference experiment will run. If the status of the inference experiment is Created, then you can update both the start and end dates. If the status of the inference experiment is Running, then you can update only the end date.
The status of the inference experiment. The following are the possible statuses for an inference experiment:
Creating - Amazon SageMaker is creating your experiment.
Created - Amazon SageMaker has finished the creation of your experiment and will begin the experiment at the scheduled time.
Updating - When you make changes to your experiment, your experiment shows as updating.
Starting - Amazon SageMaker is beginning your experiment.
Running - Your experiment is in progress.
Stopping - Amazon SageMaker is stopping your experiment.
Completed - Your experiment has completed.
Cancelled - When you conclude your experiment early using the StopInferenceExperiment API, or if any operation fails with an unexpected error, it shows as cancelled.
The status of the inference experiment.
', 'ListInferenceExperimentsRequest$StatusEquals' => 'Selects inference experiments which are in this status. For the possible statuses, see DescribeInferenceExperiment.
', ], ], 'InferenceExperimentStatusReason' => [ 'base' => NULL, 'refs' => [ 'DescribeInferenceExperimentResponse$StatusReason' => ' The error message or client-specified Reason from the StopInferenceExperiment API, that explains the status of the inference experiment.
The error message for the inference experiment status result.
', 'StopInferenceExperimentRequest$Reason' => 'The reason for stopping the experiment.
', ], ], 'InferenceExperimentStopDesiredState' => [ 'base' => NULL, 'refs' => [ 'StopInferenceExperimentRequest$DesiredState' => 'The desired state of the experiment after stopping. The possible states are the following:
Completed: The experiment completed successfully
Cancelled: The experiment was canceled
Lists a summary of properties of an inference experiment.
', 'refs' => [ 'InferenceExperimentList$member' => NULL, ], ], 'InferenceExperimentType' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceExperimentRequest$Type' => 'The type of the inference experiment that you want to run. The following types of experiments are possible:
ShadowMode: You can use this type to validate a shadow variant. For more information, see Shadow tests.
The type of the inference experiment.
', 'InferenceExperimentSummary$Type' => 'The type of the inference experiment.
', 'ListInferenceExperimentsRequest$Type' => 'Selects inference experiments of this type. For the possible types of inference experiments, see CreateInferenceExperiment.
', ], ], 'InferenceImage' => [ 'base' => NULL, 'refs' => [ 'DescribeCompilationJobResponse$InferenceImage' => 'The inference image to use when compiling a model. Specify an image only if the target device is a cloud instance.
', ], ], 'InferenceMetrics' => [ 'base' => 'The metrics for an existing endpoint compared in an Inference Recommender job.
', 'refs' => [ 'EndpointPerformance$Metrics' => 'The metrics for an existing endpoint.
', 'RecommendationJobInferenceBenchmark$EndpointMetrics' => NULL, ], ], 'InferenceRecommendation' => [ 'base' => 'A list of recommendations made by Amazon SageMaker Inference Recommender.
', 'refs' => [ 'InferenceRecommendations$member' => NULL, ], ], 'InferenceRecommendations' => [ 'base' => NULL, 'refs' => [ 'DescribeInferenceRecommendationsJobResponse$InferenceRecommendations' => 'The recommendations made by Inference Recommender.
', ], ], 'InferenceRecommendationsJob' => [ 'base' => 'A structure that contains a list of recommendation jobs.
', 'refs' => [ 'InferenceRecommendationsJobs$member' => NULL, ], ], 'InferenceRecommendationsJobStep' => [ 'base' => 'A returned array object for the Steps response field in the ListInferenceRecommendationsJobSteps API command.
A list of all subtask details in Inference Recommender.
', ], ], 'InferenceRecommendationsJobs' => [ 'base' => NULL, 'refs' => [ 'ListInferenceRecommendationsJobsResponse$InferenceRecommendationsJobs' => 'The recommendations created from the Amazon SageMaker Inference Recommender job.
', ], ], 'InferenceSpecification' => [ 'base' => 'Defines how to perform inference generation after a training job is run.
', 'refs' => [ 'BatchDescribeModelPackageSummary$InferenceSpecification' => NULL, 'CreateAlgorithmInput$InferenceSpecification' => 'Specifies details about inference jobs that the algorithm runs, including the following:
The Amazon ECR paths of containers that contain the inference code and model artifacts.
The instance types that the algorithm supports for transform jobs and real-time endpoints used for inference.
The input and output content formats that the algorithm supports for inference.
Specifies details about inference jobs that can be run with models based on this model package, including the following:
The Amazon ECR paths of containers that contain the inference code and model artifacts.
The instance types that the model package supports for transform jobs and real-time endpoints used for inference.
The input and output content formats that the model package supports for inference.
Details about inference jobs that the algorithm runs.
', 'DescribeModelPackageOutput$InferenceSpecification' => 'Details about inference jobs that can be run with models based on this model package.
', 'ModelPackage$InferenceSpecification' => 'Defines how to perform inference generation after a training job is run.
', ], ], 'InferenceSpecificationName' => [ 'base' => NULL, 'refs' => [ 'ContainerDefinition$InferenceSpecificationName' => 'The inference specification name in the model package version.
', 'EndpointInputConfiguration$InferenceSpecificationName' => 'The inference specification name in the model package version.
', 'ModelConfiguration$InferenceSpecificationName' => 'The inference specification name in the model package version.
', ], ], 'InitialInstanceCount' => [ 'base' => NULL, 'refs' => [ 'EndpointOutputConfiguration$InitialInstanceCount' => 'The number of instances recommended to launch initially.
', ], ], 'InitialNumberOfUsers' => [ 'base' => NULL, 'refs' => [ 'Phase$InitialNumberOfUsers' => 'Specifies how many concurrent users to start with. The value should be between 1 and 3.
', ], ], 'InitialTaskCount' => [ 'base' => NULL, 'refs' => [ 'ProductionVariant$InitialInstanceCount' => 'Number of instances to launch initially.
', ], ], 'InputConfig' => [ 'base' => 'Contains information about the location of input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.
', 'refs' => [ 'CreateCompilationJobRequest$InputConfig' => 'Provides information about the location of input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.
', 'DescribeCompilationJobResponse$InputConfig' => 'Information about the location in Amazon S3 of the input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.
', ], ], 'InputDataConfig' => [ 'base' => NULL, 'refs' => [ 'CreateTrainingJobRequest$InputDataConfig' => 'An array of Channel objects. Each channel is a named input source. InputDataConfig describes the input data and its location.
Algorithms can accept input data from one or more channels. For example, an algorithm might have two channels of input data, training_data and validation_data. The configuration for each channel provides the S3, EFS, or FSx location where the input data is stored. It also provides information about the stored data: the MIME type, compression method, and whether the data is wrapped in RecordIO format.
Depending on the input mode that the algorithm supports, SageMaker either copies input data files from an S3 bucket to a local directory in the Docker container, or makes it available as input streams. For example, if you specify an EFS location, input data files are available as input streams. They do not need to be downloaded.
Your input must be in the same Amazon Web Services region as your training job.
', 'DescribeTrainingJobResponse$InputDataConfig' => 'An array of Channel objects that describes each data input channel.
An array of Channel objects that specify the input for the training jobs that the tuning job launches.
', 'TrainingJob$InputDataConfig' => 'An array of Channel objects that describes each data input channel.
Your input must be in the same Amazon Web Services region as your training job.
', 'TrainingJobDefinition$InputDataConfig' => 'An array of Channel objects, each of which specifies an input source.
Whether to use File or Pipe input mode. In File (default) mode, Amazon SageMaker copies the data from the input source onto the local Amazon Elastic Block Store (Amazon EBS) volumes before starting your training algorithm. This is the most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your algorithm without using the EBS volume.
The allowed input mode, either FILE or PIPE.
In FILE mode, Amazon SageMaker copies the data from the input source onto the local Amazon Elastic Block Store (Amazon EBS) volumes before starting your training algorithm. This is the most commonly used input mode.
In PIPE mode, Amazon SageMaker streams input data from the source directly to your algorithm without using the EBS volume.
', ], ], 'InstanceGroup' => [ 'base' => 'Defines an instance group for heterogeneous cluster training. When requesting a training job using the CreateTrainingJob API, you can configure multiple instance groups .
', 'refs' => [ 'InstanceGroups$member' => NULL, ], ], 'InstanceGroupName' => [ 'base' => NULL, 'refs' => [ 'InstanceGroup$InstanceGroupName' => 'Specifies the name of the instance group.
', 'InstanceGroupNames$member' => NULL, ], ], 'InstanceGroupNames' => [ 'base' => NULL, 'refs' => [ 'S3DataSource$InstanceGroupNames' => 'A list of names of instance groups that get data from the S3 data source.
', ], ], 'InstanceGroups' => [ 'base' => NULL, 'refs' => [ 'ResourceConfig$InstanceGroups' => 'The configuration of a heterogeneous cluster in JSON format.
', ], ], 'InstanceMetadataServiceConfiguration' => [ 'base' => 'Information on the IMDS configuration of the notebook instance
', 'refs' => [ 'CreateNotebookInstanceInput$InstanceMetadataServiceConfiguration' => 'Information on the IMDS configuration of the notebook instance
', 'DescribeNotebookInstanceOutput$InstanceMetadataServiceConfiguration' => 'Information on the IMDS configuration of the notebook instance
', 'UpdateNotebookInstanceInput$InstanceMetadataServiceConfiguration' => 'Information on the IMDS configuration of the notebook instance
', ], ], 'InstanceType' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$InstanceType' => 'The type of ML compute instance to launch for the notebook instance.
', 'DescribeNotebookInstanceOutput$InstanceType' => 'The type of ML compute instance running on the notebook instance.
', 'NotebookInstanceSummary$InstanceType' => 'The type of ML compute instance that the notebook instance is running on.
', 'RealTimeInferenceConfig$InstanceType' => 'The instance type the model is deployed to.
', 'UpdateNotebookInstanceInput$InstanceType' => 'The Amazon ML compute instance type.
', ], ], 'Integer' => [ 'base' => NULL, 'refs' => [ 'CreateModelCardExportJobRequest$ModelCardVersion' => 'The version of the model card to export. If a version is not provided, then the latest version of the model card is exported.
', 'DescribeDeviceResponse$MaxModels' => 'The maximum number of models.
', 'DescribeEdgeDeploymentPlanResponse$EdgeDeploymentSuccess' => 'The number of edge devices with the successful deployment.
', 'DescribeEdgeDeploymentPlanResponse$EdgeDeploymentPending' => 'The number of edge devices yet to pick up deployment, or in progress.
', 'DescribeEdgeDeploymentPlanResponse$EdgeDeploymentFailed' => 'The number of edge devices that failed the deployment.
', 'DescribeModelCardExportJobResponse$ModelCardVersion' => 'The version of the model card that the model export job exports.
', 'DescribeModelCardRequest$ModelCardVersion' => 'The version of the model card to describe. If a version is not provided, then the latest version of the model card is described.
', 'DescribeModelCardResponse$ModelCardVersion' => 'The version of the model card.
', 'DynamicScalingConfiguration$MinCapacity' => 'The recommended minimum capacity to specify for your autoscaling policy.
', 'DynamicScalingConfiguration$MaxCapacity' => 'The recommended maximum capacity to specify for your autoscaling policy.
', 'DynamicScalingConfiguration$ScaleInCooldown' => 'The recommended scale in cooldown time for your autoscaling policy.
', 'DynamicScalingConfiguration$ScaleOutCooldown' => 'The recommended scale out cooldown time for your autoscaling policy.
', 'EdgeDeploymentPlanSummary$EdgeDeploymentSuccess' => 'The number of edge devices with the successful deployment.
', 'EdgeDeploymentPlanSummary$EdgeDeploymentPending' => 'The number of edge devices yet to pick up the deployment, or in progress.
', 'EdgeDeploymentPlanSummary$EdgeDeploymentFailed' => 'The number of edge devices that failed the deployment.
', 'EdgeDeploymentStatus$EdgeDeploymentSuccessInStage' => 'The number of edge devices with the successful deployment in the current stage.
', 'EdgeDeploymentStatus$EdgeDeploymentPendingInStage' => 'The number of edge devices yet to pick up the deployment in current stage, or in progress.
', 'EdgeDeploymentStatus$EdgeDeploymentFailedInStage' => 'The number of edge devices that failed the deployment in current stage.
', 'HyperParameterTuningJobCompletionDetails$NumberOfTrainingJobsObjectiveNotImproving' => 'The number of training jobs launched by a tuning job that are not improving (1% or less) as measured by model performance evaluated against an objective function.
', 'HyperParameterTuningJobConsumedResources$RuntimeInSeconds' => 'The wall clock runtime in seconds used by your hyperparameter tuning job.
', 'InferenceMetrics$MaxInvocations' => 'The expected maximum number of requests per minute for the instance.
', 'InferenceMetrics$ModelLatency' => 'The expected model latency at maximum invocations per minute for the instance.
', 'ListModelCardExportJobsRequest$ModelCardVersion' => 'List export jobs for the model card with the specified version.
', 'ModelCard$ModelCardVersion' => 'The version of the model card.
', 'ModelCardExportJobSummary$ModelCardVersion' => 'The version of the model card that the export job exports.
', 'ModelCardVersionSummary$ModelCardVersion' => 'A version of the model card.
', 'ModelDashboardModelCard$ModelCardVersion' => 'The model card version.
', 'ModelLatencyThreshold$ValueInMilliseconds' => 'The model latency percentile value in milliseconds.
', 'RecommendationJobStoppingConditions$MaxInvocations' => 'The maximum number of requests per minute expected for the endpoint.
', 'RecommendationMetrics$MaxInvocations' => 'The expected maximum number of requests per minute for the instance.
', 'RecommendationMetrics$ModelLatency' => 'The expected model latency at maximum invocation per minute for the instance.
', 'ScalingPolicyMetric$InvocationsPerInstance' => 'The number of invocations sent to a model, normalized by InstanceCount in each ProductionVariant. 1/numberOfInstances is sent as the value on each request, where numberOfInstances is the number of active instances for the ProductionVariant behind the endpoint at the time of the request.
The interval of time taken by a model to respond as viewed from SageMaker. This interval includes the local communication times taken to send the request and to fetch the response from the container of a model and the time taken to complete the inference in the container.
', 'ScalingPolicyObjective$MinInvocationsPerMinute' => 'The minimum number of expected requests to your endpoint per minute.
', 'ScalingPolicyObjective$MaxInvocationsPerMinute' => 'The maximum number of expected requests to your endpoint per minute.
', ], ], 'IntegerParameterRange' => [ 'base' => 'For a hyperparameter of the integer type, specifies the range that a hyperparameter tuning job searches.
', 'refs' => [ 'IntegerParameterRanges$member' => NULL, ], ], 'IntegerParameterRangeSpecification' => [ 'base' => 'Defines the possible values for an integer hyperparameter.
', 'refs' => [ 'ParameterRange$IntegerParameterRangeSpecification' => 'A IntegerParameterRangeSpecification object that defines the possible values for an integer hyperparameter.
The array of IntegerParameterRange objects that specify ranges of integer hyperparameters that a hyperparameter tuning job searches.
', ], ], 'IntegerValue' => [ 'base' => NULL, 'refs' => [ 'PipelineExecutionStep$AttemptCount' => 'The current attempt of the execution step. For more information, see Retry Policy for SageMaker Pipelines steps.
', ], ], 'InvocationEndTime' => [ 'base' => NULL, 'refs' => [ 'InferenceRecommendation$InvocationEndTime' => 'A timestamp that shows when the benchmark completed.
', 'RecommendationJobInferenceBenchmark$InvocationEndTime' => 'A timestamp that shows when the benchmark completed.
', ], ], 'InvocationStartTime' => [ 'base' => NULL, 'refs' => [ 'InferenceRecommendation$InvocationStartTime' => 'A timestamp that shows when the benchmark started.
', 'RecommendationJobInferenceBenchmark$InvocationStartTime' => 'A timestamp that shows when the benchmark started.
', ], ], 'InvocationsMaxRetries' => [ 'base' => NULL, 'refs' => [ 'ModelClientConfig$InvocationsMaxRetries' => 'The maximum number of retries when invocation requests are failing. The default value is 3.
', ], ], 'InvocationsTimeoutInSeconds' => [ 'base' => NULL, 'refs' => [ 'ModelClientConfig$InvocationsTimeoutInSeconds' => 'The timeout value in seconds for an invocation request. The default value is 600.
', ], ], 'IotRoleAlias' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceFleetResponse$IotRoleAlias' => 'The Amazon Resource Name (ARN) alias created in Amazon Web Services Internet of Things (IoT).
', ], ], 'ItemIdentifierAttributeName' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesConfig$ItemIdentifierAttributeName' => 'The name of the column that represents the set of item identifiers for which you want to predict the target value.
', ], ], 'JobDurationInSeconds' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobInputConfig$JobDurationInSeconds' => 'Specifies the maximum duration of the job, in seconds. The maximum value is 18,000 seconds.
', ], ], 'JobReferenceCode' => [ 'base' => NULL, 'refs' => [ 'DescribeLabelingJobResponse$JobReferenceCode' => 'A unique identifier for work done as part of a labeling job.
', 'LabelingJobForWorkteamSummary$JobReferenceCode' => 'A unique identifier for a labeling job. You can use this to refer to a specific labeling job.
', ], ], 'JobReferenceCodeContains' => [ 'base' => NULL, 'refs' => [ 'ListLabelingJobsForWorkteamRequest$JobReferenceCodeContains' => 'A filter the limits jobs to only the ones whose job reference code contains the specified string.
', ], ], 'JobType' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$JobType' => 'Indicates SageMaker job type compatibility.
TRAINING: The image version is compatible with SageMaker training jobs.
INFERENCE: The image version is compatible with SageMaker inference jobs.
NOTEBOOK_KERNEL: The image version is compatible with SageMaker notebook kernels.
Indicates SageMaker job type compatibility.
TRAINING: The image version is compatible with SageMaker training jobs.
INFERENCE: The image version is compatible with SageMaker inference jobs.
NOTEBOOK_KERNEL: The image version is compatible with SageMaker notebook kernels.
Indicates SageMaker job type compatibility.
TRAINING: The image version is compatible with SageMaker training jobs.
INFERENCE: The image version is compatible with SageMaker inference jobs.
NOTEBOOK_KERNEL: The image version is compatible with SageMaker notebook kernels.
Specifies the source of the data to join with the transformed data. The valid values are None and Input. The default value is None, which specifies not to join the input with the transformed data. If you want the batch transform job to join the original input data with the transformed data, set JoinSource to Input. You can specify OutputFilter as an additional filter to select a portion of the joined dataset and store it in the output file.
For JSON or JSONLines objects, such as a JSON array, SageMaker adds the transformed data to the input JSON object in an attribute called SageMakerOutput. The joined result for JSON must be a key-value pair object. If the input is not a key-value pair object, SageMaker creates a new JSON file. In the new JSON file, and the input data is stored under the SageMakerInput key and the results are stored in SageMakerOutput.
For CSV data, SageMaker takes each row as a JSON array and joins the transformed data with the input by appending each transformed row to the end of the input. The joined data has the original input data followed by the transformed data and the output is a CSV file.
For information on how joining in applied, see Workflow for Associating Inferences with Input Records.
', ], ], 'JsonContentType' => [ 'base' => NULL, 'refs' => [ 'JsonContentTypes$member' => NULL, ], ], 'JsonContentTypes' => [ 'base' => NULL, 'refs' => [ 'CaptureContentTypeHeader$JsonContentTypes' => 'The list of all content type headers that SageMaker will treat as JSON and capture accordingly.
', ], ], 'JsonPath' => [ 'base' => NULL, 'refs' => [ 'DataProcessing$InputFilter' => 'A JSONPath expression used to select a portion of the input data to pass to the algorithm. Use the InputFilter parameter to exclude fields, such as an ID column, from the input. If you want SageMaker to pass the entire input dataset to the algorithm, accept the default value $.
Examples: "$", "$[1:]", "$.features"
A JSONPath expression used to select a portion of the joined dataset to save in the output file for a batch transform job. If you want SageMaker to store the entire input dataset in the output file, leave the default value, $. If you specify indexes that aren\'t within the dimension size of the joined dataset, you get an error.
Examples: "$", "$[0,5:]", "$[\'id\',\'SageMakerOutput\']"
The JupyterServer app settings.
', 'refs' => [ 'DefaultSpaceSettings$JupyterServerAppSettings' => NULL, 'SpaceSettings$JupyterServerAppSettings' => NULL, 'UserSettings$JupyterServerAppSettings' => 'The Jupyter server\'s app settings.
', ], ], 'KeepAlivePeriodInSeconds' => [ 'base' => NULL, 'refs' => [ 'ResourceConfig$KeepAlivePeriodInSeconds' => 'The duration of time in seconds to retain configured resources in a warm pool for subsequent training jobs.
', 'ResourceConfigForUpdate$KeepAlivePeriodInSeconds' => 'The KeepAlivePeriodInSeconds value specified in the ResourceConfig to update.
The Amazon SageMaker Canvas application setting where you configure document querying.
', 'refs' => [ 'CanvasAppSettings$KendraSettings' => 'The settings for document querying.
', ], ], 'KernelDisplayName' => [ 'base' => NULL, 'refs' => [ 'KernelSpec$DisplayName' => 'The display name of the kernel.
', ], ], 'KernelGatewayAppSettings' => [ 'base' => 'The KernelGateway app settings.
', 'refs' => [ 'DefaultSpaceSettings$KernelGatewayAppSettings' => NULL, 'SpaceSettings$KernelGatewayAppSettings' => NULL, 'UserSettings$KernelGatewayAppSettings' => 'The kernel gateway app settings.
', ], ], 'KernelGatewayImageConfig' => [ 'base' => 'The configuration for the file system and kernels in a SageMaker image running as a KernelGateway app.
', 'refs' => [ 'AppImageConfigDetails$KernelGatewayImageConfig' => 'The configuration for the file system and kernels in the SageMaker image.
', 'CreateAppImageConfigRequest$KernelGatewayImageConfig' => 'The KernelGatewayImageConfig. You can only specify one image kernel in the AppImageConfig API. This kernel will be shown to users before the image starts. Once the image runs, all kernels are visible in JupyterLab.
', 'DescribeAppImageConfigResponse$KernelGatewayImageConfig' => 'The configuration of a KernelGateway app.
', 'UpdateAppImageConfigRequest$KernelGatewayImageConfig' => 'The new KernelGateway app to run on the image.
', ], ], 'KernelName' => [ 'base' => NULL, 'refs' => [ 'KernelSpec$Name' => 'The name of the Jupyter kernel in the image. This value is case sensitive.
', ], ], 'KernelSpec' => [ 'base' => 'The specification of a Jupyter kernel.
', 'refs' => [ 'KernelSpecs$member' => NULL, ], ], 'KernelSpecs' => [ 'base' => NULL, 'refs' => [ 'KernelGatewayImageConfig$KernelSpecs' => 'The specification of the Jupyter kernels in the image.
', ], ], 'Key' => [ 'base' => NULL, 'refs' => [ 'PipelineDefinitionS3Location$ObjectKey' => 'The object key (or key name) uniquely identifies the object in an S3 bucket.
', ], ], 'KmsKeyId' => [ 'base' => NULL, 'refs' => [ 'AsyncInferenceOutputConfig$KmsKeyId' => 'The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the asynchronous inference output in Amazon S3.
', 'AthenaDatasetDefinition$KmsKeyId' => 'The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data generated from an Athena query execution.
', 'AutoMLOutputDataConfig$KmsKeyId' => 'The Key Management Service (KMS) encryption key ID.
', 'AutoMLSecurityConfig$VolumeKmsKeyId' => 'The key used to encrypt stored data.
', 'BatchDataCaptureConfig$KmsKeyId' => 'The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the batch transform job.
The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
Use KmsKeyId.
SageMaker uses Amazon Web Services KMS to encrypt the EFS volume attached to the domain with an Amazon Web Services managed key by default. For more control, specify a customer managed key.
', 'CreateEdgePackagingJobRequest$ResourceKey' => 'The Amazon Web Services KMS key to use when encrypting the EBS volume the edge packaging job runs on.
', 'CreateEndpointConfigInput$KmsKeyId' => 'The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.
The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint, UpdateEndpoint requests. For more information, refer to the Amazon Web Services Key Management Service section Using Key Policies in Amazon Web Services KMS
Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can\'t request a KmsKeyId when using an instance type with local storage. If any of the models that you specify in the ProductionVariants parameter use nitro-based instances with local storage, do not specify a value for the KmsKeyId parameter. If you specify a value for KmsKeyId when using any nitro-based instances with local storage, the call to CreateEndpointConfig fails.
For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. The KmsKey can be any of the following formats:
KMS key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
Amazon Resource Name (ARN) of a KMS key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
KMS key Alias
"alias/ExampleAlias"
Amazon Resource Name (ARN) of a KMS key Alias
"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
If you use a KMS key ID or an alias of your KMS key, the Amazon SageMaker execution role must include permissions to call kms:Encrypt. If you don\'t provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role\'s account. Amazon SageMaker uses server-side encryption with KMS managed keys for OutputDataConfig. If you use a bucket policy with an s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to "aws:kms". For more information, see KMS managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint and UpdateEndpoint requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to your notebook instance. The KMS key you provide must be enabled. For information, see Enabling and Disabling Keys in the Amazon Web Services Key Management Service Developer Guide.
', 'DataCaptureConfig$KmsKeyId' => 'The Amazon Resource Name (ARN) of an Key Management Service key that SageMaker uses to encrypt the captured data at rest using Amazon S3 server-side encryption.
The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
The KMS key being used to encrypt the data in Amazon S3.
', 'DescribeDomainResponse$HomeEfsFileSystemKmsKeyId' => 'Use KmsKeyId.
The Amazon Web Services KMS customer managed key used to encrypt the EFS volume attached to the domain.
', 'DescribeEdgePackagingJobResponse$ResourceKey' => 'The Amazon Web Services KMS key to use when encrypting the EBS volume the job run on.
', 'DescribeEndpointConfigOutput$KmsKeyId' => 'Amazon Web Services KMS key ID Amazon SageMaker uses to encrypt data when storing it on the ML storage volume attached to the instance.
', 'DescribeInferenceExperimentResponse$KmsKey' => 'The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. For more information, see CreateInferenceExperiment.
', 'DescribeNotebookInstanceOutput$KmsKeyId' => 'The Amazon Web Services KMS key ID SageMaker uses to encrypt data when storing it on the ML storage volume attached to the instance.
', 'EdgeOutputConfig$KmsKeyId' => 'The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume after compilation job. If you don\'t provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role\'s account.
', 'FlowDefinitionOutputConfig$KmsKeyId' => 'The Amazon Key Management Service (KMS) key ID for server-side encryption.
', 'HyperParameterTuningResourceConfig$VolumeKmsKeyId' => 'A key used by Amazon Web Services Key Management Service to encrypt data on the storage volume attached to the compute instances used to run the training job. You can use either of the following formats to specify a key.
KMS Key ID:
"1234abcd-12ab-34cd-56ef-1234567890ab"
Amazon Resource Name (ARN) of a KMS key:
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
Some instances use local storage, which use a hardware module to encrypt storage volumes. If you choose one of these instance types, you cannot request a VolumeKmsKeyId. For a list of instance types that use local storage, see instance store volumes. For more information about Amazon Web Services Key Management Service, see KMS encryption for more information.
The Amazon Web Services Key Management Service key that Amazon SageMaker uses to encrypt captured data at rest using Amazon S3 server-side encryption.
', 'LabelingJobOutputConfig$KmsKeyId' => 'The Amazon Web Services Key Management Service ID of the key used to encrypt the output data, if any.
If you provide your own KMS key ID, you must add the required permissions to your KMS key described in Encrypt Output Data and Storage Volume with Amazon Web Services KMS.
If you don\'t provide a KMS key ID, Amazon SageMaker uses the default Amazon Web Services KMS key for Amazon S3 for your role\'s account to encrypt your output data.
If you use a bucket policy with an s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to "aws:kms". For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the training and inference jobs used for automated data labeling.
You can only specify a VolumeKmsKeyId when you create a labeling job with automated data labeling enabled using the API operation CreateLabelingJob. You cannot specify an Amazon Web Services KMS key to encrypt the storage volume used for automated data labeling model training and inference when you create a labeling job using the console. To learn more, see Output Data and Storage Volume Encryption.
The VolumeKmsKeyId can be any of the following formats:
KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
A Key Management Service key ID to use for encrypting a model card.
', 'MonitoringClusterConfig$VolumeKmsKeyId' => 'The Key Management Service (KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the model monitoring job.
', 'MonitoringOutputConfig$KmsKeyId' => 'The Key Management Service (KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
', 'OnlineStoreSecurityConfig$KmsKeyId' => 'The Amazon Web Services Key Management Service (KMS) key ARN that SageMaker Feature Store uses to encrypt the Amazon S3 objects at rest using Amazon S3 server-side encryption.
The caller (either user or IAM role) of CreateFeatureGroup must have below permissions to the OnlineStore KmsKeyId:
"kms:Encrypt"
"kms:Decrypt"
"kms:DescribeKey"
"kms:CreateGrant"
"kms:RetireGrant"
"kms:ReEncryptFrom"
"kms:ReEncryptTo"
"kms:GenerateDataKey"
"kms:ListAliases"
"kms:ListGrants"
"kms:RevokeGrant"
The caller (either user or IAM role) to all DataPlane operations (PutRecord, GetRecord, DeleteRecord) must have the following permissions to the KmsKeyId:
"kms:Decrypt"
The Amazon Web Services Key Management Service key (Amazon Web Services KMS) that Amazon SageMaker uses to encrypt your output models with Amazon S3 server-side encryption after compilation job. If you don\'t provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role\'s account. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption. The KmsKeyId can be any of the following formats:
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
// KMS Key Alias
"alias/ExampleAlias"
// Amazon Resource Name (ARN) of a KMS Key Alias
"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must include permissions to call kms:Encrypt. If you don\'t provide a KMS key ID, SageMaker uses the default KMS key for Amazon S3 for your role\'s account. SageMaker uses server-side encryption with KMS-managed keys for OutputDataConfig. If you use a bucket policy with an s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to "aws:kms". For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KMS key policy must grant permission to the IAM role that you specify in your CreateTrainingJob, CreateTransformJob, or CreateHyperParameterTuningJob requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the processing job.
Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can\'t request a VolumeKmsKeyId when using an instance type with local storage.
For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the processing job output. KmsKeyId can be an ID of a KMS key, ARN of a KMS key, alias of a KMS key, or alias of a KMS key. The KmsKeyId is applied to all outputs.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the core dump data at rest using Amazon S3 server-side encryption. The KmsKeyId can be any of the following formats:
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
// KMS Key Alias
"alias/ExampleAlias"
// Amazon Resource Name (ARN) of a KMS Key Alias
"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must include permissions to call kms:Encrypt. If you don\'t provide a KMS key ID, SageMaker uses the default KMS key for Amazon S3 for your role\'s account. SageMaker uses server-side encryption with KMS-managed keys for OutputDataConfig. If you use a bucket policy with an s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to "aws:kms". For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint and UpdateEndpoint requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. This key will be passed to SageMaker Hosting for endpoint creation.
The SageMaker execution role must have kms:CreateGrant permission in order to encrypt data on the storage volume of the endpoints created for inference recommendation. The inference recommendation job will fail asynchronously during endpoint configuration creation if the role passed does not have kms:CreateGrant permission.
The KmsKeyId can be any of the following formats:
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:<region>:<account>:key/<key-id-12ab-34cd-56ef-1234567890ab>"
// KMS Key Alias
"alias/ExampleAlias"
// Amazon Resource Name (ARN) of a KMS Key Alias
"arn:aws:kms:<region>:<account>:alias/<ExampleAlias>"
For more information about key identifiers, see Key identifiers (KeyID) in the Amazon Web Services Key Management Service (Amazon Web Services KMS) documentation.
', 'RecommendationJobOutputConfig$KmsKeyId' => 'The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt your output artifacts with Amazon S3 server-side encryption. The SageMaker execution role must have kms:GenerateDataKey permission.
The KmsKeyId can be any of the following formats:
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:<region>:<account>:key/<key-id-12ab-34cd-56ef-1234567890ab>"
// KMS Key Alias
"alias/ExampleAlias"
// Amazon Resource Name (ARN) of a KMS Key Alias
"arn:aws:kms:<region>:<account>:alias/<ExampleAlias>"
For more information about key identifiers, see Key identifiers (KeyID) in the Amazon Web Services Key Management Service (Amazon Web Services KMS) documentation.
', 'RedshiftDatasetDefinition$KmsKeyId' => 'The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data from a Redshift execution.
', 'ResourceConfig$VolumeKmsKeyId' => 'The Amazon Web Services KMS key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the training job.
Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can\'t request a VolumeKmsKeyId when using an instance type with local storage.
For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
The VolumeKmsKeyId can be in any of the following formats:
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
The Amazon Web Services Key Management Service (KMS) key ARN of the key used to encrypt any objects written into the OfflineStore S3 location.
The IAM roleARN that is passed as a parameter to CreateFeatureGroup must have below permissions to the KmsKeyId:
"kms:GenerateDataKey"
When NotebookOutputOption is Allowed, the Amazon Web Services Key Management Service (KMS) encryption key ID used to encrypt the notebook cell output in the Amazon S3 bucket.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption. The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
If you don\'t provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role\'s account. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KMS key policy must grant permission to the IAM role that you specify in your CreateModel request. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
', 'TransformResources$VolumeKmsKeyId' => 'The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt model data on the storage volume attached to the ML compute instance(s) that run the batch transform job.
Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can\'t request a VolumeKmsKeyId when using an instance type with local storage.
For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
The VolumeKmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
The Amazon Web Services Key Management Service (KMS) encryption key ID that is used to encrypt artifacts generated by Canvas in the Amazon S3 bucket.
', ], ], 'LabelAttributeName' => [ 'base' => NULL, 'refs' => [ 'CreateLabelingJobRequest$LabelAttributeName' => 'The attribute name to use for the label in the output manifest file. This is the key for the key/value pair formed with the label that a worker assigns to the object. The LabelAttributeName must meet the following requirements.
The name can\'t end with "-metadata".
If you are using one of the following built-in task types, the attribute name must end with "-ref". If the task type you are using is not listed below, the attribute name must not end with "-ref".
Image semantic segmentation (SemanticSegmentation), and adjustment (AdjustmentSemanticSegmentation) and verification (VerificationSemanticSegmentation) labeling jobs for this task type.
Video frame object detection (VideoObjectDetection), and adjustment and verification (AdjustmentVideoObjectDetection) labeling jobs for this task type.
Video frame object tracking (VideoObjectTracking), and adjustment and verification (AdjustmentVideoObjectTracking) labeling jobs for this task type.
3D point cloud semantic segmentation (3DPointCloudSemanticSegmentation), and adjustment and verification (Adjustment3DPointCloudSemanticSegmentation) labeling jobs for this task type.
3D point cloud object tracking (3DPointCloudObjectTracking), and adjustment and verification (Adjustment3DPointCloudObjectTracking) labeling jobs for this task type.
If you are creating an adjustment or verification labeling job, you must use a different LabelAttributeName than the one used in the original labeling job. The original labeling job is the Ground Truth labeling job that produced the labels that you want verified or adjusted. To learn more about adjustment and verification labeling jobs, see Verify and Adjust Labels.
The attribute used as the label in the output manifest file.
', ], ], 'LabelCounter' => [ 'base' => NULL, 'refs' => [ 'LabelCounters$TotalLabeled' => 'The total number of objects labeled.
', 'LabelCounters$HumanLabeled' => 'The total number of objects labeled by a human worker.
', 'LabelCounters$MachineLabeled' => 'The total number of objects labeled by automated data labeling.
', 'LabelCounters$FailedNonRetryableError' => 'The total number of objects that could not be labeled due to an error.
', 'LabelCounters$Unlabeled' => 'The total number of objects not yet labeled.
', 'LabelCountersForWorkteam$HumanLabeled' => 'The total number of data objects labeled by a human worker.
', 'LabelCountersForWorkteam$PendingHuman' => 'The total number of data objects that need to be labeled by a human worker.
', 'LabelCountersForWorkteam$Total' => 'The total number of tasks in the labeling job.
', ], ], 'LabelCounters' => [ 'base' => 'Provides a breakdown of the number of objects labeled.
', 'refs' => [ 'DescribeLabelingJobResponse$LabelCounters' => 'Provides a breakdown of the number of data objects labeled by humans, the number of objects labeled by machine, the number of objects than couldn\'t be labeled, and the total number of objects labeled.
', 'LabelingJobSummary$LabelCounters' => 'Counts showing the progress of the labeling job.
', ], ], 'LabelCountersForWorkteam' => [ 'base' => 'Provides counts for human-labeled tasks in the labeling job.
', 'refs' => [ 'LabelingJobForWorkteamSummary$LabelCounters' => 'Provides information about the progress of a labeling job.
', ], ], 'LabelingJobAlgorithmSpecificationArn' => [ 'base' => NULL, 'refs' => [ 'LabelingJobAlgorithmsConfig$LabelingJobAlgorithmSpecificationArn' => 'Specifies the Amazon Resource Name (ARN) of the algorithm used for auto-labeling. You must select one of the following ARNs:
Image classification
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/image-classification
Text classification
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/text-classification
Object detection
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/object-detection
Semantic Segmentation
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/semantic-segmentation
Provides configuration information for auto-labeling of your data objects. A LabelingJobAlgorithmsConfig object must be supplied in order to use auto-labeling.
Configures the information required to perform automated data labeling.
', 'DescribeLabelingJobResponse$LabelingJobAlgorithmsConfig' => 'Configuration information for automated data labeling.
', ], ], 'LabelingJobArn' => [ 'base' => NULL, 'refs' => [ 'CreateLabelingJobResponse$LabelingJobArn' => 'The Amazon Resource Name (ARN) of the labeling job. You use this ARN to identify the labeling job.
', 'DescribeLabelingJobResponse$LabelingJobArn' => 'The Amazon Resource Name (ARN) of the labeling job.
', 'DescribeTrainingJobResponse$LabelingJobArn' => 'The Amazon Resource Name (ARN) of the SageMaker Ground Truth labeling job that created the transform or training job.
', 'DescribeTransformJobResponse$LabelingJobArn' => 'The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling job that created the transform or training job.
', 'LabelingJobSummary$LabelingJobArn' => 'The Amazon Resource Name (ARN) assigned to the labeling job when it was created.
', 'TrainingJob$LabelingJobArn' => 'The Amazon Resource Name (ARN) of the labeling job.
', 'TransformJob$LabelingJobArn' => 'The Amazon Resource Name (ARN) of the labeling job that created the transform job.
', ], ], 'LabelingJobDataAttributes' => [ 'base' => 'Attributes of the data specified by the customer. Use these to describe the data to be labeled.
', 'refs' => [ 'LabelingJobInputConfig$DataAttributes' => 'Attributes of the data specified by the customer.
', ], ], 'LabelingJobDataSource' => [ 'base' => 'Provides information about the location of input data.
You must specify at least one of the following: S3DataSource or SnsDataSource.
Use SnsDataSource to specify an SNS input topic for a streaming labeling job. If you do not specify and SNS input topic ARN, Ground Truth will create a one-time labeling job.
Use S3DataSource to specify an input manifest file for both streaming and one-time labeling jobs. Adding an S3DataSource is optional if you use SnsDataSource to create a streaming labeling job.
The location of the input data.
', ], ], 'LabelingJobForWorkteamSummary' => [ 'base' => 'Provides summary information for a work team.
', 'refs' => [ 'LabelingJobForWorkteamSummaryList$member' => NULL, ], ], 'LabelingJobForWorkteamSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListLabelingJobsForWorkteamResponse$LabelingJobSummaryList' => 'An array of LabelingJobSummary objects, each describing a labeling job.
Input configuration information for a labeling job.
', 'refs' => [ 'CreateLabelingJobRequest$InputConfig' => 'Input data for the labeling job, such as the Amazon S3 location of the data objects and the location of the manifest file that describes the data objects.
You must specify at least one of the following: S3DataSource or SnsDataSource.
Use SnsDataSource to specify an SNS input topic for a streaming labeling job. If you do not specify and SNS input topic ARN, Ground Truth will create a one-time labeling job that stops after all data objects in the input manifest file have been labeled.
Use S3DataSource to specify an input manifest file for both streaming and one-time labeling jobs. Adding an S3DataSource is optional if you use SnsDataSource to create a streaming labeling job.
If you use the Amazon Mechanical Turk workforce, your input data should not include confidential information, personal information or protected health information. Use ContentClassifiers to specify that your data is free of personally identifiable information and adult content.
Input configuration information for the labeling job, such as the Amazon S3 location of the data objects and the location of the manifest file that describes the data objects.
', 'LabelingJobSummary$InputConfig' => 'Input configuration for the labeling job.
', ], ], 'LabelingJobName' => [ 'base' => NULL, 'refs' => [ 'CreateLabelingJobRequest$LabelingJobName' => 'The name of the labeling job. This name is used to identify the job in a list of labeling jobs. Labeling job names must be unique within an Amazon Web Services account and region. LabelingJobName is not case sensitive. For example, Example-job and example-job are considered the same labeling job name by Ground Truth.
The name of the labeling job to return information for.
', 'DescribeLabelingJobResponse$LabelingJobName' => 'The name assigned to the labeling job when it was created.
', 'LabelingJobForWorkteamSummary$LabelingJobName' => 'The name of the labeling job that the work team is assigned to.
', 'LabelingJobSummary$LabelingJobName' => 'The name of the labeling job.
', 'StopLabelingJobRequest$LabelingJobName' => 'The name of the labeling job to stop.
', ], ], 'LabelingJobOutput' => [ 'base' => 'Specifies the location of the output produced by the labeling job.
', 'refs' => [ 'DescribeLabelingJobResponse$LabelingJobOutput' => 'The location of the output produced by the labeling job.
', 'LabelingJobSummary$LabelingJobOutput' => 'The location of the output produced by the labeling job.
', ], ], 'LabelingJobOutputConfig' => [ 'base' => 'Output configuration information for a labeling job.
', 'refs' => [ 'CreateLabelingJobRequest$OutputConfig' => 'The location of the output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt the output data, if any.
', 'DescribeLabelingJobResponse$OutputConfig' => 'The location of the job\'s output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt the output data, if any.
', ], ], 'LabelingJobResourceConfig' => [ 'base' => 'Configure encryption on the storage volume attached to the ML compute instance used to run automated data labeling model training and inference.
', 'refs' => [ 'LabelingJobAlgorithmsConfig$LabelingJobResourceConfig' => 'Provides configuration information for a labeling job.
', ], ], 'LabelingJobS3DataSource' => [ 'base' => 'The Amazon S3 location of the input data objects.
', 'refs' => [ 'LabelingJobDataSource$S3DataSource' => 'The Amazon S3 location of the input data objects.
', ], ], 'LabelingJobSnsDataSource' => [ 'base' => 'An Amazon SNS data source used for streaming labeling jobs.
', 'refs' => [ 'LabelingJobDataSource$SnsDataSource' => 'An Amazon SNS data source used for streaming labeling jobs. To learn more, see Send Data to a Streaming Labeling Job.
', ], ], 'LabelingJobStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeLabelingJobResponse$LabelingJobStatus' => 'The processing status of the labeling job.
', 'LabelingJobSummary$LabelingJobStatus' => 'The current status of the labeling job.
', 'ListLabelingJobsRequest$StatusEquals' => 'A filter that retrieves only labeling jobs with a specific status.
', ], ], 'LabelingJobStoppingConditions' => [ 'base' => 'A set of conditions for stopping a labeling job. If any of the conditions are met, the job is automatically stopped. You can use these conditions to control the cost of data labeling.
Labeling jobs fail after 30 days with an appropriate client error message.
A set of conditions for stopping the labeling job. If any of the conditions are met, the job is automatically stopped. You can use these conditions to control the cost of data labeling.
', 'DescribeLabelingJobResponse$StoppingConditions' => 'A set of conditions for stopping a labeling job. If any of the conditions are met, the job is automatically stopped.
', ], ], 'LabelingJobSummary' => [ 'base' => 'Provides summary information about a labeling job.
', 'refs' => [ 'LabelingJobSummaryList$member' => NULL, ], ], 'LabelingJobSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListLabelingJobsResponse$LabelingJobSummaryList' => 'An array of LabelingJobSummary objects, each describing a labeling job.
The Amazon Resource Name (ARN) of a Lambda function implements the logic for annotation consolidation and to process output data.
This parameter is required for all labeling jobs. For built-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for AnnotationConsolidationLambdaArn. For custom labeling workflows, see Post-annotation Lambda.
Bounding box - Finds the most similar boxes from different workers based on the Jaccard index of the boxes.
arn:aws:lambda:us-east-1:432418664414:function:ACS-BoundingBox
arn:aws:lambda:us-east-2:266458841044:function:ACS-BoundingBox
arn:aws:lambda:us-west-2:081040173940:function:ACS-BoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:ACS-BoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-BoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-BoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:ACS-BoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:ACS-BoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-BoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:ACS-BoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-BoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:ACS-BoundingBox
Image classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClass
arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClass
arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClass
Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClassMultiLabel
Semantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as "votes" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:ACS-SemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-SemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-SemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-SemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-SemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-SemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-SemanticSegmentation
Text classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClass
arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClass
arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClass
Multi-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClassMultiLabel
Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.
arn:aws:lambda:us-east-1:432418664414:function:ACS-NamedEntityRecognition
arn:aws:lambda:us-east-2:266458841044:function:ACS-NamedEntityRecognition
arn:aws:lambda:us-west-2:081040173940:function:ACS-NamedEntityRecognition
arn:aws:lambda:eu-west-1:568282634449:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-south-1:565803892007:function:ACS-NamedEntityRecognition
arn:aws:lambda:eu-central-1:203001061592:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-NamedEntityRecognition
arn:aws:lambda:eu-west-2:487402164563:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-NamedEntityRecognition
arn:aws:lambda:ca-central-1:918755190332:function:ACS-NamedEntityRecognition
Video Classification - Use this task type when you need workers to classify videos using predefined labels that you specify. Workers are shown videos and are asked to choose one label for each video.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoMultiClass
arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoMultiClass
arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoMultiClass
Video Frame Object Detection - Use this task type to have workers identify and locate objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to identify and localize various objects in a series of video frames, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectDetection
Video Frame Object Tracking - Use this task type to have workers track the movement of objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to track the movement of objects, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectTracking
3D Point Cloud Object Detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectDetection
3D Point Cloud Object Tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectTracking
3D Point Cloud Semantic Segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudSemanticSegmentation
Use the following ARNs for Label Verification and Adjustment Jobs
Use label verification and adjustment jobs to review and adjust labels. To learn more, see Verify and Adjust Labels .
Semantic Segmentation Adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as "votes" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentSemanticSegmentation
Semantic Segmentation Verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationSemanticSegmentation
Bounding Box Adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentBoundingBox
Bounding Box Verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationBoundingBox
Video Frame Object Detection Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to classify and localize objects in a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectDetection
Video Frame Object Tracking Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to track object movement across a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectTracking
3D Point Cloud Object Detection Adjustment - Use this task type when you want workers to adjust 3D cuboids around objects in a 3D point cloud.
arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectDetection
3D Point Cloud Object Tracking Adjustment - Use this task type when you want workers to adjust 3D cuboids around objects that appear in a sequence of 3D point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectTracking
3D Point Cloud Semantic Segmentation Adjustment - Use this task type when you want workers to adjust a point-level semantic segmentation masks using a paint tool.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudSemanticSegmentation
The Amazon Resource Name (ARN) of a Lambda function that is run before a data object is sent to a human worker. Use this function to provide input to a custom labeling job.
For built-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for PreHumanTaskLambdaArn. For custom labeling workflows, see Pre-annotation Lambda.
Bounding box - Finds the most similar boxes from different workers based on the Jaccard index of the boxes.
arn:aws:lambda:us-east-1:432418664414:function:PRE-BoundingBox
arn:aws:lambda:us-east-2:266458841044:function:PRE-BoundingBox
arn:aws:lambda:us-west-2:081040173940:function:PRE-BoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:PRE-BoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:PRE-BoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:PRE-BoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:PRE-BoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-BoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-BoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:PRE-BoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-BoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-BoundingBox
Image classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClass
arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClass
arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClass
Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClassMultiLabel
Semantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as "votes" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:PRE-SemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-SemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-SemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-SemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-SemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-SemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-SemanticSegmentation
Text classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClass
arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClass
arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClass
Multi-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClassMultiLabel
Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.
arn:aws:lambda:us-east-1:432418664414:function:PRE-NamedEntityRecognition
arn:aws:lambda:us-east-2:266458841044:function:PRE-NamedEntityRecognition
arn:aws:lambda:us-west-2:081040173940:function:PRE-NamedEntityRecognition
arn:aws:lambda:ca-central-1:918755190332:function:PRE-NamedEntityRecognition
arn:aws:lambda:eu-west-1:568282634449:function:PRE-NamedEntityRecognition
arn:aws:lambda:eu-west-2:487402164563:function:PRE-NamedEntityRecognition
arn:aws:lambda:eu-central-1:203001061592:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-south-1:565803892007:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-NamedEntityRecognition
Video Classification - Use this task type when you need workers to classify videos using predefined labels that you specify. Workers are shown videos and are asked to choose one label for each video.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoMultiClass
arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoMultiClass
arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoMultiClass
Video Frame Object Detection - Use this task type to have workers identify and locate objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to identify and localize various objects in a series of video frames, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectDetection
Video Frame Object Tracking - Use this task type to have workers track the movement of objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to track the movement of objects, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectTracking
3D Point Cloud Modalities
Use the following pre-annotation lambdas for 3D point cloud labeling modality tasks. See 3D Point Cloud Task types to learn more.
3D Point Cloud Object Detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectDetection
3D Point Cloud Object Tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectTracking
3D Point Cloud Semantic Segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify.
arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudSemanticSegmentation
Use the following ARNs for Label Verification and Adjustment Jobs
Use label verification and adjustment jobs to review and adjust labels. To learn more, see Verify and Adjust Labels .
Bounding box verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationBoundingBox
Bounding box adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentBoundingBox
Semantic segmentation verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationSemanticSegmentation
Semantic segmentation adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as "votes" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentSemanticSegmentation
Video Frame Object Detection Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to classify and localize objects in a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectDetection
Video Frame Object Tracking Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to track object movement across a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectTracking
3D point cloud object detection adjustment - Adjust 3D cuboids in a point cloud frame.
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectDetection
3D point cloud object tracking adjustment - Adjust 3D cuboids across a sequence of point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectTracking
3D point cloud semantic segmentation adjustment - Adjust semantic segmentation masks in a 3D point cloud.
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudSemanticSegmentation
The Amazon Resource Name (ARN) of a Lambda function. The function is run before each data object is sent to a worker.
', 'LabelingJobSummary$AnnotationConsolidationLambdaArn' => 'The Amazon Resource Name (ARN) of the Lambda function used to consolidate the annotations from individual workers into a label for a data object. For more information, see Annotation Consolidation.
', ], ], 'LambdaStepMetadata' => [ 'base' => 'Metadata for a Lambda step.
', 'refs' => [ 'PipelineExecutionStepMetadata$Lambda' => 'The Amazon Resource Name (ARN) of the Lambda function that was run by this step execution and a list of output parameters.
', ], ], 'LastModifiedTime' => [ 'base' => NULL, 'refs' => [ 'CodeRepositorySummary$LastModifiedTime' => 'The date and time that the Git repository was last modified.
', 'CompilationJobSummary$LastModifiedTime' => 'The time when the model compilation job was last modified.
', 'DescribeCodeRepositoryOutput$LastModifiedTime' => 'The date and time that the repository was last changed.
', 'DescribeCompilationJobResponse$LastModifiedTime' => 'The time that the status of the model compilation job was last modified.
', 'DescribeDomainResponse$LastModifiedTime' => 'The last modified time.
', 'DescribeFeatureGroupResponse$LastModifiedTime' => 'A timestamp indicating when the feature group was last updated.
', 'DescribeFeatureMetadataResponse$LastModifiedTime' => 'A timestamp indicating when the metadata for the feature group was modified. For example, if you add a parameter describing the feature, the timestamp changes to reflect the last time you
', 'DescribeInferenceRecommendationsJobResponse$LastModifiedTime' => 'A timestamp that shows when the job was last modified.
', 'DescribeNotebookInstanceLifecycleConfigOutput$LastModifiedTime' => 'A timestamp that tells when the lifecycle configuration was last modified.
', 'DescribeNotebookInstanceOutput$LastModifiedTime' => 'A timestamp. Use this parameter to retrieve the time when the notebook instance was last modified.
', 'DescribeSpaceResponse$LastModifiedTime' => 'The last modified time.
', 'DescribeUserProfileResponse$LastModifiedTime' => 'The last modified time.
', 'DomainDetails$LastModifiedTime' => 'The last modified time.
', 'FeatureGroup$LastModifiedTime' => 'A timestamp indicating the last time you updated the feature group.
', 'FeatureMetadata$LastModifiedTime' => 'A timestamp indicating when the feature was last modified.
', 'InferenceRecommendationsJob$LastModifiedTime' => 'A timestamp that shows when the job was last modified.
', 'ListCompilationJobsRequest$LastModifiedTimeAfter' => 'A filter that returns the model compilation jobs that were modified after a specified time.
', 'ListCompilationJobsRequest$LastModifiedTimeBefore' => 'A filter that returns the model compilation jobs that were modified before a specified time.
', 'ListInferenceRecommendationsJobsRequest$LastModifiedTimeAfter' => 'A filter that returns only jobs that were last modified after the specified time (timestamp).
', 'ListInferenceRecommendationsJobsRequest$LastModifiedTimeBefore' => 'A filter that returns only jobs that were last modified before the specified time (timestamp).
', 'ListNotebookInstanceLifecycleConfigsInput$LastModifiedTimeBefore' => 'A filter that returns only lifecycle configurations that were modified before the specified time (timestamp).
', 'ListNotebookInstanceLifecycleConfigsInput$LastModifiedTimeAfter' => 'A filter that returns only lifecycle configurations that were modified after the specified time (timestamp).
', 'ListNotebookInstancesInput$LastModifiedTimeBefore' => 'A filter that returns only notebook instances that were modified before the specified time (timestamp).
', 'ListNotebookInstancesInput$LastModifiedTimeAfter' => 'A filter that returns only notebook instances that were modified after the specified time (timestamp).
', 'NotebookInstanceLifecycleConfigSummary$LastModifiedTime' => 'A timestamp that tells when the lifecycle configuration was last modified.
', 'NotebookInstanceSummary$LastModifiedTime' => 'A timestamp that shows when the notebook instance was last modified.
', 'SpaceDetails$LastModifiedTime' => 'The last modified time.
', 'UserProfileDetails$LastModifiedTime' => 'The last modified time.
', ], ], 'LastUpdateStatus' => [ 'base' => 'A value that indicates whether the update was successful.
', 'refs' => [ 'DescribeFeatureGroupResponse$LastUpdateStatus' => 'A value indicating whether the update made to the feature group was successful.
', 'FeatureGroup$LastUpdateStatus' => 'A value that indicates whether the feature group was updated successfully.
', ], ], 'LastUpdateStatusValue' => [ 'base' => NULL, 'refs' => [ 'LastUpdateStatus$Status' => 'A value that indicates whether the update was made successful.
', ], ], 'LifecycleConfigArns' => [ 'base' => NULL, 'refs' => [ 'JupyterServerAppSettings$LifecycleConfigArns' => ' The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the JupyterServerApp. If you use this parameter, the DefaultResourceSpec parameter is also required.
To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the the user profile or domain.
To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.
A list of properties to add to the action.
', 'CreateArtifactRequest$Properties' => 'A list of properties to add to the artifact.
', 'CreateContextRequest$Properties' => 'A list of properties to add to the context.
', 'DescribeActionResponse$Properties' => 'A list of the action\'s properties.
', 'DescribeArtifactResponse$Properties' => 'A list of the artifact\'s properties.
', 'DescribeContextResponse$Properties' => 'A list of the context\'s properties.
', 'UpdateActionRequest$Properties' => 'The new list of properties. Overwrites the current property list.
', 'UpdateArtifactRequest$Properties' => 'The new list of properties. Overwrites the current property list.
', 'UpdateContextRequest$Properties' => 'The new list of properties. Overwrites the current property list.
', ], ], 'LineageGroupArn' => [ 'base' => NULL, 'refs' => [ 'DescribeActionResponse$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group.
', 'DescribeArtifactResponse$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group.
', 'DescribeContextResponse$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group.
', 'DescribeLineageGroupResponse$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group.
', 'DescribeTrialComponentResponse$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group.
', 'GetLineageGroupPolicyResponse$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group.
', 'LineageGroupSummary$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group resource.
', 'TrialComponent$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group resource.
', ], ], 'LineageGroupNameOrArn' => [ 'base' => NULL, 'refs' => [ 'GetLineageGroupPolicyRequest$LineageGroupName' => 'The name or Amazon Resource Name (ARN) of the lineage group.
', ], ], 'LineageGroupSummaries' => [ 'base' => NULL, 'refs' => [ 'ListLineageGroupsResponse$LineageGroupSummaries' => 'A list of lineage groups and their properties.
', ], ], 'LineageGroupSummary' => [ 'base' => 'Lists a summary of the properties of a lineage group. A lineage group provides a group of shareable lineage entity resources.
', 'refs' => [ 'LineageGroupSummaries$member' => NULL, ], ], 'LineageType' => [ 'base' => NULL, 'refs' => [ 'QueryLineageTypes$member' => NULL, 'Vertex$LineageType' => 'The type of resource of the lineage entity.
', ], ], 'ListActionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListActionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListAlgorithmsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListAlgorithmsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListAliasesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListAliasesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListAppImageConfigsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListAppImageConfigsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListAppsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListAppsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListArtifactsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListArtifactsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListAssociationsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListAssociationsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListAutoMLJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListAutoMLJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListCandidatesForAutoMLJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListCandidatesForAutoMLJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListCodeRepositoriesInput' => [ 'base' => NULL, 'refs' => [], ], 'ListCodeRepositoriesOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListCompilationJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListCompilationJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListCompilationJobsSortBy' => [ 'base' => NULL, 'refs' => [ 'ListCompilationJobsRequest$SortBy' => 'The field by which to sort results. The default is CreationTime.
The column to sort by.
', ], ], 'ListDevicesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListDevicesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListDomainsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListDomainsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListEdgeDeploymentPlansRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListEdgeDeploymentPlansResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListEdgeDeploymentPlansSortBy' => [ 'base' => NULL, 'refs' => [ 'ListEdgeDeploymentPlansRequest$SortBy' => 'The column by which to sort the edge deployment plans. Can be one of NAME, DEVICEFLEETNAME, CREATIONTIME, LASTMODIFIEDTIME.
Use to specify what column to sort by.
', ], ], 'ListEndpointConfigsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListEndpointConfigsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListEndpointsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListEndpointsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListExperimentsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListExperimentsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListFeatureGroupsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListFeatureGroupsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListFlowDefinitionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListFlowDefinitionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListHubContentVersionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListHubContentVersionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListHubContentsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListHubContentsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListHubsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListHubsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListHumanTaskUisRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListHumanTaskUisResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListHyperParameterTuningJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListHyperParameterTuningJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListImageVersionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListImageVersionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListImagesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListImagesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceExperimentsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceExperimentsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceRecommendationsJobStepsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceRecommendationsJobStepsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceRecommendationsJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceRecommendationsJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceRecommendationsJobsSortBy' => [ 'base' => NULL, 'refs' => [ 'ListInferenceRecommendationsJobsRequest$SortBy' => 'The parameter by which to sort the results.
', ], ], 'ListLabelingJobsForWorkteamRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListLabelingJobsForWorkteamResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListLabelingJobsForWorkteamSortByOptions' => [ 'base' => NULL, 'refs' => [ 'ListLabelingJobsForWorkteamRequest$SortBy' => 'The field to sort results by. The default is CreationTime.
A list of properties to remove.
', 'UpdateArtifactRequest$PropertiesToRemove' => 'A list of properties to remove.
', 'UpdateContextRequest$PropertiesToRemove' => 'A list of properties to remove.
', ], ], 'ListLineageGroupsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListLineageGroupsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListMaxResults' => [ 'base' => NULL, 'refs' => [ 'ListDeviceFleetsRequest$MaxResults' => 'The maximum number of results to select.
', 'ListDevicesRequest$MaxResults' => 'Maximum number of results to select.
', 'ListEdgeDeploymentPlansRequest$MaxResults' => 'The maximum number of results to select (50 by default).
', 'ListEdgePackagingJobsRequest$MaxResults' => 'Maximum number of results to select.
', 'ListStageDevicesRequest$MaxResults' => 'The maximum number of requests to select.
', ], ], 'ListModelBiasJobDefinitionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelBiasJobDefinitionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelCardExportJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelCardExportJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelCardVersionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelCardVersionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelCardsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelCardsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelExplainabilityJobDefinitionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelExplainabilityJobDefinitionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelMetadataRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelMetadataResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelPackageGroupsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListModelPackageGroupsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListModelPackagesInput' => [ 'base' => NULL, 'refs' => [], ], 'ListModelPackagesOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListModelQualityJobDefinitionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelQualityJobDefinitionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListModelsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringAlertHistoryRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringAlertHistoryResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringAlertsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringAlertsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringExecutionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringExecutionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringSchedulesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringSchedulesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListNotebookInstanceLifecycleConfigsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListNotebookInstanceLifecycleConfigsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListNotebookInstancesInput' => [ 'base' => NULL, 'refs' => [], ], 'ListNotebookInstancesOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelineExecutionStepsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelineExecutionStepsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelineExecutionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelineExecutionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelineParametersForExecutionRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelineParametersForExecutionResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelinesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelinesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListProcessingJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListProcessingJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListProjectsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListProjectsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListResourceCatalogsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListResourceCatalogsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListSpacesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListSpacesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListStageDevicesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListStageDevicesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListStudioLifecycleConfigsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListStudioLifecycleConfigsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListSubscribedWorkteamsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListSubscribedWorkteamsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListTagsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListTagsMaxResults' => [ 'base' => NULL, 'refs' => [ 'ListTagsInput$MaxResults' => 'Maximum number of tags to return.
', ], ], 'ListTagsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListTrainingJobsForHyperParameterTuningJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListTrainingJobsForHyperParameterTuningJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListTrainingJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListTrainingJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListTransformJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListTransformJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListTrialComponentKey256' => [ 'base' => NULL, 'refs' => [ 'UpdateTrialComponentRequest$ParametersToRemove' => 'The hyperparameters to remove from the component.
', 'UpdateTrialComponentRequest$InputArtifactsToRemove' => 'The input artifacts to remove from the component.
', 'UpdateTrialComponentRequest$OutputArtifactsToRemove' => 'The output artifacts to remove from the component.
', ], ], 'ListTrialComponentsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListTrialComponentsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListTrialsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListTrialsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListUserProfilesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListUserProfilesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListWorkforcesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListWorkforcesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListWorkforcesSortByOptions' => [ 'base' => NULL, 'refs' => [ 'ListWorkforcesRequest$SortBy' => 'Sort workforces using the workforce name or creation date.
', ], ], 'ListWorkteamsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListWorkteamsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListWorkteamsSortByOptions' => [ 'base' => NULL, 'refs' => [ 'ListWorkteamsRequest$SortBy' => 'The field to sort results by. The default is CreationTime.
The number of Edge Manager agents.
', 'DeviceStats$ConnectedDeviceCount' => 'The number of devices connected with a heartbeat.
', 'DeviceStats$RegisteredDeviceCount' => 'The number of registered devices.
', 'EdgeModelStat$OfflineDeviceCount' => 'The number of devices that have this model version and do not have a heart beat.
', 'EdgeModelStat$ConnectedDeviceCount' => 'The number of devices that have this model version and have a heart beat.
', 'EdgeModelStat$ActiveDeviceCount' => 'The number of devices that have this model version, a heart beat, and are currently running.
', 'EdgeModelStat$SamplingDeviceCount' => 'The number of devices with this model version and are producing sample data.
', ], ], 'MLFramework' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$MLFramework' => 'The machine learning framework vended in the image version.
', 'DescribeImageVersionResponse$MLFramework' => 'The machine learning framework vended in the image version.
', 'UpdateImageVersionRequest$MLFramework' => 'The machine learning framework vended in the image version.
', ], ], 'MaxAutoMLJobRuntimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobCompletionCriteria$MaxAutoMLJobRuntimeInSeconds' => 'The maximum runtime, in seconds, an AutoML job has to complete.
If an AutoML job exceeds the maximum runtime, the job is stopped automatically and its processing is ended gracefully. The AutoML job identifies the best model whose training was completed and marks it as the best-performing model. Any unfinished steps of the job, such as automatic one-click Autopilot model deployment, are not completed.
', ], ], 'MaxCandidates' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobCompletionCriteria$MaxCandidates' => 'The maximum number of times a training job is allowed to run.
For text and image classification, time-series forecasting, as well as text generation (LLMs fine-tuning) problem types, the supported value is 1. For tabular problem types, the maximum value is 750.
', ], ], 'MaxConcurrentInvocationsPerInstance' => [ 'base' => NULL, 'refs' => [ 'AsyncInferenceClientConfig$MaxConcurrentInvocationsPerInstance' => 'The maximum number of concurrent requests sent by the SageMaker client to the model container. If no value is provided, SageMaker chooses an optimal value.
', ], ], 'MaxConcurrentTaskCount' => [ 'base' => NULL, 'refs' => [ 'HumanTaskConfig$MaxConcurrentTaskCount' => 'Defines the maximum number of data objects that can be labeled by human workers at the same time. Also referred to as batch size. Each object may have more than one worker at one time. The default value is 1000 objects. To increase the maximum value to 5000 objects, contact Amazon Web Services Support.
', ], ], 'MaxConcurrentTransforms' => [ 'base' => NULL, 'refs' => [ 'CreateTransformJobRequest$MaxConcurrentTransforms' => 'The maximum number of parallel requests that can be sent to each instance in a transform job. If MaxConcurrentTransforms is set to 0 or left unset, Amazon SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 1. For more information on execution-parameters, see How Containers Serve Requests. For built-in algorithms, you don\'t need to set a value for MaxConcurrentTransforms.
The maximum number of parallel requests on each instance node that can be launched in a transform job. The default value is 1.
', 'TransformJob$MaxConcurrentTransforms' => 'The maximum number of parallel requests that can be sent to each instance in a transform job. If MaxConcurrentTransforms is set to 0 or left unset, SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 1. For built-in algorithms, you don\'t need to set a value for MaxConcurrentTransforms.
The maximum number of parallel requests that can be sent to each instance in a transform job. The default value is 1.
', ], ], 'MaxHumanLabeledObjectCount' => [ 'base' => NULL, 'refs' => [ 'LabelingJobStoppingConditions$MaxHumanLabeledObjectCount' => 'The maximum number of objects that can be labeled by human workers.
', ], ], 'MaxNumberOfTests' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobResourceLimit$MaxNumberOfTests' => 'Defines the maximum number of load tests.
', ], ], 'MaxNumberOfTrainingJobs' => [ 'base' => NULL, 'refs' => [ 'ResourceLimits$MaxNumberOfTrainingJobs' => 'The maximum number of training jobs that a hyperparameter tuning job can launch.
', ], ], 'MaxNumberOfTrainingJobsNotImproving' => [ 'base' => NULL, 'refs' => [ 'BestObjectiveNotImproving$MaxNumberOfTrainingJobsNotImproving' => 'The number of training jobs that have failed to improve model performance by 1% or greater over prior training jobs as evaluated against an objective function.
', ], ], 'MaxParallelExecutionSteps' => [ 'base' => NULL, 'refs' => [ 'ParallelismConfiguration$MaxParallelExecutionSteps' => 'The max number of steps that can be executed in parallel.
', ], ], 'MaxParallelOfTests' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobResourceLimit$MaxParallelOfTests' => 'Defines the maximum number of parallel load tests.
', ], ], 'MaxParallelTrainingJobs' => [ 'base' => NULL, 'refs' => [ 'ResourceLimits$MaxParallelTrainingJobs' => 'The maximum number of concurrent training jobs that a hyperparameter tuning job can launch.
', ], ], 'MaxPayloadInMB' => [ 'base' => NULL, 'refs' => [ 'CreateTransformJobRequest$MaxPayloadInMB' => 'The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6 MB.
The value of MaxPayloadInMB cannot be greater than 100 MB. If you specify the MaxConcurrentTransforms parameter, the value of (MaxConcurrentTransforms * MaxPayloadInMB) also cannot exceed 100 MB.
For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0. This feature works only in supported algorithms. Currently, Amazon SageMaker built-in algorithms do not support HTTP chunked encoding.
The maximum payload size, in MB, used in the transform job.
', 'TransformJob$MaxPayloadInMB' => 'The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6 MB. For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0. This feature works only in supported algorithms. Currently, SageMaker built-in algorithms do not support HTTP chunked encoding.
The maximum payload size allowed, in MB. A payload is the data portion of a record (without metadata).
', ], ], 'MaxPendingTimeInSeconds' => [ 'base' => 'Maximum job scheduler pending time in seconds.', 'refs' => [ 'StoppingCondition$MaxPendingTimeInSeconds' => 'The maximum pending time in seconds.
', ], ], 'MaxPercentageOfInputDatasetLabeled' => [ 'base' => NULL, 'refs' => [ 'LabelingJobStoppingConditions$MaxPercentageOfInputDatasetLabeled' => 'The maximum number of input data objects that should be labeled.
', ], ], 'MaxResults' => [ 'base' => NULL, 'refs' => [ 'ListActionsRequest$MaxResults' => 'The maximum number of actions to return in the response. The default value is 10.
', 'ListAlgorithmsInput$MaxResults' => 'The maximum number of algorithms to return in the response.
', 'ListAliasesRequest$MaxResults' => 'The maximum number of aliases to return.
', 'ListAppImageConfigsRequest$MaxResults' => 'The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken is provided in the response. To resume pagination, provide the NextToken value in the as part of a subsequent call. The default value is 10.
The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken is provided in the response. To resume pagination, provide the NextToken value in the as part of a subsequent call. The default value is 10.
The maximum number of artifacts to return in the response. The default value is 10.
', 'ListAssociationsRequest$MaxResults' => 'The maximum number of associations to return in the response. The default value is 10.
', 'ListCodeRepositoriesInput$MaxResults' => 'The maximum number of Git repositories to return in the response.
', 'ListCompilationJobsRequest$MaxResults' => 'The maximum number of model compilation jobs to return in the response.
', 'ListContextsRequest$MaxResults' => 'The maximum number of contexts to return in the response. The default value is 10.
', 'ListDataQualityJobDefinitionsRequest$MaxResults' => 'The maximum number of data quality monitoring job definitions to return in the response.
', 'ListDomainsRequest$MaxResults' => 'The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken is provided in the response. To resume pagination, provide the NextToken value in the as part of a subsequent call. The default value is 10.
The maximum number of training jobs to return in the response.
', 'ListEndpointsInput$MaxResults' => 'The maximum number of endpoints to return in the response. This value defaults to 10.
', 'ListExperimentsRequest$MaxResults' => 'The maximum number of experiments to return in the response. The default value is 10.
', 'ListFlowDefinitionsRequest$MaxResults' => 'The total number of items to return. If the total number of available items is more than the value specified in MaxResults, then a NextToken will be provided in the output that you can use to resume pagination.
The maximum number of hub content versions to list.
', 'ListHubContentsRequest$MaxResults' => 'The maximum amount of hub content to list.
', 'ListHubsRequest$MaxResults' => 'The maximum number of hubs to list.
', 'ListHumanTaskUisRequest$MaxResults' => 'The total number of items to return. If the total number of available items is more than the value specified in MaxResults, then a NextToken will be provided in the output that you can use to resume pagination.
The maximum number of tuning jobs to return. The default value is 10.
', 'ListImageVersionsRequest$MaxResults' => 'The maximum number of versions to return in the response. The default value is 10.
', 'ListImagesRequest$MaxResults' => 'The maximum number of images to return in the response. The default value is 10.
', 'ListInferenceExperimentsRequest$MaxResults' => 'The maximum number of results to select.
', 'ListInferenceRecommendationsJobStepsRequest$MaxResults' => 'The maximum number of results to return.
', 'ListInferenceRecommendationsJobsRequest$MaxResults' => 'The maximum number of recommendations to return in the response.
', 'ListLabelingJobsForWorkteamRequest$MaxResults' => 'The maximum number of labeling jobs to return in each page of the response.
', 'ListLabelingJobsRequest$MaxResults' => 'The maximum number of labeling jobs to return in each page of the response.
', 'ListLineageGroupsRequest$MaxResults' => 'The maximum number of endpoints to return in the response. This value defaults to 10.
', 'ListModelBiasJobDefinitionsRequest$MaxResults' => 'The maximum number of model bias jobs to return in the response. The default value is 10.
', 'ListModelCardExportJobsRequest$MaxResults' => 'The maximum number of model card export jobs to list.
', 'ListModelCardVersionsRequest$MaxResults' => 'The maximum number of model card versions to list.
', 'ListModelCardsRequest$MaxResults' => 'The maximum number of model cards to list.
', 'ListModelExplainabilityJobDefinitionsRequest$MaxResults' => 'The maximum number of jobs to return in the response. The default value is 10.
', 'ListModelMetadataRequest$MaxResults' => 'The maximum number of models to return in the response.
', 'ListModelPackageGroupsInput$MaxResults' => 'The maximum number of results to return in the response.
', 'ListModelPackagesInput$MaxResults' => 'The maximum number of model packages to return in the response.
', 'ListModelQualityJobDefinitionsRequest$MaxResults' => 'The maximum number of results to return in a call to ListModelQualityJobDefinitions.
The maximum number of models to return in the response.
', 'ListMonitoringAlertHistoryRequest$MaxResults' => 'The maximum number of results to display. The default is 100.
', 'ListMonitoringAlertsRequest$MaxResults' => 'The maximum number of results to display. The default is 100.
', 'ListMonitoringExecutionsRequest$MaxResults' => 'The maximum number of jobs to return in the response. The default value is 10.
', 'ListMonitoringSchedulesRequest$MaxResults' => 'The maximum number of jobs to return in the response. The default value is 10.
', 'ListNotebookInstanceLifecycleConfigsInput$MaxResults' => 'The maximum number of lifecycle configurations to return in the response.
', 'ListNotebookInstancesInput$MaxResults' => 'The maximum number of notebook instances to return.
', 'ListPipelineExecutionStepsRequest$MaxResults' => 'The maximum number of pipeline execution steps to return in the response.
', 'ListPipelineExecutionsRequest$MaxResults' => 'The maximum number of pipeline executions to return in the response.
', 'ListPipelineParametersForExecutionRequest$MaxResults' => 'The maximum number of parameters to return in the response.
', 'ListPipelinesRequest$MaxResults' => 'The maximum number of pipelines to return in the response.
', 'ListProcessingJobsRequest$MaxResults' => 'The maximum number of processing jobs to return in the response.
', 'ListProjectsInput$MaxResults' => 'The maximum number of projects to return in the response.
', 'ListResourceCatalogsRequest$MaxResults' => ' The maximum number of results returned by ListResourceCatalogs.
The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken is provided in the response. To resume pagination, provide the NextToken value in the as part of a subsequent call. The default value is 10.
The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken is provided in the response. To resume pagination, provide the NextToken value in the as part of a subsequent call. The default value is 10.
The maximum number of work teams to return in each page of the response.
', 'ListTrainingJobsForHyperParameterTuningJobRequest$MaxResults' => 'The maximum number of training jobs to return. The default value is 10.
', 'ListTrainingJobsRequest$MaxResults' => 'The maximum number of training jobs to return in the response.
', 'ListTransformJobsRequest$MaxResults' => 'The maximum number of transform jobs to return in the response. The default value is 10.
The maximum number of components to return in the response. The default value is 10.
', 'ListTrialsRequest$MaxResults' => 'The maximum number of trials to return in the response. The default value is 10.
', 'ListUserProfilesRequest$MaxResults' => 'The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken is provided in the response. To resume pagination, provide the NextToken value in the as part of a subsequent call. The default value is 10.
The maximum number of workforces returned in the response.
', 'ListWorkteamsRequest$MaxResults' => 'The maximum number of work teams to return in each page of the response.
', 'SearchRequest$MaxResults' => 'The maximum number of results to return.
', ], ], 'MaxRuntimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'StoppingCondition$MaxRuntimeInSeconds' => 'The maximum length of time, in seconds, that a training or compilation job can run before it is stopped.
For compilation jobs, if the job does not complete during this time, a TimeOut error is generated. We recommend starting with 900 seconds and increasing as necessary based on your model.
For all other jobs, if the job does not complete during this time, SageMaker ends the job. When RetryStrategy is specified in the job request, MaxRuntimeInSeconds specifies the maximum time for all of the attempts in total, not each individual attempt. The default value is 1 day. The maximum value is 28 days.
The maximum time that a TrainingJob can run in total, including any time spent publishing metrics or archiving and uploading models after it has been stopped, is 30 days.
The maximum time, in seconds, that each training job executed inside hyperparameter tuning is allowed to run as part of a hyperparameter tuning job. For more information, see the StoppingCondition used by the CreateHyperParameterTuningJob action.
For job V2s (jobs created by calling CreateAutoMLJobV2), this field controls the runtime of the job candidate.
The maximum length of time, in seconds, that a managed Spot training job has to complete. It is the amount of time spent waiting for Spot capacity plus the amount of time the job can run. It must be equal to or greater than MaxRuntimeInSeconds. If the job does not complete during this time, SageMaker ends the job.
When RetryStrategy is specified in the job request, MaxWaitTimeInSeconds specifies the maximum time for all of the attempts in total, not each individual attempt.
Maximum execution timeout for the deployment. Note that the timeout value should be larger than the total waiting time specified in TerminationWaitInSeconds and WaitIntervalInSeconds.
The time limit for the total deployment. Exceeding this limit causes a timeout.
', ], ], 'MaximumRetryAttempts' => [ 'base' => NULL, 'refs' => [ 'RetryStrategy$MaximumRetryAttempts' => 'The number of times to retry the job. When the job is retried, it\'s SecondaryStatus is changed to STARTING.
The media type of the artifact, which indicates the type of data in the artifact file. The media type consists of a type and a subtype concatenated with a slash (/) character, for example, text/csv, image/jpeg, and s3/uri. The type specifies the category of the media. The subtype specifies the kind of data.
', ], ], 'MemberDefinition' => [ 'base' => 'Defines an Amazon Cognito or your own OIDC IdP user group that is part of a work team.
', 'refs' => [ 'MemberDefinitions$member' => NULL, ], ], 'MemberDefinitions' => [ 'base' => NULL, 'refs' => [ 'CreateWorkteamRequest$MemberDefinitions' => 'A list of MemberDefinition objects that contains objects that identify the workers that make up the work team.
Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use CognitoMemberDefinition. For workforces created using your own OIDC identity provider (IdP) use OidcMemberDefinition. Do not provide input for both of these parameters in a single request.
For workforces created using Amazon Cognito, private work teams correspond to Amazon Cognito user groups within the user pool used to create a workforce. All of the CognitoMemberDefinition objects that make up the member definition must have the same ClientId and UserPool values. To add a Amazon Cognito user group to an existing worker pool, see Adding groups to a User Pool. For more information about user pools, see Amazon Cognito User Pools.
For workforces created using your own OIDC IdP, specify the user groups that you want to include in your private work team in OidcMemberDefinition by listing those groups in Groups.
A list of MemberDefinition objects that contains objects that identify the workers that make up the work team.
Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use CognitoMemberDefinition. For workforces created using your own OIDC identity provider (IdP) use OidcMemberDefinition. You should not provide input for both of these parameters in a single request.
For workforces created using Amazon Cognito, private work teams correspond to Amazon Cognito user groups within the user pool used to create a workforce. All of the CognitoMemberDefinition objects that make up the member definition must have the same ClientId and UserPool values. To add a Amazon Cognito user group to an existing worker pool, see Adding groups to a User Pool. For more information about user pools, see Amazon Cognito User Pools.
For workforces created using your own OIDC IdP, specify the user groups that you want to include in your private work team in OidcMemberDefinition by listing those groups in Groups. Be aware that user groups that are already in the work team must also be listed in Groups when you make this request to remain on the work team. If you do not include these user groups, they will no longer be associated with the work team you update.
A list of MemberDefinition objects that contains objects that identify the workers that make up the work team.
Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use CognitoMemberDefinition. For workforces created using your own OIDC identity provider (IdP) use OidcMemberDefinition.
Metadata properties of the tracking entity, trial, or trial component.
', 'refs' => [ 'CreateActionRequest$MetadataProperties' => NULL, 'CreateArtifactRequest$MetadataProperties' => NULL, 'CreateModelPackageInput$MetadataProperties' => NULL, 'CreateTrialComponentRequest$MetadataProperties' => NULL, 'CreateTrialRequest$MetadataProperties' => NULL, 'DescribeActionResponse$MetadataProperties' => NULL, 'DescribeArtifactResponse$MetadataProperties' => NULL, 'DescribeModelPackageOutput$MetadataProperties' => NULL, 'DescribeTrialComponentResponse$MetadataProperties' => NULL, 'DescribeTrialResponse$MetadataProperties' => NULL, 'ModelPackage$MetadataProperties' => 'Metadata properties of the tracking entity, trial, or trial component.
', 'Trial$MetadataProperties' => NULL, 'TrialComponent$MetadataProperties' => NULL, ], ], 'MetadataPropertyValue' => [ 'base' => NULL, 'refs' => [ 'MetadataProperties$CommitId' => 'The commit ID.
', 'MetadataProperties$Repository' => 'The repository.
', 'MetadataProperties$GeneratedBy' => 'The entity this entity was generated by.
', 'MetadataProperties$ProjectId' => 'The project ID.
', ], ], 'MetricData' => [ 'base' => 'The name, value, and date and time of a metric that was emitted to Amazon CloudWatch.
', 'refs' => [ 'FinalMetricDataList$member' => NULL, ], ], 'MetricDataList' => [ 'base' => NULL, 'refs' => [ 'CandidateProperties$CandidateMetrics' => 'Information about the candidate metrics for an AutoML job.
', ], ], 'MetricDatum' => [ 'base' => 'Information about the metric for a candidate produced by an AutoML job.
', 'refs' => [ 'MetricDataList$member' => NULL, ], ], 'MetricDefinition' => [ 'base' => 'Specifies a metric that the training algorithm writes to stderr or stdout. You can view these logs to understand how your training job performs and check for any errors encountered during training. SageMaker hyperparameter tuning captures all defined metrics. Specify one of the defined metrics to use as an objective metric using the TuningObjective parameter in the HyperParameterTrainingJobDefinition API to evaluate job performance during hyperparameter tuning.
A list of metric definition objects. Each object specifies the metric name and regular expressions used to parse algorithm logs. SageMaker publishes each metric to Amazon CloudWatch.
', 'HyperParameterAlgorithmSpecification$MetricDefinitions' => 'An array of MetricDefinition objects that specify the metrics that the algorithm emits.
', 'TrainingSpecification$MetricDefinitions' => 'A list of MetricDefinition objects, which are used for parsing metrics generated by the algorithm.
The name of the objective metric. For SageMaker built-in algorithms, metrics are defined per algorithm. See the metrics for XGBoost as an example. You can also use a custom algorithm for training and define your own metrics. For more information, see Define metrics and environment variables.
', 'HyperParameterTuningJobObjective$MetricName' => 'The name of the metric to use for the objective metric.
', 'MetricData$MetricName' => 'The name of the metric.
', 'MetricDefinition$Name' => 'The name of the metric.
', 'TrialComponentMetricSummary$MetricName' => 'The name of the metric.
', ], ], 'MetricRegex' => [ 'base' => NULL, 'refs' => [ 'MetricDefinition$Regex' => 'A regular expression that searches the output of a training job and gets the value of the metric. For more information about using regular expressions to define metrics, see Defining metrics and environment variables.
', ], ], 'MetricSetSource' => [ 'base' => NULL, 'refs' => [ 'MetricDatum$Set' => 'The dataset split from which the AutoML job produced the metric.
', ], ], 'MetricSpecification' => [ 'base' => 'An object containing information about a metric.
', 'refs' => [ 'TargetTrackingScalingPolicyConfiguration$MetricSpecification' => 'An object containing information about a metric.
', ], ], 'MetricValue' => [ 'base' => NULL, 'refs' => [ 'FinalAutoMLJobObjectiveMetric$Value' => 'The value of the metric with the best result.
', 'FinalHyperParameterTuningJobObjectiveMetric$Value' => 'The value of the objective metric.
', ], ], 'MetricsSource' => [ 'base' => 'Details about the metrics source.
', 'refs' => [ 'Bias$Report' => 'The bias report for a model
', 'Bias$PreTrainingReport' => 'The pre-training bias report for a model.
', 'Bias$PostTrainingReport' => 'The post-training bias report for a model.
', 'DriftCheckBias$PreTrainingConstraints' => 'The pre-training constraints.
', 'DriftCheckBias$PostTrainingConstraints' => 'The post-training constraints.
', 'DriftCheckExplainability$Constraints' => 'The drift check explainability constraints.
', 'DriftCheckModelDataQuality$Statistics' => 'The drift check model data quality statistics.
', 'DriftCheckModelDataQuality$Constraints' => 'The drift check model data quality constraints.
', 'DriftCheckModelQuality$Statistics' => 'The drift check model quality statistics.
', 'DriftCheckModelQuality$Constraints' => 'The drift check model quality constraints.
', 'Explainability$Report' => 'The explainability report for a model.
', 'ModelDataQuality$Statistics' => 'Data quality statistics for a model.
', 'ModelDataQuality$Constraints' => 'Data quality constraints for a model.
', 'ModelQuality$Statistics' => 'Model quality statistics.
', 'ModelQuality$Constraints' => 'Model quality constraints.
', ], ], 'MinimumInstanceMetadataServiceVersion' => [ 'base' => NULL, 'refs' => [ 'InstanceMetadataServiceConfiguration$MinimumInstanceMetadataServiceVersion' => 'Indicates the minimum IMDS version that the notebook instance supports. When passed as part of CreateNotebookInstance, if no value is selected, then it defaults to IMDSv1. This means that both IMDSv1 and IMDSv2 are supported. If passed as part of UpdateNotebookInstance, there is no default.
The properties of a model as returned by the Search API.
', 'refs' => [ 'ModelDashboardModel$Model' => 'A model displayed in the Model Dashboard.
', ], ], 'ModelApprovalStatus' => [ 'base' => NULL, 'refs' => [ 'BatchDescribeModelPackageSummary$ModelApprovalStatus' => 'The approval status of the model.
', 'CreateModelPackageInput$ModelApprovalStatus' => 'Whether the model is approved for deployment.
This parameter is optional for versioned models, and does not apply to unversioned models.
For versioned models, the value of this parameter must be set to Approved to deploy the model.
The approval status of the model package.
', 'ListModelPackagesInput$ModelApprovalStatus' => 'A filter that returns only the model packages with the specified approval status.
', 'ModelPackage$ModelApprovalStatus' => 'The approval status of the model. This can be one of the following values.
APPROVED - The model is approved
REJECTED - The model is rejected.
PENDING_MANUAL_APPROVAL - The model is waiting for manual approval.
The approval status of the model. This can be one of the following values.
APPROVED - The model is approved
REJECTED - The model is rejected.
PENDING_MANUAL_APPROVAL - The model is waiting for manual approval.
The approval status of the model.
', ], ], 'ModelArn' => [ 'base' => NULL, 'refs' => [ 'CreateModelOutput$ModelArn' => 'The ARN of the model created in SageMaker.
', 'DescribeModelOutput$ModelArn' => 'The Amazon Resource Name (ARN) of the model.
', 'LabelingJobAlgorithmsConfig$InitialActiveLearningModelArn' => 'At the end of an auto-label job Ground Truth sends the Amazon Resource Name (ARN) of the final model used for auto-labeling. You can use this model as the starting point for subsequent similar jobs by providing the ARN of the model here.
', 'LabelingJobOutput$FinalActiveLearningModelArn' => 'The Amazon Resource Name (ARN) for the most recent SageMaker model trained as part of automated data labeling.
', 'Model$ModelArn' => 'The Amazon Resource Name (ARN) of the model.
', 'ModelSummary$ModelArn' => 'The Amazon Resource Name (ARN) of the model.
', ], ], 'ModelArtifacts' => [ 'base' => 'Provides information about the location that is configured for storing model artifacts.
Model artifacts are the output that results from training a model, and typically consist of trained parameters, a model definition that describes how to compute inferences, and other metadata.
', 'refs' => [ 'DescribeCompilationJobResponse$ModelArtifacts' => 'Information about the location in Amazon S3 that has been configured for storing the model artifacts used in the compilation job.
', 'DescribeTrainingJobResponse$ModelArtifacts' => 'Information about the Amazon S3 location that is configured for storing model artifacts.
', 'TrainingJob$ModelArtifacts' => 'Information about the Amazon S3 location that is configured for storing model artifacts.
', ], ], 'ModelBiasAppSpecification' => [ 'base' => 'Docker container image configuration object for the model bias job.
', 'refs' => [ 'CreateModelBiasJobDefinitionRequest$ModelBiasAppSpecification' => 'Configures the model bias job to run a specified Docker container image.
', 'DescribeModelBiasJobDefinitionResponse$ModelBiasAppSpecification' => 'Configures the model bias job to run a specified Docker container image.
', ], ], 'ModelBiasBaselineConfig' => [ 'base' => 'The configuration for a baseline model bias job.
', 'refs' => [ 'CreateModelBiasJobDefinitionRequest$ModelBiasBaselineConfig' => 'The baseline configuration for a model bias job.
', 'DescribeModelBiasJobDefinitionResponse$ModelBiasBaselineConfig' => 'The baseline configuration for a model bias job.
', ], ], 'ModelBiasJobInput' => [ 'base' => 'Inputs for the model bias job.
', 'refs' => [ 'CreateModelBiasJobDefinitionRequest$ModelBiasJobInput' => 'Inputs for the model bias job.
', 'DescribeModelBiasJobDefinitionResponse$ModelBiasJobInput' => 'Inputs for the model bias job.
', ], ], 'ModelCacheSetting' => [ 'base' => NULL, 'refs' => [ 'MultiModelConfig$ModelCacheSetting' => 'Whether to cache models for a multi-model endpoint. By default, multi-model endpoints cache models so that a model does not have to be loaded into memory each time it is invoked. Some use cases do not benefit from model caching. For example, if an endpoint hosts a large number of models that are each invoked infrequently, the endpoint might perform better if you disable model caching. To disable model caching, set the value of this parameter to Disabled.
An Amazon SageMaker Model Card.
', 'refs' => [ 'SearchRecord$ModelCard' => 'An Amazon SageMaker Model Card that documents details about a machine learning model.
', ], ], 'ModelCardArn' => [ 'base' => NULL, 'refs' => [ 'CreateModelCardResponse$ModelCardArn' => 'The Amazon Resource Name (ARN) of the successfully created model card.
', 'DescribeModelCardResponse$ModelCardArn' => 'The Amazon Resource Name (ARN) of the model card.
', 'ModelCard$ModelCardArn' => 'The Amazon Resource Name (ARN) of the model card.
', 'ModelCardSummary$ModelCardArn' => 'The Amazon Resource Name (ARN) of the model card.
', 'ModelCardVersionSummary$ModelCardArn' => 'The Amazon Resource Name (ARN) of the model card.
', 'ModelDashboardModelCard$ModelCardArn' => 'The Amazon Resource Name (ARN) for a model card.
', 'UpdateModelCardResponse$ModelCardArn' => 'The Amazon Resource Name (ARN) of the updated model card.
', ], ], 'ModelCardContent' => [ 'base' => NULL, 'refs' => [ 'CreateModelCardRequest$Content' => 'The content of the model card. Content must be in model card JSON schema and provided as a string.
', 'DescribeModelCardResponse$Content' => 'The content of the model card.
', 'ModelCard$Content' => 'The content of the model card. Content uses the model card JSON schema and provided as a string.
', 'UpdateModelCardRequest$Content' => 'The updated model card content. Content must be in model card JSON schema and provided as a string.
When updating model card content, be sure to include the full content and not just updated content.
', ], ], 'ModelCardExportArtifacts' => [ 'base' => 'The artifacts of the model card export job.
', 'refs' => [ 'DescribeModelCardExportJobResponse$ExportArtifacts' => 'The exported model card artifacts.
', ], ], 'ModelCardExportJobArn' => [ 'base' => NULL, 'refs' => [ 'CreateModelCardExportJobResponse$ModelCardExportJobArn' => 'The Amazon Resource Name (ARN) of the model card export job.
', 'DescribeModelCardExportJobRequest$ModelCardExportJobArn' => 'The Amazon Resource Name (ARN) of the model card export job to describe.
', 'DescribeModelCardExportJobResponse$ModelCardExportJobArn' => 'The Amazon Resource Name (ARN) of the model card export job.
', 'ModelCardExportJobSummary$ModelCardExportJobArn' => 'The Amazon Resource Name (ARN) of the model card export job.
', ], ], 'ModelCardExportJobSortBy' => [ 'base' => 'Attribute by which to sort returned export jobs.', 'refs' => [ 'ListModelCardExportJobsRequest$SortBy' => 'Sort model card export jobs by either name or creation time. Sorts by creation time by default.
', ], ], 'ModelCardExportJobSortOrder' => [ 'base' => NULL, 'refs' => [ 'ListModelCardExportJobsRequest$SortOrder' => 'Sort model card export jobs by ascending or descending order.
', ], ], 'ModelCardExportJobStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeModelCardExportJobResponse$Status' => 'The completion status of the model card export job.
InProgress: The model card export job is in progress.
Completed: The model card export job is complete.
Failed: The model card export job failed. To see the reason for the failure, see the FailureReason field in the response to a DescribeModelCardExportJob call.
Only list model card export jobs with the specified status.
', 'ModelCardExportJobSummary$Status' => 'The completion status of the model card export job.
', ], ], 'ModelCardExportJobSummary' => [ 'base' => 'The summary of the Amazon SageMaker Model Card export job.
', 'refs' => [ 'ModelCardExportJobSummaryList$member' => NULL, ], ], 'ModelCardExportJobSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListModelCardExportJobsResponse$ModelCardExportJobSummaries' => 'The summaries of the listed model card export jobs.
', ], ], 'ModelCardExportOutputConfig' => [ 'base' => 'Configure the export output details for an Amazon SageMaker Model Card.
', 'refs' => [ 'CreateModelCardExportJobRequest$OutputConfig' => 'The model card output configuration that specifies the Amazon S3 path for exporting.
', 'DescribeModelCardExportJobResponse$OutputConfig' => 'The export output details for the model card.
', ], ], 'ModelCardNameOrArn' => [ 'base' => NULL, 'refs' => [ 'CreateModelCardExportJobRequest$ModelCardName' => 'The name or Amazon Resource Name (ARN) of the model card to export.
', 'DescribeModelCardRequest$ModelCardName' => 'The name or Amazon Resource Name (ARN) of the model card to describe.
', 'ListModelCardVersionsRequest$ModelCardName' => 'List model card versions for the model card with the specified name or Amazon Resource Name (ARN).
', 'UpdateModelCardRequest$ModelCardName' => 'The name or Amazon Resource Name (ARN) of the model card to update.
', ], ], 'ModelCardProcessingStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeModelCardResponse$ModelCardProcessingStatus' => 'The processing status of model card deletion. The ModelCardProcessingStatus updates throughout the different deletion steps.
DeletePending: Model card deletion request received.
DeleteInProgress: Model card deletion is in progress.
ContentDeleted: Deleted model card content.
ExportJobsDeleted: Deleted all export jobs associated with the model card.
DeleteCompleted: Successfully deleted the model card.
DeleteFailed: The model card failed to delete.
Configure the security settings to protect model card data.
', 'refs' => [ 'CreateModelCardRequest$SecurityConfig' => 'An optional Key Management Service key to encrypt, decrypt, and re-encrypt model card content for regulated workloads with highly sensitive data.
', 'DescribeModelCardResponse$SecurityConfig' => 'The security configuration used to protect model card content.
', 'ModelCard$SecurityConfig' => 'The security configuration used to protect model card data.
', 'ModelDashboardModelCard$SecurityConfig' => 'The KMS Key ID (KMSKeyId) for encryption of model card information.
Sort model cards by either name or creation time. Sorts by creation time by default.
', ], ], 'ModelCardSortOrder' => [ 'base' => NULL, 'refs' => [ 'ListModelCardVersionsRequest$SortOrder' => 'Sort model card versions by ascending or descending order.
', 'ListModelCardsRequest$SortOrder' => 'Sort model cards by ascending or descending order.
', ], ], 'ModelCardStatus' => [ 'base' => NULL, 'refs' => [ 'CreateModelCardRequest$ModelCardStatus' => 'The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft: The model card is a work in progress.
PendingReview: The model card is pending review.
Approved: The model card is approved.
Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft: The model card is a work in progress.
PendingReview: The model card is pending review.
Approved: The model card is approved.
Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.
Only list model card versions with the specified approval status.
', 'ListModelCardsRequest$ModelCardStatus' => 'Only list model cards with the specified approval status.
', 'ModelCard$ModelCardStatus' => 'The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft: The model card is a work in progress.
PendingReview: The model card is pending review.
Approved: The model card is approved.
Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft: The model card is a work in progress.
PendingReview: The model card is pending review.
Approved: The model card is approved.
Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.
The approval status of the model card version within your organization. Different organizations might have different criteria for model card review and approval.
Draft: The model card is a work in progress.
PendingReview: The model card is pending review.
Approved: The model card is approved.
Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.
The model card status.
', 'UpdateModelCardRequest$ModelCardStatus' => 'The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft: The model card is a work in progress.
PendingReview: The model card is pending review.
Approved: The model card is approved.
Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.
A summary of the model card.
', 'refs' => [ 'ModelCardSummaryList$member' => NULL, ], ], 'ModelCardSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListModelCardsResponse$ModelCardSummaries' => 'The summaries of the listed model cards.
', ], ], 'ModelCardVersionSortBy' => [ 'base' => NULL, 'refs' => [ 'ListModelCardVersionsRequest$SortBy' => 'Sort listed model card versions by version. Sorts by version by default.
', ], ], 'ModelCardVersionSummary' => [ 'base' => 'A summary of a specific version of the model card.
', 'refs' => [ 'ModelCardVersionSummaryList$member' => NULL, ], ], 'ModelCardVersionSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListModelCardVersionsResponse$ModelCardVersionSummaryList' => 'The summaries of the listed versions of the model card.
', ], ], 'ModelClientConfig' => [ 'base' => 'Configures the timeout and maximum number of retries for processing a transform job invocation.
', 'refs' => [ 'CreateTransformJobRequest$ModelClientConfig' => 'Configures the timeout and maximum number of retries for processing a transform job invocation.
', 'DescribeTransformJobResponse$ModelClientConfig' => 'The timeout and maximum number of retries for processing a transform job invocation.
', 'TransformJob$ModelClientConfig' => NULL, ], ], 'ModelCompressionType' => [ 'base' => NULL, 'refs' => [ 'S3ModelDataSource$CompressionType' => 'Specifies how the ML model data is prepared.
If you choose Gzip and choose S3Object as the value of S3DataType, S3Uri identifies an object that is a gzip-compressed TAR archive. SageMaker will attempt to decompress and untar the object during model deployment.
If you choose None and chooose S3Object as the value of S3DataType, S3Uri identifies an object that represents an uncompressed ML model to deploy.
If you choose None and choose S3Prefix as the value of S3DataType, S3Uri identifies a key name prefix, under which all objects represents the uncompressed ML model to deploy.
If you choose None, then SageMaker will follow rules below when creating model data files under /opt/ml/model directory for use by your inference code:
If you choose S3Object as the value of S3DataType, then SageMaker will split the key of the S3 object referenced by S3Uri by slash (/), and use the last part as the filename of the file holding the content of the S3 object.
If you choose S3Prefix as the value of S3DataType, then for each S3 object under the key name pefix referenced by S3Uri, SageMaker will trim its key by the prefix, and use the remainder as the path (relative to /opt/ml/model) of the file holding the content of the S3 object. SageMaker will split the remainder by slash (/), using intermediate parts as directory names and the last part as filename of the file holding the content of the S3 object.
Do not use any of the following as file names or directory names:
An empty or blank string
A string which contains null bytes
A string longer than 255 bytes
A single dot (.)
A double dot (..)
Ambiguous file names will result in model deployment failure. For example, if your uncompressed ML model consists of two S3 objects s3://mybucket/model/weights and s3://mybucket/model/weights/part1 and you specify s3://mybucket/model/ as the value of S3Uri and S3Prefix as the value of S3DataType, then it will result in name clash between /opt/ml/model/weights (a regular file) and /opt/ml/model/weights/ (a directory).
Do not organize the model artifacts in S3 console using folders. When you create a folder in S3 console, S3 creates a 0-byte object with a key set to the folder name you provide. They key of the 0-byte object ends with a slash (/) which violates SageMaker restrictions on model artifact file names, leading to model deployment failure.
Defines the model configuration. Includes the specification name and environment parameters.
', 'refs' => [ 'InferenceRecommendation$ModelConfiguration' => 'Defines the model configuration.
', 'RecommendationJobInferenceBenchmark$ModelConfiguration' => NULL, ], ], 'ModelDashboardEndpoint' => [ 'base' => 'An endpoint that hosts a model displayed in the Amazon SageMaker Model Dashboard.
', 'refs' => [ 'ModelDashboardEndpoints$member' => NULL, ], ], 'ModelDashboardEndpoints' => [ 'base' => NULL, 'refs' => [ 'ModelDashboardModel$Endpoints' => 'The endpoints that host a model.
', ], ], 'ModelDashboardIndicatorAction' => [ 'base' => 'An alert action taken to light up an icon on the Amazon SageMaker Model Dashboard when an alert goes into InAlert status.
An alert action taken to light up an icon on the Model Dashboard when an alert goes into InAlert status.
A model displayed in the Amazon SageMaker Model Dashboard.
', 'refs' => [ 'SearchRecord$Model' => NULL, ], ], 'ModelDashboardModelCard' => [ 'base' => 'The model card for a model displayed in the Amazon SageMaker Model Dashboard.
', 'refs' => [ 'ModelDashboardModel$ModelCard' => 'The model card for a model.
', ], ], 'ModelDashboardMonitoringSchedule' => [ 'base' => 'A monitoring schedule for a model displayed in the Amazon SageMaker Model Dashboard.
', 'refs' => [ 'ModelDashboardMonitoringSchedules$member' => NULL, ], ], 'ModelDashboardMonitoringSchedules' => [ 'base' => NULL, 'refs' => [ 'ModelDashboardModel$MonitoringSchedules' => 'The monitoring schedules for a model.
', ], ], 'ModelDataQuality' => [ 'base' => 'Data quality constraints and statistics for a model.
', 'refs' => [ 'ModelMetrics$ModelDataQuality' => 'Metrics that measure the quality of the input data for a model.
', ], ], 'ModelDataSource' => [ 'base' => 'Specifies the location of ML model data to deploy. If specified, you must specify one and only one of the available data sources.
', 'refs' => [ 'ContainerDefinition$ModelDataSource' => 'Specifies the location of ML model data to deploy.
Currently you cannot use ModelDataSource in conjunction with SageMaker batch transform, SageMaker serverless endpoints, SageMaker multi-model endpoints, and SageMaker Marketplace.
Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
', 'refs' => [ 'CreateAutoMLJobRequest$ModelDeployConfig' => 'Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
', 'CreateAutoMLJobV2Request$ModelDeployConfig' => 'Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
', 'DescribeAutoMLJobResponse$ModelDeployConfig' => 'Indicates whether the model was deployed automatically to an endpoint and the name of that endpoint if deployed automatically.
', 'DescribeAutoMLJobV2Response$ModelDeployConfig' => 'Indicates whether the model was deployed automatically to an endpoint and the name of that endpoint if deployed automatically.
', ], ], 'ModelDeployResult' => [ 'base' => 'Provides information about the endpoint of the model deployment.
', 'refs' => [ 'DescribeAutoMLJobResponse$ModelDeployResult' => 'Provides information about endpoint for the model deployment.
', 'DescribeAutoMLJobV2Response$ModelDeployResult' => 'Provides information about endpoint for the model deployment.
', ], ], 'ModelDigests' => [ 'base' => 'Provides information to verify the integrity of stored model artifacts.
', 'refs' => [ 'DescribeCompilationJobResponse$ModelDigests' => 'Provides a BLAKE2 hash value that identifies the compiled model artifacts in Amazon S3.
', ], ], 'ModelExplainabilityAppSpecification' => [ 'base' => 'Docker container image configuration object for the model explainability job.
', 'refs' => [ 'CreateModelExplainabilityJobDefinitionRequest$ModelExplainabilityAppSpecification' => 'Configures the model explainability job to run a specified Docker container image.
', 'DescribeModelExplainabilityJobDefinitionResponse$ModelExplainabilityAppSpecification' => 'Configures the model explainability job to run a specified Docker container image.
', ], ], 'ModelExplainabilityBaselineConfig' => [ 'base' => 'The configuration for a baseline model explainability job.
', 'refs' => [ 'CreateModelExplainabilityJobDefinitionRequest$ModelExplainabilityBaselineConfig' => 'The baseline configuration for a model explainability job.
', 'DescribeModelExplainabilityJobDefinitionResponse$ModelExplainabilityBaselineConfig' => 'The baseline configuration for a model explainability job.
', ], ], 'ModelExplainabilityJobInput' => [ 'base' => 'Inputs for the model explainability job.
', 'refs' => [ 'CreateModelExplainabilityJobDefinitionRequest$ModelExplainabilityJobInput' => 'Inputs for the model explainability job.
', 'DescribeModelExplainabilityJobDefinitionResponse$ModelExplainabilityJobInput' => 'Inputs for the model explainability job.
', ], ], 'ModelInfrastructureConfig' => [ 'base' => 'The configuration for the infrastructure that the model will be deployed to.
', 'refs' => [ 'ModelVariantConfig$InfrastructureConfig' => 'The configuration for the infrastructure that the model will be deployed to.
', 'ModelVariantConfigSummary$InfrastructureConfig' => 'The configuration of the infrastructure that the model has been deployed to.
', ], ], 'ModelInfrastructureType' => [ 'base' => NULL, 'refs' => [ 'ModelInfrastructureConfig$InfrastructureType' => 'The inference option to which to deploy your model. Possible values are the following:
RealTime: Deploy to real-time inference.
Input object for the model.
', 'refs' => [ 'ModelPackageContainerDefinition$ModelInput' => 'A structure with Model Input details.
', ], ], 'ModelInsightsLocation' => [ 'base' => NULL, 'refs' => [ 'CandidateArtifactLocations$ModelInsights' => 'The Amazon S3 prefix to the model insight artifacts generated for the AutoML candidate.
', ], ], 'ModelLatencyThreshold' => [ 'base' => 'The model latency threshold.
', 'refs' => [ 'ModelLatencyThresholds$member' => NULL, ], ], 'ModelLatencyThresholds' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobStoppingConditions$ModelLatencyThresholds' => 'The interval of time taken by a model to respond as viewed from SageMaker. The interval includes the local communication time taken to send the request and to fetch the response from the container of a model and the time taken to complete the inference in the container.
', ], ], 'ModelMetadataFilter' => [ 'base' => 'Part of the search expression. You can specify the name and value (domain, task, framework, framework version, task, and model).
', 'refs' => [ 'ModelMetadataFilters$member' => NULL, ], ], 'ModelMetadataFilterType' => [ 'base' => NULL, 'refs' => [ 'ModelMetadataFilter$Name' => 'The name of the of the model to filter by.
', ], ], 'ModelMetadataFilters' => [ 'base' => NULL, 'refs' => [ 'ModelMetadataSearchExpression$Filters' => 'A list of filter objects.
', ], ], 'ModelMetadataSearchExpression' => [ 'base' => 'One or more filters that searches for the specified resource or resources in a search. All resource objects that satisfy the expression\'s condition are included in the search results
', 'refs' => [ 'ListModelMetadataRequest$SearchExpression' => 'One or more filters that searches for the specified resource or resources in a search. All resource objects that satisfy the expression\'s condition are included in the search results. Specify the Framework, FrameworkVersion, Domain or Task to filter supported. Filter names and values are case-sensitive.
', ], ], 'ModelMetadataSummaries' => [ 'base' => NULL, 'refs' => [ 'ListModelMetadataResponse$ModelMetadataSummaries' => 'A structure that holds model metadata.
', ], ], 'ModelMetadataSummary' => [ 'base' => 'A summary of the model metadata.
', 'refs' => [ 'ModelMetadataSummaries$member' => NULL, ], ], 'ModelMetrics' => [ 'base' => 'Contains metrics captured from a model.
', 'refs' => [ 'CreateModelPackageInput$ModelMetrics' => 'A structure that contains model metrics reports.
', 'DescribeModelPackageOutput$ModelMetrics' => 'Metrics for the model.
', 'ModelPackage$ModelMetrics' => 'Metrics for the model.
', ], ], 'ModelName' => [ 'base' => NULL, 'refs' => [ 'CreateModelInput$ModelName' => 'The name of the new model.
', 'CreateTransformJobRequest$ModelName' => 'The name of the model that you want to use for the transform job. ModelName must be the name of an existing Amazon SageMaker model within an Amazon Web Services Region in an Amazon Web Services account.
The name of the model to delete.
', 'DescribeModelInput$ModelName' => 'The name of the model.
', 'DescribeModelOutput$ModelName' => 'Name of the SageMaker model.
', 'DescribeTransformJobResponse$ModelName' => 'The name of the model used in the transform job.
', 'InferenceRecommendationsJob$ModelName' => 'The name of the created model.
', 'ListInferenceRecommendationsJobsRequest$ModelNameEquals' => 'A filter that returns only jobs that were created for this model.
', 'Model$ModelName' => 'The name of the model.
', 'ModelSummary$ModelName' => 'The name of the model that you want a summary for.
', 'ModelVariantConfig$ModelName' => 'The name of the Amazon SageMaker Model entity.
', 'ModelVariantConfigSummary$ModelName' => 'The name of the Amazon SageMaker Model entity.
', 'ProductionVariant$ModelName' => 'The name of the model that you want to host. This is the name that you specified when creating the model.
', 'RecommendationJobInputConfig$ModelName' => 'The name of the created model.
', 'TransformJob$ModelName' => 'The name of the model associated with the transform job.
', ], ], 'ModelNameContains' => [ 'base' => NULL, 'refs' => [ 'ListModelsInput$NameContains' => 'A string in the model name. This filter returns only models whose name contains the specified string.
', ], ], 'ModelPackage' => [ 'base' => 'A versioned model that can be deployed for SageMaker inference.
', 'refs' => [ 'SearchRecord$ModelPackage' => NULL, ], ], 'ModelPackageArn' => [ 'base' => NULL, 'refs' => [ 'BatchDescribeModelPackageErrorMap$key' => NULL, 'BatchDescribeModelPackageSummary$ModelPackageArn' => 'The Amazon Resource Name (ARN) of the model package.
', 'CreateCompilationJobRequest$ModelPackageVersionArn' => 'The Amazon Resource Name (ARN) of a versioned model package. Provide either a ModelPackageVersionArn or an InputConfig object in the request syntax. The presence of both objects in the CreateCompilationJob request will return an exception.
The Amazon Resource Name (ARN) of the new model package.
', 'DescribeCompilationJobResponse$ModelPackageVersionArn' => 'The Amazon Resource Name (ARN) of the versioned model package that was provided to SageMaker Neo when you initiated a compilation job.
', 'DescribeModelPackageOutput$ModelPackageArn' => 'The Amazon Resource Name (ARN) of the model package.
', 'InferenceRecommendationsJob$ModelPackageVersionArn' => 'The Amazon Resource Name (ARN) of a versioned model package.
', 'ListInferenceRecommendationsJobsRequest$ModelPackageVersionArnEquals' => 'A filter that returns only jobs that were created for this versioned model package.
', 'ModelPackage$ModelPackageArn' => 'The Amazon Resource Name (ARN) of the model package.
', 'ModelPackageArnList$member' => NULL, 'ModelPackageSummaries$key' => NULL, 'ModelPackageSummary$ModelPackageArn' => 'The Amazon Resource Name (ARN) of the model package.
', 'RecommendationJobInputConfig$ModelPackageVersionArn' => 'The Amazon Resource Name (ARN) of a versioned model package.
', 'UpdateModelPackageInput$ModelPackageArn' => 'The Amazon Resource Name (ARN) of the model package.
', 'UpdateModelPackageOutput$ModelPackageArn' => 'The Amazon Resource Name (ARN) of the model.
', ], ], 'ModelPackageArnList' => [ 'base' => NULL, 'refs' => [ 'BatchDescribeModelPackageInput$ModelPackageArnList' => 'The list of Amazon Resource Name (ARN) of the model package groups.
', ], ], 'ModelPackageContainerDefinition' => [ 'base' => 'Describes the Docker container for the model package.
', 'refs' => [ 'ModelPackageContainerDefinitionList$member' => NULL, ], ], 'ModelPackageContainerDefinitionList' => [ 'base' => NULL, 'refs' => [ 'AdditionalInferenceSpecificationDefinition$Containers' => 'The Amazon ECR registry path of the Docker image that contains the inference code.
', 'InferenceSpecification$Containers' => 'The Amazon ECR registry path of the Docker image that contains the inference code.
', ], ], 'ModelPackageFrameworkVersion' => [ 'base' => NULL, 'refs' => [ 'ModelPackageContainerDefinition$FrameworkVersion' => 'The framework version of the Model Package Container Image.
', ], ], 'ModelPackageGroup' => [ 'base' => 'A group of versioned models in the model registry.
', 'refs' => [ 'SearchRecord$ModelPackageGroup' => NULL, ], ], 'ModelPackageGroupArn' => [ 'base' => NULL, 'refs' => [ 'CreateModelPackageGroupOutput$ModelPackageGroupArn' => 'The Amazon Resource Name (ARN) of the model group.
', 'DescribeModelPackageGroupOutput$ModelPackageGroupArn' => 'The Amazon Resource Name (ARN) of the model group.
', 'ModelPackageGroup$ModelPackageGroupArn' => 'The Amazon Resource Name (ARN) of the model group.
', 'ModelPackageGroupSummary$ModelPackageGroupArn' => 'The Amazon Resource Name (ARN) of the model group.
', 'PutModelPackageGroupPolicyOutput$ModelPackageGroupArn' => 'The Amazon Resource Name (ARN) of the model package group.
', ], ], 'ModelPackageGroupSortBy' => [ 'base' => NULL, 'refs' => [ 'ListModelPackageGroupsInput$SortBy' => 'The field to sort results by. The default is CreationTime.
The status of the model group.
', 'ModelPackageGroup$ModelPackageGroupStatus' => 'The status of the model group. This can be one of the following values.
PENDING - The model group is pending being created.
IN_PROGRESS - The model group is in the process of being created.
COMPLETED - The model group was successfully created.
FAILED - The model group failed.
DELETING - The model group is in the process of being deleted.
DELETE_FAILED - SageMaker failed to delete the model group.
The status of the model group.
', ], ], 'ModelPackageGroupSummary' => [ 'base' => 'Summary information about a model group.
', 'refs' => [ 'ModelPackageGroupSummaryList$member' => NULL, ], ], 'ModelPackageGroupSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListModelPackageGroupsOutput$ModelPackageGroupSummaryList' => 'A list of summaries of the model groups in your Amazon Web Services account.
', ], ], 'ModelPackageSortBy' => [ 'base' => NULL, 'refs' => [ 'ListModelPackagesInput$SortBy' => 'The parameter by which to sort the results. The default is CreationTime.
The status of the mortgage package.
', 'DescribeModelPackageOutput$ModelPackageStatus' => 'The current status of the model package.
', 'ModelPackage$ModelPackageStatus' => 'The status of the model package. This can be one of the following values.
PENDING - The model package is pending being created.
IN_PROGRESS - The model package is in the process of being created.
COMPLETED - The model package was successfully created.
FAILED - The model package failed.
DELETING - The model package is in the process of being deleted.
The overall status of the model package.
', ], ], 'ModelPackageStatusDetails' => [ 'base' => 'Specifies the validation and image scan statuses of the model package.
', 'refs' => [ 'DescribeModelPackageOutput$ModelPackageStatusDetails' => 'Details about the current status of the model package.
', 'ModelPackage$ModelPackageStatusDetails' => 'Specifies the validation and image scan statuses of the model package.
', ], ], 'ModelPackageStatusItem' => [ 'base' => 'Represents the overall status of a model package.
', 'refs' => [ 'ModelPackageStatusItemList$member' => NULL, ], ], 'ModelPackageStatusItemList' => [ 'base' => NULL, 'refs' => [ 'ModelPackageStatusDetails$ValidationStatuses' => 'The validation status of the model package.
', 'ModelPackageStatusDetails$ImageScanStatuses' => 'The status of the scan of the Docker image container for the model package.
', ], ], 'ModelPackageSummaries' => [ 'base' => NULL, 'refs' => [ 'BatchDescribeModelPackageOutput$ModelPackageSummaries' => 'The summaries for the model package versions
', ], ], 'ModelPackageSummary' => [ 'base' => 'Provides summary information about a model package.
', 'refs' => [ 'ModelPackageSummaryList$member' => NULL, ], ], 'ModelPackageSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListModelPackagesOutput$ModelPackageSummaryList' => 'An array of ModelPackageSummary objects, each of which lists a model package.
A filter that returns only the model packages of the specified type. This can be one of the following values.
UNVERSIONED - List only unversioined models. This is the default value if no ModelPackageType is specified.
VERSIONED - List only versioned models.
BOTH - List both versioned and unversioned models.
Contains data, such as the inputs and targeted instance types that are used in the process of validating the model package.
The data provided in the validation profile is made available to your buyers on Amazon Web Services Marketplace.
', 'refs' => [ 'ModelPackageValidationProfiles$member' => NULL, ], ], 'ModelPackageValidationProfiles' => [ 'base' => NULL, 'refs' => [ 'ModelPackageValidationSpecification$ValidationProfiles' => 'An array of ModelPackageValidationProfile objects, each of which specifies a batch transform job that SageMaker runs to validate your model package.
Specifies batch transform jobs that SageMaker runs to validate your model package.
', 'refs' => [ 'CreateModelPackageInput$ValidationSpecification' => 'Specifies configurations for one or more transform jobs that SageMaker runs to test the model package.
', 'DescribeModelPackageOutput$ValidationSpecification' => 'Configurations for one or more transform jobs that SageMaker runs to test the model package.
', 'ModelPackage$ValidationSpecification' => 'Specifies batch transform jobs that SageMaker runs to validate your model package.
', ], ], 'ModelPackageVersion' => [ 'base' => NULL, 'refs' => [ 'BatchDescribeModelPackageSummary$ModelPackageVersion' => 'The version number of a versioned model.
', 'DescribeModelPackageOutput$ModelPackageVersion' => 'The version of the model package.
', 'ModelPackage$ModelPackageVersion' => 'The version number of a versioned model.
', 'ModelPackageSummary$ModelPackageVersion' => 'If the model package is a versioned model, the version of the model.
', ], ], 'ModelQuality' => [ 'base' => 'Model quality statistics and constraints.
', 'refs' => [ 'ModelMetrics$ModelQuality' => 'Metrics that measure the quality of a model.
', ], ], 'ModelQualityAppSpecification' => [ 'base' => 'Container image configuration object for the monitoring job.
', 'refs' => [ 'CreateModelQualityJobDefinitionRequest$ModelQualityAppSpecification' => 'The container that runs the monitoring job.
', 'DescribeModelQualityJobDefinitionResponse$ModelQualityAppSpecification' => 'Configures the model quality job to run a specified Docker container image.
', ], ], 'ModelQualityBaselineConfig' => [ 'base' => 'Configuration for monitoring constraints and monitoring statistics. These baseline resources are compared against the results of the current job from the series of jobs scheduled to collect data periodically.
', 'refs' => [ 'CreateModelQualityJobDefinitionRequest$ModelQualityBaselineConfig' => 'Specifies the constraints and baselines for the monitoring job.
', 'DescribeModelQualityJobDefinitionResponse$ModelQualityBaselineConfig' => 'The baseline configuration for a model quality job.
', ], ], 'ModelQualityJobInput' => [ 'base' => 'The input for the model quality monitoring job. Currently endpoints are supported for input for model quality monitoring jobs.
', 'refs' => [ 'CreateModelQualityJobDefinitionRequest$ModelQualityJobInput' => 'A list of the inputs that are monitored. Currently endpoints are supported.
', 'DescribeModelQualityJobDefinitionResponse$ModelQualityJobInput' => 'Inputs for the model quality job.
', ], ], 'ModelRegisterSettings' => [ 'base' => 'The model registry settings for the SageMaker Canvas application.
', 'refs' => [ 'CanvasAppSettings$ModelRegisterSettings' => 'The model registry settings for the SageMaker Canvas application.
', ], ], 'ModelSetupTime' => [ 'base' => NULL, 'refs' => [ 'RecommendationMetrics$ModelSetupTime' => 'The time it takes to launch new compute resources for a serverless endpoint. The time can vary depending on the model size, how long it takes to download the model, and the start-up time of the container.
NaN indicates that the value is not available.
Sorts the list of results. The default is CreationTime.
Metadata for Model steps.
', 'refs' => [ 'PipelineExecutionStepMetadata$Model' => 'The Amazon Resource Name (ARN) of the model that was created by this step execution.
', ], ], 'ModelSummary' => [ 'base' => 'Provides summary information about a model.
', 'refs' => [ 'ModelSummaryList$member' => NULL, ], ], 'ModelSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListModelsOutput$Models' => 'An array of ModelSummary objects, each of which lists a model.
Array of key-value pairs, with names of variants mapped to actions. The possible actions are the following:
Promote - Promote the shadow variant to a production variant
Remove - Delete the variant
Retain - Keep the variant as it is
Contains information about the deployment options of a model.
', 'refs' => [ 'ModelVariantConfigList$member' => NULL, ], ], 'ModelVariantConfigList' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceExperimentRequest$ModelVariants' => ' An array of ModelVariantConfig objects. There is one for each variant in the inference experiment. Each ModelVariantConfig object in the array describes the infrastructure configuration for the corresponding variant.
An array of ModelVariantConfig objects. There is one for each variant that you want to deploy after the inference experiment stops. Each ModelVariantConfig describes the infrastructure configuration for deploying the corresponding variant.
An array of ModelVariantConfig objects. There is one for each variant, whose infrastructure configuration you want to update.
Summary of the deployment configuration of a model.
', 'refs' => [ 'ModelVariantConfigSummaryList$member' => NULL, ], ], 'ModelVariantConfigSummaryList' => [ 'base' => NULL, 'refs' => [ 'DescribeInferenceExperimentResponse$ModelVariants' => ' An array of ModelVariantConfigSummary objects. There is one for each variant in the inference experiment. Each ModelVariantConfigSummary object in the array describes the infrastructure configuration for deploying the corresponding variant.
The name of the variant.
', 'ModelVariantConfigSummary$VariantName' => 'The name of the variant.
', 'ShadowModeConfig$SourceModelVariantName' => 'The name of the production variant, which takes all the inference requests.
', 'ShadowModelVariantConfig$ShadowModelVariantName' => 'The name of the shadow variant.
', ], ], 'ModelVariantStatus' => [ 'base' => NULL, 'refs' => [ 'ModelVariantConfigSummary$Status' => 'The status of deployment for the model variant on the hosted inference endpoint.
Creating - Amazon SageMaker is preparing the model variant on the hosted inference endpoint.
InService - The model variant is running on the hosted inference endpoint.
Updating - Amazon SageMaker is updating the model variant on the hosted inference endpoint.
Deleting - Amazon SageMaker is deleting the model variant on the hosted inference endpoint.
Deleted - The model variant has been deleted on the hosted inference endpoint. This can only happen after stopping the experiment.
A list of alert actions taken in response to an alert going into InAlert status.
A list of alert actions taken in response to an alert going into InAlert status.
An alert history for a model monitoring schedule.
', ], ], 'MonitoringAlertHistorySortKey' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringAlertHistoryRequest$SortBy' => 'The field used to sort results. The default is CreationTime.
Provides summary information of an alert\'s history.
', 'refs' => [ 'MonitoringAlertHistoryList$member' => NULL, ], ], 'MonitoringAlertName' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringAlertHistoryRequest$MonitoringAlertName' => 'The name of a monitoring alert.
', 'MonitoringAlertHistorySummary$MonitoringAlertName' => 'The name of a monitoring alert.
', 'MonitoringAlertSummary$MonitoringAlertName' => 'The name of a monitoring alert.
', 'UpdateMonitoringAlertRequest$MonitoringAlertName' => 'The name of a monitoring alert.
', 'UpdateMonitoringAlertResponse$MonitoringAlertName' => 'The name of a monitoring alert.
', ], ], 'MonitoringAlertStatus' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringAlertHistoryRequest$StatusEquals' => 'A filter that retrieves only alerts with a specific status.
', 'MonitoringAlertHistorySummary$AlertStatus' => 'The current alert status of an alert.
', 'MonitoringAlertSummary$AlertStatus' => 'The current status of an alert.
', ], ], 'MonitoringAlertSummary' => [ 'base' => 'Provides summary information about a monitor alert.
', 'refs' => [ 'MonitoringAlertSummaryList$member' => NULL, ], ], 'MonitoringAlertSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringAlertsResponse$MonitoringAlertSummaries' => 'A JSON array where each element is a summary for a monitoring alert.
', 'ModelDashboardMonitoringSchedule$MonitoringAlertSummaries' => 'A JSON array where each element is a summary for a monitoring alert.
', ], ], 'MonitoringAppSpecification' => [ 'base' => 'Container image configuration object for the monitoring job.
', 'refs' => [ 'MonitoringJobDefinition$MonitoringAppSpecification' => 'Configures the monitoring job to run a specified Docker container image.
', ], ], 'MonitoringBaselineConfig' => [ 'base' => 'Configuration for monitoring constraints and monitoring statistics. These baseline resources are compared against the results of the current job from the series of jobs scheduled to collect data periodically.
', 'refs' => [ 'MonitoringJobDefinition$BaselineConfig' => 'Baseline configuration used to validate that the data conforms to the specified constraints and statistics
', ], ], 'MonitoringClusterConfig' => [ 'base' => 'Configuration for the cluster used to run model monitoring jobs.
', 'refs' => [ 'MonitoringResources$ClusterConfig' => 'The configuration for the cluster resources used to run the processing job.
', ], ], 'MonitoringConstraintsResource' => [ 'base' => 'The constraints resource for a monitoring job.
', 'refs' => [ 'DataQualityBaselineConfig$ConstraintsResource' => NULL, 'ModelBiasBaselineConfig$ConstraintsResource' => NULL, 'ModelExplainabilityBaselineConfig$ConstraintsResource' => NULL, 'ModelQualityBaselineConfig$ConstraintsResource' => NULL, 'MonitoringBaselineConfig$ConstraintsResource' => 'The baseline constraint file in Amazon S3 that the current monitoring job should validated against.
', ], ], 'MonitoringContainerArguments' => [ 'base' => NULL, 'refs' => [ 'DataQualityAppSpecification$ContainerArguments' => 'The arguments to send to the container that the monitoring job runs.
', 'ModelQualityAppSpecification$ContainerArguments' => 'An array of arguments for the container used to run the monitoring job.
', 'MonitoringAppSpecification$ContainerArguments' => 'An array of arguments for the container used to run the monitoring job.
', ], ], 'MonitoringCsvDatasetFormat' => [ 'base' => 'Represents the CSV dataset format used when running a monitoring job.
', 'refs' => [ 'MonitoringDatasetFormat$Csv' => 'The CSV dataset used in the monitoring job.
', ], ], 'MonitoringDatapointsToAlert' => [ 'base' => NULL, 'refs' => [ 'MonitoringAlertSummary$DatapointsToAlert' => 'Within EvaluationPeriod, how many execution failures will raise an alert.
Within EvaluationPeriod, how many execution failures will raise an alert.
Represents the dataset format used when running a monitoring job.
', 'refs' => [ 'BatchTransformInput$DatasetFormat' => 'The dataset format for your batch transform job.
', ], ], 'MonitoringEnvironmentMap' => [ 'base' => NULL, 'refs' => [ 'DataQualityAppSpecification$Environment' => 'Sets the environment variables in the container that the monitoring job runs.
', 'ModelBiasAppSpecification$Environment' => 'Sets the environment variables in the Docker container.
', 'ModelExplainabilityAppSpecification$Environment' => 'Sets the environment variables in the Docker container.
', 'ModelQualityAppSpecification$Environment' => 'Sets the environment variables in the container that the monitoring job runs.
', 'MonitoringJobDefinition$Environment' => 'Sets the environment variables in the Docker container.
', ], ], 'MonitoringEvaluationPeriod' => [ 'base' => NULL, 'refs' => [ 'MonitoringAlertSummary$EvaluationPeriod' => 'The number of most recent monitoring executions to consider when evaluating alert status.
', 'UpdateMonitoringAlertRequest$EvaluationPeriod' => 'The number of most recent monitoring executions to consider when evaluating alert status.
', ], ], 'MonitoringExecutionSortKey' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringExecutionsRequest$SortBy' => 'Whether to sort the results by the Status, CreationTime, or ScheduledTime field. The default is CreationTime.
Summary of information about the last monitoring job to run.
', 'refs' => [ 'DescribeMonitoringScheduleResponse$LastMonitoringExecutionSummary' => 'Describes metadata on the last execution to run, if there was one.
', 'ModelDashboardMonitoringSchedule$LastMonitoringExecutionSummary' => NULL, 'MonitoringExecutionSummaryList$member' => NULL, 'MonitoringSchedule$LastMonitoringExecutionSummary' => NULL, ], ], 'MonitoringExecutionSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringExecutionsResponse$MonitoringExecutionSummaries' => 'A JSON array in which each element is a summary for a monitoring execution.
', ], ], 'MonitoringGroundTruthS3Input' => [ 'base' => 'The ground truth labels for the dataset used for the monitoring job.
', 'refs' => [ 'ModelBiasJobInput$GroundTruthS3Input' => 'Location of ground truth labels to use in model bias job.
', 'ModelQualityJobInput$GroundTruthS3Input' => 'The ground truth label provided for the model.
', ], ], 'MonitoringInput' => [ 'base' => 'The inputs for a monitoring job.
', 'refs' => [ 'MonitoringInputs$member' => NULL, ], ], 'MonitoringInputs' => [ 'base' => NULL, 'refs' => [ 'MonitoringJobDefinition$MonitoringInputs' => 'The array of inputs for the monitoring job. Currently we support monitoring an Amazon SageMaker Endpoint.
', ], ], 'MonitoringJobDefinition' => [ 'base' => 'Defines the monitoring job.
', 'refs' => [ 'MonitoringScheduleConfig$MonitoringJobDefinition' => 'Defines the monitoring job.
', ], ], 'MonitoringJobDefinitionArn' => [ 'base' => NULL, 'refs' => [ 'CreateDataQualityJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the job definition.
', 'CreateModelBiasJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the model bias job.
', 'CreateModelExplainabilityJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the model explainability job.
', 'CreateModelQualityJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the model quality monitoring job.
', 'DescribeDataQualityJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the data quality monitoring job definition.
', 'DescribeModelBiasJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the model bias job.
', 'DescribeModelExplainabilityJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the model explainability job.
', 'DescribeModelQualityJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the model quality job.
', 'MonitoringJobDefinitionSummary$MonitoringJobDefinitionArn' => 'The Amazon Resource Name (ARN) of the monitoring job.
', ], ], 'MonitoringJobDefinitionName' => [ 'base' => NULL, 'refs' => [ 'CreateDataQualityJobDefinitionRequest$JobDefinitionName' => 'The name for the monitoring job definition.
', 'CreateModelBiasJobDefinitionRequest$JobDefinitionName' => 'The name of the bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'CreateModelExplainabilityJobDefinitionRequest$JobDefinitionName' => 'The name of the model explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'CreateModelQualityJobDefinitionRequest$JobDefinitionName' => 'The name of the monitoring job definition.
', 'DeleteDataQualityJobDefinitionRequest$JobDefinitionName' => 'The name of the data quality monitoring job definition to delete.
', 'DeleteModelBiasJobDefinitionRequest$JobDefinitionName' => 'The name of the model bias job definition to delete.
', 'DeleteModelExplainabilityJobDefinitionRequest$JobDefinitionName' => 'The name of the model explainability job definition to delete.
', 'DeleteModelQualityJobDefinitionRequest$JobDefinitionName' => 'The name of the model quality monitoring job definition to delete.
', 'DescribeDataQualityJobDefinitionRequest$JobDefinitionName' => 'The name of the data quality monitoring job definition to describe.
', 'DescribeDataQualityJobDefinitionResponse$JobDefinitionName' => 'The name of the data quality monitoring job definition.
', 'DescribeModelBiasJobDefinitionRequest$JobDefinitionName' => 'The name of the model bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeModelBiasJobDefinitionResponse$JobDefinitionName' => 'The name of the bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeModelExplainabilityJobDefinitionRequest$JobDefinitionName' => 'The name of the model explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeModelExplainabilityJobDefinitionResponse$JobDefinitionName' => 'The name of the explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeModelQualityJobDefinitionRequest$JobDefinitionName' => 'The name of the model quality job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeModelQualityJobDefinitionResponse$JobDefinitionName' => 'The name of the quality job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'ListMonitoringExecutionsRequest$MonitoringJobDefinitionName' => 'Gets a list of the monitoring job runs of the specified monitoring job definitions.
', 'ListMonitoringSchedulesRequest$MonitoringJobDefinitionName' => 'Gets a list of the monitoring schedules for the specified monitoring job definition.
', 'MonitoringExecutionSummary$MonitoringJobDefinitionName' => 'The name of the monitoring job.
', 'MonitoringJobDefinitionSummary$MonitoringJobDefinitionName' => 'The name of the monitoring job.
', 'MonitoringScheduleConfig$MonitoringJobDefinitionName' => 'The name of the monitoring job definition to schedule.
', 'MonitoringScheduleSummary$MonitoringJobDefinitionName' => 'The name of the monitoring job definition that the schedule is for.
', ], ], 'MonitoringJobDefinitionSortKey' => [ 'base' => NULL, 'refs' => [ 'ListDataQualityJobDefinitionsRequest$SortBy' => 'The field to sort results by. The default is CreationTime.
Whether to sort results by the Name or CreationTime field. The default is CreationTime.
Whether to sort results by the Name or CreationTime field. The default is CreationTime.
The field to sort results by. The default is CreationTime.
Summary information about a monitoring job.
', 'refs' => [ 'MonitoringJobDefinitionSummaryList$member' => NULL, ], ], 'MonitoringJobDefinitionSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListDataQualityJobDefinitionsResponse$JobDefinitionSummaries' => 'A list of data quality monitoring job definitions.
', 'ListModelBiasJobDefinitionsResponse$JobDefinitionSummaries' => 'A JSON array in which each element is a summary for a model bias jobs.
', 'ListModelExplainabilityJobDefinitionsResponse$JobDefinitionSummaries' => 'A JSON array in which each element is a summary for a explainability bias jobs.
', 'ListModelQualityJobDefinitionsResponse$JobDefinitionSummaries' => 'A list of summaries of model quality monitoring job definitions.
', ], ], 'MonitoringJsonDatasetFormat' => [ 'base' => 'Represents the JSON dataset format used when running a monitoring job.
', 'refs' => [ 'MonitoringDatasetFormat$Json' => 'The JSON dataset used in the monitoring job
', ], ], 'MonitoringMaxRuntimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'MonitoringStoppingCondition$MaxRuntimeInSeconds' => 'The maximum runtime allowed in seconds.
The MaxRuntimeInSeconds cannot exceed the frequency of the job. For data quality and model explainability, this can be up to 3600 seconds for an hourly schedule. For model bias and model quality hourly schedules, this can be up to 1800 seconds.
The networking configuration for the monitoring job.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$NetworkConfig' => 'Specifies networking configuration for the monitoring job.
', 'CreateModelBiasJobDefinitionRequest$NetworkConfig' => 'Networking options for a model bias job.
', 'CreateModelExplainabilityJobDefinitionRequest$NetworkConfig' => 'Networking options for a model explainability job.
', 'CreateModelQualityJobDefinitionRequest$NetworkConfig' => 'Specifies the network configuration for the monitoring job.
', 'DescribeDataQualityJobDefinitionResponse$NetworkConfig' => 'The networking configuration for the data quality monitoring job.
', 'DescribeModelBiasJobDefinitionResponse$NetworkConfig' => 'Networking options for a model bias job.
', 'DescribeModelExplainabilityJobDefinitionResponse$NetworkConfig' => 'Networking options for a model explainability job.
', 'DescribeModelQualityJobDefinitionResponse$NetworkConfig' => 'Networking options for a model quality job.
', ], ], 'MonitoringOutput' => [ 'base' => 'The output object for a monitoring job.
', 'refs' => [ 'MonitoringOutputs$member' => NULL, ], ], 'MonitoringOutputConfig' => [ 'base' => 'The output configuration for monitoring jobs.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$DataQualityJobOutputConfig' => NULL, 'CreateModelBiasJobDefinitionRequest$ModelBiasJobOutputConfig' => NULL, 'CreateModelExplainabilityJobDefinitionRequest$ModelExplainabilityJobOutputConfig' => NULL, 'CreateModelQualityJobDefinitionRequest$ModelQualityJobOutputConfig' => NULL, 'DescribeDataQualityJobDefinitionResponse$DataQualityJobOutputConfig' => NULL, 'DescribeModelBiasJobDefinitionResponse$ModelBiasJobOutputConfig' => NULL, 'DescribeModelExplainabilityJobDefinitionResponse$ModelExplainabilityJobOutputConfig' => NULL, 'DescribeModelQualityJobDefinitionResponse$ModelQualityJobOutputConfig' => NULL, 'MonitoringJobDefinition$MonitoringOutputConfig' => 'The array of outputs from the monitoring job to be uploaded to Amazon S3.
', ], ], 'MonitoringOutputs' => [ 'base' => NULL, 'refs' => [ 'MonitoringOutputConfig$MonitoringOutputs' => 'Monitoring outputs for monitoring jobs. This is where the output of the periodic monitoring jobs is uploaded.
', ], ], 'MonitoringParquetDatasetFormat' => [ 'base' => 'Represents the Parquet dataset format used when running a monitoring job.
', 'refs' => [ 'MonitoringDatasetFormat$Parquet' => 'The Parquet dataset used in the monitoring job
', ], ], 'MonitoringProblemType' => [ 'base' => NULL, 'refs' => [ 'ModelQualityAppSpecification$ProblemType' => 'The machine learning problem type of the model that the monitoring job monitors.
', ], ], 'MonitoringResources' => [ 'base' => 'Identifies the resources to deploy for a monitoring job.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$JobResources' => NULL, 'CreateModelBiasJobDefinitionRequest$JobResources' => NULL, 'CreateModelExplainabilityJobDefinitionRequest$JobResources' => NULL, 'CreateModelQualityJobDefinitionRequest$JobResources' => NULL, 'DescribeDataQualityJobDefinitionResponse$JobResources' => NULL, 'DescribeModelBiasJobDefinitionResponse$JobResources' => NULL, 'DescribeModelExplainabilityJobDefinitionResponse$JobResources' => NULL, 'DescribeModelQualityJobDefinitionResponse$JobResources' => NULL, 'MonitoringJobDefinition$MonitoringResources' => 'Identifies the resources, ML compute instances, and ML storage volumes to deploy for a monitoring job. In distributed processing, you specify more than one instance.
', ], ], 'MonitoringS3Output' => [ 'base' => 'Information about where and how you want to store the results of a monitoring job.
', 'refs' => [ 'MonitoringOutput$S3Output' => 'The Amazon S3 storage location where the results of a monitoring job are saved.
', ], ], 'MonitoringS3Uri' => [ 'base' => NULL, 'refs' => [ 'MonitoringGroundTruthS3Input$S3Uri' => 'The address of the Amazon S3 location of the ground truth labels.
', 'MonitoringS3Output$S3Uri' => 'A URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job.
', ], ], 'MonitoringSchedule' => [ 'base' => 'A schedule for a model monitoring job. For information about model monitor, see Amazon SageMaker Model Monitor.
', 'refs' => [ 'MonitoringScheduleList$member' => NULL, ], ], 'MonitoringScheduleArn' => [ 'base' => NULL, 'refs' => [ 'CreateMonitoringScheduleResponse$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of the monitoring schedule.
', 'DescribeMonitoringScheduleResponse$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of the monitoring schedule.
', 'DescribeProcessingJobResponse$MonitoringScheduleArn' => 'The ARN of a monitoring schedule for an endpoint associated with this processing job.
', 'ModelDashboardMonitoringSchedule$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of a monitoring schedule.
', 'MonitoringSchedule$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of the monitoring schedule.
', 'MonitoringScheduleSummary$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of the monitoring schedule.
', 'ProcessingJob$MonitoringScheduleArn' => 'The ARN of a monitoring schedule for an endpoint associated with this processing job.
', 'UpdateMonitoringAlertResponse$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of the monitoring schedule.
', 'UpdateMonitoringScheduleResponse$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of the monitoring schedule.
', ], ], 'MonitoringScheduleConfig' => [ 'base' => 'Configures the monitoring schedule and defines the monitoring job.
', 'refs' => [ 'CreateMonitoringScheduleRequest$MonitoringScheduleConfig' => 'The configuration object that specifies the monitoring schedule and defines the monitoring job.
', 'DescribeMonitoringScheduleResponse$MonitoringScheduleConfig' => 'The configuration object that specifies the monitoring schedule and defines the monitoring job.
', 'ModelDashboardMonitoringSchedule$MonitoringScheduleConfig' => NULL, 'MonitoringSchedule$MonitoringScheduleConfig' => NULL, 'UpdateMonitoringScheduleRequest$MonitoringScheduleConfig' => 'The configuration object that specifies the monitoring schedule and defines the monitoring job.
', ], ], 'MonitoringScheduleList' => [ 'base' => NULL, 'refs' => [ 'Endpoint$MonitoringSchedules' => 'A list of monitoring schedules for the endpoint. For information about model monitoring, see Amazon SageMaker Model Monitor.
', ], ], 'MonitoringScheduleName' => [ 'base' => NULL, 'refs' => [ 'CreateMonitoringScheduleRequest$MonitoringScheduleName' => 'The name of the monitoring schedule. The name must be unique within an Amazon Web Services Region within an Amazon Web Services account.
', 'DeleteMonitoringScheduleRequest$MonitoringScheduleName' => 'The name of the monitoring schedule to delete.
', 'DescribeMonitoringScheduleRequest$MonitoringScheduleName' => 'Name of a previously created monitoring schedule.
', 'DescribeMonitoringScheduleResponse$MonitoringScheduleName' => 'Name of the monitoring schedule.
', 'ListMonitoringAlertHistoryRequest$MonitoringScheduleName' => 'The name of a monitoring schedule.
', 'ListMonitoringAlertsRequest$MonitoringScheduleName' => 'The name of a monitoring schedule.
', 'ListMonitoringExecutionsRequest$MonitoringScheduleName' => 'Name of a specific schedule to fetch jobs for.
', 'ModelDashboardMonitoringSchedule$MonitoringScheduleName' => 'The name of a monitoring schedule.
', 'MonitoringAlertHistorySummary$MonitoringScheduleName' => 'The name of a monitoring schedule.
', 'MonitoringExecutionSummary$MonitoringScheduleName' => 'The name of the monitoring schedule.
', 'MonitoringSchedule$MonitoringScheduleName' => 'The name of the monitoring schedule.
', 'MonitoringScheduleSummary$MonitoringScheduleName' => 'The name of the monitoring schedule.
', 'StartMonitoringScheduleRequest$MonitoringScheduleName' => 'The name of the schedule to start.
', 'StopMonitoringScheduleRequest$MonitoringScheduleName' => 'The name of the schedule to stop.
', 'UpdateMonitoringAlertRequest$MonitoringScheduleName' => 'The name of a monitoring schedule.
', 'UpdateMonitoringScheduleRequest$MonitoringScheduleName' => 'The name of the monitoring schedule. The name must be unique within an Amazon Web Services Region within an Amazon Web Services account.
', ], ], 'MonitoringScheduleSortKey' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringSchedulesRequest$SortBy' => 'Whether to sort the results by the Status, CreationTime, or ScheduledTime field. The default is CreationTime.
Summarizes the monitoring schedule.
', 'refs' => [ 'MonitoringScheduleSummaryList$member' => NULL, ], ], 'MonitoringScheduleSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringSchedulesResponse$MonitoringScheduleSummaries' => 'A JSON array in which each element is a summary for a monitoring schedule.
', ], ], 'MonitoringStatisticsResource' => [ 'base' => 'The statistics resource for a monitoring job.
', 'refs' => [ 'DataQualityBaselineConfig$StatisticsResource' => NULL, 'MonitoringBaselineConfig$StatisticsResource' => 'The baseline statistics file in Amazon S3 that the current monitoring job should be validated against.
', ], ], 'MonitoringStoppingCondition' => [ 'base' => 'A time limit for how long the monitoring job is allowed to run before stopping.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$StoppingCondition' => NULL, 'CreateModelBiasJobDefinitionRequest$StoppingCondition' => NULL, 'CreateModelExplainabilityJobDefinitionRequest$StoppingCondition' => NULL, 'CreateModelQualityJobDefinitionRequest$StoppingCondition' => NULL, 'DescribeDataQualityJobDefinitionResponse$StoppingCondition' => NULL, 'DescribeModelBiasJobDefinitionResponse$StoppingCondition' => NULL, 'DescribeModelExplainabilityJobDefinitionResponse$StoppingCondition' => NULL, 'DescribeModelQualityJobDefinitionResponse$StoppingCondition' => NULL, 'MonitoringJobDefinition$StoppingCondition' => 'Specifies a time limit for how long the monitoring job is allowed to run.
', ], ], 'MonitoringTimeOffsetString' => [ 'base' => NULL, 'refs' => [ 'BatchTransformInput$StartTimeOffset' => 'If specified, monitoring jobs substract this time from the start time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
', 'BatchTransformInput$EndTimeOffset' => 'If specified, monitoring jobs subtract this time from the end time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
', 'EndpointInput$StartTimeOffset' => 'If specified, monitoring jobs substract this time from the start time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
', 'EndpointInput$EndTimeOffset' => 'If specified, monitoring jobs substract this time from the end time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
', ], ], 'MonitoringType' => [ 'base' => NULL, 'refs' => [ 'DescribeMonitoringScheduleResponse$MonitoringType' => 'The type of the monitoring job that this schedule runs. This is one of the following values.
DATA_QUALITY - The schedule is for a data quality monitoring job.
MODEL_QUALITY - The schedule is for a model quality monitoring job.
MODEL_BIAS - The schedule is for a bias monitoring job.
MODEL_EXPLAINABILITY - The schedule is for an explainability monitoring job.
A filter that returns only the monitoring job runs of the specified monitoring type.
', 'ListMonitoringSchedulesRequest$MonitoringTypeEquals' => 'A filter that returns only the monitoring schedules for the specified monitoring type.
', 'ModelDashboardMonitoringSchedule$MonitoringType' => 'The monitor type of a model monitor.
', 'MonitoringExecutionSummary$MonitoringType' => 'The type of the monitoring job.
', 'MonitoringSchedule$MonitoringType' => 'The type of the monitoring job definition to schedule.
', 'MonitoringScheduleConfig$MonitoringType' => 'The type of the monitoring job definition to schedule.
', 'MonitoringScheduleSummary$MonitoringType' => 'The type of the monitoring job definition that the schedule is for.
', ], ], 'MountPath' => [ 'base' => NULL, 'refs' => [ 'FileSystemConfig$MountPath' => 'The path within the image to mount the user\'s EFS home directory. The directory should be empty. If not specified, defaults to /home/sagemaker-user.
', ], ], 'MultiModelConfig' => [ 'base' => 'Specifies additional configuration for hosting multi-model endpoints.
', 'refs' => [ 'ContainerDefinition$MultiModelConfig' => 'Specifies additional configuration for multi-model endpoints.
', ], ], 'NameContains' => [ 'base' => NULL, 'refs' => [ 'ListAlgorithmsInput$NameContains' => 'A string in the algorithm name. This filter returns only algorithms whose name contains the specified string.
', 'ListCompilationJobsRequest$NameContains' => 'A filter that returns the model compilation jobs whose name contains a specified string.
', 'ListDataQualityJobDefinitionsRequest$NameContains' => 'A string in the data quality monitoring job definition name. This filter returns only data quality monitoring job definitions whose name contains the specified string.
', 'ListDeviceFleetsRequest$NameContains' => 'Filter for fleets containing this name in their fleet device name.
', 'ListEdgeDeploymentPlansRequest$NameContains' => 'Selects edge deployment plans with names containing this name.
', 'ListEdgeDeploymentPlansRequest$DeviceFleetNameContains' => 'Selects edge deployment plans with a device fleet name containing this name.
', 'ListEdgePackagingJobsRequest$NameContains' => 'Filter for jobs containing this name in their packaging job name.
', 'ListEdgePackagingJobsRequest$ModelNameContains' => 'Filter for jobs where the model name contains this string.
', 'ListHubContentsRequest$NameContains' => 'Only list hub content if the name contains the specified string.
', 'ListHubsRequest$NameContains' => 'Only list hubs with names that contain the specified string.
', 'ListHyperParameterTuningJobsRequest$NameContains' => 'A string in the tuning job name. This filter returns only tuning jobs whose name contains the specified string.
', 'ListInferenceExperimentsRequest$NameContains' => 'Selects inference experiments whose names contain this name.
', 'ListInferenceRecommendationsJobsRequest$NameContains' => 'A string in the job name. This filter returns only recommendations whose name contains the specified string.
', 'ListLabelingJobsRequest$NameContains' => 'A string in the labeling job name. This filter returns only labeling jobs whose name contains the specified string.
', 'ListModelBiasJobDefinitionsRequest$NameContains' => 'Filter for model bias jobs whose name contains a specified string.
', 'ListModelExplainabilityJobDefinitionsRequest$NameContains' => 'Filter for model explainability jobs whose name contains a specified string.
', 'ListModelPackageGroupsInput$NameContains' => 'A string in the model group name. This filter returns only model groups whose name contains the specified string.
', 'ListModelPackagesInput$NameContains' => 'A string in the model package name. This filter returns only model packages whose name contains the specified string.
', 'ListModelQualityJobDefinitionsRequest$NameContains' => 'A string in the transform job name. This filter returns only model quality monitoring job definitions whose name contains the specified string.
', 'ListMonitoringSchedulesRequest$NameContains' => 'Filter for monitoring schedules whose name contains a specified string.
', 'ListTrainingJobsRequest$NameContains' => 'A string in the training job name. This filter returns only training jobs whose name contains the specified string.
', 'ListTransformJobsRequest$NameContains' => 'A string in the transform job name. This filter returns only transform jobs whose name contains the specified string.
', ], ], 'NeoVpcConfig' => [ 'base' => 'The VpcConfig configuration object that specifies the VPC that you want the compilation jobs to connect to. For more information on controlling access to your Amazon S3 buckets used for compilation job, see Give Amazon SageMaker Compilation Jobs Access to Resources in Your Amazon VPC.
', 'refs' => [ 'CreateCompilationJobRequest$VpcConfig' => 'A VpcConfig object that specifies the VPC that you want your compilation job to connect to. Control access to your models by configuring the VPC. For more information, see Protect Compilation Jobs by Using an Amazon Virtual Private Cloud.
', 'DescribeCompilationJobResponse$VpcConfig' => 'A VpcConfig object that specifies the VPC that you want your compilation job to connect to. Control access to your models by configuring the VPC. For more information, see Protect Compilation Jobs by Using an Amazon Virtual Private Cloud.
', ], ], 'NeoVpcSecurityGroupId' => [ 'base' => NULL, 'refs' => [ 'NeoVpcSecurityGroupIds$member' => NULL, ], ], 'NeoVpcSecurityGroupIds' => [ 'base' => NULL, 'refs' => [ 'NeoVpcConfig$SecurityGroupIds' => 'The VPC security group IDs. IDs have the form of sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
The ID of the subnets in the VPC that you want to connect the compilation job to for accessing the model in Amazon S3.
', ], ], 'NestedFilters' => [ 'base' => 'A list of nested Filter objects. A resource must satisfy the conditions of all filters to be included in the results returned from the Search API.
For example, to filter on a training job\'s InputDataConfig property with a specific channel name and S3Uri prefix, define the following filters:
\'{Name:"InputDataConfig.ChannelName", "Operator":"Equals", "Value":"train"}\',
\'{Name:"InputDataConfig.DataSource.S3DataSource.S3Uri", "Operator":"Contains", "Value":"mybucket/catdata"}\'
A list of nested filter objects.
', ], ], 'NetworkConfig' => [ 'base' => 'Networking options for a job, such as network traffic encryption between containers, whether to allow inbound and outbound network calls to and from containers, and the VPC subnets and security groups to use for VPC-enabled jobs.
', 'refs' => [ 'CreateProcessingJobRequest$NetworkConfig' => 'Networking options for a processing job, such as whether to allow inbound and outbound network calls to and from processing containers, and the VPC subnets and security groups to use for VPC-enabled processing jobs.
', 'DescribeProcessingJobResponse$NetworkConfig' => 'Networking options for a processing job.
', 'MonitoringJobDefinition$NetworkConfig' => 'Specifies networking options for an monitoring job.
', 'ProcessingJob$NetworkConfig' => NULL, ], ], 'NetworkInterfaceId' => [ 'base' => NULL, 'refs' => [ 'DescribeNotebookInstanceOutput$NetworkInterfaceId' => 'The network interface IDs that SageMaker created at the time of creating the instance.
', ], ], 'NextToken' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceRequest$NextToken' => 'Next token of device description.
', 'DescribeDeviceResponse$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'DescribeEdgeDeploymentPlanRequest$NextToken' => 'If the edge deployment plan has enough stages to require tokening, then this is the response from the last list of stages returned.
', 'DescribeEdgeDeploymentPlanResponse$NextToken' => 'Token to use when calling the next set of stages in the edge deployment plan.
', 'DescribeFeatureGroupRequest$NextToken' => 'A token to resume pagination of the list of Features (FeatureDefinitions). 2,500 Features are returned by default.
A token to resume pagination of the list of Features (FeatureDefinitions).
If the previous call to ListActions didn\'t return the full set of actions, the call returns a token for getting the next set of actions.
A token for getting the next set of actions, if there are any.
', 'ListAlgorithmsInput$NextToken' => 'If the response to a previous ListAlgorithms request was truncated, the response includes a NextToken. To retrieve the next set of algorithms, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of algorithms, use it in the subsequent request.
', 'ListAliasesRequest$NextToken' => 'If the previous call to ListAliases didn\'t return the full set of aliases, the call returns a token for retrieving the next set of aliases.
A token for getting the next set of aliases, if more aliases exist.
', 'ListAppImageConfigsRequest$NextToken' => 'If the previous call to ListImages didn\'t return the full set of AppImageConfigs, the call returns a token for getting the next set of AppImageConfigs.
A token for getting the next set of AppImageConfigs, if there are any.
', 'ListAppsRequest$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListAppsResponse$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListArtifactsRequest$NextToken' => 'If the previous call to ListArtifacts didn\'t return the full set of artifacts, the call returns a token for getting the next set of artifacts.
A token for getting the next set of artifacts, if there are any.
', 'ListAssociationsRequest$NextToken' => 'If the previous call to ListAssociations didn\'t return the full set of associations, the call returns a token for getting the next set of associations.
A token for getting the next set of associations, if there are any.
', 'ListAutoMLJobsRequest$NextToken' => 'If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
', 'ListAutoMLJobsResponse$NextToken' => 'If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
', 'ListCandidatesForAutoMLJobRequest$NextToken' => 'If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
', 'ListCandidatesForAutoMLJobResponse$NextToken' => 'If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
', 'ListCodeRepositoriesInput$NextToken' => 'If the result of a ListCodeRepositoriesOutput request was truncated, the response includes a NextToken. To get the next set of Git repositories, use the token in the next request.
If the result of a ListCodeRepositoriesOutput request was truncated, the response includes a NextToken. To get the next set of Git repositories, use the token in the next request.
If the result of the previous ListCompilationJobs request was truncated, the response includes a NextToken. To retrieve the next set of model compilation jobs, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this NextToken. To retrieve the next set of model compilation jobs, use this token in the next request.
If the previous call to ListContexts didn\'t return the full set of contexts, the call returns a token for getting the next set of contexts.
A token for getting the next set of contexts, if there are any.
', 'ListDataQualityJobDefinitionsRequest$NextToken' => 'If the result of the previous ListDataQualityJobDefinitions request was truncated, the response includes a NextToken. To retrieve the next set of transform jobs, use the token in the next request.>
If the result of the previous ListDataQualityJobDefinitions request was truncated, the response includes a NextToken. To retrieve the next set of data quality monitoring job definitions, use the token in the next request.
The response from the last list when returning a list large enough to need tokening.
', 'ListDeviceFleetsResponse$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'ListDevicesRequest$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'ListDevicesResponse$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'ListDomainsRequest$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListDomainsResponse$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListEdgeDeploymentPlansRequest$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'ListEdgeDeploymentPlansResponse$NextToken' => 'The token to use when calling the next page of results.
', 'ListEdgePackagingJobsRequest$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'ListEdgePackagingJobsResponse$NextToken' => 'Token to use when calling the next page of results.
', 'ListExperimentsRequest$NextToken' => 'If the previous call to ListExperiments didn\'t return the full set of experiments, the call returns a token for getting the next set of experiments.
A token for getting the next set of experiments, if there are any.
', 'ListFeatureGroupsRequest$NextToken' => 'A token to resume pagination of ListFeatureGroups results.
A token to resume pagination of ListFeatureGroups results.
A token to resume pagination.
', 'ListFlowDefinitionsResponse$NextToken' => 'A token to resume pagination.
', 'ListHubContentVersionsRequest$NextToken' => 'If the response to a previous ListHubContentVersions request was truncated, the response includes a NextToken. To retrieve the next set of hub content versions, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of hub content versions, use it in the subsequent request.
', 'ListHubContentsRequest$NextToken' => 'If the response to a previous ListHubContents request was truncated, the response includes a NextToken. To retrieve the next set of hub content, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of hub content, use it in the subsequent request.
', 'ListHubsRequest$NextToken' => 'If the response to a previous ListHubs request was truncated, the response includes a NextToken. To retrieve the next set of hubs, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of hubs, use it in the subsequent request.
', 'ListHumanTaskUisRequest$NextToken' => 'A token to resume pagination.
', 'ListHumanTaskUisResponse$NextToken' => 'A token to resume pagination.
', 'ListHyperParameterTuningJobsRequest$NextToken' => 'If the result of the previous ListHyperParameterTuningJobs request was truncated, the response includes a NextToken. To retrieve the next set of tuning jobs, use the token in the next request.
If the result of this ListHyperParameterTuningJobs request was truncated, the response includes a NextToken. To retrieve the next set of tuning jobs, use the token in the next request.
If the previous call to ListImageVersions didn\'t return the full set of versions, the call returns a token for getting the next set of versions.
A token for getting the next set of versions, if there are any.
', 'ListImagesRequest$NextToken' => 'If the previous call to ListImages didn\'t return the full set of images, the call returns a token for getting the next set of images.
A token for getting the next set of images, if there are any.
', 'ListInferenceExperimentsRequest$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'ListInferenceExperimentsResponse$NextToken' => 'The token to use when calling the next page of results.
', 'ListInferenceRecommendationsJobStepsRequest$NextToken' => 'A token that you can specify to return more results from the list. Specify this field if you have a token that was returned from a previous request.
', 'ListInferenceRecommendationsJobStepsResponse$NextToken' => 'A token that you can specify in your next request to return more results from the list.
', 'ListInferenceRecommendationsJobsRequest$NextToken' => 'If the response to a previous ListInferenceRecommendationsJobsRequest request was truncated, the response includes a NextToken. To retrieve the next set of recommendations, use the token in the next request.
A token for getting the next set of recommendations, if there are any.
', 'ListLabelingJobsForWorkteamRequest$NextToken' => 'If the result of the previous ListLabelingJobsForWorkteam request was truncated, the response includes a NextToken. To retrieve the next set of labeling jobs, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of labeling jobs, use it in the subsequent request.
', 'ListLabelingJobsRequest$NextToken' => 'If the result of the previous ListLabelingJobs request was truncated, the response includes a NextToken. To retrieve the next set of labeling jobs, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of labeling jobs, use it in the subsequent request.
', 'ListLineageGroupsRequest$NextToken' => 'If the response is truncated, SageMaker returns this token. To retrieve the next set of algorithms, use it in the subsequent request.
', 'ListLineageGroupsResponse$NextToken' => 'If the response is truncated, SageMaker returns this token. To retrieve the next set of algorithms, use it in the subsequent request.
', 'ListModelBiasJobDefinitionsRequest$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListModelBiasJobDefinitionsResponse$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListModelCardExportJobsRequest$NextToken' => 'If the response to a previous ListModelCardExportJobs request was truncated, the response includes a NextToken. To retrieve the next set of model card export jobs, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of model card export jobs, use it in the subsequent request.
', 'ListModelCardVersionsRequest$NextToken' => 'If the response to a previous ListModelCardVersions request was truncated, the response includes a NextToken. To retrieve the next set of model card versions, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of model card versions, use it in the subsequent request.
', 'ListModelCardsRequest$NextToken' => 'If the response to a previous ListModelCards request was truncated, the response includes a NextToken. To retrieve the next set of model cards, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of model cards, use it in the subsequent request.
', 'ListModelExplainabilityJobDefinitionsRequest$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListModelExplainabilityJobDefinitionsResponse$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListModelMetadataRequest$NextToken' => 'If the response to a previous ListModelMetadataResponse request was truncated, the response includes a NextToken. To retrieve the next set of model metadata, use the token in the next request.
A token for getting the next set of recommendations, if there are any.
', 'ListModelPackageGroupsInput$NextToken' => 'If the result of the previous ListModelPackageGroups request was truncated, the response includes a NextToken. To retrieve the next set of model groups, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of model groups, use it in the subsequent request.
', 'ListModelPackagesInput$NextToken' => 'If the response to a previous ListModelPackages request was truncated, the response includes a NextToken. To retrieve the next set of model packages, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of model packages, use it in the subsequent request.
', 'ListModelQualityJobDefinitionsRequest$NextToken' => 'If the result of the previous ListModelQualityJobDefinitions request was truncated, the response includes a NextToken. To retrieve the next set of model quality monitoring job definitions, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of model quality monitoring job definitions, use it in the next request.
', 'ListMonitoringAlertHistoryRequest$NextToken' => 'If the result of the previous ListMonitoringAlertHistory request was truncated, the response includes a NextToken. To retrieve the next set of alerts in the history, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of alerts, use it in the subsequent request.
', 'ListMonitoringAlertsRequest$NextToken' => 'If the result of the previous ListMonitoringAlerts request was truncated, the response includes a NextToken. To retrieve the next set of alerts in the history, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of alerts, use it in the subsequent request.
', 'ListMonitoringExecutionsRequest$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListMonitoringExecutionsResponse$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListMonitoringSchedulesRequest$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListMonitoringSchedulesResponse$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListNotebookInstanceLifecycleConfigsInput$NextToken' => 'If the result of a ListNotebookInstanceLifecycleConfigs request was truncated, the response includes a NextToken. To get the next set of lifecycle configurations, use the token in the next request.
If the response is truncated, SageMaker returns this token. To get the next set of lifecycle configurations, use it in the next request.
', 'ListNotebookInstancesInput$NextToken' => ' If the previous call to the ListNotebookInstances is truncated, the response includes a NextToken. You can use this token in your subsequent ListNotebookInstances request to fetch the next set of notebook instances.
You might specify a filter or a sort order in your request. When response is truncated, you must use the same values for the filer and sort order in the next request.
If the response to the previous ListNotebookInstances request was truncated, SageMaker returns this token. To retrieve the next set of notebook instances, use the token in the next request.
If the result of the previous ListPipelineExecutionSteps request was truncated, the response includes a NextToken. To retrieve the next set of pipeline execution steps, use the token in the next request.
If the result of the previous ListPipelineExecutionSteps request was truncated, the response includes a NextToken. To retrieve the next set of pipeline execution steps, use the token in the next request.
If the result of the previous ListPipelineExecutions request was truncated, the response includes a NextToken. To retrieve the next set of pipeline executions, use the token in the next request.
If the result of the previous ListPipelineExecutions request was truncated, the response includes a NextToken. To retrieve the next set of pipeline executions, use the token in the next request.
If the result of the previous ListPipelineParametersForExecution request was truncated, the response includes a NextToken. To retrieve the next set of parameters, use the token in the next request.
If the result of the previous ListPipelineParametersForExecution request was truncated, the response includes a NextToken. To retrieve the next set of parameters, use the token in the next request.
If the result of the previous ListPipelines request was truncated, the response includes a NextToken. To retrieve the next set of pipelines, use the token in the next request.
If the result of the previous ListPipelines request was truncated, the response includes a NextToken. To retrieve the next set of pipelines, use the token in the next request.
If the result of the previous ListProcessingJobs request was truncated, the response includes a NextToken. To retrieve the next set of processing jobs, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of processing jobs, use it in the subsequent request.
', 'ListProjectsInput$NextToken' => 'If the result of the previous ListProjects request was truncated, the response includes a NextToken. To retrieve the next set of projects, use the token in the next request.
If the result of the previous ListCompilationJobs request was truncated, the response includes a NextToken. To retrieve the next set of model compilation jobs, use the token in the next request.
A token to resume pagination of ListResourceCatalogs results.
A token to resume pagination of ListResourceCatalogs results.
If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListSpacesResponse$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListStageDevicesRequest$NextToken' => 'The response from the last list when returning a list large enough to neeed tokening.
', 'ListStageDevicesResponse$NextToken' => 'The token to use when calling the next page of results.
', 'ListStudioLifecycleConfigsRequest$NextToken' => 'If the previous call to ListStudioLifecycleConfigs didn\'t return the full set of Lifecycle Configurations, the call returns a token for getting the next set of Lifecycle Configurations.
', 'ListStudioLifecycleConfigsResponse$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListSubscribedWorkteamsRequest$NextToken' => 'If the result of the previous ListSubscribedWorkteams request was truncated, the response includes a NextToken. To retrieve the next set of labeling jobs, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of work teams, use it in the subsequent request.
', 'ListTagsInput$NextToken' => ' If the response to the previous ListTags request is truncated, SageMaker returns this token. To retrieve the next set of tags, use it in the subsequent request.
If response is truncated, SageMaker includes a token in the response. You can use this token in your subsequent request to fetch next set of tokens.
', 'ListTrainingJobsForHyperParameterTuningJobRequest$NextToken' => 'If the result of the previous ListTrainingJobsForHyperParameterTuningJob request was truncated, the response includes a NextToken. To retrieve the next set of training jobs, use the token in the next request.
If the result of this ListTrainingJobsForHyperParameterTuningJob request was truncated, the response includes a NextToken. To retrieve the next set of training jobs, use the token in the next request.
If the result of the previous ListTrainingJobs request was truncated, the response includes a NextToken. To retrieve the next set of training jobs, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of training jobs, use it in the subsequent request.
', 'ListTransformJobsRequest$NextToken' => 'If the result of the previous ListTransformJobs request was truncated, the response includes a NextToken. To retrieve the next set of transform jobs, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of transform jobs, use it in the next request.
', 'ListTrialComponentsRequest$NextToken' => 'If the previous call to ListTrialComponents didn\'t return the full set of components, the call returns a token for getting the next set of components.
A token for getting the next set of components, if there are any.
', 'ListTrialsRequest$NextToken' => 'If the previous call to ListTrials didn\'t return the full set of trials, the call returns a token for getting the next set of trials.
A token for getting the next set of trials, if there are any.
', 'ListUserProfilesRequest$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListUserProfilesResponse$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListWorkforcesRequest$NextToken' => 'A token to resume pagination.
', 'ListWorkforcesResponse$NextToken' => 'A token to resume pagination.
', 'ListWorkteamsRequest$NextToken' => 'If the result of the previous ListWorkteams request was truncated, the response includes a NextToken. To retrieve the next set of labeling jobs, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of work teams, use it in the subsequent request.
', 'SearchRequest$NextToken' => 'If more than MaxResults resources match the specified SearchExpression, the response includes a NextToken. The NextToken can be passed to the next SearchRequest to continue retrieving results.
If the result of the previous Search request was truncated, the response includes a NextToken. To retrieve the next set of results, use the token in the next request.
A list of Elastic Inference (EI) instance types to associate with this notebook instance. Currently, only one instance type can be associated with a notebook instance. For more information, see Using Elastic Inference in Amazon SageMaker.
', 'DescribeNotebookInstanceOutput$AcceleratorTypes' => 'A list of the Elastic Inference (EI) instance types associated with this notebook instance. Currently only one EI instance type can be associated with a notebook instance. For more information, see Using Elastic Inference in Amazon SageMaker.
', 'UpdateNotebookInstanceInput$AcceleratorTypes' => 'A list of the Elastic Inference (EI) instance types to associate with this notebook instance. Currently only one EI instance type can be associated with a notebook instance. For more information, see Using Elastic Inference in Amazon SageMaker.
', ], ], 'NotebookInstanceArn' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceOutput$NotebookInstanceArn' => 'The Amazon Resource Name (ARN) of the notebook instance.
', 'DescribeNotebookInstanceOutput$NotebookInstanceArn' => 'The Amazon Resource Name (ARN) of the notebook instance.
', 'NotebookInstanceSummary$NotebookInstanceArn' => 'The Amazon Resource Name (ARN) of the notebook instance.
', ], ], 'NotebookInstanceLifecycleConfigArn' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceLifecycleConfigOutput$NotebookInstanceLifecycleConfigArn' => 'The Amazon Resource Name (ARN) of the lifecycle configuration.
', 'DescribeNotebookInstanceLifecycleConfigOutput$NotebookInstanceLifecycleConfigArn' => 'The Amazon Resource Name (ARN) of the lifecycle configuration.
', 'NotebookInstanceLifecycleConfigSummary$NotebookInstanceLifecycleConfigArn' => 'The Amazon Resource Name (ARN) of the lifecycle configuration.
', ], ], 'NotebookInstanceLifecycleConfigContent' => [ 'base' => NULL, 'refs' => [ 'NotebookInstanceLifecycleHook$Content' => 'A base64-encoded string that contains a shell script for a notebook instance lifecycle configuration.
', ], ], 'NotebookInstanceLifecycleConfigList' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceLifecycleConfigInput$OnCreate' => 'A shell script that runs only once, when you create a notebook instance. The shell script must be a base64-encoded string.
', 'CreateNotebookInstanceLifecycleConfigInput$OnStart' => 'A shell script that runs every time you start a notebook instance, including when you create the notebook instance. The shell script must be a base64-encoded string.
', 'DescribeNotebookInstanceLifecycleConfigOutput$OnCreate' => 'The shell script that runs only once, when you create a notebook instance.
', 'DescribeNotebookInstanceLifecycleConfigOutput$OnStart' => 'The shell script that runs every time you start a notebook instance, including when you create the notebook instance.
', 'UpdateNotebookInstanceLifecycleConfigInput$OnCreate' => 'The shell script that runs only once, when you create a notebook instance. The shell script must be a base64-encoded string.
', 'UpdateNotebookInstanceLifecycleConfigInput$OnStart' => 'The shell script that runs every time you start a notebook instance, including when you create the notebook instance. The shell script must be a base64-encoded string.
', ], ], 'NotebookInstanceLifecycleConfigName' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$LifecycleConfigName' => 'The name of a lifecycle configuration to associate with the notebook instance. For information about lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
', 'CreateNotebookInstanceLifecycleConfigInput$NotebookInstanceLifecycleConfigName' => 'The name of the lifecycle configuration.
', 'DeleteNotebookInstanceLifecycleConfigInput$NotebookInstanceLifecycleConfigName' => 'The name of the lifecycle configuration to delete.
', 'DescribeNotebookInstanceLifecycleConfigInput$NotebookInstanceLifecycleConfigName' => 'The name of the lifecycle configuration to describe.
', 'DescribeNotebookInstanceLifecycleConfigOutput$NotebookInstanceLifecycleConfigName' => 'The name of the lifecycle configuration.
', 'DescribeNotebookInstanceOutput$NotebookInstanceLifecycleConfigName' => 'Returns the name of a notebook instance lifecycle configuration.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance
', 'ListNotebookInstancesInput$NotebookInstanceLifecycleConfigNameContains' => 'A string in the name of a notebook instances lifecycle configuration associated with this notebook instance. This filter returns only notebook instances associated with a lifecycle configuration with a name that contains the specified string.
', 'NotebookInstanceLifecycleConfigSummary$NotebookInstanceLifecycleConfigName' => 'The name of the lifecycle configuration.
', 'NotebookInstanceSummary$NotebookInstanceLifecycleConfigName' => 'The name of a notebook instance lifecycle configuration associated with this notebook instance.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
', 'UpdateNotebookInstanceInput$LifecycleConfigName' => 'The name of a lifecycle configuration to associate with the notebook instance. For information about lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
', 'UpdateNotebookInstanceLifecycleConfigInput$NotebookInstanceLifecycleConfigName' => 'The name of the lifecycle configuration.
', ], ], 'NotebookInstanceLifecycleConfigNameContains' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstanceLifecycleConfigsInput$NameContains' => 'A string in the lifecycle configuration name. This filter returns only lifecycle configurations whose name contains the specified string.
', ], ], 'NotebookInstanceLifecycleConfigSortKey' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstanceLifecycleConfigsInput$SortBy' => 'Sorts the list of results. The default is CreationTime.
The sort order for results.
', ], ], 'NotebookInstanceLifecycleConfigSummary' => [ 'base' => 'Provides a summary of a notebook instance lifecycle configuration.
', 'refs' => [ 'NotebookInstanceLifecycleConfigSummaryList$member' => NULL, ], ], 'NotebookInstanceLifecycleConfigSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstanceLifecycleConfigsOutput$NotebookInstanceLifecycleConfigs' => 'An array of NotebookInstanceLifecycleConfiguration objects, each listing a lifecycle configuration.
Contains the notebook instance lifecycle configuration script.
Each lifecycle configuration script has a limit of 16384 characters.
The value of the $PATH environment variable that is available to both scripts is /sbin:bin:/usr/sbin:/usr/bin.
View CloudWatch Logs for notebook instance lifecycle configurations in log group /aws/sagemaker/NotebookInstances in log stream [notebook-instance-name]/[LifecycleConfigHook].
Lifecycle configuration scripts cannot run for longer than 5 minutes. If a script runs for longer than 5 minutes, it fails and the notebook instance is not created or started.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
', 'refs' => [ 'NotebookInstanceLifecycleConfigList$member' => NULL, ], ], 'NotebookInstanceName' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$NotebookInstanceName' => 'The name of the new notebook instance.
', 'CreatePresignedNotebookInstanceUrlInput$NotebookInstanceName' => 'The name of the notebook instance.
', 'DeleteNotebookInstanceInput$NotebookInstanceName' => 'The name of the SageMaker notebook instance to delete.
', 'DescribeNotebookInstanceInput$NotebookInstanceName' => 'The name of the notebook instance that you want information about.
', 'DescribeNotebookInstanceOutput$NotebookInstanceName' => 'The name of the SageMaker notebook instance.
', 'NotebookInstanceSummary$NotebookInstanceName' => 'The name of the notebook instance that you want a summary for.
', 'StartNotebookInstanceInput$NotebookInstanceName' => 'The name of the notebook instance to start.
', 'StopNotebookInstanceInput$NotebookInstanceName' => 'The name of the notebook instance to terminate.
', 'UpdateNotebookInstanceInput$NotebookInstanceName' => 'The name of the notebook instance to update.
', ], ], 'NotebookInstanceNameContains' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstancesInput$NameContains' => 'A string in the notebook instances\' name. This filter returns only notebook instances whose name contains the specified string.
', ], ], 'NotebookInstanceSortKey' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstancesInput$SortBy' => 'The field to sort results by. The default is Name.
The sort order for results.
', ], ], 'NotebookInstanceStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeNotebookInstanceOutput$NotebookInstanceStatus' => 'The status of the notebook instance.
', 'ListNotebookInstancesInput$StatusEquals' => 'A filter that returns only notebook instances with the specified status.
', 'NotebookInstanceSummary$NotebookInstanceStatus' => 'The status of the notebook instance.
', ], ], 'NotebookInstanceSummary' => [ 'base' => 'Provides summary information for an SageMaker notebook instance.
', 'refs' => [ 'NotebookInstanceSummaryList$member' => NULL, ], ], 'NotebookInstanceSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstancesOutput$NotebookInstances' => 'An array of NotebookInstanceSummary objects, one for each notebook instance.
A JSON object that contains the URL string.
', 'DescribeNotebookInstanceOutput$Url' => 'The URL that you use to connect to the Jupyter notebook that is running in your notebook instance.
', 'NotebookInstanceSummary$Url' => 'The URL that you use to connect to the Jupyter notebook running in your notebook instance.
', ], ], 'NotebookInstanceVolumeSizeInGB' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$VolumeSizeInGB' => 'The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB.
', 'DescribeNotebookInstanceOutput$VolumeSizeInGB' => 'The size, in GB, of the ML storage volume attached to the notebook instance.
', 'UpdateNotebookInstanceInput$VolumeSizeInGB' => 'The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB. ML storage volumes are encrypted, so SageMaker can\'t determine the amount of available free space on the volume. Because of this, you can increase the volume size when you update a notebook instance, but you can\'t decrease the volume size. If you want to decrease the size of the ML storage volume in use, create a new notebook instance with the desired size.
', ], ], 'NotebookOutputOption' => [ 'base' => NULL, 'refs' => [ 'SharingSettings$NotebookOutputOption' => 'Whether to include the notebook cell output when sharing the notebook. The default is Disabled.
Configures Amazon SNS notifications of available or expiring work items for work teams.
', 'refs' => [ 'CreateWorkteamRequest$NotificationConfiguration' => 'Configures notification of workers regarding available or expiring work items.
', 'UpdateWorkteamRequest$NotificationConfiguration' => 'Configures SNS topic notifications for available or expiring work items
', 'Workteam$NotificationConfiguration' => 'Configures SNS notifications of available or expiring work items for work teams.
', ], ], 'NotificationTopicArn' => [ 'base' => NULL, 'refs' => [ 'NotificationConfiguration$NotificationTopicArn' => 'The ARN for the Amazon SNS topic to which notifications should be published.
', ], ], 'NumberOfHumanWorkersPerDataObject' => [ 'base' => NULL, 'refs' => [ 'HumanTaskConfig$NumberOfHumanWorkersPerDataObject' => 'The number of human workers that will label an object.
', 'LabelingJobForWorkteamSummary$NumberOfHumanWorkersPerDataObject' => 'The configured number of workers per data object.
', ], ], 'NumberOfSteps' => [ 'base' => NULL, 'refs' => [ 'Stairs$NumberOfSteps' => 'Specifies how many steps to perform during traffic.
', ], ], 'ObjectiveStatus' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidate$ObjectiveStatus' => 'The objective\'s status.
', 'HyperParameterTrainingJobSummary$ObjectiveStatus' => 'The status of the objective metric for the training job:
Succeeded: The final objective metric for the training job was evaluated by the hyperparameter tuning job and used in the hyperparameter tuning process.
Pending: The training job is in progress and evaluation of its final objective metric is pending.
Failed: The final objective metric for the training job was not evaluated, and was not used in the hyperparameter tuning process. This typically occurs when the training job failed or did not emit an objective metric.
The number of training jobs whose final objective metric was evaluated by the hyperparameter tuning job and used in the hyperparameter tuning process.
', 'ObjectiveStatusCounters$Pending' => 'The number of training jobs that are in progress and pending evaluation of their final objective metric.
', 'ObjectiveStatusCounters$Failed' => 'The number of training jobs whose final objective metric was not evaluated and used in the hyperparameter tuning process. This typically occurs when the training job failed or did not emit an objective metric.
', ], ], 'ObjectiveStatusCounters' => [ 'base' => 'Specifies the number of training jobs that this hyperparameter tuning job launched, categorized by the status of their objective metric. The objective metric status shows whether the final objective metric for the training job has been evaluated by the tuning job and used in the hyperparameter tuning process.
', 'refs' => [ 'DescribeHyperParameterTuningJobResponse$ObjectiveStatusCounters' => 'The ObjectiveStatusCounters object that specifies the number of training jobs, categorized by the status of their final objective metric, that this tuning job launched.
', 'HyperParameterTuningJobSearchEntity$ObjectiveStatusCounters' => NULL, 'HyperParameterTuningJobSummary$ObjectiveStatusCounters' => 'The ObjectiveStatusCounters object that specifies the numbers of training jobs, categorized by objective metric status, that this tuning job launched.
', ], ], 'OfflineStoreConfig' => [ 'base' => 'The configuration of an OfflineStore.
Provide an OfflineStoreConfig in a request to CreateFeatureGroup to create an OfflineStore.
To encrypt an OfflineStore using at rest data encryption, specify Amazon Web Services Key Management Service (KMS) key ID, or KMSKeyId, in S3StorageConfig.
Use this to configure an OfflineFeatureStore. This parameter allows you to specify:
The Amazon Simple Storage Service (Amazon S3) location of an OfflineStore.
A configuration for an Amazon Web Services Glue or Amazon Web Services Hive data catalog.
An KMS encryption key to encrypt the Amazon S3 location used for OfflineStore. If KMS encryption key is not specified, by default we encrypt all data at rest using Amazon Web Services KMS key. By defining your bucket-level key for SSE, you can reduce Amazon Web Services KMS requests costs by up to 99 percent.
Format for the offline store table. Supported formats are Glue (Default) and Apache Iceberg.
To learn more about this parameter, see OfflineStoreConfig.
', 'DescribeFeatureGroupResponse$OfflineStoreConfig' => 'The configuration of the offline store. It includes the following configurations:
Amazon S3 location of the offline store.
Configuration of the Glue data catalog.
Table format of the offline store.
Option to disable the automatic creation of a Glue table for the offline store.
Encryption configuration.
The status of OfflineStore.
The status of the OfflineStore. Notifies you if replicating data into the OfflineStore has failed. Returns either: Active or Blocked
Notifies you if replicating data into the OfflineStore has failed. Returns either: Active or Blocked.
An OfflineStore status. Filters by OfflineStore status.
An OfflineStore status.
Use this parameter to configure your OIDC Identity Provider (IdP).
', 'refs' => [ 'CreateWorkforceRequest$OidcConfig' => 'Use this parameter to configure a private workforce using your own OIDC Identity Provider.
Do not use CognitoConfig if you specify values for OidcConfig.
Use this parameter to update your OIDC Identity Provider (IdP) configuration for a workforce made using your own IdP.
', ], ], 'OidcConfigForResponse' => [ 'base' => 'Your OIDC IdP workforce configuration.
', 'refs' => [ 'Workforce$OidcConfig' => 'The configuration of an OIDC Identity Provider (IdP) private workforce.
', ], ], 'OidcEndpoint' => [ 'base' => NULL, 'refs' => [ 'OidcConfig$Issuer' => 'The OIDC IdP issuer used to configure your private workforce.
', 'OidcConfig$AuthorizationEndpoint' => 'The OIDC IdP authorization endpoint used to configure your private workforce.
', 'OidcConfig$TokenEndpoint' => 'The OIDC IdP token endpoint used to configure your private workforce.
', 'OidcConfig$UserInfoEndpoint' => 'The OIDC IdP user information endpoint used to configure your private workforce.
', 'OidcConfig$LogoutEndpoint' => 'The OIDC IdP logout endpoint used to configure your private workforce.
', 'OidcConfig$JwksUri' => 'The OIDC IdP JSON Web Key Set (Jwks) URI used to configure your private workforce.
', 'OidcConfigForResponse$Issuer' => 'The OIDC IdP issuer used to configure your private workforce.
', 'OidcConfigForResponse$AuthorizationEndpoint' => 'The OIDC IdP authorization endpoint used to configure your private workforce.
', 'OidcConfigForResponse$TokenEndpoint' => 'The OIDC IdP token endpoint used to configure your private workforce.
', 'OidcConfigForResponse$UserInfoEndpoint' => 'The OIDC IdP user information endpoint used to configure your private workforce.
', 'OidcConfigForResponse$LogoutEndpoint' => 'The OIDC IdP logout endpoint used to configure your private workforce.
', 'OidcConfigForResponse$JwksUri' => 'The OIDC IdP JSON Web Key Set (Jwks) URI used to configure your private workforce.
', ], ], 'OidcMemberDefinition' => [ 'base' => 'A list of user groups that exist in your OIDC Identity Provider (IdP). One to ten groups can be used to create a single private work team. When you add a user group to the list of Groups, you can add that user group to one or more private work teams. If you add a user group to a private work team, all workers in that user group are added to the work team.
A list user groups that exist in your OIDC Identity Provider (IdP). One to ten groups can be used to create a single private work team. When you add a user group to the list of Groups, you can add that user group to one or more private work teams. If you add a user group to a private work team, all workers in that user group are added to the work team.
Use this to specify the Amazon Web Services Key Management Service (KMS) Key ID, or KMSKeyId, for at rest data encryption. You can turn OnlineStore on or off by specifying the EnableOnlineStore flag at General Assembly.
The default value is False.
You can turn the OnlineStore on or off by specifying True for the EnableOnlineStore flag in OnlineStoreConfig.
You can also include an Amazon Web Services KMS key ID (KMSKeyId) for at-rest encryption of the OnlineStore.
The default value is False.
The configuration for the OnlineStore.
Updates the feature group online store configuration.
', 'refs' => [ 'UpdateFeatureGroupRequest$OnlineStoreConfig' => 'Updates the feature group online store configuration.
', ], ], 'OnlineStoreSecurityConfig' => [ 'base' => 'The security configuration for OnlineStore.
Use to specify KMS Key ID (KMSKeyId) for at-rest encryption of your OnlineStore.
The size of the OnlineStore in bytes.
A Boolean binary operator that is used to evaluate the filter. The operator field contains one of the following values:
The value of Name equals Value.
The value of Name doesn\'t equal Value.
The Name property exists.
The Name property does not exist.
The value of Name is greater than Value. Not supported for text properties.
The value of Name is greater than or equal to Value. Not supported for text properties.
The value of Name is less than Value. Not supported for text properties.
The value of Name is less than or equal to Value. Not supported for text properties.
The value of Name is one of the comma delimited strings in Value. Only supported for text properties.
The value of Name contains the string Value. Only supported for text properties.
A SearchExpression can include the Contains operator multiple times when the value of Name is one of the following:
Experiment.DisplayName
Experiment.ExperimentName
Experiment.Tags
Trial.DisplayName
Trial.TrialName
Trial.Tags
TrialComponent.DisplayName
TrialComponent.TrialComponentName
TrialComponent.Tags
TrialComponent.InputArtifacts
TrialComponent.OutputArtifacts
A SearchExpression can include only one Contains operator for all other values of Name. In these cases, if you include multiple Contains operators in the SearchExpression, the result is the following error message: "\'CONTAINS\' operator usage limit of 1 exceeded."
The maximum value of the metric.
', 'TrialComponentMetricSummary$Min' => 'The minimum value of the metric.
', 'TrialComponentMetricSummary$Last' => 'The most recent value of the metric.
', 'TrialComponentMetricSummary$Avg' => 'The average value of the metric.
', 'TrialComponentMetricSummary$StdDev' => 'The standard deviation of the metric.
', ], ], 'OptionalInteger' => [ 'base' => NULL, 'refs' => [ 'TrialComponentMetricSummary$Count' => 'The number of samples used to generate the metric.
', ], ], 'OptionalVolumeSizeInGB' => [ 'base' => NULL, 'refs' => [ 'DebugRuleConfiguration$VolumeSizeInGB' => 'The size, in GB, of the ML storage volume attached to the processing instance.
', 'HyperParameterTuningResourceConfig$VolumeSizeInGB' => 'The volume size in GB for the storage volume to be used in processing hyperparameter optimization jobs (optional). These volumes store model artifacts, incremental states and optionally, scratch space for training algorithms. Do not provide a value for this parameter if a value for InstanceConfigs is also specified.
Some instance types have a fixed total local storage size. If you select one of these instances for training, VolumeSizeInGB cannot be greater than this total size. For a list of instance types with local instance storage and their sizes, see instance store volumes.
SageMaker supports only the General Purpose SSD (gp2) storage volume type.
The size, in GB, of the ML storage volume attached to the processing instance.
', ], ], 'OrderKey' => [ 'base' => NULL, 'refs' => [ 'ListEndpointConfigsInput$SortOrder' => 'The sort order for results. The default is Descending.
The sort order for results. The default is Descending.
The sort order for results. The default is Descending.
The model output compression type. Select None to output an uncompressed model, recommended for large model outputs. Defaults to gzip.
Contains information about the output location for the compiled model and the target device that the model runs on. TargetDevice and TargetPlatform are mutually exclusive, so you need to choose one between the two to specify your target device or platform. If you cannot find your device you want to use from the TargetDevice list, use TargetPlatform to describe the platform of your edge device and CompilerOptions if there are specific settings that are required or recommended to use for particular TargetPlatform.
Provides information about the output location for the compiled model and the target device the model runs on.
', 'DescribeCompilationJobResponse$OutputConfig' => 'Information about the output location for the compiled model and the target device that the model runs on.
', ], ], 'OutputDataConfig' => [ 'base' => 'Provides information about how to store model training results (model artifacts).
', 'refs' => [ 'CreateTrainingJobRequest$OutputDataConfig' => 'Specifies the path to the S3 location where you want to store model artifacts. SageMaker creates subfolders for the artifacts.
', 'DescribeTrainingJobResponse$OutputDataConfig' => 'The S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.
', 'HyperParameterTrainingJobDefinition$OutputDataConfig' => 'Specifies the path to the Amazon S3 bucket where you store model artifacts from the training jobs that the tuning job launches.
', 'TrainingJob$OutputDataConfig' => 'The S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.
', 'TrainingJobDefinition$OutputDataConfig' => 'the path to the S3 bucket where you want to store model artifacts. SageMaker creates subfolders for the artifacts.
', ], ], 'OutputParameter' => [ 'base' => 'An output parameter of a pipeline step.
', 'refs' => [ 'OutputParameterList$member' => NULL, ], ], 'OutputParameterList' => [ 'base' => NULL, 'refs' => [ 'CallbackStepMetadata$OutputParameters' => 'A list of the output parameters of the callback step.
', 'LambdaStepMetadata$OutputParameters' => 'A list of the output parameters of the Lambda step.
', 'SendPipelineExecutionStepSuccessRequest$OutputParameters' => 'A list of the output parameters of the callback step.
', ], ], 'PaginationToken' => [ 'base' => NULL, 'refs' => [ 'ListEndpointConfigsInput$NextToken' => 'If the result of the previous ListEndpointConfig request was truncated, the response includes a NextToken. To retrieve the next set of endpoint configurations, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of endpoint configurations, use it in the subsequent request
', 'ListEndpointsInput$NextToken' => 'If the result of a ListEndpoints request was truncated, the response includes a NextToken. To retrieve the next set of endpoints, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of training jobs, use it in the subsequent request.
', 'ListModelsInput$NextToken' => 'If the response to a previous ListModels request was truncated, the response includes a NextToken. To retrieve the next set of models, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of models, use it in the subsequent request.
', ], ], 'ParallelismConfiguration' => [ 'base' => 'Configuration that controls the parallelism of the pipeline. By default, the parallelism configuration specified applies to all executions of the pipeline unless overridden.
', 'refs' => [ 'CreatePipelineRequest$ParallelismConfiguration' => 'This is the configuration that controls the parallelism of the pipeline. If specified, it applies to all runs of this pipeline by default.
', 'DescribePipelineExecutionResponse$ParallelismConfiguration' => 'The parallelism configuration applied to the pipeline.
', 'DescribePipelineResponse$ParallelismConfiguration' => 'Lists the parallelism configuration applied to the pipeline.
', 'Pipeline$ParallelismConfiguration' => 'The parallelism configuration applied to the pipeline.
', 'PipelineExecution$ParallelismConfiguration' => 'The parallelism configuration applied to the pipeline execution.
', 'RetryPipelineExecutionRequest$ParallelismConfiguration' => 'This configuration, if specified, overrides the parallelism configuration of the parent pipeline.
', 'StartPipelineExecutionRequest$ParallelismConfiguration' => 'This configuration, if specified, overrides the parallelism configuration of the parent pipeline for this specific run.
', 'UpdatePipelineExecutionRequest$ParallelismConfiguration' => 'This configuration, if specified, overrides the parallelism configuration of the parent pipeline for this specific run.
', 'UpdatePipelineRequest$ParallelismConfiguration' => 'If specified, it applies to all executions of this pipeline by default.
', ], ], 'Parameter' => [ 'base' => 'Assigns a value to a named Pipeline parameter.
', 'refs' => [ 'ParameterList$member' => NULL, ], ], 'ParameterKey' => [ 'base' => NULL, 'refs' => [ 'AutoParameter$Name' => 'The name of the hyperparameter to optimize using Autotune.
', 'CategoricalParameterRange$Name' => 'The name of the categorical hyperparameter to tune.
', 'ContinuousParameterRange$Name' => 'The name of the continuous hyperparameter to tune.
', 'IntegerParameterRange$Name' => 'The name of the hyperparameter to search.
', ], ], 'ParameterList' => [ 'base' => NULL, 'refs' => [ 'ListPipelineParametersForExecutionResponse$PipelineParameters' => 'Contains a list of pipeline parameters. This list can be empty.
', 'PipelineExecution$PipelineParameters' => 'Contains a list of pipeline parameters. This list can be empty.
', 'StartPipelineExecutionRequest$PipelineParameters' => 'Contains a list of pipeline parameters. This list can be empty.
', ], ], 'ParameterName' => [ 'base' => NULL, 'refs' => [ 'HyperParameterSpecification$Name' => 'The name of this hyperparameter. The name must be unique.
', ], ], 'ParameterRange' => [ 'base' => 'Defines the possible values for categorical, continuous, and integer hyperparameters to be used by an algorithm.
', 'refs' => [ 'HyperParameterSpecification$Range' => 'The allowed range for this hyperparameter.
', ], ], 'ParameterRanges' => [ 'base' => 'Specifies ranges of integer, continuous, and categorical hyperparameters that a hyperparameter tuning job searches. The hyperparameter tuning job launches training jobs with hyperparameter values within these ranges to find the combination of values that result in the training job with the best performance as measured by the objective metric of the hyperparameter tuning job.
The maximum number of items specified for Array Members refers to the maximum number of hyperparameters for each range and also the maximum for the hyperparameter tuning job itself. That is, the sum of the number of hyperparameters for all the ranges can\'t exceed the maximum number specified.
The ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches over to find the optimal configuration for the highest model performance against your chosen objective metric.
', ], ], 'ParameterType' => [ 'base' => NULL, 'refs' => [ 'HyperParameterSpecification$Type' => 'The type of this hyperparameter. The valid types are Integer, Continuous, Categorical, and FreeText.
An example value of the hyperparameter to optimize using Autotune.
', 'ContinuousParameterRange$MinValue' => 'The minimum value for the hyperparameter. The tuning job uses floating-point values between this value and MaxValuefor tuning.
The maximum value for the hyperparameter. The tuning job uses floating-point values between MinValue value and this value for tuning.
The minimum floating-point value allowed.
', 'ContinuousParameterRangeSpecification$MaxValue' => 'The maximum floating-point value allowed.
', 'IntegerParameterRange$MinValue' => 'The minimum value of the hyperparameter to search.
', 'IntegerParameterRange$MaxValue' => 'The maximum value of the hyperparameter to search.
', 'IntegerParameterRangeSpecification$MinValue' => 'The minimum integer value allowed.
', 'IntegerParameterRangeSpecification$MaxValue' => 'The maximum integer value allowed.
', 'ParameterValues$member' => NULL, ], ], 'ParameterValues' => [ 'base' => NULL, 'refs' => [ 'CategoricalParameterRange$Values' => 'A list of the categories for the hyperparameter.
', 'CategoricalParameterRangeSpecification$Values' => 'The allowed categories for the hyperparameter.
', ], ], 'Parent' => [ 'base' => 'The trial that a trial component is associated with and the experiment the trial is part of. A component might not be associated with a trial. A component can be associated with multiple trials.
', 'refs' => [ 'Parents$member' => NULL, ], ], 'ParentHyperParameterTuningJob' => [ 'base' => 'A previously completed or stopped hyperparameter tuning job to be used as a starting point for a new hyperparameter tuning job.
', 'refs' => [ 'ParentHyperParameterTuningJobs$member' => NULL, ], ], 'ParentHyperParameterTuningJobs' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTuningJobWarmStartConfig$ParentHyperParameterTuningJobs' => 'An array of hyperparameter tuning jobs that are used as the starting point for the new hyperparameter tuning job. For more information about warm starting a hyperparameter tuning job, see Using a Previous Hyperparameter Tuning Job as a Starting Point.
Hyperparameter tuning jobs created before October 1, 2018 cannot be used as parent jobs for warm start tuning jobs.
', ], ], 'Parents' => [ 'base' => NULL, 'refs' => [ 'TrialComponent$Parents' => 'An array of the parents of the component. A parent is a trial the component is associated with and the experiment the trial is part of. A component might not have any parents.
', ], ], 'PendingDeploymentSummary' => [ 'base' => 'The summary of an in-progress deployment when an endpoint is creating or updating with a new endpoint configuration.
', 'refs' => [ 'DescribeEndpointOutput$PendingDeploymentSummary' => 'Returns the summary of an in-progress deployment. This field is only returned when the endpoint is creating or updating with a new endpoint configuration.
', ], ], 'PendingProductionVariantSummary' => [ 'base' => 'The production variant summary for a deployment when an endpoint is creating or updating with the CreateEndpoint or UpdateEndpoint operations. Describes the VariantStatus , weight and capacity for a production variant associated with an endpoint.
An array of PendingProductionVariantSummary objects, one for each model hosted behind this endpoint for the in-progress deployment.
', 'PendingDeploymentSummary$ShadowProductionVariants' => 'An array of PendingProductionVariantSummary objects, one for each model hosted behind this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants for the in-progress deployment.
Percentage of devices in the fleet to deploy to the current stage.
', 'ShadowModelVariantConfig$SamplingPercentage' => 'The percentage of inference requests that Amazon SageMaker replicates from the production variant to the shadow variant.
', ], ], 'Phase' => [ 'base' => 'Defines the traffic pattern.
', 'refs' => [ 'Phases$member' => NULL, ], ], 'Phases' => [ 'base' => NULL, 'refs' => [ 'TrafficPattern$Phases' => 'Defines the phases traffic specification.
', ], ], 'Pipeline' => [ 'base' => 'A SageMaker Model Building Pipeline instance.
', 'refs' => [ 'SearchRecord$Pipeline' => NULL, ], ], 'PipelineArn' => [ 'base' => NULL, 'refs' => [ 'CreatePipelineResponse$PipelineArn' => 'The Amazon Resource Name (ARN) of the created pipeline.
', 'DeletePipelineResponse$PipelineArn' => 'The Amazon Resource Name (ARN) of the pipeline to delete.
', 'DescribePipelineExecutionResponse$PipelineArn' => 'The Amazon Resource Name (ARN) of the pipeline.
', 'DescribePipelineResponse$PipelineArn' => 'The Amazon Resource Name (ARN) of the pipeline.
', 'Pipeline$PipelineArn' => 'The Amazon Resource Name (ARN) of the pipeline.
', 'PipelineExecution$PipelineArn' => 'The Amazon Resource Name (ARN) of the pipeline that was executed.
', 'PipelineSummary$PipelineArn' => 'The Amazon Resource Name (ARN) of the pipeline.
', 'UpdatePipelineResponse$PipelineArn' => 'The Amazon Resource Name (ARN) of the updated pipeline.
', ], ], 'PipelineDefinition' => [ 'base' => NULL, 'refs' => [ 'CreatePipelineRequest$PipelineDefinition' => 'The JSON pipeline definition of the pipeline.
', 'DescribePipelineDefinitionForExecutionResponse$PipelineDefinition' => 'The JSON pipeline definition.
', 'DescribePipelineResponse$PipelineDefinition' => 'The JSON pipeline definition.
', 'UpdatePipelineRequest$PipelineDefinition' => 'The JSON pipeline definition.
', ], ], 'PipelineDefinitionS3Location' => [ 'base' => 'The location of the pipeline definition stored in Amazon S3.
', 'refs' => [ 'CreatePipelineRequest$PipelineDefinitionS3Location' => 'The location of the pipeline definition stored in Amazon S3. If specified, SageMaker will retrieve the pipeline definition from this location.
', 'UpdatePipelineRequest$PipelineDefinitionS3Location' => 'The location of the pipeline definition stored in Amazon S3. If specified, SageMaker will retrieve the pipeline definition from this location.
', ], ], 'PipelineDescription' => [ 'base' => NULL, 'refs' => [ 'CreatePipelineRequest$PipelineDescription' => 'A description of the pipeline.
', 'DescribePipelineResponse$PipelineDescription' => 'The description of the pipeline.
', 'Pipeline$PipelineDescription' => 'The description of the pipeline.
', 'PipelineSummary$PipelineDescription' => 'The description of the pipeline.
', 'UpdatePipelineRequest$PipelineDescription' => 'The description of the pipeline.
', ], ], 'PipelineExecution' => [ 'base' => 'An execution of a pipeline.
', 'refs' => [ 'SearchRecord$PipelineExecution' => NULL, ], ], 'PipelineExecutionArn' => [ 'base' => NULL, 'refs' => [ 'CacheHitResult$SourcePipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'DescribePipelineDefinitionForExecutionRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'DescribePipelineExecutionRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'DescribePipelineExecutionResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'ListPipelineExecutionStepsRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'ListPipelineParametersForExecutionRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'PipelineExecution$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'PipelineExecutionSummary$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'RetryPipelineExecutionRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'RetryPipelineExecutionResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'SelectiveExecutionConfig$SourcePipelineExecutionArn' => 'The ARN from a reference execution of the current pipeline. Used to copy input collaterals needed for the selected steps to run. The execution status of the pipeline can be either Failed or Success.
This field is required if the steps you specify for SelectedSteps depend on output collaterals from any non-specified pipeline steps. For more information, see Selective Execution for Pipeline Steps.
The ARN from an execution of the current pipeline.
', 'SendPipelineExecutionStepFailureResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'SendPipelineExecutionStepSuccessResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'StartPipelineExecutionResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'StopPipelineExecutionRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'StopPipelineExecutionResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'UpdatePipelineExecutionRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'UpdatePipelineExecutionResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the updated pipeline execution.
', ], ], 'PipelineExecutionDescription' => [ 'base' => NULL, 'refs' => [ 'DescribePipelineExecutionResponse$PipelineExecutionDescription' => 'The description of the pipeline execution.
', 'PipelineExecution$PipelineExecutionDescription' => 'The description of the pipeline execution.
', 'PipelineExecutionSummary$PipelineExecutionDescription' => 'The description of the pipeline execution.
', 'StartPipelineExecutionRequest$PipelineExecutionDescription' => 'The description of the pipeline execution.
', 'UpdatePipelineExecutionRequest$PipelineExecutionDescription' => 'The description of the pipeline execution.
', ], ], 'PipelineExecutionFailureReason' => [ 'base' => NULL, 'refs' => [ 'DescribePipelineExecutionResponse$FailureReason' => 'If the execution failed, a message describing why.
', 'PipelineExecution$FailureReason' => 'If the execution failed, a message describing why.
', ], ], 'PipelineExecutionName' => [ 'base' => NULL, 'refs' => [ 'DescribePipelineExecutionResponse$PipelineExecutionDisplayName' => 'The display name of the pipeline execution.
', 'PipelineExecution$PipelineExecutionDisplayName' => 'The display name of the pipeline execution.
', 'PipelineExecutionSummary$PipelineExecutionDisplayName' => 'The display name of the pipeline execution.
', 'StartPipelineExecutionRequest$PipelineExecutionDisplayName' => 'The display name of the pipeline execution.
', 'UpdatePipelineExecutionRequest$PipelineExecutionDisplayName' => 'The display name of the pipeline execution.
', ], ], 'PipelineExecutionStatus' => [ 'base' => NULL, 'refs' => [ 'DescribePipelineExecutionResponse$PipelineExecutionStatus' => 'The status of the pipeline execution.
', 'PipelineExecution$PipelineExecutionStatus' => 'The status of the pipeline status.
', 'PipelineExecutionSummary$PipelineExecutionStatus' => 'The status of the pipeline execution.
', ], ], 'PipelineExecutionStep' => [ 'base' => 'An execution of a step in a pipeline.
', 'refs' => [ 'PipelineExecutionStepList$member' => NULL, ], ], 'PipelineExecutionStepList' => [ 'base' => NULL, 'refs' => [ 'ListPipelineExecutionStepsResponse$PipelineExecutionSteps' => 'A list of PipeLineExecutionStep objects. Each PipeLineExecutionStep consists of StepName, StartTime, EndTime, StepStatus, and Metadata. Metadata is an object with properties for each job that contains relevant information about the job created by the step.
Metadata for a step execution.
', 'refs' => [ 'PipelineExecutionStep$Metadata' => 'Metadata to run the pipeline step.
', ], ], 'PipelineExecutionSummary' => [ 'base' => 'A pipeline execution summary.
', 'refs' => [ 'PipelineExecutionSummaryList$member' => NULL, ], ], 'PipelineExecutionSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListPipelineExecutionsResponse$PipelineExecutionSummaries' => 'Contains a sorted list of pipeline execution summary objects matching the specified filters. Each run summary includes the Amazon Resource Name (ARN) of the pipeline execution, the run date, and the status. This list can be empty.
', ], ], 'PipelineExperimentConfig' => [ 'base' => 'Specifies the names of the experiment and trial created by a pipeline.
', 'refs' => [ 'DescribePipelineExecutionResponse$PipelineExperimentConfig' => NULL, 'PipelineExecution$PipelineExperimentConfig' => NULL, ], ], 'PipelineName' => [ 'base' => NULL, 'refs' => [ 'CreatePipelineRequest$PipelineName' => 'The name of the pipeline.
', 'CreatePipelineRequest$PipelineDisplayName' => 'The display name of the pipeline.
', 'DeletePipelineRequest$PipelineName' => 'The name of the pipeline to delete.
', 'DescribePipelineResponse$PipelineName' => 'The name of the pipeline.
', 'DescribePipelineResponse$PipelineDisplayName' => 'The display name of the pipeline.
', 'ListPipelinesRequest$PipelineNamePrefix' => 'The prefix of the pipeline name.
', 'Pipeline$PipelineName' => 'The name of the pipeline.
', 'Pipeline$PipelineDisplayName' => 'The display name of the pipeline.
', 'PipelineSummary$PipelineName' => 'The name of the pipeline.
', 'PipelineSummary$PipelineDisplayName' => 'The display name of the pipeline.
', 'UpdatePipelineRequest$PipelineName' => 'The name of the pipeline to update.
', 'UpdatePipelineRequest$PipelineDisplayName' => 'The display name of the pipeline.
', ], ], 'PipelineNameOrArn' => [ 'base' => NULL, 'refs' => [ 'DescribePipelineRequest$PipelineName' => 'The name or Amazon Resource Name (ARN) of the pipeline to describe.
', 'ListPipelineExecutionsRequest$PipelineName' => 'The name or Amazon Resource Name (ARN) of the pipeline.
', 'StartPipelineExecutionRequest$PipelineName' => 'The name or Amazon Resource Name (ARN) of the pipeline.
', ], ], 'PipelineParameterName' => [ 'base' => NULL, 'refs' => [ 'Parameter$Name' => 'The name of the parameter to assign a value to. This parameter name must match a named parameter in the pipeline definition.
', ], ], 'PipelineStatus' => [ 'base' => NULL, 'refs' => [ 'DescribePipelineResponse$PipelineStatus' => 'The status of the pipeline execution.
', 'Pipeline$PipelineStatus' => 'The status of the pipeline.
', ], ], 'PipelineSummary' => [ 'base' => 'A summary of a pipeline.
', 'refs' => [ 'PipelineSummaryList$member' => NULL, ], ], 'PipelineSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListPipelinesResponse$PipelineSummaries' => 'Contains a sorted list of PipelineSummary objects matching the specified filters. Each PipelineSummary consists of PipelineArn, PipelineName, ExperimentName, PipelineDescription, CreationTime, LastModifiedTime, LastRunTime, and RoleArn. This list can be empty.
The platform identifier of the notebook instance runtime environment.
', 'DescribeNotebookInstanceOutput$PlatformIdentifier' => 'The platform identifier of the notebook instance runtime environment.
', ], ], 'PolicyString' => [ 'base' => NULL, 'refs' => [ 'GetModelPackageGroupPolicyOutput$ResourcePolicy' => 'The resource policy for the model group.
', 'PutModelPackageGroupPolicyInput$ResourcePolicy' => 'The resource policy for the model group.
', ], ], 'PredefinedMetricSpecification' => [ 'base' => 'A specification for a predefined metric.
', 'refs' => [ 'MetricSpecification$Predefined' => 'Information about a predefined metric.
', ], ], 'PresignedDomainUrl' => [ 'base' => NULL, 'refs' => [ 'CreatePresignedDomainUrlResponse$AuthorizedUrl' => 'The presigned URL.
', ], ], 'ProbabilityThresholdAttribute' => [ 'base' => NULL, 'refs' => [ 'BatchTransformInput$ProbabilityThresholdAttribute' => 'The threshold for the class probability to be evaluated as a positive result.
', 'EndpointInput$ProbabilityThresholdAttribute' => 'The threshold for the class probability to be evaluated as a positive result.
', ], ], 'ProblemType' => [ 'base' => NULL, 'refs' => [ 'CreateAutoMLJobRequest$ProblemType' => 'Defines the type of supervised learning problem available for the candidates. For more information, see Amazon SageMaker Autopilot problem types.
', 'DescribeAutoMLJobResponse$ProblemType' => 'Returns the job\'s problem type.
', 'ResolvedAttributes$ProblemType' => 'The problem type.
', 'TabularJobConfig$ProblemType' => 'The type of supervised learning problem available for the model candidates of the AutoML job V2. For more information, see Amazon SageMaker Autopilot problem types.
You must either specify the type of supervised learning problem in ProblemType and provide the AutoMLJobObjective metric, or none at all.
The type of supervised learning problem available for the model candidates of the AutoML job V2 (Binary Classification, Multiclass Classification, Regression). For more information, see Amazon SageMaker Autopilot problem types.
', ], ], 'ProcessingClusterConfig' => [ 'base' => 'Configuration for the cluster used to run a processing job.
', 'refs' => [ 'ProcessingResources$ClusterConfig' => 'The configuration for the resources in a cluster used to run the processing job.
', ], ], 'ProcessingEnvironmentKey' => [ 'base' => NULL, 'refs' => [ 'MonitoringEnvironmentMap$key' => NULL, 'ProcessingEnvironmentMap$key' => NULL, ], ], 'ProcessingEnvironmentMap' => [ 'base' => NULL, 'refs' => [ 'CreateProcessingJobRequest$Environment' => 'The environment variables to set in the Docker container. Up to 100 key and values entries in the map are supported.
', 'DescribeProcessingJobResponse$Environment' => 'The environment variables set in the Docker container.
', 'ProcessingJob$Environment' => 'Sets the environment variables in the Docker container.
', ], ], 'ProcessingEnvironmentValue' => [ 'base' => NULL, 'refs' => [ 'MonitoringEnvironmentMap$value' => NULL, 'ProcessingEnvironmentMap$value' => NULL, ], ], 'ProcessingFeatureStoreOutput' => [ 'base' => 'Configuration for processing job outputs in Amazon SageMaker Feature Store.
', 'refs' => [ 'ProcessingOutput$FeatureStoreOutput' => 'Configuration for processing job outputs in Amazon SageMaker Feature Store. This processing output type is only supported when AppManaged is specified.
The inputs for a processing job. The processing input must specify exactly one of either S3Input or DatasetDefinition types.
An array of inputs configuring the data to download into the processing container.
', 'DescribeProcessingJobResponse$ProcessingInputs' => 'The inputs for a processing job.
', 'ProcessingJob$ProcessingInputs' => 'List of input configurations for the processing job.
', ], ], 'ProcessingInstanceCount' => [ 'base' => NULL, 'refs' => [ 'MonitoringClusterConfig$InstanceCount' => 'The number of ML compute instances to use in the model monitoring job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
', 'ProcessingClusterConfig$InstanceCount' => 'The number of ML compute instances to use in the processing job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
', ], ], 'ProcessingInstanceType' => [ 'base' => NULL, 'refs' => [ 'DebugRuleConfiguration$InstanceType' => 'The instance type to deploy a custom rule for debugging a training job.
', 'MonitoringClusterConfig$InstanceType' => 'The ML compute instance type for the processing job.
', 'ProcessingClusterConfig$InstanceType' => 'The ML compute instance type for the processing job.
', 'ProfilerRuleConfiguration$InstanceType' => 'The instance type to deploy a custom rule for profiling a training job.
', ], ], 'ProcessingJob' => [ 'base' => 'An Amazon SageMaker processing job that is used to analyze data and evaluate models. For more information, see Process Data and Evaluate Models.
', 'refs' => [ 'TrialComponentSourceDetail$ProcessingJob' => 'Information about a processing job that\'s the source of a trial component.
', ], ], 'ProcessingJobArn' => [ 'base' => NULL, 'refs' => [ 'CreateProcessingJobResponse$ProcessingJobArn' => 'The Amazon Resource Name (ARN) of the processing job.
', 'DebugRuleEvaluationStatus$RuleEvaluationJobArn' => 'The Amazon Resource Name (ARN) of the rule evaluation job.
', 'DescribeProcessingJobResponse$ProcessingJobArn' => 'The Amazon Resource Name (ARN) of the processing job.
', 'MonitoringExecutionSummary$ProcessingJobArn' => 'The Amazon Resource Name (ARN) of the monitoring job.
', 'ProcessingJob$ProcessingJobArn' => 'The ARN of the processing job.
', 'ProcessingJobStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the processing job.
', 'ProcessingJobSummary$ProcessingJobArn' => 'The Amazon Resource Name (ARN) of the processing job..
', 'ProfilerRuleEvaluationStatus$RuleEvaluationJobArn' => 'The Amazon Resource Name (ARN) of the rule evaluation job.
', ], ], 'ProcessingJobName' => [ 'base' => NULL, 'refs' => [ 'CreateProcessingJobRequest$ProcessingJobName' => 'The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DataQualityBaselineConfig$BaseliningJobName' => 'The name of the job that performs baselining for the data quality monitoring job.
', 'DescribeProcessingJobRequest$ProcessingJobName' => 'The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeProcessingJobResponse$ProcessingJobName' => 'The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'ModelBiasBaselineConfig$BaseliningJobName' => 'The name of the baseline model bias job.
', 'ModelExplainabilityBaselineConfig$BaseliningJobName' => 'The name of the baseline model explainability job.
', 'ModelQualityBaselineConfig$BaseliningJobName' => 'The name of the job that performs baselining for the monitoring job.
', 'MonitoringBaselineConfig$BaseliningJobName' => 'The name of the job that performs baselining for the monitoring job.
', 'ProcessingJob$ProcessingJobName' => 'The name of the processing job.
', 'ProcessingJobSummary$ProcessingJobName' => 'The name of the processing job.
', 'StopProcessingJobRequest$ProcessingJobName' => 'The name of the processing job to stop.
', ], ], 'ProcessingJobStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeProcessingJobResponse$ProcessingJobStatus' => 'Provides the status of a processing job.
', 'ListProcessingJobsRequest$StatusEquals' => 'A filter that retrieves only processing jobs with a specific status.
', 'ProcessingJob$ProcessingJobStatus' => 'The status of the processing job.
', 'ProcessingJobSummary$ProcessingJobStatus' => 'The status of the processing job.
', ], ], 'ProcessingJobStepMetadata' => [ 'base' => 'Metadata for a processing job step.
', 'refs' => [ 'PipelineExecutionStepMetadata$ProcessingJob' => 'The Amazon Resource Name (ARN) of the processing job that was run by this step execution.
', ], ], 'ProcessingJobSummaries' => [ 'base' => NULL, 'refs' => [ 'ListProcessingJobsResponse$ProcessingJobSummaries' => 'An array of ProcessingJobSummary objects, each listing a processing job.
Summary of information about a processing job.
', 'refs' => [ 'ProcessingJobSummaries$member' => NULL, ], ], 'ProcessingLocalPath' => [ 'base' => NULL, 'refs' => [ 'BatchTransformInput$LocalPath' => 'Path to the filesystem where the batch transform data is available to the container.
', 'DatasetDefinition$LocalPath' => 'The local path where you want Amazon SageMaker to download the Dataset Definition inputs to run a processing job. LocalPath is an absolute path to the input data. This is a required parameter when AppManaged is False (default).
Path to the filesystem where the endpoint data is available to the container.
', 'MonitoringS3Output$LocalPath' => 'The local path to the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job. LocalPath is an absolute path for the output data.
', 'ProcessingS3Input$LocalPath' => 'The local path in your container where you want Amazon SageMaker to write input data to. LocalPath is an absolute path to the input data and must begin with /opt/ml/processing/. LocalPath is a required parameter when AppManaged is False (default).
The local path of a directory where you want Amazon SageMaker to upload its contents to Amazon S3. LocalPath is an absolute path to a directory containing output files. This directory will be created by the platform and exist when your container\'s entrypoint is invoked.
Specifies the maximum runtime in seconds.
', ], ], 'ProcessingOutput' => [ 'base' => 'Describes the results of a processing job. The processing output must specify exactly one of either S3Output or FeatureStoreOutput types.
Configuration for uploading output from the processing container.
', 'refs' => [ 'CreateProcessingJobRequest$ProcessingOutputConfig' => 'Output configuration for the processing job.
', 'DescribeProcessingJobResponse$ProcessingOutputConfig' => 'Output configuration for the processing job.
', 'ProcessingJob$ProcessingOutputConfig' => NULL, ], ], 'ProcessingOutputs' => [ 'base' => NULL, 'refs' => [ 'ProcessingOutputConfig$Outputs' => 'An array of outputs configuring the data to upload from the processing container.
', ], ], 'ProcessingResources' => [ 'base' => 'Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.
', 'refs' => [ 'CreateProcessingJobRequest$ProcessingResources' => 'Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.
', 'DescribeProcessingJobResponse$ProcessingResources' => 'Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.
', 'ProcessingJob$ProcessingResources' => NULL, ], ], 'ProcessingS3CompressionType' => [ 'base' => NULL, 'refs' => [ 'ProcessingS3Input$S3CompressionType' => 'Whether to GZIP-decompress the data in Amazon S3 as it is streamed into the processing container. Gzip can only be used when Pipe mode is specified as the S3InputMode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your container without using the EBS volume.
Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defaults to FullyReplicated
Whether input data distributed in Amazon S3 is fully replicated or sharded by an Amazon S3 key. Defaults to FullyReplicated
Whether to distribute the data from Amazon S3 to all processing instances with FullyReplicated, or whether the data from Amazon S3 is shared by Amazon S3 key, downloading one shard of data to each processing instance.
Whether you use an S3Prefix or a ManifestFile for the data type. If you choose S3Prefix, S3Uri identifies a key name prefix. Amazon SageMaker uses all objects with the specified key name prefix for the processing job. If you choose ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want Amazon SageMaker to use for the processing job.
Configuration for downloading input data from Amazon S3 into the processing container.
', 'refs' => [ 'ProcessingInput$S3Input' => 'Configuration for downloading input data from Amazon S3 into the processing container.
', ], ], 'ProcessingS3InputMode' => [ 'base' => NULL, 'refs' => [ 'BatchTransformInput$S3InputMode' => 'Whether the Pipe or File is used as the input mode for transferring data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
Whether the Pipe or File is used as the input mode for transferring data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
Whether to use File or Pipe input mode. In File mode, Amazon SageMaker copies the data from the input source onto the local ML storage volume before starting your processing container. This is the most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your processing container into named pipes without using the ML storage volume.
Configuration for uploading output data to Amazon S3 from the processing container.
', 'refs' => [ 'ProcessingOutput$S3Output' => 'Configuration for processing job outputs in Amazon S3.
', ], ], 'ProcessingS3UploadMode' => [ 'base' => NULL, 'refs' => [ 'MonitoringS3Output$S3UploadMode' => 'Whether to upload the results of the monitoring job continuously or after the job completes.
', 'ProcessingS3Output$S3UploadMode' => 'Whether to upload the results of the processing job continuously or after the job completes.
', ], ], 'ProcessingStoppingCondition' => [ 'base' => 'Configures conditions under which the processing job should be stopped, such as how long the processing job has been running. After the condition is met, the processing job is stopped.
', 'refs' => [ 'CreateProcessingJobRequest$StoppingCondition' => 'The time limit for how long the processing job is allowed to run.
', 'DescribeProcessingJobResponse$StoppingCondition' => 'The time limit for how long the processing job is allowed to run.
', 'ProcessingJob$StoppingCondition' => NULL, ], ], 'ProcessingVolumeSizeInGB' => [ 'base' => NULL, 'refs' => [ 'MonitoringClusterConfig$VolumeSizeInGB' => 'The size of the ML storage volume, in gigabytes, that you want to provision. You must specify sufficient ML storage for your scenario.
', 'ProcessingClusterConfig$VolumeSizeInGB' => 'The size of the ML storage volume in gigabytes that you want to provision. You must specify sufficient ML storage for your scenario.
Certain Nitro-based instances include local storage with a fixed total size, dependent on the instance type. When using these instances for processing, Amazon SageMaker mounts the local instance storage instead of Amazon EBS gp2 storage. You can\'t request a VolumeSizeInGB greater than the total size of the local instance storage.
For a list of instance types that support local instance storage, including the total size per instance type, see Instance Store Volumes.
Indicates CPU or GPU compatibility.
CPU: The image version is compatible with CPU.
GPU: The image version is compatible with GPU.
Indicates CPU or GPU compatibility.
CPU: The image version is compatible with CPU.
GPU: The image version is compatible with GPU.
Indicates CPU or GPU compatibility.
CPU: The image version is compatible with CPU.
GPU: The image version is compatible with GPU.
The product identifier of the algorithm.
', 'ModelPackageContainerDefinition$ProductId' => 'The Amazon Web Services Marketplace product ID of the model package.
', ], ], 'ProductListings' => [ 'base' => NULL, 'refs' => [ 'Workteam$ProductListingIds' => 'The Amazon Marketplace identifier for a vendor\'s work team.
', ], ], 'ProductionVariant' => [ 'base' => 'Identifies a model that you want to host and the resources chosen to deploy for hosting it. If you are deploying multiple models, tell SageMaker how to distribute traffic among the models by specifying variant weights. For more information on production variants, check Production variants.
', 'refs' => [ 'ProductionVariantList$member' => NULL, ], ], 'ProductionVariantAcceleratorType' => [ 'base' => NULL, 'refs' => [ 'PendingProductionVariantSummary$AcceleratorType' => 'The size of the Elastic Inference (EI) instance to use for the production variant. EI instances provide on-demand GPU computing for inference. For more information, see Using Elastic Inference in Amazon SageMaker.
', 'ProductionVariant$AcceleratorType' => 'The size of the Elastic Inference (EI) instance to use for the production variant. EI instances provide on-demand GPU computing for inference. For more information, see Using Elastic Inference in Amazon SageMaker.
', ], ], 'ProductionVariantContainerStartupHealthCheckTimeoutInSeconds' => [ 'base' => NULL, 'refs' => [ 'ProductionVariant$ContainerStartupHealthCheckTimeoutInSeconds' => 'The timeout value, in seconds, for your inference container to pass health check by SageMaker Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests.
', ], ], 'ProductionVariantCoreDumpConfig' => [ 'base' => 'Specifies configuration for a core dump from the model container when the process crashes.
', 'refs' => [ 'ProductionVariant$CoreDumpConfig' => 'Specifies configuration for a core dump from the model container when the process crashes.
', ], ], 'ProductionVariantInstanceType' => [ 'base' => NULL, 'refs' => [ 'EndpointInputConfiguration$InstanceType' => 'The instance types to use for the load test.
', 'EndpointOutputConfiguration$InstanceType' => 'The instance type recommended by Amazon SageMaker Inference Recommender.
', 'PendingProductionVariantSummary$InstanceType' => 'The type of instances associated with the variant.
', 'ProductionVariant$InstanceType' => 'The ML compute instance type.
', 'RealTimeInferenceRecommendation$InstanceType' => 'The recommended instance type for Real-Time Inference.
', 'RealtimeInferenceInstanceTypes$member' => NULL, ], ], 'ProductionVariantList' => [ 'base' => NULL, 'refs' => [ 'CreateEndpointConfigInput$ProductionVariants' => 'An array of ProductionVariant objects, one for each model that you want to host at this endpoint.
An array of ProductionVariant objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants. If you use this field, you can only specify one variant for ProductionVariants and one variant for ShadowProductionVariants.
An array of ProductionVariant objects, one for each model that you want to host at this endpoint.
An array of ProductionVariant objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants.
The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this production variant.
', ], ], 'ProductionVariantSSMAccess' => [ 'base' => NULL, 'refs' => [ 'ProductionVariant$EnableSSMAccess' => ' You can use this parameter to turn on native Amazon Web Services Systems Manager (SSM) access for a production variant behind an endpoint. By default, SSM access is disabled for all production variants behind an endpoint. You can turn on or turn off SSM access for a production variant behind an existing endpoint by creating a new endpoint configuration and calling UpdateEndpoint.
Specifies the serverless configuration for an endpoint variant.
', 'refs' => [ 'EndpointInputConfiguration$ServerlessConfig' => NULL, 'EndpointOutputConfiguration$ServerlessConfig' => NULL, 'PendingProductionVariantSummary$CurrentServerlessConfig' => 'The serverless configuration for the endpoint.
', 'PendingProductionVariantSummary$DesiredServerlessConfig' => 'The serverless configuration requested for this deployment, as specified in the endpoint configuration for the endpoint.
', 'ProductionVariant$ServerlessConfig' => 'The serverless configuration for an endpoint. Specifies a serverless endpoint configuration instead of an instance-based endpoint configuration.
', 'ProductionVariantSummary$CurrentServerlessConfig' => 'The serverless configuration for the endpoint.
', 'ProductionVariantSummary$DesiredServerlessConfig' => 'The serverless configuration requested for the endpoint update.
', ], ], 'ProductionVariantServerlessUpdateConfig' => [ 'base' => 'Specifies the serverless update concurrency configuration for an endpoint variant.
', 'refs' => [ 'DesiredWeightAndCapacity$ServerlessUpdateConfig' => 'Specifies the serverless update concurrency configuration for an endpoint variant.
', ], ], 'ProductionVariantStatus' => [ 'base' => 'Describes the status of the production variant.
', 'refs' => [ 'ProductionVariantStatusList$member' => NULL, ], ], 'ProductionVariantStatusList' => [ 'base' => NULL, 'refs' => [ 'PendingProductionVariantSummary$VariantStatus' => 'The endpoint variant status which describes the current deployment stage status or operational status.
', 'ProductionVariantSummary$VariantStatus' => 'The endpoint variant status which describes the current deployment stage status or operational status.
', ], ], 'ProductionVariantSummary' => [ 'base' => 'Describes weight and capacities for a production variant associated with an endpoint. If you sent a request to the UpdateEndpointWeightsAndCapacities API and the endpoint status is Updating, you get different desired and current values.
An array of ProductionVariantSummary objects, one for each model hosted behind this endpoint.
', 'DescribeEndpointOutput$ShadowProductionVariants' => 'An array of ProductionVariantSummary objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants.
A list of the production variants hosted on the endpoint. Each production variant is a model.
', 'Endpoint$ShadowProductionVariants' => 'A list of the shadow variants hosted on the endpoint. Each shadow variant is a model in shadow mode with production traffic replicated from the production variant.
', ], ], 'ProductionVariantVolumeSizeInGB' => [ 'base' => NULL, 'refs' => [ 'ProductionVariant$VolumeSizeInGB' => 'The size, in GB, of the ML storage volume attached to individual inference instance associated with the production variant. Currently only Amazon EBS gp2 storage volumes are supported.
', ], ], 'ProfilerConfig' => [ 'base' => 'Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.
', 'refs' => [ 'CreateTrainingJobRequest$ProfilerConfig' => NULL, 'DescribeTrainingJobResponse$ProfilerConfig' => NULL, 'TrainingJob$ProfilerConfig' => NULL, ], ], 'ProfilerConfigForUpdate' => [ 'base' => 'Configuration information for updating the Amazon SageMaker Debugger profile parameters, system and framework metrics configurations, and storage paths.
', 'refs' => [ 'UpdateTrainingJobRequest$ProfilerConfig' => 'Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.
', ], ], 'ProfilerRuleConfiguration' => [ 'base' => 'Configuration information for profiling rules.
', 'refs' => [ 'ProfilerRuleConfigurations$member' => NULL, ], ], 'ProfilerRuleConfigurations' => [ 'base' => NULL, 'refs' => [ 'CreateTrainingJobRequest$ProfilerRuleConfigurations' => 'Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
', 'DescribeTrainingJobResponse$ProfilerRuleConfigurations' => 'Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
', 'UpdateTrainingJobRequest$ProfilerRuleConfigurations' => 'Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
', ], ], 'ProfilerRuleEvaluationStatus' => [ 'base' => 'Information about the status of the rule evaluation.
', 'refs' => [ 'ProfilerRuleEvaluationStatuses$member' => NULL, ], ], 'ProfilerRuleEvaluationStatuses' => [ 'base' => NULL, 'refs' => [ 'DescribeTrainingJobResponse$ProfilerRuleEvaluationStatuses' => 'Evaluation status of Amazon SageMaker Debugger rules for profiling on a training job.
', ], ], 'ProfilingIntervalInMilliseconds' => [ 'base' => NULL, 'refs' => [ 'ProfilerConfig$ProfilingIntervalInMilliseconds' => 'A time interval for capturing system metrics in milliseconds. Available values are 100, 200, 500, 1000 (1 second), 5000 (5 seconds), and 60000 (1 minute) milliseconds. The default value is 500 milliseconds.
', 'ProfilerConfigForUpdate$ProfilingIntervalInMilliseconds' => 'A time interval for capturing system metrics in milliseconds. Available values are 100, 200, 500, 1000 (1 second), 5000 (5 seconds), and 60000 (1 minute) milliseconds. The default value is 500 milliseconds.
', ], ], 'ProfilingParameters' => [ 'base' => NULL, 'refs' => [ 'ProfilerConfig$ProfilingParameters' => 'Configuration information for capturing framework metrics. Available key strings for different profiling options are DetailedProfilingConfig, PythonProfilingConfig, and DataLoaderProfilingConfig. The following codes are configuration structures for the ProfilingParameters parameter. To learn more about how to configure the ProfilingParameters parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Configuration information for capturing framework metrics. Available key strings for different profiling options are DetailedProfilingConfig, PythonProfilingConfig, and DataLoaderProfilingConfig. The following codes are configuration structures for the ProfilingParameters parameter. To learn more about how to configure the ProfilingParameters parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Profiling status of a training job.
', ], ], 'ProgrammingLang' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$ProgrammingLang' => 'The supported programming language and its version.
', 'DescribeImageVersionResponse$ProgrammingLang' => 'The supported programming language and its version.
', 'UpdateImageVersionRequest$ProgrammingLang' => 'The supported programming language and its version.
', ], ], 'Project' => [ 'base' => 'The properties of a project as returned by the Search API.
', 'refs' => [ 'SearchRecord$Project' => 'The properties of a project.
', ], ], 'ProjectArn' => [ 'base' => NULL, 'refs' => [ 'CreateProjectOutput$ProjectArn' => 'The Amazon Resource Name (ARN) of the project.
', 'DescribeProjectOutput$ProjectArn' => 'The Amazon Resource Name (ARN) of the project.
', 'Project$ProjectArn' => 'The Amazon Resource Name (ARN) of the project.
', 'ProjectSummary$ProjectArn' => 'The Amazon Resource Name (ARN) of the project.
', 'UpdateProjectOutput$ProjectArn' => 'The Amazon Resource Name (ARN) of the project.
', ], ], 'ProjectEntityName' => [ 'base' => NULL, 'refs' => [ 'CreateProjectInput$ProjectName' => 'The name of the project.
', 'DeleteProjectInput$ProjectName' => 'The name of the project to delete.
', 'DescribeProjectInput$ProjectName' => 'The name of the project to describe.
', 'DescribeProjectOutput$ProjectName' => 'The name of the project.
', 'ListProjectsInput$NameContains' => 'A filter that returns the projects whose name contains a specified string.
', 'Project$ProjectName' => 'The name of the project.
', 'ProjectSummary$ProjectName' => 'The name of the project.
', 'UpdateProjectInput$ProjectName' => 'The name of the project.
', ], ], 'ProjectId' => [ 'base' => NULL, 'refs' => [ 'CreateProjectOutput$ProjectId' => 'The ID of the new project.
', 'DescribeProjectOutput$ProjectId' => 'The ID of the project.
', 'Project$ProjectId' => 'The ID of the project.
', 'ProjectSummary$ProjectId' => 'The ID of the project.
', ], ], 'ProjectSortBy' => [ 'base' => NULL, 'refs' => [ 'ListProjectsInput$SortBy' => 'The field by which to sort results. The default is CreationTime.
The sort order for results. The default is Ascending.
The status of the project.
', 'Project$ProjectStatus' => 'The status of the project.
', 'ProjectSummary$ProjectStatus' => 'The status of the project.
', ], ], 'ProjectSummary' => [ 'base' => 'Information about a project.
', 'refs' => [ 'ProjectSummaryList$member' => NULL, ], ], 'ProjectSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListProjectsOutput$ProjectSummaryList' => 'A list of summaries of projects.
', ], ], 'PropertyNameHint' => [ 'base' => NULL, 'refs' => [ 'PropertyNameQuery$PropertyNameHint' => 'Text that begins a property\'s name.
', ], ], 'PropertyNameQuery' => [ 'base' => 'Part of the SuggestionQuery type. Specifies a hint for retrieving property names that begin with the specified text.
Defines a property name hint. Only property names that begin with the specified hint are included in the response.
', ], ], 'PropertyNameSuggestion' => [ 'base' => 'A property name returned from a GetSearchSuggestions call that specifies a value in the PropertyNameQuery field.
A list of property names for a Resource that match a SuggestionQuery.
The current status of the product.
AVAILABLE - Stable state, ready to perform any operation. The most recent operation succeeded and completed.
UNDER_CHANGE - Transitive state. Operations performed might not have valid results. Wait for an AVAILABLE status before performing operations.
TAINTED - Stable state, ready to perform any operation. The stack has completed the requested operation but is not exactly what was requested. For example, a request to update to a new version failed and the stack rolled back to the current version.
ERROR - An unexpected error occurred. The provisioned product exists but the stack is not running. For example, CloudFormation received a parameter value that was not valid and could not launch the stack.
PLAN_IN_PROGRESS - Transitive state. The plan operations were performed to provision a new product, but resources have not yet been created. After reviewing the list of resources to be created, execute the plan. Wait for an AVAILABLE status before performing operations.
A key value pair used when you provision a project as a service catalog product. For information, see What is Amazon Web Services Service Catalog.
', 'refs' => [ 'ProvisioningParameters$member' => NULL, ], ], 'ProvisioningParameterKey' => [ 'base' => NULL, 'refs' => [ 'ProvisioningParameter$Key' => 'The key that identifies a provisioning parameter.
', ], ], 'ProvisioningParameterValue' => [ 'base' => NULL, 'refs' => [ 'ProvisioningParameter$Value' => 'The value of the provisioning parameter.
', ], ], 'ProvisioningParameters' => [ 'base' => NULL, 'refs' => [ 'ServiceCatalogProvisioningDetails$ProvisioningParameters' => 'A list of key value pairs that you specify when you provision a product.
', 'ServiceCatalogProvisioningUpdateDetails$ProvisioningParameters' => 'A list of key value pairs that you specify when you provision a product.
', ], ], 'PublicWorkforceTaskPrice' => [ 'base' => 'Defines the amount of money paid to an Amazon Mechanical Turk worker for each task performed.
Use one of the following prices for bounding box tasks. Prices are in US dollars and should be based on the complexity of the task; the longer it takes in your initial testing, the more you should offer.
0.036
0.048
0.060
0.072
0.120
0.240
0.360
0.480
0.600
0.720
0.840
0.960
1.080
1.200
Use one of the following prices for image classification, text classification, and custom tasks. Prices are in US dollars.
0.012
0.024
0.036
0.048
0.060
0.072
0.120
0.240
0.360
0.480
0.600
0.720
0.840
0.960
1.080
1.200
Use one of the following prices for semantic segmentation tasks. Prices are in US dollars.
0.840
0.960
1.080
1.200
Use one of the following prices for Textract AnalyzeDocument Important Form Key Amazon Augmented AI review tasks. Prices are in US dollars.
2.400
2.280
2.160
2.040
1.920
1.800
1.680
1.560
1.440
1.320
1.200
1.080
0.960
0.840
0.720
0.600
0.480
0.360
0.240
0.120
0.072
0.060
0.048
0.036
0.024
0.012
Use one of the following prices for Rekognition DetectModerationLabels Amazon Augmented AI review tasks. Prices are in US dollars.
1.200
1.080
0.960
0.840
0.720
0.600
0.480
0.360
0.240
0.120
0.072
0.060
0.048
0.036
0.024
0.012
Use one of the following prices for Amazon Augmented AI custom human review tasks. Prices are in US dollars.
1.200
1.080
0.960
0.840
0.720
0.600
0.480
0.360
0.240
0.120
0.072
0.060
0.048
0.036
0.024
0.012
The price that you pay for each task performed by an Amazon Mechanical Turk worker.
', ], ], 'PutModelPackageGroupPolicyInput' => [ 'base' => NULL, 'refs' => [], ], 'PutModelPackageGroupPolicyOutput' => [ 'base' => NULL, 'refs' => [], ], 'QualityCheckStepMetadata' => [ 'base' => 'Container for the metadata for a Quality check step. For more information, see the topic on QualityCheck step in the Amazon SageMaker Developer Guide.
', 'refs' => [ 'PipelineExecutionStepMetadata$QualityCheck' => 'The configurations and outcomes of the check step execution. This includes:
The type of the check conducted.
The Amazon S3 URIs of baseline constraints and statistics files to be used for the drift check.
The Amazon S3 URIs of newly calculated baseline constraints and statistics.
The model package group name provided.
The Amazon S3 URI of the violation report if violations detected.
The Amazon Resource Name (ARN) of check processing job initiated by the step execution.
The Boolean flags indicating if the drift check is skipped.
If step property BaselineUsedForDriftCheck is set the same as CalculatedBaseline.
A set of filters to narrow the set of lineage entities connected to the StartArn(s) returned by the QueryLineage API action.
A set of filtering parameters that allow you to specify which entities should be returned.
Properties - Key-value pairs to match on the lineage entities\' properties.
LineageTypes - A set of lineage entity types to match on. For example: TrialComponent, Artifact, or Context.
CreatedBefore - Filter entities created before this date.
ModifiedBefore - Filter entities modified before this date.
ModifiedAfter - Filter entities modified after this date.
The maximum depth in lineage relationships from the StartArns that are traversed. Depth is a measure of the number of Associations from the StartArn entity to the matched results.
Limits the number of vertices in the results. Use the NextToken in a response to to retrieve the next page of results.
A list of resource Amazon Resource Name (ARN) that represent the starting point for your lineage query.
', ], ], 'QueryLineageTypes' => [ 'base' => NULL, 'refs' => [ 'QueryFilters$LineageTypes' => 'Filter the lineage entities connected to the StartArn(s) by the type of the lineage entity.
Filter the lineage entities connected to the StartArn(s) by a set if property key value pairs. If multiple pairs are provided, an entity is included in the results if it matches any of the provided pairs.
Filter the lineage entities connected to the StartArn by type. For example: DataSet, Model, Endpoint, or ModelDeployment.
A collection of settings that apply to an RSessionGateway app.
A collection of settings that configure the RSessionGateway app.
Indicates whether the current user has access to the RStudioServerPro app.
A collection of settings that configure user interaction with the RStudioServerPro app.
A collection of settings that configure user interaction with the RStudioServerPro app.
A collection of settings that configure the RStudioServerPro Domain-level app.
A collection of settings that configure the RStudioServerPro Domain-level app.
A collection of settings that update the current configuration for the RStudioServerPro Domain-level app.
A collection of RStudioServerPro Domain-level app settings to update. A single RStudioServerPro application is created for a domain.
The level of permissions that the user has within the RStudioServerPro app. This value defaults to `User`. The `Admin` value allows the user access to the RStudio Administrative Dashboard.
A value used to initialize a pseudo-random number generator. Setting a random seed and using the same seed later for the same tuning job will allow hyperparameter optimization to find more a consistent hyperparameter configuration between the two runs.
', ], ], 'RealTimeInferenceConfig' => [ 'base' => 'The infrastructure configuration for deploying the model to a real-time inference endpoint.
', 'refs' => [ 'ModelInfrastructureConfig$RealTimeInferenceConfig' => 'The infrastructure configuration for deploying the model to real-time inference.
', ], ], 'RealTimeInferenceRecommendation' => [ 'base' => 'The recommended configuration to use for Real-Time Inference.
', 'refs' => [ 'RealTimeInferenceRecommendations$member' => NULL, ], ], 'RealTimeInferenceRecommendations' => [ 'base' => NULL, 'refs' => [ 'DeploymentRecommendation$RealTimeInferenceRecommendations' => 'A list of RealTimeInferenceRecommendation items.
', ], ], 'RealtimeInferenceInstanceTypes' => [ 'base' => NULL, 'refs' => [ 'AdditionalInferenceSpecificationDefinition$SupportedRealtimeInferenceInstanceTypes' => 'A list of the instance types that are used to generate inferences in real-time.
', 'InferenceSpecification$SupportedRealtimeInferenceInstanceTypes' => 'A list of the instance types that are used to generate inferences in real-time.
This parameter is required for unversioned models, and optional for versioned models.
', ], ], 'RecommendationFailureReason' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobInferenceBenchmark$FailureReason' => 'The reason why a benchmark failed.
', ], ], 'RecommendationJobArn' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceRecommendationsJobResponse$JobArn' => 'The Amazon Resource Name (ARN) of the recommendation job.
', 'DescribeInferenceRecommendationsJobResponse$JobArn' => 'The Amazon Resource Name (ARN) of the job.
', 'InferenceRecommendationsJob$JobArn' => 'The Amazon Resource Name (ARN) of the recommendation job.
', ], ], 'RecommendationJobCompilationJobName' => [ 'base' => NULL, 'refs' => [ 'ModelConfiguration$CompilationJobName' => 'The name of the compilation job used to create the recommended model artifacts.
', ], ], 'RecommendationJobCompiledOutputConfig' => [ 'base' => 'Provides information about the output configuration for the compiled model.
', 'refs' => [ 'RecommendationJobOutputConfig$CompiledOutputConfig' => 'Provides information about the output configuration for the compiled model.
', ], ], 'RecommendationJobContainerConfig' => [ 'base' => 'Specifies mandatory fields for running an Inference Recommender job directly in the CreateInferenceRecommendationsJob API. The fields specified in ContainerConfig override the corresponding fields in the model package. Use ContainerConfig if you want to specify these fields for the recommendation job but don\'t want to edit them in your model package.
Specifies mandatory fields for running an Inference Recommender job. The fields specified in ContainerConfig override the corresponding fields in the model package.
Specifies the name and shape of the expected data inputs for your trained model with a JSON dictionary form. This field is used for optimizing your model using SageMaker Neo. For more information, see DataInputConfig.
', ], ], 'RecommendationJobDescription' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceRecommendationsJobRequest$JobDescription' => 'Description of the recommendation job.
', 'DescribeInferenceRecommendationsJobResponse$JobDescription' => 'The job description that you provided when you initiated the job.
', 'InferenceRecommendationsJob$JobDescription' => 'The job description.
', ], ], 'RecommendationJobInferenceBenchmark' => [ 'base' => 'The details for a specific benchmark from an Inference Recommender job.
', 'refs' => [ 'InferenceRecommendationsJobStep$InferenceBenchmark' => 'The details for a specific benchmark.
', ], ], 'RecommendationJobInputConfig' => [ 'base' => 'The input configuration of the recommendation job.
', 'refs' => [ 'CreateInferenceRecommendationsJobRequest$InputConfig' => 'Provides information about the versioned model package Amazon Resource Name (ARN), the traffic pattern, and endpoint configurations.
', 'DescribeInferenceRecommendationsJobResponse$InputConfig' => 'Returns information about the versioned model package Amazon Resource Name (ARN), the traffic pattern, and endpoint configurations you provided when you initiated the job.
', ], ], 'RecommendationJobName' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceRecommendationsJobRequest$JobName' => 'A name for the recommendation job. The name must be unique within the Amazon Web Services Region and within your Amazon Web Services account. The job name is passed down to the resources created by the recommendation job. The names of resources (such as the model, endpoint configuration, endpoint, and compilation) that are prefixed with the job name are truncated at 40 characters.
', 'DescribeInferenceRecommendationsJobRequest$JobName' => 'The name of the job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeInferenceRecommendationsJobResponse$JobName' => 'The name of the job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'GetScalingConfigurationRecommendationRequest$InferenceRecommendationsJobName' => 'The name of a previously completed Inference Recommender job.
', 'GetScalingConfigurationRecommendationResponse$InferenceRecommendationsJobName' => 'The name of a previously completed Inference Recommender job.
', 'InferenceRecommendationsJob$JobName' => 'The name of the job.
', 'InferenceRecommendationsJobStep$JobName' => 'The name of the Inference Recommender job.
', 'ListInferenceRecommendationsJobStepsRequest$JobName' => 'The name for the Inference Recommender job.
', 'StopInferenceRecommendationsJobRequest$JobName' => 'The name of the job you want to stop.
', ], ], 'RecommendationJobOutputConfig' => [ 'base' => 'Provides information about the output configuration for the compiled model.
', 'refs' => [ 'CreateInferenceRecommendationsJobRequest$OutputConfig' => 'Provides information about the output artifacts and the KMS key to use for Amazon S3 server-side encryption.
', ], ], 'RecommendationJobPayloadConfig' => [ 'base' => 'The configuration for the payload for a recommendation job.
', 'refs' => [ 'RecommendationJobContainerConfig$PayloadConfig' => 'Specifies the SamplePayloadUrl and all other sample payload-related fields.
Specifies the maximum number of jobs that can run in parallel and the maximum number of jobs that can run.
', 'refs' => [ 'RecommendationJobInputConfig$ResourceLimit' => 'Defines the resource limit of the job.
', ], ], 'RecommendationJobStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeInferenceRecommendationsJobResponse$Status' => 'The status of the job.
', 'InferenceRecommendationsJob$Status' => 'The status of the job.
', 'InferenceRecommendationsJobStep$Status' => 'The current status of the benchmark.
', 'ListInferenceRecommendationsJobStepsRequest$Status' => 'A filter to return benchmarks of a specified status. If this field is left empty, then all benchmarks are returned.
', 'ListInferenceRecommendationsJobsRequest$StatusEquals' => 'A filter that retrieves only inference recommendations jobs with a specific status.
', ], ], 'RecommendationJobStoppingConditions' => [ 'base' => 'Specifies conditions for stopping a job. When a job reaches a stopping condition limit, SageMaker ends the job.
', 'refs' => [ 'CreateInferenceRecommendationsJobRequest$StoppingConditions' => 'A set of conditions for stopping a recommendation job. If any of the conditions are met, the job is automatically stopped.
', 'DescribeInferenceRecommendationsJobResponse$StoppingConditions' => 'The stopping conditions that you provided when you initiated the job.
', ], ], 'RecommendationJobSupportedContentTypes' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobPayloadConfig$SupportedContentTypes' => 'The supported MIME types for the input data.
', ], ], 'RecommendationJobSupportedEndpointType' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobContainerConfig$SupportedEndpointType' => 'The endpoint type to receive recommendations for. By default this is null, and the results of the inference recommendation job return a combined list of both real-time and serverless benchmarks. By specifying a value for this field, you can receive a longer list of benchmarks for the desired endpoint type.
', ], ], 'RecommendationJobSupportedInstanceTypes' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobContainerConfig$SupportedInstanceTypes' => 'A list of the instance types that are used to generate inferences in real-time.
', ], ], 'RecommendationJobSupportedResponseMIMEType' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobSupportedResponseMIMETypes$member' => NULL, ], ], 'RecommendationJobSupportedResponseMIMETypes' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobContainerConfig$SupportedResponseMIMETypes' => 'The supported MIME types for the output data.
', ], ], 'RecommendationJobType' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceRecommendationsJobRequest$JobType' => 'Defines the type of recommendation job. Specify Default to initiate an instance recommendation and Advanced to initiate a load test. If left unspecified, Amazon SageMaker Inference Recommender will run an instance recommendation (DEFAULT) job.
The job type that you provided when you initiated the job.
', 'InferenceRecommendationsJob$JobType' => 'The recommendation job type.
', ], ], 'RecommendationJobVpcConfig' => [ 'base' => 'Inference Recommender provisions SageMaker endpoints with access to VPC in the inference recommendation job.
', 'refs' => [ 'RecommendationJobInputConfig$VpcConfig' => 'Inference Recommender provisions SageMaker endpoints with access to VPC in the inference recommendation job.
', ], ], 'RecommendationJobVpcSecurityGroupId' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobVpcSecurityGroupIds$member' => NULL, ], ], 'RecommendationJobVpcSecurityGroupIds' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobVpcConfig$SecurityGroupIds' => 'The VPC security group IDs. IDs have the form of sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
The ID of the subnets in the VPC to which you want to connect your model.
', ], ], 'RecommendationMetrics' => [ 'base' => 'The metrics of recommendations.
', 'refs' => [ 'InferenceRecommendation$Metrics' => 'The metrics used to decide what recommendation to make.
', 'RecommendationJobInferenceBenchmark$Metrics' => NULL, ], ], 'RecommendationStatus' => [ 'base' => NULL, 'refs' => [ 'DeploymentRecommendation$RecommendationStatus' => 'Status of the deployment recommendation. The status NOT_APPLICABLE means that SageMaker is unable to provide a default recommendation for the model using the information provided. If the deployment status is IN_PROGRESS, retry your API call after a few seconds to get a COMPLETED deployment recommendation.
The type of the subtask.
BENCHMARK: Evaluate the performance of your model on different instance types.
A filter to return details about the specified type of subtask.
BENCHMARK: Evaluate the performance of your model on different instance types.
Specify RecordIO as the value when input data is in raw format but the training algorithm requires the RecordIO format. In this case, SageMaker wraps each individual S3 object in a RecordIO record. If the input data is already in RecordIO format, you don\'t need to set this attribute. For more information, see Create a Dataset Using RecordIO.
In File mode, leave this field unset or set it to None.
', ], ], 'RedshiftClusterId' => [ 'base' => 'The Redshift cluster Identifier.
', 'refs' => [ 'RedshiftDatasetDefinition$ClusterId' => NULL, ], ], 'RedshiftDatabase' => [ 'base' => 'The name of the Redshift database used in Redshift query execution.
', 'refs' => [ 'RedshiftDatasetDefinition$Database' => NULL, ], ], 'RedshiftDatasetDefinition' => [ 'base' => 'Configuration for Redshift Dataset Definition input.
', 'refs' => [ 'DatasetDefinition$RedshiftDatasetDefinition' => NULL, ], ], 'RedshiftQueryString' => [ 'base' => 'The SQL query statements to be executed.
', 'refs' => [ 'RedshiftDatasetDefinition$QueryString' => NULL, ], ], 'RedshiftResultCompressionType' => [ 'base' => 'The compression used for Redshift query results.
', 'refs' => [ 'RedshiftDatasetDefinition$OutputCompression' => NULL, ], ], 'RedshiftResultFormat' => [ 'base' => 'The data storage format for Redshift query results.
', 'refs' => [ 'RedshiftDatasetDefinition$OutputFormat' => NULL, ], ], 'RedshiftUserName' => [ 'base' => 'The database user name used in Redshift query execution.
', 'refs' => [ 'RedshiftDatasetDefinition$DbUser' => NULL, ], ], 'RegisterDevicesRequest' => [ 'base' => NULL, 'refs' => [], ], 'RegisterModelStepMetadata' => [ 'base' => 'Metadata for a register model job step.
', 'refs' => [ 'PipelineExecutionStepMetadata$RegisterModel' => 'The Amazon Resource Name (ARN) of the model package that the model was registered to by this step execution.
', ], ], 'ReleaseNotes' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$ReleaseNotes' => 'The maintainer description of the image version.
', 'DescribeImageVersionResponse$ReleaseNotes' => 'The maintainer description of the image version.
', 'UpdateImageVersionRequest$ReleaseNotes' => 'The maintainer description of the image version.
', ], ], 'RenderUiTemplateRequest' => [ 'base' => NULL, 'refs' => [], ], 'RenderUiTemplateResponse' => [ 'base' => NULL, 'refs' => [], ], 'RenderableTask' => [ 'base' => 'Contains input values for a task.
', 'refs' => [ 'RenderUiTemplateRequest$Task' => 'A RenderableTask object containing a representative task to render.
A description of an error that occurred while rendering the template.
', 'refs' => [ 'RenderingErrorList$member' => NULL, ], ], 'RenderingErrorList' => [ 'base' => NULL, 'refs' => [ 'RenderUiTemplateResponse$Errors' => 'A list of one or more RenderingError objects if any were encountered while rendering the template. If there were no errors, the list is empty.
Set this to one of the following values:
Platform - The model image is hosted in Amazon ECR.
Vpc - The model image is hosted in a private Docker registry in your VPC.
Specifies an authentication configuration for the private docker registry where your model image is hosted. Specify a value for this property only if you specified Vpc as the value for the RepositoryAccessMode field of the ImageConfig object that you passed to a call to CreateModel and the private Docker registry where the model image is hosted requires authentication.
(Optional) Specifies an authentication configuration for the private docker registry where your model image is hosted. Specify a value for this property only if you specified Vpc as the value for the RepositoryAccessMode field, and the private Docker registry where the model image is hosted requires authentication.
The Amazon Resource Name (ARN) of an Amazon Web Services Lambda function that provides credentials to authenticate to the private Docker registry where your model image is hosted. For information about how to create an Amazon Web Services Lambda function, see Create a Lambda function with the console in the Amazon Web Services Lambda Developer Guide.
', ], ], 'RepositoryUrl' => [ 'base' => NULL, 'refs' => [ 'CodeRepository$RepositoryUrl' => 'The URL of the Git repository.
', ], ], 'ResolvedAttributes' => [ 'base' => 'The resolved attributes.
', 'refs' => [ 'DescribeAutoMLJobResponse$ResolvedAttributes' => 'Contains ProblemType, AutoMLJobObjective, and CompletionCriteria. If you do not provide these values, they are inferred.
The Amazon Resource Name (ARN) of the resource that you want to tag.
', 'DeleteTagsInput$ResourceArn' => 'The Amazon Resource Name (ARN) of the resource whose tags you want to delete.
', 'ListTagsInput$ResourceArn' => 'The Amazon Resource Name (ARN) of the resource whose tags you want to retrieve.
', ], ], 'ResourceCatalog' => [ 'base' => ' A resource catalog containing all of the resources of a specific resource type within a resource owner account. For an example on sharing the Amazon SageMaker Feature Store DefaultFeatureGroupCatalog, see Share Amazon SageMaker Catalog resource type in the Amazon SageMaker Developer Guide.
The Amazon Resource Name (ARN) of the ResourceCatalog.
A free form description of the ResourceCatalog.
A list of the requested ResourceCatalogs.
A string that partially matches one or more ResourceCatalogs names. Filters ResourceCatalog by name.
The name of the ResourceCatalog.
The value on which the resource catalog list is sorted.
', ], ], 'ResourceCatalogSortOrder' => [ 'base' => NULL, 'refs' => [ 'ListResourceCatalogsRequest$SortOrder' => 'The order in which the resource catalogs are listed.
', ], ], 'ResourceConfig' => [ 'base' => 'Describes the resources, including machine learning (ML) compute instances and ML storage volumes, to use for model training.
', 'refs' => [ 'CreateTrainingJobRequest$ResourceConfig' => 'The resources, including the ML compute instances and ML storage volumes, to use for model training.
ML storage volumes store model artifacts and incremental states. Training algorithms might also use ML storage volumes for scratch space. If you want SageMaker to use the ML storage volume to store the training data, choose File as the TrainingInputMode in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.
Resources, including ML compute instances and ML storage volumes, that are configured for model training.
', 'HyperParameterTrainingJobDefinition$ResourceConfig' => 'The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.
Storage volumes store model artifacts and incremental states. Training algorithms might also use storage volumes for scratch space. If you want SageMaker to use the storage volume to store the training data, choose File as the TrainingInputMode in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.
If you want to use hyperparameter optimization with instance type flexibility, use HyperParameterTuningResourceConfig instead.
Resources, including ML compute instances and ML storage volumes, that are configured for model training.
', 'TrainingJobDefinition$ResourceConfig' => 'The resources, including the ML compute instances and ML storage volumes, to use for model training.
', ], ], 'ResourceConfigForUpdate' => [ 'base' => 'The ResourceConfig to update KeepAlivePeriodInSeconds. Other fields in the ResourceConfig cannot be updated.
The training job ResourceConfig to update warm pool retention length.
The ID of the Amazon Elastic File System (EFS) managed by this Domain.
', ], ], 'ResourceInUse' => [ 'base' => 'Resource being accessed is in use.
', 'refs' => [], ], 'ResourceLimitExceeded' => [ 'base' => 'You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
', 'refs' => [], ], 'ResourceLimits' => [ 'base' => 'Specifies the maximum number of training jobs and parallel training jobs that a hyperparameter tuning job can launch.
', 'refs' => [ 'HyperParameterTuningJobConfig$ResourceLimits' => 'The ResourceLimits object that specifies the maximum number of training and parallel training jobs that can be used for this hyperparameter tuning job.
', 'HyperParameterTuningJobSummary$ResourceLimits' => 'The ResourceLimits object that specifies the maximum number of training jobs and parallel training jobs allowed for this tuning job.
', ], ], 'ResourceNotFound' => [ 'base' => 'Resource being access is not found.
', 'refs' => [], ], 'ResourcePolicyString' => [ 'base' => NULL, 'refs' => [ 'GetLineageGroupPolicyResponse$ResourcePolicy' => 'The resource policy that gives access to the lineage group in another account.
', ], ], 'ResourcePropertyName' => [ 'base' => NULL, 'refs' => [ 'Filter$Name' => 'A resource property name. For example, TrainingJobName. For valid property names, see SearchRecord. You must specify a valid property for the resource.
The name of the property to use in the nested filters. The value must match a listed property name, such as InputDataConfig.
A suggested property name based on what you entered in the search textbox in the SageMaker console.
', 'SearchRequest$SortBy' => 'The name of the resource property used to sort the SearchResults. The default is LastModifiedTime.
The billable time in seconds used by the warm pool. Billable time refers to the absolute wall-clock time.
Multiply ResourceRetainedBillableTimeInSeconds by the number of instances (InstanceCount) in your training cluster to get the total compute time SageMaker bills you if you run warm pool training. The formula is as follows: ResourceRetainedBillableTimeInSeconds * InstanceCount.
Specifies the ARN\'s of a SageMaker image and SageMaker image version, and the instance type that the version runs on.
', 'refs' => [ 'CreateAppRequest$ResourceSpec' => 'The instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.
The value of InstanceType passed as part of the ResourceSpec in the CreateApp call overrides the value passed as part of the ResourceSpec configured for the user profile or the domain. If InstanceType is not specified in any of those three ResourceSpec values for a KernelGateway app, the CreateApp call fails with a request validation error.
The instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.
', 'JupyterServerAppSettings$DefaultResourceSpec' => 'The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the JupyterServer app. If you use the LifecycleConfigArns parameter, then this parameter is also required.
The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the KernelGateway app.
The Amazon SageMaker Studio UI does not use the default instance type value set here. The default instance type set here is used when Apps are created using the Amazon Web Services Command Line Interface or Amazon Web Services CloudFormation and the instance type parameter value is not passed.
The default instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.
', ], ], 'ResourceType' => [ 'base' => NULL, 'refs' => [ 'GetSearchSuggestionsRequest$Resource' => 'The name of the SageMaker resource to search for.
', 'SearchRequest$Resource' => 'The name of the SageMaker resource to search for.
', ], ], 'ResponseMIMEType' => [ 'base' => NULL, 'refs' => [ 'ResponseMIMETypes$member' => NULL, ], ], 'ResponseMIMETypes' => [ 'base' => NULL, 'refs' => [ 'AdditionalInferenceSpecificationDefinition$SupportedResponseMIMETypes' => 'The supported MIME types for the output data.
', 'InferenceSpecification$SupportedResponseMIMETypes' => 'The supported MIME types for the output data.
', ], ], 'RetentionPolicy' => [ 'base' => 'The retention policy for data stored on an Amazon Elastic File System (EFS) volume.
', 'refs' => [ 'DeleteDomainRequest$RetentionPolicy' => 'The retention policy for this domain, which specifies whether resources will be retained after the Domain is deleted. By default, all resources are retained (not automatically deleted).
', ], ], 'RetentionType' => [ 'base' => NULL, 'refs' => [ 'RetentionPolicy$HomeEfsFileSystem' => 'The default is Retain, which specifies to keep the data stored on the EFS volume.
Specify Delete to delete the data stored on the EFS volume.
The retry strategy to use when a training job fails due to an InternalServerError. RetryStrategy is specified as part of the CreateTrainingJob and CreateHyperParameterTuningJob requests. You can add the StoppingCondition parameter to the request to limit the training time for the complete job.
The number of times to retry the job when the job fails due to an InternalServerError.
The number of times to retry the job when the job fails due to an InternalServerError.
The number of times to retry the job when the job fails due to an InternalServerError.
The number of times to retry the job when the job fails due to an InternalServerError.
The IAM roles that SageMaker uses to run the training jobs.
', 'CreateAutoMLJobRequest$RoleArn' => 'The ARN of the role that is used to access the data.
', 'CreateAutoMLJobV2Request$RoleArn' => 'The ARN of the role that is used to access the data.
', 'CreateCompilationJobRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.
During model compilation, Amazon SageMaker needs your permission to:
Read input data from an S3 bucket
Write model artifacts to an S3 bucket
Write logs to Amazon CloudWatch Logs
Publish metrics to Amazon CloudWatch
You grant permissions for all of these tasks to an IAM role. To pass this role to Amazon SageMaker, the caller of this API must have the iam:PassRole permission. For more information, see Amazon SageMaker Roles.
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'CreateDeviceFleetRequest$RoleArn' => 'The Amazon Resource Name (ARN) that has access to Amazon Web Services Internet of Things (IoT).
', 'CreateEdgePackagingJobRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to download and upload the model, and to contact SageMaker Neo.
', 'CreateFeatureGroupRequest$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM execution role used to persist data into the OfflineStore if an OfflineStoreConfig is provided.
The Amazon Resource Name (ARN) of the role needed to call other services on your behalf. For example, arn:aws:iam::1234567890:role/service-role/AmazonSageMaker-ExecutionRole-20180111T151298.
The ARN of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.
', 'CreateInferenceExperimentRequest$RoleArn' => 'The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.
', 'CreateInferenceRecommendationsJobRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.
', 'CreateLabelingJobRequest$RoleArn' => 'The Amazon Resource Number (ARN) that Amazon SageMaker assumes to perform tasks on your behalf during data labeling. You must grant this role the necessary permissions so that Amazon SageMaker can successfully complete data labeling.
', 'CreateModelBiasJobDefinitionRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'CreateModelExplainabilityJobDefinitionRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'CreateModelInput$ExecutionRoleArn' => 'The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access model artifacts and docker image for deployment on ML compute instances or for batch transform jobs. Deploying on ML compute instances is part of model hosting. For more information, see SageMaker Roles.
To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole permission.
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'CreateNotebookInstanceInput$RoleArn' => 'When you send any requests to Amazon Web Services resources from the notebook instance, SageMaker assumes this role to perform tasks on your behalf. You must grant this role necessary permissions so SageMaker can perform these tasks. The policy must allow the SageMaker service principal (sagemaker.amazonaws.com) permissions to assume this role. For more information, see SageMaker Roles.
To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole permission.
The Amazon Resource Name (ARN) of the role used by the pipeline to access and create resources.
', 'CreateProcessingJobRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'CreateTrainingJobRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that SageMaker can assume to perform tasks on your behalf.
During model training, SageMaker needs your permission to read input data from an S3 bucket, download a Docker image that contains training code, write model artifacts to an S3 bucket, write logs to Amazon CloudWatch Logs, and publish metrics to Amazon CloudWatch. You grant permissions for all of these tasks to an IAM role. For more information, see SageMaker Roles.
To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole permission.
The ARN of the execution role for the space.
', 'DescribeAutoMLJobResponse$RoleArn' => 'The Amazon Resource Name (ARN) of the Identity and Access Management (IAM) role that has read permission to the input data location and write permission to the output data location in Amazon S3.
', 'DescribeAutoMLJobV2Response$RoleArn' => 'The ARN of the Identity and Access Management role that has read permission to the input data location and write permission to the output data location in Amazon S3.
', 'DescribeCompilationJobResponse$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker assumes to perform the model compilation job.
', 'DescribeDataQualityJobDefinitionResponse$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'DescribeDeviceFleetResponse$RoleArn' => 'The Amazon Resource Name (ARN) that has access to Amazon Web Services Internet of Things (IoT).
', 'DescribeEdgePackagingJobResponse$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to download and upload the model, and to contact Neo.
', 'DescribeFeatureGroupResponse$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM execution role used to persist data into the OfflineStore if an OfflineStoreConfig is provided.
', 'DescribeFlowDefinitionResponse$RoleArn' => 'The Amazon Resource Name (ARN) of the Amazon Web Services Identity and Access Management (IAM) execution role for the flow definition.
', 'DescribeImageResponse$RoleArn' => 'The ARN of the IAM role that enables Amazon SageMaker to perform tasks on your behalf.
', 'DescribeInferenceExperimentResponse$RoleArn' => 'The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.
', 'DescribeInferenceRecommendationsJobResponse$RoleArn' => 'The Amazon Resource Name (ARN) of the Amazon Web Services Identity and Access Management (IAM) role you provided when you initiated the job.
', 'DescribeLabelingJobResponse$RoleArn' => 'The Amazon Resource Name (ARN) that SageMaker assumes to perform tasks on your behalf during data labeling.
', 'DescribeModelBiasJobDefinitionResponse$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM role that has read permission to the input data location and write permission to the output data location in Amazon S3.
', 'DescribeModelExplainabilityJobDefinitionResponse$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM role that has read permission to the input data location and write permission to the output data location in Amazon S3.
', 'DescribeModelOutput$ExecutionRoleArn' => 'The Amazon Resource Name (ARN) of the IAM role that you specified for the model.
', 'DescribeModelQualityJobDefinitionResponse$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'DescribeNotebookInstanceOutput$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM role associated with the instance.
', 'DescribePipelineResponse$RoleArn' => 'The Amazon Resource Name (ARN) that the pipeline uses to execute.
', 'DescribeProcessingJobResponse$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'DescribeTrainingJobResponse$RoleArn' => 'The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.
', 'FeatureGroup$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM execution role used to create the feature group.
', 'HyperParameterTrainingJobDefinition$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM role associated with the training jobs that the tuning job launches.
', 'InferenceExperimentSummary$RoleArn' => 'The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.
', 'InferenceRecommendationsJob$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.
', 'Model$ExecutionRoleArn' => 'The Amazon Resource Name (ARN) of the IAM role that you specified for the model.
', 'ModelPackageValidationSpecification$ValidationRole' => 'The IAM roles to be used for the validation of the model package.
', 'ModelRegisterSettings$CrossAccountModelRegisterRoleArn' => 'The Amazon Resource Name (ARN) of the SageMaker model registry account. Required only to register model versions created by a different SageMaker Canvas Amazon Web Services account than the Amazon Web Services account in which SageMaker model registry is set up.
', 'MonitoringJobDefinition$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'Pipeline$RoleArn' => 'The Amazon Resource Name (ARN) of the role that created the pipeline.
', 'PipelineSummary$RoleArn' => 'The Amazon Resource Name (ARN) that the pipeline used to execute.
', 'ProcessingJob$RoleArn' => 'The ARN of the role used to create the processing job.
', 'RStudioServerProDomainSettings$DomainExecutionRoleArn' => 'The ARN of the execution role for the RStudioServerPro Domain-level app.
The execution role for the RStudioServerPro Domain-level app.
The IAM role attached to your Redshift cluster that Amazon SageMaker uses to generate datasets.
', 'RenderUiTemplateRequest$RoleArn' => 'The Amazon Resource Name (ARN) that has access to the S3 objects that are used by the template.
', 'TimeSeriesForecastingSettings$AmazonForecastRoleArn' => 'The IAM role that Canvas passes to Amazon Forecast for time series forecasting. By default, Canvas uses the execution role specified in the UserProfile that launches the Canvas application. If an execution role is not specified in the UserProfile, Canvas uses the execution role specified in the Domain that owns the UserProfile. To allow time series forecasting, this IAM role should have the AmazonSageMakerCanvasForecastAccess policy attached and forecast.amazonaws.com added in the trust relationship as a service principal.
The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.
', 'UpdateDeviceFleetRequest$RoleArn' => 'The Amazon Resource Name (ARN) of the device.
', 'UpdateImageRequest$RoleArn' => 'The new ARN for the IAM role that enables Amazon SageMaker to perform tasks on your behalf.
', 'UpdateNotebookInstanceInput$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access the notebook instance. For more information, see SageMaker Roles.
To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole permission.
The Amazon Resource Name (ARN) that the pipeline uses to execute.
', 'UserSettings$ExecutionRole' => 'The execution role for the user.
', ], ], 'RollingUpdatePolicy' => [ 'base' => 'Specifies a rolling deployment strategy for updating a SageMaker endpoint.
', 'refs' => [ 'DeploymentConfig$RollingUpdatePolicy' => 'Specifies a rolling deployment strategy for updating a SageMaker endpoint.
', ], ], 'RootAccess' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$RootAccess' => 'Whether root access is enabled or disabled for users of the notebook instance. The default value is Enabled.
Lifecycle configurations need root access to be able to set up a notebook instance. Because of this, lifecycle configurations associated with a notebook instance always run with root access even if you disable root access for users.
Whether root access is enabled or disabled for users of the notebook instance.
Lifecycle configurations need root access to be able to set up a notebook instance. Because of this, lifecycle configurations associated with a notebook instance always run with root access even if you disable root access for users.
Whether root access is enabled or disabled for users of the notebook instance. The default value is Enabled.
If you set this to Disabled, users don\'t have root access on the notebook instance, but lifecycle configuration scripts still run with root permissions.
The name of the rule configuration. It must be unique relative to other rule configuration names.
', 'DebugRuleEvaluationStatus$RuleConfigurationName' => 'The name of the rule configuration.
', 'ProfilerRuleConfiguration$RuleConfigurationName' => 'The name of the rule configuration. It must be unique relative to other rule configuration names.
', 'ProfilerRuleEvaluationStatus$RuleConfigurationName' => 'The name of the rule configuration.
', ], ], 'RuleEvaluationStatus' => [ 'base' => NULL, 'refs' => [ 'DebugRuleEvaluationStatus$RuleEvaluationStatus' => 'Status of the rule evaluation.
', 'ProfilerRuleEvaluationStatus$RuleEvaluationStatus' => 'Status of the rule evaluation.
', ], ], 'RuleParameters' => [ 'base' => NULL, 'refs' => [ 'DebugRuleConfiguration$RuleParameters' => 'Runtime configuration for rule container.
', 'ProfilerRuleConfiguration$RuleParameters' => 'Runtime configuration for rule container.
', ], ], 'S3DataDistribution' => [ 'base' => NULL, 'refs' => [ 'S3DataSource$S3DataDistributionType' => 'If you want SageMaker to replicate the entire dataset on each ML compute instance that is launched for model training, specify FullyReplicated.
If you want SageMaker to replicate a subset of data on each ML compute instance that is launched for model training, specify ShardedByS3Key. If there are n ML compute instances launched for a training job, each instance gets approximately 1/n of the number of S3 objects. In this case, model training on each machine uses only the subset of training data.
Don\'t choose more ML compute instances for training than available S3 objects. If you do, some nodes won\'t get any data and you will pay for nodes that aren\'t getting any training data. This applies in both File and Pipe modes. Keep this in mind when developing algorithms.
In distributed training, where you use multiple ML compute EC2 instances, you might choose ShardedByS3Key. If the algorithm requires copying training data to the ML storage volume (when TrainingInputMode is set to File), this copies 1/n of the number of objects.
Describes the S3 data source.
Your input bucket must be in the same Amazon Web Services region as your training job.
', 'refs' => [ 'DataSource$S3DataSource' => 'The S3 location of the data source that is associated with a channel.
', ], ], 'S3DataType' => [ 'base' => NULL, 'refs' => [ 'S3DataSource$S3DataType' => 'If you choose S3Prefix, S3Uri identifies a key name prefix. SageMaker uses all objects that match the specified key name prefix for model training.
If you choose ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want SageMaker to use for model training.
If you choose AugmentedManifestFile, S3Uri identifies an object that is an augmented manifest file in JSON lines format. This file contains the data you want to use for model training. AugmentedManifestFile can only be used if the Channel\'s input mode is Pipe.
If you choose S3Prefix, S3Uri identifies a key name prefix. Amazon SageMaker uses all objects with the specified key name prefix for batch transform.
If you choose ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want Amazon SageMaker to use for batch transform.
The following values are compatible: ManifestFile, S3Prefix
The following value is not compatible: AugmentedManifestFile
Specifies the S3 location of ML model data to deploy.
', 'refs' => [ 'ModelDataSource$S3DataSource' => 'Specifies the S3 location of ML model data to deploy.
', ], ], 'S3ModelDataType' => [ 'base' => NULL, 'refs' => [ 'S3ModelDataSource$S3DataType' => 'Specifies the type of ML model data to deploy.
If you choose S3Prefix, S3Uri identifies a key name prefix. SageMaker uses all objects that match the specified key name prefix as part of the ML model data to deploy. A valid key name prefix identified by S3Uri always ends with a forward slash (/).
If you choose S3Object, S3Uri identifies an object that is the ML model data to deploy.
Specifies the S3 path of ML model data to deploy.
', ], ], 'S3OutputPath' => [ 'base' => NULL, 'refs' => [ 'HubS3StorageConfig$S3OutputPath' => 'The Amazon S3 bucket prefix for hosting hub content.
', ], ], 'S3StorageConfig' => [ 'base' => 'The Amazon Simple Storage (Amazon S3) location and and security configuration for OfflineStore.
The Amazon Simple Storage (Amazon S3) location of OfflineStore.
The uniform resource identifier (URI) used to identify an additional data source used in inference or training.
', 'AthenaDatasetDefinition$OutputS3Uri' => 'The location in Amazon S3 where Athena query results are stored.
', 'AutoMLCandidateGenerationConfig$FeatureSpecificationS3Uri' => 'A URL to the Amazon S3 data source containing selected features from the input data source to run an Autopilot job. You can input FeatureAttributeNames (optional) in JSON format as shown below:
{ "FeatureAttributeNames":["col1", "col2", ...] }.
You can also specify the data type of the feature (optional) in the format shown below:
{ "FeatureDataTypes":{"col1":"numeric", "col2":"categorical" ... } }
These column keys may not include the target column.
In ensembling mode, Autopilot only supports the following data types: numeric, categorical, text, and datetime. In HPO mode, Autopilot can support numeric, categorical, text, datetime, and sequence.
If only FeatureDataTypes is provided, the column keys (col1, col2,..) should be a subset of the column names in the input data.
If both FeatureDataTypes and FeatureAttributeNames are provided, then the column keys should be a subset of the column names provided in FeatureAttributeNames.
The key name FeatureAttributeNames is fixed. The values listed in ["col1", "col2", ...] are case sensitive and should be a list of strings containing unique values that are a subset of the column names in the input data. The list of columns provided must not include the target column.
The Amazon S3 output path. Must be 128 characters or less.
', 'AutoMLS3DataSource$S3Uri' => 'The URL to the Amazon S3 data source. The Uri refers to the Amazon S3 prefix or ManifestFile depending on the data type.
', 'BatchDataCaptureConfig$DestinationS3Uri' => 'The Amazon S3 location being used to capture the data.
', 'CheckpointConfig$S3Uri' => 'Identifies the S3 path where you want SageMaker to store checkpoints. For example, s3://bucket-name/key-name-prefix.
The S3 URI of the file, referred to as a label category configuration file, that defines the categories used to label the data objects.
For 3D point cloud and video frame task types, you can add label category attributes and frame attributes to your label category configuration file. To learn how, see Create a Labeling Category Configuration File for 3D Point Cloud Labeling Jobs.
For named entity recognition jobs, in addition to "labels", you must provide worker instructions in the label category configuration file using the "instructions" parameter: "instructions": {"shortInstruction":"<h1>Add header</h1><p>Add Instructions</p>", "fullInstruction":"<p>Add additional instructions.</p>"}. For details and an example, see Create a Named Entity Recognition Labeling Job (API) .
For all other built-in task types and custom tasks, your label category configuration file must be a JSON file in the following format. Identify the labels you want to use by replacing label_1, label_2,...,label_n with your label categories.
{
"document-version": "2018-11-28",
"labels": [{"label": "label_1"},{"label": "label_2"},...{"label": "label_n"}]
}
Note the following about the label category configuration file:
For image classification and text classification (single and multi-label) you must specify at least two label categories. For all other task types, the minimum number of label categories required is one.
Each label category must be unique, you cannot specify duplicate label categories.
If you create a 3D point cloud or video frame adjustment or verification labeling job, you must include auditLabelAttributeName in the label category configuration. Use this parameter to enter the LabelAttributeName of the labeling job you want to adjust or verify annotations of.
The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix). This archive can hold multiple files that are all equally used in the load test. Each file in the archive must satisfy the size constraints of the InvokeEndpoint call.
', 'DataQualityAppSpecification$RecordPreprocessorSourceUri' => 'An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flattened JSON so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers.
', 'DataQualityAppSpecification$PostAnalyticsProcessorSourceUri' => 'An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
', 'DebugHookConfig$S3OutputPath' => 'Path to Amazon S3 storage location for metrics and tensors.
', 'DebugRuleConfiguration$S3OutputPath' => 'Path to Amazon S3 storage location for rules.
', 'DescribeEdgePackagingJobResponse$ModelArtifact' => 'The Amazon Simple Storage (S3) URI where model artifacts ares stored.
', 'DescribeLabelingJobResponse$LabelCategoryConfigS3Uri' => 'The S3 location of the JSON file that defines the categories used to label data objects. Please note the following label-category limits:
Semantic segmentation labeling jobs using automated labeling: 20 labels
Box bounding labeling jobs (all): 10 labels
The file is a JSON structure in the following format:
{
"document-version": "2018-11-28"
"labels": [
{
"label": "label 1"
},
{
"label": "label 2"
},
...
{
"label": "label n"
}
]
}
The Amazon Simple Storage (S3) bucker URI.
', 'FileSource$S3Uri' => 'The Amazon S3 URI for the file source.
', 'FlowDefinitionOutputConfig$S3OutputPath' => 'The Amazon S3 path where the object containing human output will be made available.
To learn more about the format of Amazon A2I output data, see Amazon A2I Output Data.
', 'InferenceRecommendationsJob$SamplePayloadUrl' => 'The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
', 'InputConfig$S3Uri' => 'The S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
', 'LabelingJobOutput$OutputDatasetS3Uri' => 'The Amazon S3 bucket location of the manifest file for labeled data.
', 'LabelingJobOutputConfig$S3OutputPath' => 'The Amazon S3 location to write output data.
', 'LabelingJobS3DataSource$ManifestS3Uri' => 'The Amazon S3 location of the manifest file that describes the input data objects.
The input manifest file referenced in ManifestS3Uri must contain one of the following keys: source-ref or source. The value of the keys are interpreted as follows:
source-ref: The source of the object is the Amazon S3 object specified in the value. Use this value when the object is a binary object, such as an image.
source: The source of the object is the value. Use this value when the object is a text value.
If you are a new user of Ground Truth, it is recommended you review Use an Input Manifest File in the Amazon SageMaker Developer Guide to learn how to create an input manifest file.
', 'MetricsSource$S3Uri' => 'The S3 URI for the metrics source.
', 'ModelArtifacts$S3ModelArtifacts' => 'The path of the S3 object that contains the model artifacts. For example, s3://bucket-name/keynameprefix/model.tar.gz.
JSON formatted S3 file that defines bias parameters. For more information on this JSON configuration file, see Configure bias parameters.
', 'ModelCardExportArtifacts$S3ExportArtifacts' => 'The Amazon S3 URI of the exported model artifacts.
', 'ModelCardExportOutputConfig$S3OutputPath' => 'The Amazon S3 output path to export your model card PDF.
', 'ModelExplainabilityAppSpecification$ConfigUri' => 'JSON formatted Amazon S3 file that defines explainability parameters. For more information on this JSON configuration file, see Configure model explainability parameters.
', 'ModelQualityAppSpecification$RecordPreprocessorSourceUri' => 'An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flattened JSON so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers.
', 'ModelQualityAppSpecification$PostAnalyticsProcessorSourceUri' => 'An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
', 'MonitoringAppSpecification$RecordPreprocessorSourceUri' => 'An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flattened JSON so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers.
', 'MonitoringAppSpecification$PostAnalyticsProcessorSourceUri' => 'An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
', 'MonitoringConstraintsResource$S3Uri' => 'The Amazon S3 URI for the constraints resource.
', 'MonitoringStatisticsResource$S3Uri' => 'The Amazon S3 URI for the statistics resource.
', 'OutputConfig$S3OutputLocation' => 'Identifies the S3 bucket where you want Amazon SageMaker to store the model artifacts. For example, s3://bucket-name/key-name-prefix.
Identifies the S3 path where you want SageMaker to store the model artifacts. For example, s3://bucket-name/key-name-prefix.
The URI of the Amazon S3 prefix Amazon SageMaker downloads data required to run a processing job.
', 'ProcessingS3Output$S3Uri' => 'A URI that identifies the Amazon S3 bucket where you want Amazon SageMaker to save the results of a processing job.
', 'ProfilerConfig$S3OutputPath' => 'Path to Amazon S3 storage location for system and framework metrics.
', 'ProfilerConfigForUpdate$S3OutputPath' => 'Path to Amazon S3 storage location for system and framework metrics.
', 'ProfilerRuleConfiguration$S3OutputPath' => 'Path to Amazon S3 storage location for rules.
', 'RecommendationJobCompiledOutputConfig$S3OutputUri' => 'Identifies the Amazon S3 bucket where you want SageMaker to store the compiled model artifacts.
', 'RedshiftDatasetDefinition$OutputS3Uri' => 'The location in Amazon S3 where the Redshift query results are stored.
', 'S3DataSource$S3Uri' => 'Depending on the value specified for the S3DataType, identifies either a key name prefix or a manifest. For example:
A key name prefix might look like this: s3://bucketname/exampleprefix
A manifest might look like this: s3://bucketname/example.manifest
A manifest is an S3 object which is a JSON file consisting of an array of elements. The first element is a prefix which is followed by one or more suffixes. SageMaker appends the suffix elements to the prefix to get a full set of S3Uri. Note that the prefix must be a valid non-empty S3Uri that precludes users from specifying a manifest whose individual S3Uri is sourced from different S3 buckets.
The following code example shows a valid manifest format:
[ {"prefix": "s3://customer_bucket/some/prefix/"},
"relative/path/to/custdata-1",
"relative/path/custdata-2",
...
"relative/path/custdata-N"
]
This JSON is equivalent to the following S3Uri list:
s3://customer_bucket/some/prefix/relative/path/to/custdata-1
s3://customer_bucket/some/prefix/relative/path/custdata-2
...
s3://customer_bucket/some/prefix/relative/path/custdata-N
The complete set of S3Uri in this manifest is the input data for the channel for this data source. The object that each S3Uri points to must be readable by the IAM role that SageMaker uses to perform tasks on your behalf.
Your input bucket must be located in same Amazon Web Services region as your training job.
', 'S3StorageConfig$S3Uri' => 'The S3 URI, or location in Amazon S3, of OfflineStore.
S3 URIs have a format similar to the following: s3://example-bucket/prefix/.
The S3 path where offline records are written.
', 'SharingSettings$S3OutputPath' => 'When NotebookOutputOption is Allowed, the Amazon S3 bucket used to store the shared notebook snapshots.
A URL to the Amazon S3 data source containing selected features from the input data source to run an Autopilot job V2. You can input FeatureAttributeNames (optional) in JSON format as shown below:
{ "FeatureAttributeNames":["col1", "col2", ...] }.
You can also specify the data type of the feature (optional) in the format shown below:
{ "FeatureDataTypes":{"col1":"numeric", "col2":"categorical" ... } }
These column keys may not include the target column.
In ensembling mode, Autopilot only supports the following data types: numeric, categorical, text, and datetime. In HPO mode, Autopilot can support numeric, categorical, text, datetime, and sequence.
If only FeatureDataTypes is provided, the column keys (col1, col2,..) should be a subset of the column names in the input data.
If both FeatureDataTypes and FeatureAttributeNames are provided, then the column keys should be a subset of the column names provided in FeatureAttributeNames.
The key name FeatureAttributeNames is fixed. The values listed in ["col1", "col2", ...] are case sensitive and should be a list of strings containing unique values that are a subset of the column names in the input data. The list of columns provided must not include the target column.
Path to Amazon S3 storage location for TensorBoard output.
', 'TimeSeriesForecastingJobConfig$FeatureSpecificationS3Uri' => 'A URL to the Amazon S3 data source containing additional selected features that complement the target, itemID, timestamp, and grouped columns set in TimeSeriesConfig. When not provided, the AutoML job V2 includes all the columns from the original dataset that are not already declared in TimeSeriesConfig. If provided, the AutoML job V2 only considers these additional columns as a complement to the ones declared in TimeSeriesConfig.
You can input FeatureAttributeNames (optional) in JSON format as shown below:
{ "FeatureAttributeNames":["col1", "col2", ...] }.
You can also specify the data type of the feature (optional) in the format shown below:
{ "FeatureDataTypes":{"col1":"numeric", "col2":"categorical" ... } }
Autopilot supports the following data types: numeric, categorical, text, and datetime.
These column keys must not include any column set in TimeSeriesConfig.
The Amazon S3 path where you want Amazon SageMaker to store the results of the transform job. For example, s3://bucket-name/key-name-prefix.
For every S3 object used as input for the transform job, batch transform stores the transformed data with an .out suffix in a corresponding subfolder in the location in the output prefix. For example, for the input data stored at s3://bucket-name/input-name-prefix/dataset01/data.csv, batch transform stores the transformed data at s3://bucket-name/output-name-prefix/input-name-prefix/data.csv.out. Batch transform doesn\'t upload partially processed objects. For an input S3 object that contains multiple records, it creates an .out file only if the transform job succeeds on the entire file. When the input contains multiple S3 objects, the batch transform job processes the listed S3 objects and uploads only the output for successfully processed objects. If any object fails in the transform job batch transform marks the job as failed to prompt investigation.
Depending on the value specified for the S3DataType, identifies either a key name prefix or a manifest. For example:
A key name prefix might look like this: s3://bucketname/exampleprefix.
A manifest might look like this: s3://bucketname/example.manifest
The manifest is an S3 object which is a JSON file with the following format:
[ {"prefix": "s3://customer_bucket/some/prefix/"},
"relative/path/to/custdata-1",
"relative/path/custdata-2",
...
"relative/path/custdata-N"
]
The preceding JSON matches the following S3Uris:
s3://customer_bucket/some/prefix/relative/path/to/custdata-1
s3://customer_bucket/some/prefix/relative/path/custdata-2
...
s3://customer_bucket/some/prefix/relative/path/custdata-N
The complete set of S3Uris in this manifest constitutes the input data for the channel for this datasource. The object that each S3Uris points to must be readable by the IAM role that Amazon SageMaker uses to perform tasks on your behalf.
The Amazon S3 bucket location of the UI template, or worker task template. This is the template used to render the worker UI and tools for labeling job tasks. For more information about the contents of a UI template, see Creating Your Custom Labeling Task Template.
', 'WorkspaceSettings$S3ArtifactPath' => 'The Amazon S3 bucket used to store artifacts generated by Canvas. Updating the Amazon S3 location impacts existing configuration settings, and Canvas users no longer have access to their artifacts. Canvas users must log out and log back in to apply the new location.
', ], ], 'SageMakerImageVersionAlias' => [ 'base' => NULL, 'refs' => [ 'DeleteImageVersionRequest$Alias' => 'The alias of the image to delete.
', 'DescribeImageVersionRequest$Alias' => 'The alias of the image version.
', 'ListAliasesRequest$Alias' => 'The alias of the image version.
', 'SageMakerImageVersionAliases$member' => NULL, 'UpdateImageVersionRequest$Alias' => 'The alias of the image version.
', ], ], 'SageMakerImageVersionAliases' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$Aliases' => 'A list of aliases created with the image version.
', 'ListAliasesResponse$SageMakerImageVersionAliases' => 'A list of SageMaker image version aliases.
', 'UpdateImageVersionRequest$AliasesToAdd' => 'A list of aliases to add.
', 'UpdateImageVersionRequest$AliasesToDelete' => 'A list of aliases to delete.
', ], ], 'SagemakerServicecatalogStatus' => [ 'base' => NULL, 'refs' => [ 'GetSagemakerServicecatalogPortfolioStatusOutput$Status' => 'Whether Service Catalog is enabled or disabled in SageMaker.
', ], ], 'SampleWeightAttributeName' => [ 'base' => NULL, 'refs' => [ 'AutoMLChannel$SampleWeightAttributeName' => 'If specified, this column name indicates which column of the dataset should be treated as sample weights for use by the objective metric during the training, evaluation, and the selection of the best model. This column is not considered as a predictive feature. For more information on Autopilot metrics, see Metrics and validation.
Sample weights should be numeric, non-negative, with larger values indicating which rows are more important than others. Data points that have invalid or no weight value are excluded.
Support for sample weights is available in Ensembling mode only.
', 'TabularJobConfig$SampleWeightAttributeName' => 'If specified, this column name indicates which column of the dataset should be treated as sample weights for use by the objective metric during the training, evaluation, and the selection of the best model. This column is not considered as a predictive feature. For more information on Autopilot metrics, see Metrics and validation.
Sample weights should be numeric, non-negative, with larger values indicating which rows are more important than others. Data points that have invalid or no weight value are excluded.
Support for sample weights is available in Ensembling mode only.
', ], ], 'SamplingPercentage' => [ 'base' => NULL, 'refs' => [ 'DataCaptureConfig$InitialSamplingPercentage' => 'The percentage of requests SageMaker will capture. A lower value is recommended for Endpoints with high traffic.
', 'DataCaptureConfigSummary$CurrentSamplingPercentage' => 'The percentage of requests being captured by your Endpoint.
', ], ], 'ScalingPolicies' => [ 'base' => NULL, 'refs' => [ 'DynamicScalingConfiguration$ScalingPolicies' => 'An object of the scaling policies for each metric.
', ], ], 'ScalingPolicy' => [ 'base' => 'An object containing a recommended scaling policy.
', 'refs' => [ 'ScalingPolicies$member' => NULL, ], ], 'ScalingPolicyMetric' => [ 'base' => 'The metric for a scaling policy.
', 'refs' => [ 'GetScalingConfigurationRecommendationResponse$Metric' => 'An object with a list of metrics that were benchmarked during the previously completed Inference Recommender job.
', ], ], 'ScalingPolicyObjective' => [ 'base' => 'An object where you specify the anticipated traffic pattern for an endpoint.
', 'refs' => [ 'GetScalingConfigurationRecommendationRequest$ScalingPolicyObjective' => 'An object where you specify the anticipated traffic pattern for an endpoint.
', 'GetScalingConfigurationRecommendationResponse$ScalingPolicyObjective' => 'An object representing the anticipated traffic pattern for an endpoint that you specified in the request.
', ], ], 'ScheduleConfig' => [ 'base' => 'Configuration details about the monitoring schedule.
', 'refs' => [ 'MonitoringScheduleConfig$ScheduleConfig' => 'Configures the monitoring schedule.
', ], ], 'ScheduleExpression' => [ 'base' => NULL, 'refs' => [ 'ScheduleConfig$ScheduleExpression' => 'A cron expression that describes details about the monitoring schedule.
The supported cron expressions are:
If you want to set the job to start every hour, use the following:
Hourly: cron(0 * ? * * *)
If you want to start the job daily:
cron(0 [00-23] ? * * *)
If you want to run the job one time, immediately, use the following keyword:
NOW
For example, the following are valid cron expressions:
Daily at noon UTC: cron(0 12 ? * * *)
Daily at midnight UTC: cron(0 0 ? * * *)
To support running every 6, 12 hours, the following are also supported:
cron(0 [00-23]/[01-24] ? * * *)
For example, the following are valid cron expressions:
Every 12 hours, starting at 5pm UTC: cron(0 17/12 ? * * *)
Every two hours starting at midnight: cron(0 0/2 ? * * *)
Even though the cron expression is set to start at 5PM UTC, note that there could be a delay of 0-20 minutes from the actual requested time to run the execution.
We recommend that if you would like a daily schedule, you do not provide this parameter. Amazon SageMaker will pick a time for running every day.
You can also specify the keyword NOW to run the monitoring job immediately, one time, without recurring.
The status of an monitoring job.
', 'ListMonitoringSchedulesRequest$StatusEquals' => 'A filter that returns only monitoring schedules modified before a specified time.
', 'ModelDashboardMonitoringSchedule$MonitoringScheduleStatus' => 'The status of the monitoring schedule.
', 'MonitoringSchedule$MonitoringScheduleStatus' => 'The status of the monitoring schedule. This can be one of the following values.
PENDING - The schedule is pending being created.
FAILED - The schedule failed.
SCHEDULED - The schedule was successfully created.
STOPPED - The schedule was stopped.
The status of the monitoring schedule.
', ], ], 'SearchExpression' => [ 'base' => 'A multi-expression that searches for the specified resource or resources in a search. All resource objects that satisfy the expression\'s condition are included in the search results. You must specify at least one subexpression, filter, or nested filter. A SearchExpression can contain up to twenty elements.
A SearchExpression contains the following components:
A list of Filter objects. Each filter defines a simple Boolean expression comprised of a resource property name, Boolean operator, and value.
A list of NestedFilter objects. Each nested filter defines a list of Boolean expressions using a list of resource properties. A nested filter is satisfied if a single object in the list satisfies all Boolean expressions.
A list of SearchExpression objects. A search expression object can be nested in a list of search expression objects.
A Boolean operator: And or Or.
A Boolean conditional statement. Resources must satisfy this condition to be included in search results. You must provide at least one subexpression, filter, or nested filter. The maximum number of recursive SubExpressions, NestedFilters, and Filters that can be included in a SearchExpression object is 50.
A list of search expression objects.
', ], ], 'SearchRecord' => [ 'base' => 'A single resource returned as part of the Search API response.
', 'refs' => [ 'SearchResultsList$member' => NULL, ], ], 'SearchRequest' => [ 'base' => NULL, 'refs' => [], ], 'SearchResponse' => [ 'base' => NULL, 'refs' => [], ], 'SearchResultsList' => [ 'base' => NULL, 'refs' => [ 'SearchResponse$Results' => 'A list of SearchRecord objects.
How SearchResults are ordered. Valid values are Ascending or Descending. The default is Descending.
Provides detailed information about the state of the training job. For detailed information on the secondary status of the training job, see StatusMessage under SecondaryStatusTransition.
SageMaker provides primary statuses and secondary statuses that apply to each of them:
Starting - Starting the training job.
Downloading - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.
Training - Training is in progress.
Interrupted - The job stopped because the managed spot training instances were interrupted.
Uploading - Training is complete and the model artifacts are being uploaded to the S3 location.
Completed - The training job has completed.
Failed - The training job has failed. The reason for the failure is returned in the FailureReason field of DescribeTrainingJobResponse.
MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.
MaxWaitTimeExceeded - The job stopped because it exceeded the maximum allowed wait time.
Stopped - The training job has stopped.
Stopping - Stopping the training job.
Valid values for SecondaryStatus are subject to change.
We no longer support the following secondary statuses:
LaunchingMLInstances
PreparingTraining
DownloadingTrainingImage
Contains a secondary status information from a training job.
Status might be one of the following secondary statuses:
Starting - Starting the training job.
Downloading - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.
Training - Training is in progress.
Uploading - Training is complete and the model artifacts are being uploaded to the S3 location.
Completed - The training job has completed.
Failed - The training job has failed. The reason for the failure is returned in the FailureReason field of DescribeTrainingJobResponse.
MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.
Stopped - The training job has stopped.
Stopping - Stopping the training job.
We no longer support the following secondary statuses:
LaunchingMLInstances
PreparingTrainingStack
DownloadingTrainingImage
Provides detailed information about the state of the training job. For detailed information about the secondary status of the training job, see StatusMessage under SecondaryStatusTransition.
SageMaker provides primary statuses and secondary statuses that apply to each of them:
Starting - Starting the training job.
Downloading - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.
Training - Training is in progress.
Uploading - Training is complete and the model artifacts are being uploaded to the S3 location.
Completed - The training job has completed.
Failed - The training job has failed. The reason for the failure is returned in the FailureReason field of DescribeTrainingJobResponse.
MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.
Stopped - The training job has stopped.
Stopping - Stopping the training job.
Valid values for SecondaryStatus are subject to change.
We no longer support the following secondary statuses:
LaunchingMLInstances
PreparingTrainingStack
DownloadingTrainingImage
An array element of SecondaryStatusTransitions for DescribeTrainingJob. It provides additional details about a status that the training job has transitioned through. A training job can be in one of several states, for example, starting, downloading, training, or uploading. Within each state, there are a number of intermediate states. For example, within the starting state, SageMaker could be starting the training job or launching the ML instances. These transitional states are referred to as the job\'s secondary status.
A history of all of the secondary statuses that the training job has transitioned through.
', 'TrainingJob$SecondaryStatusTransitions' => 'A history of all of the secondary statuses that the training job has transitioned through.
', ], ], 'SecretArn' => [ 'base' => NULL, 'refs' => [ 'GitConfig$SecretArn' => 'The Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the git repository. The secret must have a staging label of AWSCURRENT and must be in the following format:
{"username": UserName, "password": Password}
The Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the git repository. The secret must have a staging label of AWSCURRENT and must be in the following format:
{"username": UserName, "password": Password}
The ARN of an Amazon Web Services Secrets Manager secret that stores the credentials from your identity provider, such as the client ID and secret, authorization URL, and token URL.
', ], ], 'SecurityGroupId' => [ 'base' => NULL, 'refs' => [ 'DescribeDomainResponse$SecurityGroupIdForDomainBoundary' => 'The ID of the security group that authorizes traffic between the RSessionGateway apps and the RStudioServerPro app.
The VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be for the same VPC as specified in the subnet.
', 'DefaultSpaceSettings$SecurityGroups' => 'The security group IDs for the Amazon Virtual Private Cloud that the space uses for communication.
', 'DescribeNotebookInstanceOutput$SecurityGroups' => 'The IDs of the VPC security groups.
', 'UserSettings$SecurityGroups' => 'The security groups for the Amazon Virtual Private Cloud (VPC) that Studio uses for communication.
Optional when the CreateDomain.AppNetworkAccessType parameter is set to PublicInternetOnly.
Required when the CreateDomain.AppNetworkAccessType parameter is set to VpcOnly, unless specified as part of the DefaultUserSettings for the domain.
Amazon SageMaker adds a security group to allow NFS traffic from SageMaker Studio. Therefore, the number of security groups that you can specify is one less than the maximum number shown.
', ], ], 'Seed' => [ 'base' => NULL, 'refs' => [ 'ShuffleConfig$Seed' => 'Determines the shuffling order in ShuffleConfig value.
A step selected to run in selective execution mode.
', 'refs' => [ 'SelectedStepList$member' => NULL, ], ], 'SelectedStepList' => [ 'base' => NULL, 'refs' => [ 'SelectiveExecutionConfig$SelectedSteps' => 'A list of pipeline steps to run. All step(s) in all path(s) between two selected steps should be included.
', ], ], 'SelectiveExecutionConfig' => [ 'base' => 'The selective execution configuration applied to the pipeline run.
', 'refs' => [ 'DescribePipelineExecutionResponse$SelectiveExecutionConfig' => 'The selective execution configuration applied to the pipeline run.
', 'PipelineExecution$SelectiveExecutionConfig' => 'The selective execution configuration applied to the pipeline run.
', 'StartPipelineExecutionRequest$SelectiveExecutionConfig' => 'The selective execution configuration applied to the pipeline run.
', ], ], 'SelectiveExecutionResult' => [ 'base' => 'The ARN from an execution of the current pipeline.
', 'refs' => [ 'PipelineExecutionStep$SelectiveExecutionResult' => 'The ARN from an execution of the current pipeline from which results are reused for this step.
', ], ], 'SendPipelineExecutionStepFailureRequest' => [ 'base' => NULL, 'refs' => [], ], 'SendPipelineExecutionStepFailureResponse' => [ 'base' => NULL, 'refs' => [], ], 'SendPipelineExecutionStepSuccessRequest' => [ 'base' => NULL, 'refs' => [], ], 'SendPipelineExecutionStepSuccessResponse' => [ 'base' => NULL, 'refs' => [], ], 'ServerlessMaxConcurrency' => [ 'base' => NULL, 'refs' => [ 'ProductionVariantServerlessConfig$MaxConcurrency' => 'The maximum number of concurrent invocations your serverless endpoint can process.
', 'ProductionVariantServerlessUpdateConfig$MaxConcurrency' => 'The updated maximum number of concurrent invocations your serverless endpoint can process.
', ], ], 'ServerlessMemorySizeInMB' => [ 'base' => NULL, 'refs' => [ 'ProductionVariantServerlessConfig$MemorySizeInMB' => 'The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.
', ], ], 'ServerlessProvisionedConcurrency' => [ 'base' => NULL, 'refs' => [ 'ProductionVariantServerlessConfig$ProvisionedConcurrency' => 'The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency.
This field is not supported for serverless endpoint recommendations for Inference Recommender jobs. For more information about creating an Inference Recommender job, see CreateInferenceRecommendationsJobs.
The updated amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency.
The ID of the provisioned product.
', 'ServiceCatalogProvisioningDetails$ProductId' => 'The ID of the product to provision.
', 'ServiceCatalogProvisioningDetails$ProvisioningArtifactId' => 'The ID of the provisioning artifact.
', 'ServiceCatalogProvisioningDetails$PathId' => 'The path identifier of the product. This value is optional if the product has a default path, and required if the product has more than one path.
', 'ServiceCatalogProvisioningUpdateDetails$ProvisioningArtifactId' => 'The ID of the provisioning artifact.
', ], ], 'ServiceCatalogProvisionedProductDetails' => [ 'base' => 'Details of a provisioned service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog.
', 'refs' => [ 'DescribeProjectOutput$ServiceCatalogProvisionedProductDetails' => 'Information about a provisioned service catalog product.
', 'Project$ServiceCatalogProvisionedProductDetails' => NULL, ], ], 'ServiceCatalogProvisioningDetails' => [ 'base' => 'Details that you specify to provision a service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog.
', 'refs' => [ 'CreateProjectInput$ServiceCatalogProvisioningDetails' => 'The product ID and provisioning artifact ID to provision a service catalog. The provisioning artifact ID will default to the latest provisioning artifact ID of the product, if you don\'t provide the provisioning artifact ID. For more information, see What is Amazon Web Services Service Catalog.
', 'DescribeProjectOutput$ServiceCatalogProvisioningDetails' => 'Information used to provision a service catalog product. For information, see What is Amazon Web Services Service Catalog.
', 'Project$ServiceCatalogProvisioningDetails' => NULL, ], ], 'ServiceCatalogProvisioningUpdateDetails' => [ 'base' => 'Details that you specify to provision a service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog.
', 'refs' => [ 'UpdateProjectInput$ServiceCatalogProvisioningUpdateDetails' => 'The product ID and provisioning artifact ID to provision a service catalog. The provisioning artifact ID will default to the latest provisioning artifact ID of the product, if you don\'t provide the provisioning artifact ID. For more information, see What is Amazon Web Services Service Catalog.
', ], ], 'SessionExpirationDurationInSeconds' => [ 'base' => NULL, 'refs' => [ 'CreatePresignedDomainUrlRequest$SessionExpirationDurationInSeconds' => 'The session expiration duration in seconds. This value defaults to 43200.
', 'CreatePresignedNotebookInstanceUrlInput$SessionExpirationDurationInSeconds' => 'The duration of the session, in seconds. The default is 12 hours.
', ], ], 'ShadowModeConfig' => [ 'base' => ' The configuration of ShadowMode inference experiment type, which specifies a production variant to take all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant it also specifies the percentage of requests that Amazon SageMaker replicates.
The configuration of ShadowMode inference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates.
The configuration of ShadowMode inference experiment type, which shows the production variant that takes all the inference requests, and the shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant it also shows the percentage of requests that Amazon SageMaker replicates.
The configuration of ShadowMode inference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates.
The name and sampling percentage of a shadow variant.
', 'refs' => [ 'ShadowModelVariantConfigList$member' => NULL, ], ], 'ShadowModelVariantConfigList' => [ 'base' => NULL, 'refs' => [ 'ShadowModeConfig$ShadowModelVariants' => 'List of shadow variant configurations.
', ], ], 'SharingSettings' => [ 'base' => 'Specifies options for sharing SageMaker Studio notebooks. These settings are specified as part of DefaultUserSettings when the CreateDomain API is called, and as part of UserSettings when the CreateUserProfile API is called. When SharingSettings is not specified, notebook sharing isn\'t allowed.
Specifies options for sharing SageMaker Studio notebooks.
', ], ], 'ShuffleConfig' => [ 'base' => 'A configuration for a shuffle option for input data in a channel. If you use S3Prefix for S3DataType, the results of the S3 key prefix matches are shuffled. If you use ManifestFile, the order of the S3 object references in the ManifestFile is shuffled. If you use AugmentedManifestFile, the order of the JSON lines in the AugmentedManifestFile is shuffled. The shuffling order is determined using the Seed value.
For Pipe input mode, when ShuffleConfig is specified shuffling is done at the start of every epoch. With large datasets, this ensures that the order of the training data is different for each epoch, and it helps reduce bias and possible overfitting. In a multi-node training job when ShuffleConfig is combined with S3DataDistributionType of ShardedByS3Key, the data is shuffled across nodes so that the content sent to a particular node on the first epoch might be sent to a different node on the second epoch.
A configuration for a shuffle option for input data in a channel. If you use S3Prefix for S3DataType, this shuffles the results of the S3 key prefix matches. If you use ManifestFile, the order of the S3 object references in the ManifestFile is shuffled. If you use AugmentedManifestFile, the order of the JSON lines in the AugmentedManifestFile is shuffled. The shuffling order is determined using the Seed value.
For Pipe input mode, shuffling is done at the start of every epoch. With large datasets this ensures that the order of the training data is different for each epoch, it helps reduce bias and possible overfitting. In a multi-node training job when ShuffleConfig is combined with S3DataDistributionType of ShardedByS3Key, the data is shuffled across nodes so that the content sent to a particular node on the first epoch might be sent to a different node on the second epoch.
The ARN of the associated Amazon Web Services Single Sign-On application for this Domain.
', ], ], 'SingleSignOnUserIdentifier' => [ 'base' => NULL, 'refs' => [ 'CreateUserProfileRequest$SingleSignOnUserIdentifier' => 'A specifier for the type of value specified in SingleSignOnUserValue. Currently, the only supported value is "UserName". If the Domain\'s AuthMode is IAM Identity Center, this field is required. If the Domain\'s AuthMode is not IAM Identity Center, this field cannot be specified.
', 'DescribeUserProfileResponse$SingleSignOnUserIdentifier' => 'The IAM Identity Center user identifier.
', ], ], 'SkipModelValidation' => [ 'base' => NULL, 'refs' => [ 'CreateModelPackageInput$SkipModelValidation' => 'Indicates if you want to skip model validation.
', 'DescribeModelPackageOutput$SkipModelValidation' => 'Indicates if you want to skip model validation.
', 'ModelPackage$SkipModelValidation' => 'Indicates if you want to skip model validation.
', ], ], 'SnsTopicArn' => [ 'base' => NULL, 'refs' => [ 'AsyncInferenceNotificationConfig$SuccessTopic' => 'Amazon SNS topic to post a notification to when inference completes successfully. If no topic is provided, no notification is sent on success.
', 'AsyncInferenceNotificationConfig$ErrorTopic' => 'Amazon SNS topic to post a notification to when inference fails. If no topic is provided, no notification is sent on failure.
', 'LabelingJobOutputConfig$SnsTopicArn' => 'An Amazon Simple Notification Service (Amazon SNS) output topic ARN. Provide a SnsTopicArn if you want to do real time chaining to another streaming job and receive an Amazon SNS notifications each time a data object is submitted by a worker.
If you provide an SnsTopicArn in OutputConfig, when workers complete labeling tasks, Ground Truth will send labeling task output data to the SNS output topic you specify here.
To learn more, see Receive Output Data from a Streaming Labeling Job.
', 'LabelingJobSnsDataSource$SnsTopicArn' => 'The Amazon SNS input topic Amazon Resource Name (ARN). Specify the ARN of the input topic you will use to send new data objects to a streaming labeling job.
', ], ], 'SortActionsBy' => [ 'base' => NULL, 'refs' => [ 'ListActionsRequest$SortBy' => 'The property used to sort results. The default value is CreationTime.
The property used to sort results. The default value is CreationTime.
The property used to sort results. The default value is CreationTime.
The field to sort results by. The default is CreationTime.
The field to sort results by. The default is CreationTime.
The field to sort results by. The default is CreationTime.
The field to sort results by. The default is CreationTime.
The property used to sort results. The default value is CreationTime.
The property used to sort results. The default value is CreationTime.
The column by which to sort the listed inference experiments.
', ], ], 'SortLineageGroupsBy' => [ 'base' => NULL, 'refs' => [ 'ListLineageGroupsRequest$SortBy' => 'The parameter by which to sort the results. The default is CreationTime.
The sort order. The default value is Descending.
The sort order for the results. The default is Ascending.
The sort order. The default value is Descending.
The sort order for the results. The default is Ascending.
', 'ListArtifactsRequest$SortOrder' => 'The sort order. The default value is Descending.
The sort order. The default value is Descending.
The sort order for results. The default is Ascending.
The sort order. The default value is Descending.
Whether to sort the results in Ascending or Descending order. The default is Descending.
What direction to sort in.
', 'ListEdgeDeploymentPlansRequest$SortOrder' => 'The direction of the sorting (ascending or descending).
', 'ListEdgePackagingJobsRequest$SortOrder' => 'What direction to sort by.
', 'ListExperimentsRequest$SortOrder' => 'The sort order. The default value is Descending.
An optional value that specifies whether you want the results sorted in Ascending or Descending order.
Sort hub content versions by ascending or descending order.
', 'ListHubContentsRequest$SortOrder' => 'Sort hubs by ascending or descending order.
', 'ListHubsRequest$SortOrder' => 'Sort hubs by ascending or descending order.
', 'ListHumanTaskUisRequest$SortOrder' => 'An optional value that specifies whether you want the results sorted in Ascending or Descending order.
The sort order for results. The default is Ascending.
The direction of sorting (ascending or descending).
', 'ListInferenceRecommendationsJobsRequest$SortOrder' => 'The sort order for the results.
', 'ListLabelingJobsForWorkteamRequest$SortOrder' => 'The sort order for results. The default is Ascending.
The sort order for results. The default is Ascending.
The sort order for the results. The default is Ascending.
Whether to sort the results in Ascending or Descending order. The default is Descending.
Whether to sort the results in Ascending or Descending order. The default is Descending.
The sort order for results. The default is Ascending.
The sort order for the results. The default is Ascending.
Whether to sort the results in Ascending or Descending order. The default is Descending.
The sort order, whether Ascending or Descending, of the alert history. The default is Descending.
Whether to sort the results in Ascending or Descending order. The default is Descending.
Whether to sort the results in Ascending or Descending order. The default is Descending.
The field by which to sort results. The default is CreatedTime.
The sort order for results.
', 'ListPipelinesRequest$SortOrder' => 'The sort order for results.
', 'ListProcessingJobsRequest$SortOrder' => 'The sort order for results. The default is Ascending.
The sort order for the results. The default is Ascending.
The sort order. The default value is Descending.
', 'ListTrainingJobsForHyperParameterTuningJobRequest$SortOrder' => 'The sort order for results. The default is Ascending.
The sort order for results. The default is Ascending.
The sort order for results. The default is Descending.
The sort order. The default value is Descending.
The sort order. The default value is Descending.
The sort order for the results. The default is Ascending.
', 'ListWorkforcesRequest$SortOrder' => 'Sort workforces in ascending or descending order.
', 'ListWorkteamsRequest$SortOrder' => 'The sort order for results. The default is Ascending.
The field by which to sort results. The default is CreatedTime.
The field by which to sort results. The default is CreatedTime.
The property used to sort results. The default value is CreationTime.
The property used to sort results. The default value is CreationTime.
Specifies an algorithm that was used to create the model package. The algorithm must be either an algorithm resource in your SageMaker account or an algorithm in Amazon Web Services Marketplace that you are subscribed to.
', 'refs' => [ 'SourceAlgorithmList$member' => NULL, ], ], 'SourceAlgorithmList' => [ 'base' => NULL, 'refs' => [ 'SourceAlgorithmSpecification$SourceAlgorithms' => 'A list of the algorithms that were used to create a model package.
', ], ], 'SourceAlgorithmSpecification' => [ 'base' => 'A list of algorithms that were used to create a model package.
', 'refs' => [ 'CreateModelPackageInput$SourceAlgorithmSpecification' => 'Details about the algorithm that was used to create the model package.
', 'DescribeModelPackageOutput$SourceAlgorithmSpecification' => 'Details about the algorithm that was used to create the model package.
', 'ModelPackage$SourceAlgorithmSpecification' => 'A list of algorithms that were used to create a model package.
', ], ], 'SourceIpConfig' => [ 'base' => 'A list of IP address ranges (CIDRs). Used to create an allow list of IP addresses for a private workforce. Workers will only be able to login to their worker portal from an IP address within this range. By default, a workforce isn\'t restricted to specific IP addresses.
', 'refs' => [ 'CreateWorkforceRequest$SourceIpConfig' => NULL, 'UpdateWorkforceRequest$SourceIpConfig' => 'A list of one to ten worker IP address ranges (CIDRs) that can be used to access tasks assigned to this workforce.
Maximum: Ten CIDR values
', 'Workforce$SourceIpConfig' => 'A list of one to ten IP address ranges (CIDRs) to be added to the workforce allow list. By default, a workforce isn\'t restricted to specific IP addresses.
', ], ], 'SourceType' => [ 'base' => NULL, 'refs' => [ 'ExperimentSource$SourceType' => 'The source type.
', 'TrialComponentSource$SourceType' => 'The source job type.
', 'TrialSource$SourceType' => 'The source job type.
', ], ], 'SourceUri' => [ 'base' => NULL, 'refs' => [ 'ListActionsRequest$SourceUri' => 'A filter that returns only actions with the specified source URI.
', 'ListArtifactsRequest$SourceUri' => 'A filter that returns only artifacts with the specified source URI.
', 'ListContextsRequest$SourceUri' => 'A filter that returns only contexts with the specified source URI.
', ], ], 'SpaceArn' => [ 'base' => NULL, 'refs' => [ 'CreateSpaceResponse$SpaceArn' => 'The space\'s Amazon Resource Name (ARN).
', 'DescribeSpaceResponse$SpaceArn' => 'The space\'s Amazon Resource Name (ARN).
', 'UpdateSpaceResponse$SpaceArn' => 'The space\'s Amazon Resource Name (ARN).
', ], ], 'SpaceDetails' => [ 'base' => 'The space\'s details.
', 'refs' => [ 'SpaceList$member' => NULL, ], ], 'SpaceList' => [ 'base' => NULL, 'refs' => [ 'ListSpacesResponse$Spaces' => 'The list of spaces.
', ], ], 'SpaceName' => [ 'base' => NULL, 'refs' => [ 'AppDetails$SpaceName' => 'The name of the space.
', 'CreateAppRequest$SpaceName' => 'The name of the space. If this value is not set, then UserProfileName must be set.
The name of the space.
', 'CreateSpaceRequest$SpaceName' => 'The name of the space.
', 'DeleteAppRequest$SpaceName' => 'The name of the space. If this value is not set, then UserProfileName must be set.
The name of the space.
', 'DescribeAppRequest$SpaceName' => 'The name of the space.
', 'DescribeAppResponse$SpaceName' => 'The name of the space. If this value is not set, then UserProfileName must be set.
The name of the space.
', 'DescribeSpaceResponse$SpaceName' => 'The name of the space.
', 'ListAppsRequest$SpaceNameEquals' => 'A parameter to search by space name. If UserProfileNameEquals is set, then this value cannot be set.
A parameter by which to filter the results.
', 'SpaceDetails$SpaceName' => 'The name of the space.
', 'UpdateSpaceRequest$SpaceName' => 'The name of the space.
', ], ], 'SpaceSettings' => [ 'base' => 'A collection of space settings.
', 'refs' => [ 'CreateSpaceRequest$SpaceSettings' => 'A collection of space settings.
', 'DescribeSpaceResponse$SpaceSettings' => 'A collection of space settings.
', 'UpdateSpaceRequest$SpaceSettings' => 'A collection of space settings.
', ], ], 'SpaceSortKey' => [ 'base' => NULL, 'refs' => [ 'ListSpacesRequest$SortBy' => 'The parameter by which to sort the results. The default is CreationTime.
The status.
', 'SpaceDetails$Status' => 'The status.
', ], ], 'SpawnRate' => [ 'base' => NULL, 'refs' => [ 'Phase$SpawnRate' => 'Specified how many new users to spawn in a minute.
', ], ], 'SplitType' => [ 'base' => NULL, 'refs' => [ 'TransformInput$SplitType' => 'The method to use to split the transform job\'s data files into smaller batches. Splitting is necessary when the total size of each object is too large to fit in a single request. You can also use data splitting to improve performance by processing multiple concurrent mini-batches. The default value for SplitType is None, which indicates that input data files are not split, and request payloads contain the entire contents of an input object. Set the value of this parameter to Line to split records on a newline character boundary. SplitType also supports a number of record-oriented binary data formats. Currently, the supported record formats are:
RecordIO
TFRecord
When splitting is enabled, the size of a mini-batch depends on the values of the BatchStrategy and MaxPayloadInMB parameters. When the value of BatchStrategy is MultiRecord, Amazon SageMaker sends the maximum number of records in each request, up to the MaxPayloadInMB limit. If the value of BatchStrategy is SingleRecord, Amazon SageMaker sends individual records in each request.
Some data formats represent a record as a binary payload wrapped with extra padding bytes. When splitting is applied to a binary data format, padding is removed if the value of BatchStrategy is set to SingleRecord. Padding is not removed if the value of BatchStrategy is set to MultiRecord.
For more information about RecordIO, see Create a Dataset Using RecordIO in the MXNet documentation. For more information about TFRecord, see Consuming TFRecord data in the TensorFlow documentation.
The general status of the current stage.
', ], ], 'Stairs' => [ 'base' => 'Defines the stairs traffic pattern for an Inference Recommender load test. This pattern type consists of multiple steps where the number of users increases at each step.
Specify either the stairs or phases traffic pattern.
', 'refs' => [ 'TrafficPattern$Stairs' => 'Defines the stairs traffic pattern.
', ], ], 'StartEdgeDeploymentStageRequest' => [ 'base' => NULL, 'refs' => [], ], 'StartInferenceExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'StartInferenceExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'StartMonitoringScheduleRequest' => [ 'base' => NULL, 'refs' => [], ], 'StartNotebookInstanceInput' => [ 'base' => NULL, 'refs' => [], ], 'StartPipelineExecutionRequest' => [ 'base' => NULL, 'refs' => [], ], 'StartPipelineExecutionResponse' => [ 'base' => NULL, 'refs' => [], ], 'Statistic' => [ 'base' => NULL, 'refs' => [ 'CustomizedMetricSpecification$Statistic' => 'The statistic of the customized metric.
', ], ], 'StatusDetails' => [ 'base' => NULL, 'refs' => [ 'DebugRuleEvaluationStatus$StatusDetails' => 'Details from the rule evaluation.
', 'ProfilerRuleEvaluationStatus$StatusDetails' => 'Details from the rule evaluation.
', ], ], 'StatusMessage' => [ 'base' => NULL, 'refs' => [ 'SecondaryStatusTransition$StatusMessage' => 'A detailed description of the progress within a secondary status.
SageMaker provides secondary statuses and status messages that apply to each of them:
Starting the training job.
Launching requested ML instances.
Insufficient capacity error from EC2 while launching instances, retrying!
Launched instance was unhealthy, replacing it!
Preparing the instances for training.
Downloading the training image.
Training image download completed. Training in progress.
Status messages are subject to change. Therefore, we recommend not including them in code that programmatically initiates actions. For examples, don\'t use status messages in if statements.
To have an overview of your training job\'s progress, view TrainingJobStatus and SecondaryStatus in DescribeTrainingJob, and StatusMessage together. For example, at the start of a training job, you might see the following:
TrainingJobStatus - InProgress
SecondaryStatus - Training
StatusMessage - Downloading the training image
The description of the step.
', ], ], 'StepDisplayName' => [ 'base' => NULL, 'refs' => [ 'PipelineExecutionStep$StepDisplayName' => 'The display name of the step.
', ], ], 'StepName' => [ 'base' => NULL, 'refs' => [ 'PipelineExecutionStep$StepName' => 'The name of the step that is executed.
', ], ], 'StepStatus' => [ 'base' => NULL, 'refs' => [ 'PipelineExecutionStep$StepStatus' => 'The status of the step execution.
', ], ], 'StopAutoMLJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopCompilationJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopEdgeDeploymentStageRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopEdgePackagingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopHyperParameterTuningJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopInferenceExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopInferenceExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'StopInferenceRecommendationsJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopLabelingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopMonitoringScheduleRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopNotebookInstanceInput' => [ 'base' => NULL, 'refs' => [], ], 'StopPipelineExecutionRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopPipelineExecutionResponse' => [ 'base' => NULL, 'refs' => [], ], 'StopProcessingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopTrainingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopTransformJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StoppingCondition' => [ 'base' => 'Specifies a limit to how long a model training job or model compilation job can run. It also specifies how long a managed spot training job has to complete. When the job reaches the time limit, SageMaker ends the training or compilation job. Use this API to cap model training costs.
To stop a training job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
The training algorithms provided by SageMaker automatically save the intermediate results of a model training job when possible. This attempt to save artifacts is only a best effort case as model might not be in a state from which it can be saved. For example, if training has just started, the model might not be ready to save. When saved, this intermediate data is a valid model artifact. You can use it to create a model with CreateModel.
The Neural Topic Model (NTM) currently does not support saving intermediate model artifacts. When training NTMs, make sure that the maximum runtime is sufficient for the training job to complete.
Specifies a limit to how long a model compilation job can run. When the job reaches the time limit, Amazon SageMaker ends the compilation job. Use this API to cap model training costs.
', 'CreateTrainingJobRequest$StoppingCondition' => 'Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
Specifies a limit to how long a model compilation job can run. When the job reaches the time limit, Amazon SageMaker ends the compilation job. Use this API to cap model training costs.
', 'DescribeTrainingJobResponse$StoppingCondition' => 'Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
Specifies a limit to how long a model hyperparameter training job can run. It also specifies how long a managed spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
', 'TrainingJob$StoppingCondition' => 'Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts.
', ], ], 'StorageType' => [ 'base' => NULL, 'refs' => [ 'OnlineStoreConfig$StorageType' => 'Option for different tiers of low latency storage for real-time data retrieval.
Standard: A managed low latency data store for feature groups.
InMemory: A managed data store for feature groups that supports very low latency retrieval.
if the overall status is Failed, the reason for the failure.
The attributes of the input data that are the input features.
', 'BatchTransformInput$InferenceAttribute' => 'The attribute of the input data that represents the ground truth label.
', 'BatchTransformInput$ProbabilityAttribute' => 'In a classification problem, the attribute that represents the class probability.
', 'CreateModelPackageInput$Domain' => 'The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.
', 'CreateModelPackageInput$Task' => 'The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification. The following tasks are supported by Inference Recommender: "IMAGE_CLASSIFICATION" | "OBJECT_DETECTION" | "TEXT_GENERATION" |"IMAGE_SEGMENTATION" | "FILL_MASK" | "CLASSIFICATION" | "REGRESSION" | "OTHER".
Specify "OTHER" if none of the tasks listed fit your use case.
', 'CustomizedMetricSpecification$MetricName' => 'The name of the customized metric.
', 'CustomizedMetricSpecification$Namespace' => 'The namespace of the customized metric.
', 'DescribeEdgePackagingJobResponse$EdgePackagingJobStatusMessage' => 'Returns a message describing the job status and error messages.
', 'DescribeEdgePackagingJobResponse$ModelSignature' => 'The signature document of files in the model artifact.
', 'DescribeModelPackageOutput$Domain' => 'The machine learning domain of the model package you specified. Common machine learning domains include computer vision and natural language processing.
', 'DescribeModelPackageOutput$Task' => 'The machine learning task you specified that your model package accomplishes. Common machine learning tasks include object detection and image classification.
', 'DescribeModelPackageOutput$SamplePayloadUrl' => 'The Amazon Simple Storage Service (Amazon S3) path where the sample payload are stored. This path points to a single gzip compressed tar archive (.tar.gz suffix).
', 'DeviceDeploymentSummary$DeviceDeploymentStatusMessage' => 'The detailed error message for the deployoment status result.
', 'EdgeDeploymentStatus$EdgeDeploymentStatusMessage' => 'A detailed message about deployment status in current stage.
', 'EdgeOutputConfig$PresetDeploymentConfig' => 'The configuration used to create deployment artifacts. Specify configuration options with a JSON string. The available configuration options for each type are:
ComponentName (optional) - Name of the GreenGrass V2 component. If not specified, the default name generated consists of "SagemakerEdgeManager" and the name of your SageMaker Edge Manager packaging job.
ComponentDescription (optional) - Description of the component.
ComponentVersion (optional) - The version of the component.
Amazon Web Services IoT Greengrass uses semantic versions for components. Semantic versions follow a major.minor.patch number system. For example, version 1.0.0 represents the first major release for a component. For more information, see the semantic version specification.
PlatformOS (optional) - The name of the operating system for the platform. Supported platforms include Windows and Linux.
PlatformArchitecture (optional) - The processor architecture for the platform.
Supported architectures Windows include: Windows32_x86, Windows64_x64.
Supported architectures for Linux include: Linux x86_64, Linux ARMV8.
Returns a message describing the status of the deployed resource.
', 'EndpointInput$FeaturesAttribute' => 'The attributes of the input data that are the input features.
', 'EndpointInput$InferenceAttribute' => 'The attribute of the input data that represents the ground truth label.
', 'EndpointInput$ProbabilityAttribute' => 'In a classification problem, the attribute that represents the class probability.
', 'EndpointOutputConfiguration$EndpointName' => 'The name of the endpoint made during a recommendation job.
', 'EndpointOutputConfiguration$VariantName' => 'The name of the production variant (deployed model) made during a recommendation job.
', 'EnvironmentParameter$Key' => 'The environment key suggested by the Amazon SageMaker Inference Recommender.
', 'EnvironmentParameter$ValueType' => 'The value type suggested by the Amazon SageMaker Inference Recommender.
', 'EnvironmentParameter$Value' => 'The value suggested by the Amazon SageMaker Inference Recommender.
', 'GetScalingConfigurationRecommendationRequest$RecommendationId' => 'The recommendation ID of a previously completed inference recommendation. This ID should come from one of the recommendations returned by the job specified in the InferenceRecommendationsJobName field.
Specify either this field or the EndpointName field.
The recommendation ID of a previously completed inference recommendation.
', 'IamIdentity$Arn' => 'The Amazon Resource Name (ARN) of the IAM identity.
', 'IamIdentity$PrincipalId' => 'The ID of the principal that assumes the IAM identity.
', 'IamIdentity$SourceIdentity' => 'The person or application which assumes the IAM identity.
', 'InferenceRecommendation$RecommendationId' => 'The recommendation ID which uniquely identifies each recommendation.
', 'ListProcessingJobsRequest$NameContains' => 'A string in the processing job name. This filter returns only processing jobs whose name contains the specified string.
', 'ModelCard$ModelId' => 'The unique name (ID) of the model.
', 'ModelCard$RiskRating' => 'The risk rating of the model. Different organizations might have different criteria for model card risk ratings. For more information, see Risk ratings.
', 'ModelCard$ModelPackageGroupName' => 'The model package group that contains the model package. Only relevant for model cards created for model packages in the Amazon SageMaker Model Registry.
', 'ModelDashboardModelCard$ModelId' => 'For models created in SageMaker, this is the model ARN. For models created outside of SageMaker, this is a user-customized string.
', 'ModelDashboardModelCard$RiskRating' => 'A model card\'s risk rating. Can be low, medium, or high.
', 'ModelMetadataSummary$Domain' => 'The machine learning domain of the model.
', 'ModelMetadataSummary$Framework' => 'The machine learning framework of the model.
', 'ModelMetadataSummary$Task' => 'The machine learning task of the model.
', 'ModelMetadataSummary$Model' => 'The name of the model.
', 'ModelMetadataSummary$FrameworkVersion' => 'The framework version of the model.
', 'ModelPackage$Domain' => 'The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.
', 'ModelPackage$Task' => 'The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification.
', 'ModelPackage$SamplePayloadUrl' => 'The Amazon Simple Storage Service path where the sample payload are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
', 'ModelPackageContainerDefinition$Framework' => 'The machine learning framework of the model package container image.
', 'ModelPackageContainerDefinition$NearestModelName' => 'The name of a pre-trained machine learning benchmarked by Amazon SageMaker Inference Recommender model that matches your model. You can find a list of benchmarked models by calling ListModelMetadata.
if the overall status is Failed, the reason for the failure.
The metric type. You can only apply SageMaker metric types to SageMaker endpoints.
', 'ProcessingInput$InputName' => 'The name for the processing job input.
', 'ProcessingOutput$OutputName' => 'The name for the processing job output.
', 'ProductListings$member' => NULL, 'RStudioServerProDomainSettings$RStudioConnectUrl' => 'A URL pointing to an RStudio Connect server.
', 'RStudioServerProDomainSettings$RStudioPackageManagerUrl' => 'A URL pointing to an RStudio Package Manager server.
', 'RStudioServerProDomainSettingsForUpdate$RStudioConnectUrl' => 'A URL pointing to an RStudio Connect server.
', 'RStudioServerProDomainSettingsForUpdate$RStudioPackageManagerUrl' => 'A URL pointing to an RStudio Package Manager server.
', 'RealTimeInferenceRecommendation$RecommendationId' => 'The recommendation ID which uniquely identifies each recommendation.
', 'RecommendationJobContainerConfig$Domain' => 'The machine learning domain of the model and its components.
Valid Values: COMPUTER_VISION | NATURAL_LANGUAGE_PROCESSING | MACHINE_LEARNING
The machine learning task that the model accomplishes.
Valid Values: IMAGE_CLASSIFICATION | OBJECT_DETECTION | TEXT_GENERATION | IMAGE_SEGMENTATION | FILL_MASK | CLASSIFICATION | REGRESSION | OTHER
The machine learning framework of the container image.
Valid Values: TENSORFLOW | PYTORCH | XGBOOST | SAGEMAKER-SCIKIT-LEARN
The framework version of the container image.
', 'RecommendationJobContainerConfig$NearestModelName' => 'The name of a pre-trained machine learning model benchmarked by Amazon SageMaker Inference Recommender that matches your model.
Valid Values: efficientnetb7 | unet | xgboost | faster-rcnn-resnet101 | nasnetlarge | vgg16 | inception-v3 | mask-rcnn | sagemaker-scikit-learn | densenet201-gluon | resnet18v2-gluon | xception | densenet201 | yolov4 | resnet152 | bert-base-cased | xceptionV1-keras | resnet50 | retinanet
The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
', 'RecommendationJobSupportedContentTypes$member' => NULL, 'RecommendationJobSupportedInstanceTypes$member' => NULL, 'RenderUiTemplateResponse$RenderedContent' => 'A Liquid template that renders the HTML for the worker UI.
', 'RenderingError$Code' => 'A unique identifier for a specific class of errors.
', 'RenderingError$Message' => 'A human-readable message describing the error.
', 'ScheduleConfig$DataAnalysisStartTime' => 'Sets the start time for a monitoring job window. Express this time as an offset to the times that you schedule your monitoring jobs to run. You schedule monitoring jobs with the ScheduleExpression parameter. Specify this offset in ISO 8601 duration format. For example, if you want to monitor the five hours of data in your dataset that precede the start of each monitoring job, you would specify: "-PT5H".
The start time that you specify must not precede the end time that you specify by more than 24 hours. You specify the end time with the DataAnalysisEndTime parameter.
If you set ScheduleExpression to NOW, this parameter is required.
Sets the end time for a monitoring job window. Express this time as an offset to the times that you schedule your monitoring jobs to run. You schedule monitoring jobs with the ScheduleExpression parameter. Specify this offset in ISO 8601 duration format. For example, if you want to end the window one hour before the start of each monitoring job, you would specify: "-PT1H".
The end time that you specify must not follow the start time that you specify by more than 24 hours. You specify the start time with the DataAnalysisStartTime parameter.
If you set ScheduleExpression to NOW, this parameter is required.
The name of the vendor in the Amazon Marketplace.
', 'SubscribedWorkteam$ListingId' => 'Marketplace product listing ID.
', 'UserContext$UserProfileArn' => 'The Amazon Resource Name (ARN) of the user\'s profile.
', 'UserContext$UserProfileName' => 'The name of the user\'s profile.
', 'UserContext$DomainId' => 'The domain associated with the user.
', 'Workforce$SubDomain' => 'The subdomain for your OIDC Identity Provider.
', 'Workteam$SubDomain' => 'The URI of the labeling job\'s user interface. Workers open this URI to start labeling your data objects.
', ], ], 'String1024' => [ 'base' => NULL, 'refs' => [ 'ClarifyCheckStepMetadata$BaselineUsedForDriftCheckConstraints' => 'The Amazon S3 URI of baseline constraints file to be used for the drift check.
', 'ClarifyCheckStepMetadata$CalculatedBaselineConstraints' => 'The Amazon S3 URI of the newly calculated baseline constraints file.
', 'ClarifyCheckStepMetadata$ViolationReport' => 'The Amazon S3 URI of the violation report if violations are detected.
', 'CreateDomainResponse$Url' => 'The URL to the created domain.
', 'DescribeDomainResponse$Url' => 'The domain\'s URL.
', 'DomainDetails$Url' => 'The domain\'s URL.
', 'EMRStepMetadata$LogFilePath' => 'The path to the log file where the cluster step\'s failure root cause is recorded.
', 'OutputParameter$Value' => 'The value of the output parameter.
', 'Parameter$Value' => 'The literal value for the parameter.
', 'QualityCheckStepMetadata$BaselineUsedForDriftCheckStatistics' => 'The Amazon S3 URI of the baseline statistics file used for the drift check.
', 'QualityCheckStepMetadata$BaselineUsedForDriftCheckConstraints' => 'The Amazon S3 URI of the baseline constraints file used for the drift check.
', 'QualityCheckStepMetadata$CalculatedBaselineStatistics' => 'The Amazon S3 URI of the newly calculated baseline statistics file.
', 'QualityCheckStepMetadata$CalculatedBaselineConstraints' => 'The Amazon S3 URI of the newly calculated baseline constraints file.
', 'QualityCheckStepMetadata$ViolationReport' => 'The Amazon S3 URI of violation report if violations are detected.
', ], ], 'String128' => [ 'base' => NULL, 'refs' => [ 'CategoricalParameterRangeValues$member' => NULL, ], ], 'String200' => [ 'base' => NULL, 'refs' => [ 'CreateWorkteamRequest$Description' => 'A description of the work team.
', 'SubscribedWorkteam$MarketplaceTitle' => 'The title of the service provided by the vendor in the Amazon Marketplace.
', 'SubscribedWorkteam$MarketplaceDescription' => 'The description of the vendor from the Amazon Marketplace.
', 'UpdateWorkteamRequest$Description' => 'An updated description for the work team.
', 'Workteam$Description' => 'A description of the work team.
', ], ], 'String2048' => [ 'base' => NULL, 'refs' => [ 'ActionSource$SourceUri' => 'The URI of the source.
', 'ArtifactSource$SourceUri' => 'The URI of the source.
', 'ContextSource$SourceUri' => 'The URI of the source.
', ], ], 'String256' => [ 'base' => NULL, 'refs' => [ 'ActionSource$SourceType' => 'The type of the source.
', 'ActionSource$SourceId' => 'The ID of the source.
', 'ArtifactSourceType$Value' => 'The ID.
', 'ArtifactSummary$ArtifactType' => 'The type of the artifact.
', 'AssociationSummary$SourceType' => 'The source type.
', 'AssociationSummary$DestinationType' => 'The destination type.
', 'CallbackStepMetadata$SqsQueueUrl' => 'The URL of the Amazon Simple Queue Service (Amazon SQS) queue used by the callback step.
', 'ClarifyCheckStepMetadata$CheckType' => 'The type of the Clarify Check step
', 'ClarifyCheckStepMetadata$ModelPackageGroupName' => 'The model package group name.
', 'ClarifyCheckStepMetadata$CheckJobArn' => 'The Amazon Resource Name (ARN) of the check processing job that was run by this step\'s execution.
', 'ContextSource$SourceType' => 'The type of the source.
', 'ContextSource$SourceId' => 'The ID of the source.
', 'ContextSummary$ContextType' => 'The type of the context.
', 'CreateActionRequest$ActionType' => 'The action type.
', 'CreateArtifactRequest$ArtifactType' => 'The artifact type.
', 'CreateContextRequest$ContextType' => 'The context type.
', 'CreateUserProfileRequest$SingleSignOnUserValue' => 'The username of the associated Amazon Web Services Single Sign-On User for this UserProfile. If the Domain\'s AuthMode is IAM Identity Center, this field is required, and must match a valid username of a user in your directory. If the Domain\'s AuthMode is not IAM Identity Center, this field cannot be specified.
', 'DescribeActionResponse$ActionType' => 'The type of the action.
', 'DescribeArtifactResponse$ArtifactType' => 'The type of the artifact.
', 'DescribeContextResponse$ContextType' => 'The type of the context.
', 'DescribeDomainResponse$SingleSignOnManagedApplicationInstanceId' => 'The IAM Identity Center managed application instance ID.
', 'DescribeUserProfileResponse$SingleSignOnUserValue' => 'The IAM Identity Center user value.
', 'EMRStepMetadata$ClusterId' => 'The identifier of the EMR cluster.
', 'EMRStepMetadata$StepId' => 'The identifier of the EMR cluster step.
', 'EMRStepMetadata$StepName' => 'The name of the EMR cluster step.
', 'LambdaStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the Lambda function that was run by this step execution.
', 'ListActionsRequest$ActionType' => 'A filter that returns only actions of the specified type.
', 'ListArtifactsRequest$ArtifactType' => 'A filter that returns only artifacts of the specified type.
', 'ListAssociationsRequest$SourceType' => 'A filter that returns only associations with the specified source type.
', 'ListAssociationsRequest$DestinationType' => 'A filter that returns only associations with the specified destination type.
', 'ListContextsRequest$ContextType' => 'A filter that returns only contexts of the specified type.
', 'ListTrialComponentsRequest$SourceArn' => 'A filter that returns only components that have the specified source Amazon Resource Name (ARN). If you specify SourceArn, you can\'t filter by ExperimentName or TrialName.
The value to filter the model metadata.
', 'ModelStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the created model.
', 'OutputParameter$Name' => 'The name of the output parameter.
', 'QualityCheckStepMetadata$CheckType' => 'The type of the Quality check step.
', 'QualityCheckStepMetadata$ModelPackageGroupName' => 'The model package group name.
', 'QualityCheckStepMetadata$CheckJobArn' => 'The Amazon Resource Name (ARN) of the Quality check processing job that was run by this step execution.
', 'QueryProperties$key' => NULL, 'QueryProperties$value' => NULL, 'RegisterModelStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the model package.
', 'SelectedStep$StepName' => 'The name of the pipeline step.
', 'SendPipelineExecutionStepFailureRequest$FailureReason' => 'A message describing why the step failed.
', ], ], 'String3072' => [ 'base' => NULL, 'refs' => [ 'FailStepMetadata$ErrorMessage' => 'A message that you define and then is processed and rendered by the Fail step when the error occurs.
', 'PipelineExecutionSummary$PipelineExecutionFailureReason' => 'A message generated by SageMaker Pipelines describing why the pipeline execution failed.
', ], ], 'String40' => [ 'base' => NULL, 'refs' => [ 'QueryTypes$member' => NULL, 'Vertex$Type' => 'The type of the lineage entity resource. For example: DataSet, Model, Endpoint, etc...
The type of the action.
', 'CategoricalParameter$Name' => 'The Name of the environment variable.
', 'ModelLatencyThreshold$Percentile' => 'The model latency percentile threshold. Acceptable values are P95 and P99. For custom load tests, specify the value as P95.
Limits the number of vertices in the request. Use the NextToken in a response to to retrieve the next page of results.
Limits the number of vertices in the response. Use the NextToken in a response to to retrieve the next page of results.
The string value of a categorical hyperparameter. If you specify a value for this parameter, you can\'t specify the NumberValue parameter.
The App type that the Lifecycle Configuration is attached to.
', 'DescribeStudioLifecycleConfigResponse$StudioLifecycleConfigAppType' => 'The App type that the Lifecycle Configuration is attached to.
', 'ListStudioLifecycleConfigsRequest$AppTypeEquals' => 'A parameter to search for the App Type to which the Lifecycle Configuration is attached.
', 'StudioLifecycleConfigDetails$StudioLifecycleConfigAppType' => 'The App type to which the Lifecycle Configuration is attached.
', ], ], 'StudioLifecycleConfigArn' => [ 'base' => NULL, 'refs' => [ 'CreateStudioLifecycleConfigResponse$StudioLifecycleConfigArn' => 'The ARN of your created Lifecycle Configuration.
', 'DescribeStudioLifecycleConfigResponse$StudioLifecycleConfigArn' => 'The ARN of the Lifecycle Configuration to describe.
', 'LifecycleConfigArns$member' => NULL, 'ResourceSpec$LifecycleConfigArn' => 'The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
', 'StudioLifecycleConfigDetails$StudioLifecycleConfigArn' => 'The Amazon Resource Name (ARN) of the Lifecycle Configuration.
', ], ], 'StudioLifecycleConfigContent' => [ 'base' => NULL, 'refs' => [ 'CreateStudioLifecycleConfigRequest$StudioLifecycleConfigContent' => 'The content of your Studio Lifecycle Configuration script. This content must be base64 encoded.
', 'DescribeStudioLifecycleConfigResponse$StudioLifecycleConfigContent' => 'The content of your Studio Lifecycle Configuration script.
', ], ], 'StudioLifecycleConfigDetails' => [ 'base' => 'Details of the Studio Lifecycle Configuration.
', 'refs' => [ 'StudioLifecycleConfigsList$member' => NULL, ], ], 'StudioLifecycleConfigName' => [ 'base' => NULL, 'refs' => [ 'CreateStudioLifecycleConfigRequest$StudioLifecycleConfigName' => 'The name of the Studio Lifecycle Configuration to create.
', 'DeleteStudioLifecycleConfigRequest$StudioLifecycleConfigName' => 'The name of the Studio Lifecycle Configuration to delete.
', 'DescribeStudioLifecycleConfigRequest$StudioLifecycleConfigName' => 'The name of the Studio Lifecycle Configuration to describe.
', 'DescribeStudioLifecycleConfigResponse$StudioLifecycleConfigName' => 'The name of the Studio Lifecycle Configuration that is described.
', 'ListStudioLifecycleConfigsRequest$NameContains' => 'A string in the Lifecycle Configuration name. This filter returns only Lifecycle Configurations whose name contains the specified string.
', 'StudioLifecycleConfigDetails$StudioLifecycleConfigName' => 'The name of the Studio Lifecycle Configuration.
', ], ], 'StudioLifecycleConfigSortKey' => [ 'base' => NULL, 'refs' => [ 'ListStudioLifecycleConfigsRequest$SortBy' => 'The property used to sort results. The default value is CreationTime.
', ], ], 'StudioLifecycleConfigsList' => [ 'base' => NULL, 'refs' => [ 'ListStudioLifecycleConfigsResponse$StudioLifecycleConfigs' => 'A list of Lifecycle Configurations and their properties.
', ], ], 'SubnetId' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$SubnetId' => 'The ID of the subnet in a VPC to which you would like to have a connectivity from your ML compute instance.
', 'DescribeNotebookInstanceOutput$SubnetId' => 'The ID of the VPC subnet.
', 'Subnets$member' => NULL, ], ], 'Subnets' => [ 'base' => NULL, 'refs' => [ 'CreateDomainRequest$SubnetIds' => 'The VPC subnets that Studio uses for communication.
', 'DescribeDomainResponse$SubnetIds' => 'The VPC subnets that Studio uses for communication.
', 'VpcConfig$Subnets' => 'The ID of the subnets in the VPC to which you want to connect your training job or model. For information about the availability of specific instance types, see Supported Instance Types and Availability Zones.
', ], ], 'SubscribedWorkteam' => [ 'base' => 'Describes a work team of a vendor that does the a labelling job.
', 'refs' => [ 'DescribeSubscribedWorkteamResponse$SubscribedWorkteam' => 'A Workteam instance that contains information about the work team.
An array of Workteam objects, each describing a work team.
Returns true if the work team was successfully deleted; otherwise, returns false.
Specified in the GetSearchSuggestions request. Limits the property names that are included in the response.
', 'refs' => [ 'GetSearchSuggestionsRequest$SuggestionQuery' => 'Limits the property names that are included in the response.
', ], ], 'TableFormat' => [ 'base' => NULL, 'refs' => [ 'OfflineStoreConfig$TableFormat' => 'Format for the offline store table. Supported formats are Glue (Default) and Apache Iceberg.
', ], ], 'TableName' => [ 'base' => NULL, 'refs' => [ 'DataCatalogConfig$TableName' => 'The name of the Glue table.
', ], ], 'TabularJobConfig' => [ 'base' => 'The collection of settings used by an AutoML job V2 for the tabular problem type.
', 'refs' => [ 'AutoMLProblemTypeConfig$TabularJobConfig' => 'Settings used to configure an AutoML job V2 for the tabular problem type (regression, classification).
', ], ], 'TabularResolvedAttributes' => [ 'base' => 'The resolved attributes specific to the tabular problem type.
', 'refs' => [ 'AutoMLProblemTypeResolvedAttributes$TabularResolvedAttributes' => 'The resolved attributes for the tabular problem type.
', ], ], 'Tag' => [ 'base' => 'A tag object that consists of a key and an optional value, used to manage metadata for SageMaker Amazon Web Services resources.
You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints. For more information on adding tags to SageMaker resources, see AddTags.
For more information on adding metadata to your Amazon Web Services resources with tagging, see Tagging Amazon Web Services resources. For advice on best practices for managing Amazon Web Services resources with tagging, see Tagging Best Practices: Implement an Effective Amazon Web Services Resource Tagging Strategy.
', 'refs' => [ 'TagList$member' => NULL, ], ], 'TagKey' => [ 'base' => NULL, 'refs' => [ 'Tag$Key' => 'The tag key. Tag keys must be unique per resource.
', 'TagKeyList$member' => NULL, ], ], 'TagKeyList' => [ 'base' => NULL, 'refs' => [ 'DeleteTagsInput$TagKeys' => 'An array or one or more tag keys to delete.
', ], ], 'TagList' => [ 'base' => NULL, 'refs' => [ 'AddTagsInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'AddTagsOutput$Tags' => 'A list of tags associated with the SageMaker resource.
', 'CreateActionRequest$Tags' => 'A list of tags to apply to the action.
', 'CreateAlgorithmInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateAppImageConfigRequest$Tags' => 'A list of tags to apply to the AppImageConfig.
', 'CreateAppRequest$Tags' => 'Each tag consists of a key and an optional value. Tag keys must be unique per resource.
', 'CreateArtifactRequest$Tags' => 'A list of tags to apply to the artifact.
', 'CreateAutoMLJobRequest$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web ServicesResources. Tag keys must be unique per resource.
', 'CreateAutoMLJobV2Request$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, such as by purpose, owner, or environment. For more information, see Tagging Amazon Web ServicesResources. Tag keys must be unique per resource.
', 'CreateCodeRepositoryInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateCompilationJobRequest$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateContextRequest$Tags' => 'A list of tags to apply to the context.
', 'CreateDataQualityJobDefinitionRequest$Tags' => '(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateDeviceFleetRequest$Tags' => 'Creates tags for the specified fleet.
', 'CreateDomainRequest$Tags' => 'Tags to associated with the Domain. Each tag consists of a key and an optional value. Tag keys must be unique per resource. Tags are searchable using the Search API.
Tags that you specify for the Domain are also added to all Apps that the Domain launches.
', 'CreateEdgeDeploymentPlanRequest$Tags' => 'List of tags with which to tag the edge deployment plan.
', 'CreateEdgePackagingJobRequest$Tags' => 'Creates tags for the packaging job.
', 'CreateEndpointConfigInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateEndpointInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateExperimentRequest$Tags' => 'A list of tags to associate with the experiment. You can use Search API to search on the tags.
', 'CreateFeatureGroupRequest$Tags' => 'Tags used to identify Features in each FeatureGroup.
An array of key-value pairs that contain metadata to help you categorize and organize a flow definition. Each tag consists of a key and a value, both of which you define.
', 'CreateHubRequest$Tags' => 'Any tags to associate with the hub.
', 'CreateHumanTaskUiRequest$Tags' => 'An array of key-value pairs that contain metadata to help you categorize and organize a human review workflow user interface. Each tag consists of a key and a value, both of which you define.
', 'CreateHyperParameterTuningJobRequest$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
Tags that you specify for the tuning job are also added to all training jobs that the tuning job launches.
', 'CreateImageRequest$Tags' => 'A list of tags to apply to the image.
', 'CreateInferenceExperimentRequest$Tags' => 'Array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging your Amazon Web Services Resources.
', 'CreateInferenceRecommendationsJobRequest$Tags' => 'The metadata that you apply to Amazon Web Services resources to help you categorize and organize them. Each tag consists of a key and a value, both of which you define. For more information, see Tagging Amazon Web Services Resources in the Amazon Web Services General Reference.
', 'CreateLabelingJobRequest$Tags' => 'An array of key/value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateModelBiasJobDefinitionRequest$Tags' => '(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateModelCardRequest$Tags' => 'Key-value pairs used to manage metadata for model cards.
', 'CreateModelExplainabilityJobDefinitionRequest$Tags' => '(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateModelInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateModelPackageGroupInput$Tags' => 'A list of key value pairs associated with the model group. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'CreateModelPackageInput$Tags' => 'A list of key value pairs associated with the model. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
If you supply ModelPackageGroupName, your model package belongs to the model group you specify and uses the tags associated with the model group. In this case, you cannot supply a tag argument.
(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateMonitoringScheduleRequest$Tags' => '(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateNotebookInstanceInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreatePipelineRequest$Tags' => 'A list of tags to apply to the created pipeline.
', 'CreateProcessingJobRequest$Tags' => '(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateProjectInput$Tags' => 'An array of key-value pairs that you want to use to organize and track your Amazon Web Services resource costs. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'CreateSpaceRequest$Tags' => 'Tags to associated with the space. Each tag consists of a key and an optional value. Tag keys must be unique for each resource. Tags are searchable using the Search API.
Tags to be associated with the Lifecycle Configuration. Each tag consists of a key and an optional value. Tag keys must be unique per resource. Tags are searchable using the Search API.
', 'CreateTrainingJobRequest$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateTransformJobRequest$Tags' => '(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateTrialComponentRequest$Tags' => 'A list of tags to associate with the component. You can use Search API to search on the tags.
', 'CreateTrialRequest$Tags' => 'A list of tags to associate with the trial. You can use Search API to search on the tags.
', 'CreateUserProfileRequest$Tags' => 'Each tag consists of a key and an optional value. Tag keys must be unique per resource.
Tags that you specify for the User Profile are also added to all Apps that the User Profile launches.
', 'CreateWorkforceRequest$Tags' => 'An array of key-value pairs that contain metadata to help you categorize and organize our workforce. Each tag consists of a key and a value, both of which you define.
', 'CreateWorkteamRequest$Tags' => 'An array of key-value pairs.
For more information, see Resource Tag and Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'DescribeLabelingJobResponse$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'Endpoint$Tags' => 'A list of the tags associated with the endpoint. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'Experiment$Tags' => 'The list of tags that are associated with the experiment. You can use Search API to search on the tags.
', 'FeatureGroup$Tags' => 'Tags used to define a FeatureGroup.
The tags associated with a hyperparameter tuning job. For more information see Tagging Amazon Web Services resources.
', 'ImportHubContentRequest$Tags' => 'Any tags associated with the hub content.
', 'ListTagsOutput$Tags' => 'An array of Tag objects, each with a tag key and a value.
A list of key-value pairs associated with the model. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'ModelCard$Tags' => 'Key-value pairs used to manage metadata for the model card.
', 'ModelDashboardModelCard$Tags' => 'The tags associated with a model card.
', 'ModelPackage$Tags' => 'A list of the tags associated with the model package. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'ModelPackageGroup$Tags' => 'A list of the tags associated with the model group. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'MonitoringSchedule$Tags' => 'A list of the tags associated with the monitoring schedlue. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'Pipeline$Tags' => 'A list of tags that apply to the pipeline.
', 'ProcessingJob$Tags' => 'An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'Project$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'RegisterDevicesRequest$Tags' => 'The tags associated with devices.
', 'TrainingJob$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'TransformJob$Tags' => 'A list of tags associated with the transform job.
', 'Trial$Tags' => 'The list of tags that are associated with the trial. You can use Search API to search on the tags.
', 'TrialComponent$Tags' => 'The list of tags that are associated with the component. You can use Search API to search on the tags.
', 'UpdateProjectInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources. In addition, the project must have tag update constraints set in order to include this parameter in the request. For more information, see Amazon Web Services Service Catalog Tag Update Constraints.
', ], ], 'TagValue' => [ 'base' => NULL, 'refs' => [ 'Tag$Value' => 'The tag value.
', ], ], 'TargetAttributeName' => [ 'base' => NULL, 'refs' => [ 'AutoMLChannel$TargetAttributeName' => 'The name of the target variable in supervised learning, usually represented by \'y\'.
', 'TabularJobConfig$TargetAttributeName' => 'The name of the target variable in supervised learning, usually represented by \'y\'.
', 'TimeSeriesConfig$TargetAttributeName' => 'The name of the column representing the target variable that you want to predict for each item in your dataset. The data type of the target variable must be numerical.
', ], ], 'TargetDevice' => [ 'base' => NULL, 'refs' => [ 'CompilationJobSummary$CompilationTargetDevice' => 'The type of device that the model will run on after the compilation job has completed.
', 'OutputConfig$TargetDevice' => 'Identifies the target device or the machine learning instance that you want to run your model on after the compilation has completed. Alternatively, you can specify OS, architecture, and accelerator using TargetPlatform fields. It can be used instead of TargetPlatform.
Currently ml_trn1 is available only in US East (N. Virginia) Region, and ml_inf2 is available only in US East (Ohio) Region.
The name of the column used to provide the class labels. It should not be same as the content column.
', ], ], 'TargetObjectiveMetricValue' => [ 'base' => NULL, 'refs' => [ 'TuningJobCompletionCriteria$TargetObjectiveMetricValue' => 'The value of the objective metric.
', ], ], 'TargetPlatform' => [ 'base' => 'Contains information about a target platform that you want your model to run on, such as OS, architecture, and accelerators. It is an alternative of TargetDevice.
Contains information about a target platform that you want your model to run on, such as OS, architecture, and accelerators. It is an alternative of TargetDevice.
The following examples show how to configure the TargetPlatform and CompilerOptions JSON strings for popular target platforms:
Raspberry Pi 3 Model B+
"TargetPlatform": {"Os": "LINUX", "Arch": "ARM_EABIHF"},
"CompilerOptions": {\'mattr\': [\'+neon\']}
Jetson TX2
"TargetPlatform": {"Os": "LINUX", "Arch": "ARM64", "Accelerator": "NVIDIA"},
"CompilerOptions": {\'gpu-code\': \'sm_62\', \'trt-ver\': \'6.0.1\', \'cuda-ver\': \'10.0\'}
EC2 m5.2xlarge instance OS
"TargetPlatform": {"Os": "LINUX", "Arch": "X86_64", "Accelerator": "NVIDIA"},
"CompilerOptions": {\'mcpu\': \'skylake-avx512\'}
RK3399
"TargetPlatform": {"Os": "LINUX", "Arch": "ARM64", "Accelerator": "MALI"}
ARMv7 phone (CPU)
"TargetPlatform": {"Os": "ANDROID", "Arch": "ARM_EABI"},
"CompilerOptions": {\'ANDROID_PLATFORM\': 25, \'mattr\': [\'+neon\']}
ARMv8 phone (CPU)
"TargetPlatform": {"Os": "ANDROID", "Arch": "ARM64"},
"CompilerOptions": {\'ANDROID_PLATFORM\': 29}
The type of accelerator that the model will run on after the compilation job has completed.
', 'TargetPlatform$Accelerator' => 'Specifies a target platform accelerator (optional).
NVIDIA: Nvidia graphics processing unit. It also requires gpu-code, trt-ver, cuda-ver compiler options
MALI: ARM Mali graphics processor
INTEL_GRAPHICS: Integrated Intel graphics
The type of architecture that the model will run on after the compilation job has completed.
', 'TargetPlatform$Arch' => 'Specifies a target platform architecture.
X86_64: 64-bit version of the x86 instruction set.
X86: 32-bit version of the x86 instruction set.
ARM64: ARMv8 64-bit CPU.
ARM_EABIHF: ARMv7 32-bit, Hard Float.
ARM_EABI: ARMv7 32-bit, Soft Float. Used by Android 32-bit ARM platform.
The type of OS that the model will run on after the compilation job has completed.
', 'TargetPlatform$Os' => 'Specifies a target platform OS.
LINUX: Linux-based operating systems.
ANDROID: Android operating systems. Android API level can be specified using the ANDROID_PLATFORM compiler option. For example, "CompilerOptions": {\'ANDROID_PLATFORM\': 28}
A target tracking scaling policy. Includes support for predefined or customized metrics.
When using the PutScalingPolicy API, this parameter is required when you are creating a policy with the policy type TargetTrackingScaling.
A target tracking scaling policy. Includes support for predefined or customized metrics.
', ], ], 'TaskAvailabilityLifetimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'HumanTaskConfig$TaskAvailabilityLifetimeInSeconds' => 'The length of time that a task remains available for labeling by human workers. The default and maximum values for this parameter depend on the type of workforce you use.
If you choose the Amazon Mechanical Turk workforce, the maximum is 12 hours (43,200 seconds). The default is 6 hours (21,600 seconds).
If you choose a private or vendor workforce, the default value is 30 days (2592,000 seconds) for non-AL mode. For most users, the maximum is also 30 days.
The variant\'s capacity.
', 'PendingProductionVariantSummary$CurrentInstanceCount' => 'The number of instances associated with the variant.
', 'PendingProductionVariantSummary$DesiredInstanceCount' => 'The number of instances requested in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the CreateEndpointConfig operation.
', 'ProductionVariantSummary$CurrentInstanceCount' => 'The number of instances associated with the variant.
', 'ProductionVariantSummary$DesiredInstanceCount' => 'The number of instances requested in the UpdateEndpointWeightsAndCapacities request.
The number of instances of the type specified by InstanceType.
A description of the task for your human workers.
', ], ], 'TaskInput' => [ 'base' => NULL, 'refs' => [ 'RenderableTask$Input' => 'A JSON object that contains values for the variables defined in the template. It is made available to the template under the substitution variable task.input. For example, if you define a variable task.input.text in your template, you can supply the variable in the JSON object as "text": "sample text".
Keywords used to describe the task so that workers on Amazon Mechanical Turk can discover the task.
', ], ], 'TaskTimeLimitInSeconds' => [ 'base' => NULL, 'refs' => [ 'HumanTaskConfig$TaskTimeLimitInSeconds' => 'The amount of time that a worker has to complete a task.
If you create a custom labeling job, the maximum value for this parameter is 8 hours (28,800 seconds).
If you create a labeling job using a built-in task type the maximum for this parameter depends on the task type you use:
For image and text labeling jobs, the maximum is 8 hours (28,800 seconds).
For 3D point cloud and video frame labeling jobs, the maximum is 30 days (2952,000 seconds) for non-AL mode. For most users, the maximum is also 30 days.
A title for the task for your human workers.
', ], ], 'TemplateContent' => [ 'base' => NULL, 'refs' => [ 'UiTemplate$Content' => 'The content of the Liquid template for the worker user interface.
', ], ], 'TemplateContentSha256' => [ 'base' => NULL, 'refs' => [ 'UiTemplateInfo$ContentSha256' => 'The SHA-256 digest of the contents of the template.
', ], ], 'TemplateUrl' => [ 'base' => NULL, 'refs' => [ 'UiTemplateInfo$Url' => 'The URL for the user interface template.
', ], ], 'TensorBoardAppSettings' => [ 'base' => 'The TensorBoard app settings.
', 'refs' => [ 'UserSettings$TensorBoardAppSettings' => 'The TensorBoard app settings.
', ], ], 'TensorBoardOutputConfig' => [ 'base' => 'Configuration of storage locations for the Amazon SageMaker Debugger TensorBoard output data.
', 'refs' => [ 'CreateTrainingJobRequest$TensorBoardOutputConfig' => NULL, 'DescribeTrainingJobResponse$TensorBoardOutputConfig' => NULL, 'TrainingJob$TensorBoardOutputConfig' => NULL, ], ], 'TenthFractionsOfACent' => [ 'base' => NULL, 'refs' => [ 'USD$TenthFractionsOfACent' => 'Fractions of a cent, in tenths.
', ], ], 'TerminationWaitInSeconds' => [ 'base' => NULL, 'refs' => [ 'BlueGreenUpdatePolicy$TerminationWaitInSeconds' => 'Additional waiting time in seconds after the completion of an endpoint deployment before terminating the old endpoint fleet. Default is 0.
', ], ], 'TextClassificationJobConfig' => [ 'base' => 'The collection of settings used by an AutoML job V2 for the text classification problem type.
', 'refs' => [ 'AutoMLProblemTypeConfig$TextClassificationJobConfig' => 'Settings used to configure an AutoML job V2 for the text classification problem type.
', ], ], 'TextGenerationJobConfig' => [ 'base' => 'The collection of settings used by an AutoML job V2 for the text generation problem type.
The text generation models that support fine-tuning in Autopilot are currently accessible exclusively in regions supported by Canvas. Refer to the documentation of Canvas for the full list of its supported Regions.
Settings used to configure an AutoML job V2 for the text generation (LLMs fine-tuning) problem type.
The text generation models that support fine-tuning in Autopilot are currently accessible exclusively in regions supported by Canvas. Refer to the documentation of Canvas for the full list of its supported Regions.
The resolved attributes specific to the text generation problem type.
', 'refs' => [ 'AutoMLProblemTypeResolvedAttributes$TextGenerationResolvedAttributes' => 'The resolved attributes for the text generation problem type.
', ], ], 'ThingName' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceResponse$IotThingName' => 'The Amazon Web Services Internet of Things (IoT) object thing name associated with the device.
', 'Device$IotThingName' => 'Amazon Web Services Internet of Things (IoT) object name.
', 'DeviceSummary$IotThingName' => 'The Amazon Web Services Internet of Things (IoT) object thing name associated with the device..
', ], ], 'TimeSeriesConfig' => [ 'base' => 'The collection of components that defines the time-series.
', 'refs' => [ 'TimeSeriesForecastingJobConfig$TimeSeriesConfig' => 'The collection of components that defines the time-series.
', ], ], 'TimeSeriesForecastingJobConfig' => [ 'base' => 'The collection of settings used by an AutoML job V2 for the time-series forecasting problem type.
', 'refs' => [ 'AutoMLProblemTypeConfig$TimeSeriesForecastingJobConfig' => 'Settings used to configure an AutoML job V2 for the time-series forecasting problem type.
', ], ], 'TimeSeriesForecastingSettings' => [ 'base' => 'Time series forecast settings for the SageMaker Canvas application.
', 'refs' => [ 'CanvasAppSettings$TimeSeriesForecastingSettings' => 'Time series forecast settings for the SageMaker Canvas application.
', ], ], 'TimeSeriesTransformations' => [ 'base' => 'Transformations allowed on the dataset. Supported transformations are Filling and Aggregation. Filling specifies how to add values to missing values in the dataset. Aggregation defines how to aggregate data that does not align with forecast frequency.
The transformations modifying specific attributes of the time-series, such as filling strategies for missing values.
', ], ], 'Timestamp' => [ 'base' => NULL, 'refs' => [ 'ActionSummary$CreationTime' => 'When the action was created.
', 'ActionSummary$LastModifiedTime' => 'When the action was last modified.
', 'AppImageConfigDetails$CreationTime' => 'When the AppImageConfig was created.
', 'AppImageConfigDetails$LastModifiedTime' => 'When the AppImageConfig was last modified.
', 'ArtifactSummary$CreationTime' => 'When the artifact was created.
', 'ArtifactSummary$LastModifiedTime' => 'When the artifact was last modified.
', 'AssociationSummary$CreationTime' => 'When the association was created.
', 'AutoMLCandidate$CreationTime' => 'The creation time.
', 'AutoMLCandidate$EndTime' => 'The end time.
', 'AutoMLCandidate$LastModifiedTime' => 'The last modified time.
', 'AutoMLJobSummary$CreationTime' => 'When the AutoML job was created.
', 'AutoMLJobSummary$EndTime' => 'The end time of an AutoML job.
', 'AutoMLJobSummary$LastModifiedTime' => 'When the AutoML job was last modified.
', 'CompilationJobSummary$CompilationStartTime' => 'The time when the model compilation job started.
', 'CompilationJobSummary$CompilationEndTime' => 'The time when the model compilation job completed.
', 'ContextSummary$CreationTime' => 'When the context was created.
', 'ContextSummary$LastModifiedTime' => 'When the context was last modified.
', 'CreateTrialComponentRequest$StartTime' => 'When the component started.
', 'CreateTrialComponentRequest$EndTime' => 'When the component ended.
', 'DebugRuleEvaluationStatus$LastModifiedTime' => 'Timestamp when the rule evaluation status was last modified.
', 'DeployedImage$ResolutionTime' => 'The date and time when the image path for the model resolved to the ResolvedImage
When the action was created.
', 'DescribeActionResponse$LastModifiedTime' => 'When the action was last modified.
', 'DescribeAppImageConfigResponse$CreationTime' => 'When the AppImageConfig was created.
', 'DescribeAppImageConfigResponse$LastModifiedTime' => 'When the AppImageConfig was last modified.
', 'DescribeAppResponse$LastHealthCheckTimestamp' => 'The timestamp of the last health check.
', 'DescribeAppResponse$LastUserActivityTimestamp' => 'The timestamp of the last user\'s activity. LastUserActivityTimestamp is also updated when SageMaker performs health checks without user activity. As a result, this value is set to the same value as LastHealthCheckTimestamp.
When the artifact was created.
', 'DescribeArtifactResponse$LastModifiedTime' => 'When the artifact was last modified.
', 'DescribeAutoMLJobResponse$CreationTime' => 'Returns the creation time of the AutoML job.
', 'DescribeAutoMLJobResponse$EndTime' => 'Returns the end time of the AutoML job.
', 'DescribeAutoMLJobResponse$LastModifiedTime' => 'Returns the job\'s last modified time.
', 'DescribeAutoMLJobV2Response$CreationTime' => 'Returns the creation time of the AutoML job V2.
', 'DescribeAutoMLJobV2Response$EndTime' => 'Returns the end time of the AutoML job V2.
', 'DescribeAutoMLJobV2Response$LastModifiedTime' => 'Returns the job\'s last modified time.
', 'DescribeCompilationJobResponse$CompilationStartTime' => 'The time when the model compilation job started the CompilationJob instances.
You are billed for the time between this timestamp and the timestamp in the CompilationEndTime field. In Amazon CloudWatch Logs, the start time might be later than this time. That\'s because it takes time to download the compilation job, which depends on the size of the compilation job container.
The time when the model compilation job on a compilation job instance ended. For a successful or stopped job, this is when the job\'s model artifacts have finished uploading. For a failed job, this is when Amazon SageMaker detected that the job failed.
', 'DescribeContextResponse$CreationTime' => 'When the context was created.
', 'DescribeContextResponse$LastModifiedTime' => 'When the context was last modified.
', 'DescribeDataQualityJobDefinitionResponse$CreationTime' => 'The time that the data quality monitoring job definition was created.
', 'DescribeDeviceFleetResponse$CreationTime' => 'Timestamp of when the device fleet was created.
', 'DescribeDeviceFleetResponse$LastModifiedTime' => 'Timestamp of when the device fleet was last updated.
', 'DescribeDeviceResponse$RegistrationTime' => 'The timestamp of the last registration or de-reregistration.
', 'DescribeDeviceResponse$LatestHeartbeat' => 'The last heartbeat received from the device.
', 'DescribeEdgeDeploymentPlanResponse$CreationTime' => 'The time when the edge deployment plan was created.
', 'DescribeEdgeDeploymentPlanResponse$LastModifiedTime' => 'The time when the edge deployment plan was last updated.
', 'DescribeEdgePackagingJobResponse$CreationTime' => 'The timestamp of when the packaging job was created.
', 'DescribeEdgePackagingJobResponse$LastModifiedTime' => 'The timestamp of when the job was last updated.
', 'DescribeEndpointConfigOutput$CreationTime' => 'A timestamp that shows when the endpoint configuration was created.
', 'DescribeEndpointOutput$CreationTime' => 'A timestamp that shows when the endpoint was created.
', 'DescribeEndpointOutput$LastModifiedTime' => 'A timestamp that shows when the endpoint was last modified.
', 'DescribeExperimentResponse$CreationTime' => 'When the experiment was created.
', 'DescribeExperimentResponse$LastModifiedTime' => 'When the experiment was last modified.
', 'DescribeFlowDefinitionResponse$CreationTime' => 'The timestamp when the flow definition was created.
', 'DescribeHubContentResponse$CreationTime' => 'The date and time that hub content was created.
', 'DescribeHubResponse$CreationTime' => 'The date and time that the hub was created.
', 'DescribeHubResponse$LastModifiedTime' => 'The date and time that the hub was last modified.
', 'DescribeHumanTaskUiResponse$CreationTime' => 'The timestamp when the human task user interface was created.
', 'DescribeHyperParameterTuningJobResponse$CreationTime' => 'The date and time that the tuning job started.
', 'DescribeHyperParameterTuningJobResponse$HyperParameterTuningEndTime' => 'The date and time that the tuning job ended.
', 'DescribeHyperParameterTuningJobResponse$LastModifiedTime' => 'The date and time that the status of the tuning job was modified.
', 'DescribeImageResponse$CreationTime' => 'When the image was created.
', 'DescribeImageResponse$LastModifiedTime' => 'When the image was last modified.
', 'DescribeImageVersionResponse$CreationTime' => 'When the version was created.
', 'DescribeImageVersionResponse$LastModifiedTime' => 'When the version was last modified.
', 'DescribeInferenceExperimentResponse$CreationTime' => 'The timestamp at which you created the inference experiment.
', 'DescribeInferenceExperimentResponse$CompletionTime' => 'The timestamp at which the inference experiment was completed.
', 'DescribeInferenceExperimentResponse$LastModifiedTime' => 'The timestamp at which you last modified the inference experiment.
', 'DescribeInferenceRecommendationsJobResponse$CompletionTime' => 'A timestamp that shows when the job completed.
', 'DescribeLabelingJobResponse$CreationTime' => 'The date and time that the labeling job was created.
', 'DescribeLabelingJobResponse$LastModifiedTime' => 'The date and time that the labeling job was last updated.
', 'DescribeLineageGroupResponse$CreationTime' => 'The creation time of lineage group.
', 'DescribeLineageGroupResponse$LastModifiedTime' => 'The last modified time of the lineage group.
', 'DescribeModelBiasJobDefinitionResponse$CreationTime' => 'The time at which the model bias job was created.
', 'DescribeModelCardExportJobResponse$CreatedAt' => 'The date and time that the model export job was created.
', 'DescribeModelCardExportJobResponse$LastModifiedAt' => 'The date and time that the model export job was last modified.
', 'DescribeModelCardResponse$CreationTime' => 'The date and time the model card was created.
', 'DescribeModelCardResponse$LastModifiedTime' => 'The date and time the model card was last modified.
', 'DescribeModelExplainabilityJobDefinitionResponse$CreationTime' => 'The time at which the model explainability job was created.
', 'DescribeModelOutput$CreationTime' => 'A timestamp that shows when the model was created.
', 'DescribeModelPackageOutput$LastModifiedTime' => 'The last time that the model package was modified.
', 'DescribeModelQualityJobDefinitionResponse$CreationTime' => 'The time at which the model quality job was created.
', 'DescribeMonitoringScheduleResponse$CreationTime' => 'The time at which the monitoring job was created.
', 'DescribeMonitoringScheduleResponse$LastModifiedTime' => 'The time at which the monitoring job was last modified.
', 'DescribePipelineDefinitionForExecutionResponse$CreationTime' => 'The time when the pipeline was created.
', 'DescribePipelineExecutionResponse$CreationTime' => 'The time when the pipeline execution was created.
', 'DescribePipelineExecutionResponse$LastModifiedTime' => 'The time when the pipeline execution was modified last.
', 'DescribePipelineResponse$CreationTime' => 'The time when the pipeline was created.
', 'DescribePipelineResponse$LastModifiedTime' => 'The time when the pipeline was last modified.
', 'DescribePipelineResponse$LastRunTime' => 'The time when the pipeline was last run.
', 'DescribeProcessingJobResponse$ProcessingEndTime' => 'The time at which the processing job completed.
', 'DescribeProcessingJobResponse$ProcessingStartTime' => 'The time at which the processing job started.
', 'DescribeProcessingJobResponse$LastModifiedTime' => 'The time at which the processing job was last modified.
', 'DescribeProcessingJobResponse$CreationTime' => 'The time at which the processing job was created.
', 'DescribeProjectOutput$CreationTime' => 'The time when the project was created.
', 'DescribeProjectOutput$LastModifiedTime' => 'The timestamp when project was last modified.
', 'DescribeStudioLifecycleConfigResponse$CreationTime' => 'The creation time of the Studio Lifecycle Configuration.
', 'DescribeStudioLifecycleConfigResponse$LastModifiedTime' => 'This value is equivalent to CreationTime because Studio Lifecycle Configurations are immutable.
', 'DescribeTrainingJobResponse$CreationTime' => 'A timestamp that indicates when the training job was created.
', 'DescribeTrainingJobResponse$TrainingStartTime' => 'Indicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of TrainingEndTime. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container.
Indicates the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.
A timestamp that indicates when the status of the training job was last modified.
', 'DescribeTransformJobResponse$CreationTime' => 'A timestamp that shows when the transform Job was created.
', 'DescribeTransformJobResponse$TransformStartTime' => 'Indicates when the transform job starts on ML instances. You are billed for the time interval between this time and the value of TransformEndTime.
Indicates when the transform job has been completed, or has stopped or failed. You are billed for the time interval between this time and the value of TransformStartTime.
When the component started.
', 'DescribeTrialComponentResponse$EndTime' => 'When the component ended.
', 'DescribeTrialComponentResponse$CreationTime' => 'When the component was created.
', 'DescribeTrialComponentResponse$LastModifiedTime' => 'When the component was last modified.
', 'DescribeTrialResponse$CreationTime' => 'When the trial was created.
', 'DescribeTrialResponse$LastModifiedTime' => 'When the trial was last modified.
', 'DeviceDeploymentSummary$DeploymentStartTime' => 'The time when the deployment on the device started.
', 'DeviceFleetSummary$CreationTime' => 'Timestamp of when the device fleet was created.
', 'DeviceFleetSummary$LastModifiedTime' => 'Timestamp of when the device fleet was last updated.
', 'DeviceSummary$RegistrationTime' => 'The timestamp of the last registration or de-reregistration.
', 'DeviceSummary$LatestHeartbeat' => 'The last heartbeat received from the device.
', 'EdgeDeploymentPlanSummary$CreationTime' => 'The time when the edge deployment plan was created.
', 'EdgeDeploymentPlanSummary$LastModifiedTime' => 'The time when the edge deployment plan was last updated.
', 'EdgeDeploymentStatus$EdgeDeploymentStageStartTime' => 'The time when the deployment API started.
', 'EdgeModel$LatestSampleTime' => 'The timestamp of the last data sample taken.
', 'EdgeModel$LatestInference' => 'The timestamp of the last inference that was made.
', 'EdgePackagingJobSummary$CreationTime' => 'The timestamp of when the job was created.
', 'EdgePackagingJobSummary$LastModifiedTime' => 'The timestamp of when the edge packaging job was last updated.
', 'Endpoint$CreationTime' => 'The time that the endpoint was created.
', 'Endpoint$LastModifiedTime' => 'The last time the endpoint was modified.
', 'EndpointConfigSummary$CreationTime' => 'A timestamp that shows when the endpoint configuration was created.
', 'EndpointSummary$CreationTime' => 'A timestamp that shows when the endpoint was created.
', 'EndpointSummary$LastModifiedTime' => 'A timestamp that shows when the endpoint was last modified.
', 'Experiment$CreationTime' => 'When the experiment was created.
', 'Experiment$LastModifiedTime' => 'When the experiment was last modified.
', 'ExperimentSummary$CreationTime' => 'When the experiment was created.
', 'ExperimentSummary$LastModifiedTime' => 'When the experiment was last modified.
', 'FeatureGroupSummary$CreationTime' => 'A timestamp indicating the time of creation time of the FeatureGroup.
The timestamp when SageMaker created the flow definition.
', 'GetDeviceFleetReportResponse$ReportGenerated' => 'Timestamp of when the report was generated.
', 'HubContentInfo$CreationTime' => 'The date and time that the hub content was created.
', 'HubInfo$CreationTime' => 'The date and time that the hub was created.
', 'HubInfo$LastModifiedTime' => 'The date and time that the hub was last modified.
', 'HumanTaskUiSummary$CreationTime' => 'A timestamp when SageMaker created the human task user interface.
', 'HyperParameterTrainingJobSummary$CreationTime' => 'The date and time that the training job was created.
', 'HyperParameterTrainingJobSummary$TrainingStartTime' => 'The date and time that the training job started.
', 'HyperParameterTrainingJobSummary$TrainingEndTime' => 'Specifies the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.
The time in timestamp format that AMT detected model convergence, as defined by a lack of significant improvement over time based on criteria developed over a wide range of diverse benchmarking tests.
', 'HyperParameterTuningJobSearchEntity$CreationTime' => 'The time that a hyperparameter tuning job was created.
', 'HyperParameterTuningJobSearchEntity$HyperParameterTuningEndTime' => 'The time that a hyperparameter tuning job ended.
', 'HyperParameterTuningJobSearchEntity$LastModifiedTime' => 'The time that a hyperparameter tuning job was last modified.
', 'HyperParameterTuningJobSummary$CreationTime' => 'The date and time that the tuning job was created.
', 'HyperParameterTuningJobSummary$HyperParameterTuningEndTime' => 'The date and time that the tuning job ended.
', 'HyperParameterTuningJobSummary$LastModifiedTime' => 'The date and time that the tuning job was modified.
', 'Image$CreationTime' => 'When the image was created.
', 'Image$LastModifiedTime' => 'When the image was last modified.
', 'ImageVersion$CreationTime' => 'When the version was created.
', 'ImageVersion$LastModifiedTime' => 'When the version was last modified.
', 'InferenceExperimentSchedule$StartTime' => 'The timestamp at which the inference experiment started or will start.
', 'InferenceExperimentSchedule$EndTime' => 'The timestamp at which the inference experiment ended or will end.
', 'InferenceExperimentSummary$CreationTime' => 'The timestamp at which the inference experiment was created.
', 'InferenceExperimentSummary$CompletionTime' => 'The timestamp at which the inference experiment was completed.
', 'InferenceExperimentSummary$LastModifiedTime' => 'The timestamp when you last modified the inference experiment.
', 'InferenceRecommendationsJob$CompletionTime' => 'A timestamp that shows when the job completed.
', 'LabelingJobForWorkteamSummary$CreationTime' => 'The date and time that the labeling job was created.
', 'LabelingJobSummary$CreationTime' => 'The date and time that the job was created (timestamp).
', 'LabelingJobSummary$LastModifiedTime' => 'The date and time that the job was last modified (timestamp).
', 'LineageGroupSummary$CreationTime' => 'The creation time of the lineage group summary.
', 'LineageGroupSummary$LastModifiedTime' => 'The last modified time of the lineage group summary.
', 'ListActionsRequest$CreatedAfter' => 'A filter that returns only actions created on or after the specified time.
', 'ListActionsRequest$CreatedBefore' => 'A filter that returns only actions created on or before the specified time.
', 'ListAppImageConfigsRequest$CreationTimeBefore' => 'A filter that returns only AppImageConfigs created on or before the specified time.
', 'ListAppImageConfigsRequest$CreationTimeAfter' => 'A filter that returns only AppImageConfigs created on or after the specified time.
', 'ListAppImageConfigsRequest$ModifiedTimeBefore' => 'A filter that returns only AppImageConfigs modified on or before the specified time.
', 'ListAppImageConfigsRequest$ModifiedTimeAfter' => 'A filter that returns only AppImageConfigs modified on or after the specified time.
', 'ListArtifactsRequest$CreatedAfter' => 'A filter that returns only artifacts created on or after the specified time.
', 'ListArtifactsRequest$CreatedBefore' => 'A filter that returns only artifacts created on or before the specified time.
', 'ListAssociationsRequest$CreatedAfter' => 'A filter that returns only associations created on or after the specified time.
', 'ListAssociationsRequest$CreatedBefore' => 'A filter that returns only associations created on or before the specified time.
', 'ListAutoMLJobsRequest$CreationTimeAfter' => 'Request a list of jobs, using a filter for time.
', 'ListAutoMLJobsRequest$CreationTimeBefore' => 'Request a list of jobs, using a filter for time.
', 'ListAutoMLJobsRequest$LastModifiedTimeAfter' => 'Request a list of jobs, using a filter for time.
', 'ListAutoMLJobsRequest$LastModifiedTimeBefore' => 'Request a list of jobs, using a filter for time.
', 'ListCodeRepositoriesInput$LastModifiedTimeAfter' => 'A filter that returns only Git repositories that were last modified after the specified time.
', 'ListCodeRepositoriesInput$LastModifiedTimeBefore' => 'A filter that returns only Git repositories that were last modified before the specified time.
', 'ListContextsRequest$CreatedAfter' => 'A filter that returns only contexts created on or after the specified time.
', 'ListContextsRequest$CreatedBefore' => 'A filter that returns only contexts created on or before the specified time.
', 'ListDataQualityJobDefinitionsRequest$CreationTimeBefore' => 'A filter that returns only data quality monitoring job definitions created before the specified time.
', 'ListDataQualityJobDefinitionsRequest$CreationTimeAfter' => 'A filter that returns only data quality monitoring job definitions created after the specified time.
', 'ListDeviceFleetsRequest$CreationTimeAfter' => 'Filter fleets where packaging job was created after specified time.
', 'ListDeviceFleetsRequest$CreationTimeBefore' => 'Filter fleets where the edge packaging job was created before specified time.
', 'ListDeviceFleetsRequest$LastModifiedTimeAfter' => 'Select fleets where the job was updated after X
', 'ListDeviceFleetsRequest$LastModifiedTimeBefore' => 'Select fleets where the job was updated before X
', 'ListDevicesRequest$LatestHeartbeatAfter' => 'Select fleets where the job was updated after X
', 'ListEdgeDeploymentPlansRequest$CreationTimeAfter' => 'Selects edge deployment plans created after this time.
', 'ListEdgeDeploymentPlansRequest$CreationTimeBefore' => 'Selects edge deployment plans created before this time.
', 'ListEdgeDeploymentPlansRequest$LastModifiedTimeAfter' => 'Selects edge deployment plans that were last updated after this time.
', 'ListEdgeDeploymentPlansRequest$LastModifiedTimeBefore' => 'Selects edge deployment plans that were last updated before this time.
', 'ListEdgePackagingJobsRequest$CreationTimeAfter' => 'Select jobs where the job was created after specified time.
', 'ListEdgePackagingJobsRequest$CreationTimeBefore' => 'Select jobs where the job was created before specified time.
', 'ListEdgePackagingJobsRequest$LastModifiedTimeAfter' => 'Select jobs where the job was updated after specified time.
', 'ListEdgePackagingJobsRequest$LastModifiedTimeBefore' => 'Select jobs where the job was updated before specified time.
', 'ListEndpointConfigsInput$CreationTimeBefore' => 'A filter that returns only endpoint configurations created before the specified time (timestamp).
', 'ListEndpointConfigsInput$CreationTimeAfter' => 'A filter that returns only endpoint configurations with a creation time greater than or equal to the specified time (timestamp).
', 'ListEndpointsInput$CreationTimeBefore' => 'A filter that returns only endpoints that were created before the specified time (timestamp).
', 'ListEndpointsInput$CreationTimeAfter' => 'A filter that returns only endpoints with a creation time greater than or equal to the specified time (timestamp).
', 'ListEndpointsInput$LastModifiedTimeBefore' => 'A filter that returns only endpoints that were modified before the specified timestamp.
', 'ListEndpointsInput$LastModifiedTimeAfter' => 'A filter that returns only endpoints that were modified after the specified timestamp.
', 'ListExperimentsRequest$CreatedAfter' => 'A filter that returns only experiments created after the specified time.
', 'ListExperimentsRequest$CreatedBefore' => 'A filter that returns only experiments created before the specified time.
', 'ListFlowDefinitionsRequest$CreationTimeAfter' => 'A filter that returns only flow definitions with a creation time greater than or equal to the specified timestamp.
', 'ListFlowDefinitionsRequest$CreationTimeBefore' => 'A filter that returns only flow definitions that were created before the specified timestamp.
', 'ListHubContentVersionsRequest$CreationTimeBefore' => 'Only list hub content versions that were created before the time specified.
', 'ListHubContentVersionsRequest$CreationTimeAfter' => 'Only list hub content versions that were created after the time specified.
', 'ListHubContentsRequest$CreationTimeBefore' => 'Only list hub content that was created before the time specified.
', 'ListHubContentsRequest$CreationTimeAfter' => 'Only list hub content that was created after the time specified.
', 'ListHubsRequest$CreationTimeBefore' => 'Only list hubs that were created before the time specified.
', 'ListHubsRequest$CreationTimeAfter' => 'Only list hubs that were created after the time specified.
', 'ListHubsRequest$LastModifiedTimeBefore' => 'Only list hubs that were last modified before the time specified.
', 'ListHubsRequest$LastModifiedTimeAfter' => 'Only list hubs that were last modified after the time specified.
', 'ListHumanTaskUisRequest$CreationTimeAfter' => 'A filter that returns only human task user interfaces with a creation time greater than or equal to the specified timestamp.
', 'ListHumanTaskUisRequest$CreationTimeBefore' => 'A filter that returns only human task user interfaces that were created before the specified timestamp.
', 'ListHyperParameterTuningJobsRequest$CreationTimeAfter' => 'A filter that returns only tuning jobs that were created after the specified time.
', 'ListHyperParameterTuningJobsRequest$CreationTimeBefore' => 'A filter that returns only tuning jobs that were created before the specified time.
', 'ListHyperParameterTuningJobsRequest$LastModifiedTimeAfter' => 'A filter that returns only tuning jobs that were modified after the specified time.
', 'ListHyperParameterTuningJobsRequest$LastModifiedTimeBefore' => 'A filter that returns only tuning jobs that were modified before the specified time.
', 'ListImageVersionsRequest$CreationTimeAfter' => 'A filter that returns only versions created on or after the specified time.
', 'ListImageVersionsRequest$CreationTimeBefore' => 'A filter that returns only versions created on or before the specified time.
', 'ListImageVersionsRequest$LastModifiedTimeAfter' => 'A filter that returns only versions modified on or after the specified time.
', 'ListImageVersionsRequest$LastModifiedTimeBefore' => 'A filter that returns only versions modified on or before the specified time.
', 'ListImagesRequest$CreationTimeAfter' => 'A filter that returns only images created on or after the specified time.
', 'ListImagesRequest$CreationTimeBefore' => 'A filter that returns only images created on or before the specified time.
', 'ListImagesRequest$LastModifiedTimeAfter' => 'A filter that returns only images modified on or after the specified time.
', 'ListImagesRequest$LastModifiedTimeBefore' => 'A filter that returns only images modified on or before the specified time.
', 'ListInferenceExperimentsRequest$CreationTimeAfter' => 'Selects inference experiments which were created after this timestamp.
', 'ListInferenceExperimentsRequest$CreationTimeBefore' => 'Selects inference experiments which were created before this timestamp.
', 'ListInferenceExperimentsRequest$LastModifiedTimeAfter' => 'Selects inference experiments which were last modified after this timestamp.
', 'ListInferenceExperimentsRequest$LastModifiedTimeBefore' => 'Selects inference experiments which were last modified before this timestamp.
', 'ListLabelingJobsForWorkteamRequest$CreationTimeAfter' => 'A filter that returns only labeling jobs created after the specified time (timestamp).
', 'ListLabelingJobsForWorkteamRequest$CreationTimeBefore' => 'A filter that returns only labeling jobs created before the specified time (timestamp).
', 'ListLabelingJobsRequest$CreationTimeAfter' => 'A filter that returns only labeling jobs created after the specified time (timestamp).
', 'ListLabelingJobsRequest$CreationTimeBefore' => 'A filter that returns only labeling jobs created before the specified time (timestamp).
', 'ListLabelingJobsRequest$LastModifiedTimeAfter' => 'A filter that returns only labeling jobs modified after the specified time (timestamp).
', 'ListLabelingJobsRequest$LastModifiedTimeBefore' => 'A filter that returns only labeling jobs modified before the specified time (timestamp).
', 'ListLineageGroupsRequest$CreatedAfter' => 'A timestamp to filter against lineage groups created after a certain point in time.
', 'ListLineageGroupsRequest$CreatedBefore' => 'A timestamp to filter against lineage groups created before a certain point in time.
', 'ListModelBiasJobDefinitionsRequest$CreationTimeBefore' => 'A filter that returns only model bias jobs created before a specified time.
', 'ListModelBiasJobDefinitionsRequest$CreationTimeAfter' => 'A filter that returns only model bias jobs created after a specified time.
', 'ListModelCardExportJobsRequest$CreationTimeAfter' => 'Only list model card export jobs that were created after the time specified.
', 'ListModelCardExportJobsRequest$CreationTimeBefore' => 'Only list model card export jobs that were created before the time specified.
', 'ListModelCardVersionsRequest$CreationTimeAfter' => 'Only list model card versions that were created after the time specified.
', 'ListModelCardVersionsRequest$CreationTimeBefore' => 'Only list model card versions that were created before the time specified.
', 'ListModelCardsRequest$CreationTimeAfter' => 'Only list model cards that were created after the time specified.
', 'ListModelCardsRequest$CreationTimeBefore' => 'Only list model cards that were created before the time specified.
', 'ListModelExplainabilityJobDefinitionsRequest$CreationTimeBefore' => 'A filter that returns only model explainability jobs created before a specified time.
', 'ListModelExplainabilityJobDefinitionsRequest$CreationTimeAfter' => 'A filter that returns only model explainability jobs created after a specified time.
', 'ListModelQualityJobDefinitionsRequest$CreationTimeBefore' => 'A filter that returns only model quality monitoring job definitions created before the specified time.
', 'ListModelQualityJobDefinitionsRequest$CreationTimeAfter' => 'A filter that returns only model quality monitoring job definitions created after the specified time.
', 'ListModelsInput$CreationTimeBefore' => 'A filter that returns only models created before the specified time (timestamp).
', 'ListModelsInput$CreationTimeAfter' => 'A filter that returns only models with a creation time greater than or equal to the specified time (timestamp).
', 'ListMonitoringAlertHistoryRequest$CreationTimeBefore' => 'A filter that returns only alerts created on or before the specified time.
', 'ListMonitoringAlertHistoryRequest$CreationTimeAfter' => 'A filter that returns only alerts created on or after the specified time.
', 'ListMonitoringExecutionsRequest$ScheduledTimeBefore' => 'Filter for jobs scheduled before a specified time.
', 'ListMonitoringExecutionsRequest$ScheduledTimeAfter' => 'Filter for jobs scheduled after a specified time.
', 'ListMonitoringExecutionsRequest$CreationTimeBefore' => 'A filter that returns only jobs created before a specified time.
', 'ListMonitoringExecutionsRequest$CreationTimeAfter' => 'A filter that returns only jobs created after a specified time.
', 'ListMonitoringExecutionsRequest$LastModifiedTimeBefore' => 'A filter that returns only jobs modified after a specified time.
', 'ListMonitoringExecutionsRequest$LastModifiedTimeAfter' => 'A filter that returns only jobs modified before a specified time.
', 'ListMonitoringSchedulesRequest$CreationTimeBefore' => 'A filter that returns only monitoring schedules created before a specified time.
', 'ListMonitoringSchedulesRequest$CreationTimeAfter' => 'A filter that returns only monitoring schedules created after a specified time.
', 'ListMonitoringSchedulesRequest$LastModifiedTimeBefore' => 'A filter that returns only monitoring schedules modified before a specified time.
', 'ListMonitoringSchedulesRequest$LastModifiedTimeAfter' => 'A filter that returns only monitoring schedules modified after a specified time.
', 'ListPipelineExecutionsRequest$CreatedAfter' => 'A filter that returns the pipeline executions that were created after a specified time.
', 'ListPipelineExecutionsRequest$CreatedBefore' => 'A filter that returns the pipeline executions that were created before a specified time.
', 'ListPipelinesRequest$CreatedAfter' => 'A filter that returns the pipelines that were created after a specified time.
', 'ListPipelinesRequest$CreatedBefore' => 'A filter that returns the pipelines that were created before a specified time.
', 'ListProcessingJobsRequest$CreationTimeAfter' => 'A filter that returns only processing jobs created after the specified time.
', 'ListProcessingJobsRequest$CreationTimeBefore' => 'A filter that returns only processing jobs created after the specified time.
', 'ListProcessingJobsRequest$LastModifiedTimeAfter' => 'A filter that returns only processing jobs modified after the specified time.
', 'ListProcessingJobsRequest$LastModifiedTimeBefore' => 'A filter that returns only processing jobs modified before the specified time.
', 'ListProjectsInput$CreationTimeAfter' => 'A filter that returns the projects that were created after a specified time.
', 'ListProjectsInput$CreationTimeBefore' => 'A filter that returns the projects that were created before a specified time.
', 'ListResourceCatalogsRequest$CreationTimeAfter' => ' Use this parameter to search for ResourceCatalogs created after a specific date and time.
Use this parameter to search for ResourceCatalogs created before a specific date and time.
A filter that returns only Lifecycle Configurations created on or before the specified time.
', 'ListStudioLifecycleConfigsRequest$CreationTimeAfter' => 'A filter that returns only Lifecycle Configurations created on or after the specified time.
', 'ListStudioLifecycleConfigsRequest$ModifiedTimeBefore' => 'A filter that returns only Lifecycle Configurations modified before the specified time.
', 'ListStudioLifecycleConfigsRequest$ModifiedTimeAfter' => 'A filter that returns only Lifecycle Configurations modified after the specified time.
', 'ListTrainingJobsRequest$CreationTimeAfter' => 'A filter that returns only training jobs created after the specified time (timestamp).
', 'ListTrainingJobsRequest$CreationTimeBefore' => 'A filter that returns only training jobs created before the specified time (timestamp).
', 'ListTrainingJobsRequest$LastModifiedTimeAfter' => 'A filter that returns only training jobs modified after the specified time (timestamp).
', 'ListTrainingJobsRequest$LastModifiedTimeBefore' => 'A filter that returns only training jobs modified before the specified time (timestamp).
', 'ListTransformJobsRequest$CreationTimeAfter' => 'A filter that returns only transform jobs created after the specified time.
', 'ListTransformJobsRequest$CreationTimeBefore' => 'A filter that returns only transform jobs created before the specified time.
', 'ListTransformJobsRequest$LastModifiedTimeAfter' => 'A filter that returns only transform jobs modified after the specified time.
', 'ListTransformJobsRequest$LastModifiedTimeBefore' => 'A filter that returns only transform jobs modified before the specified time.
', 'ListTrialComponentsRequest$CreatedAfter' => 'A filter that returns only components created after the specified time.
', 'ListTrialComponentsRequest$CreatedBefore' => 'A filter that returns only components created before the specified time.
', 'ListTrialsRequest$CreatedAfter' => 'A filter that returns only trials created after the specified time.
', 'ListTrialsRequest$CreatedBefore' => 'A filter that returns only trials created before the specified time.
', 'MetricData$Timestamp' => 'The date and time that the algorithm emitted the metric.
', 'Model$CreationTime' => 'A timestamp that indicates when the model was created.
', 'ModelCard$CreationTime' => 'The date and time that the model card was created.
', 'ModelCard$LastModifiedTime' => 'The date and time that the model card was last modified.
', 'ModelCardExportJobSummary$CreatedAt' => 'The date and time that the model card export job was created.
', 'ModelCardExportJobSummary$LastModifiedAt' => 'The date and time that the model card export job was last modified..
', 'ModelCardSummary$CreationTime' => 'The date and time that the model card was created.
', 'ModelCardSummary$LastModifiedTime' => 'The date and time that the model card was last modified.
', 'ModelCardVersionSummary$CreationTime' => 'The date and time that the model card version was created.
', 'ModelCardVersionSummary$LastModifiedTime' => 'The time date and time that the model card version was last modified.
', 'ModelDashboardEndpoint$CreationTime' => 'A timestamp that indicates when the endpoint was created.
', 'ModelDashboardEndpoint$LastModifiedTime' => 'The last time the endpoint was modified.
', 'ModelDashboardModelCard$CreationTime' => 'A timestamp that indicates when the model card was created.
', 'ModelDashboardModelCard$LastModifiedTime' => 'A timestamp that indicates when the model card was last updated.
', 'ModelDashboardMonitoringSchedule$CreationTime' => 'A timestamp that indicates when the monitoring schedule was created.
', 'ModelDashboardMonitoringSchedule$LastModifiedTime' => 'A timestamp that indicates when the monitoring schedule was last updated.
', 'ModelPackage$LastModifiedTime' => 'The last time the model package was modified.
', 'ModelSummary$CreationTime' => 'A timestamp that indicates when the model was created.
', 'MonitoringAlertHistorySummary$CreationTime' => 'A timestamp that indicates when the first alert transition occurred in an alert history. An alert transition can be from status InAlert to OK, or from OK to InAlert.
A timestamp that indicates when a monitor alert was created.
', 'MonitoringAlertSummary$LastModifiedTime' => 'A timestamp that indicates when a monitor alert was last updated.
', 'MonitoringExecutionSummary$ScheduledTime' => 'The time the monitoring job was scheduled.
', 'MonitoringExecutionSummary$CreationTime' => 'The time at which the monitoring job was created.
', 'MonitoringExecutionSummary$LastModifiedTime' => 'A timestamp that indicates the last time the monitoring job was modified.
', 'MonitoringJobDefinitionSummary$CreationTime' => 'The time that the monitoring job was created.
', 'MonitoringSchedule$CreationTime' => 'The time that the monitoring schedule was created.
', 'MonitoringSchedule$LastModifiedTime' => 'The last time the monitoring schedule was changed.
', 'MonitoringScheduleSummary$CreationTime' => 'The creation time of the monitoring schedule.
', 'MonitoringScheduleSummary$LastModifiedTime' => 'The last time the monitoring schedule was modified.
', 'PendingDeploymentSummary$StartTime' => 'The start time of the deployment.
', 'Pipeline$CreationTime' => 'The creation time of the pipeline.
', 'Pipeline$LastModifiedTime' => 'The time that the pipeline was last modified.
', 'Pipeline$LastRunTime' => 'The time when the pipeline was last run.
', 'PipelineExecution$CreationTime' => 'The creation time of the pipeline execution.
', 'PipelineExecution$LastModifiedTime' => 'The time that the pipeline execution was last modified.
', 'PipelineExecutionStep$StartTime' => 'The time that the step started executing.
', 'PipelineExecutionStep$EndTime' => 'The time that the step stopped executing.
', 'PipelineExecutionSummary$StartTime' => 'The start time of the pipeline execution.
', 'PipelineSummary$CreationTime' => 'The creation time of the pipeline.
', 'PipelineSummary$LastModifiedTime' => 'The time that the pipeline was last modified.
', 'PipelineSummary$LastExecutionTime' => 'The last time that a pipeline execution began.
', 'ProcessingJob$ProcessingEndTime' => 'The time that the processing job ended.
', 'ProcessingJob$ProcessingStartTime' => 'The time that the processing job started.
', 'ProcessingJob$LastModifiedTime' => 'The time the processing job was last modified.
', 'ProcessingJob$CreationTime' => 'The time the processing job was created.
', 'ProcessingJobSummary$CreationTime' => 'The time at which the processing job was created.
', 'ProcessingJobSummary$ProcessingEndTime' => 'The time at which the processing job completed.
', 'ProcessingJobSummary$LastModifiedTime' => 'A timestamp that indicates the last time the processing job was modified.
', 'ProductionVariantStatus$StartTime' => 'The start time of the current status change.
', 'ProfilerRuleEvaluationStatus$LastModifiedTime' => 'Timestamp when the rule evaluation status was last modified.
', 'Project$CreationTime' => 'A timestamp specifying when the project was created.
', 'Project$LastModifiedTime' => 'A timestamp container for when the project was last modified.
', 'ProjectSummary$CreationTime' => 'The time that the project was created.
', 'QueryFilters$CreatedBefore' => 'Filter the lineage entities connected to the StartArn(s) by created date.
Filter the lineage entities connected to the StartArn(s) after the create date.
Filter the lineage entities connected to the StartArn(s) before the last modified date.
Filter the lineage entities connected to the StartArn(s) after the last modified date.
The time the ResourceCatalog was created.
A timestamp that shows when the training job transitioned to the current secondary status state.
', 'SecondaryStatusTransition$EndTime' => 'A timestamp that shows when the training job transitioned out of this secondary status state into another secondary status state or when the training job has ended.
', 'StudioLifecycleConfigDetails$CreationTime' => 'The creation time of the Studio Lifecycle Configuration.
', 'StudioLifecycleConfigDetails$LastModifiedTime' => 'This value is equivalent to CreationTime because Studio Lifecycle Configurations are immutable.
', 'TrainingJob$CreationTime' => 'A timestamp that indicates when the training job was created.
', 'TrainingJob$TrainingStartTime' => 'Indicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of TrainingEndTime. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container.
Indicates the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.
A timestamp that indicates when the status of the training job was last modified.
', 'TrainingJobSummary$CreationTime' => 'A timestamp that shows when the training job was created.
', 'TrainingJobSummary$TrainingEndTime' => 'A timestamp that shows when the training job ended. This field is set only if the training job has one of the terminal statuses (Completed, Failed, or Stopped).
Timestamp when the training job was last modified.
', 'TransformJob$CreationTime' => 'A timestamp that shows when the transform Job was created.
', 'TransformJob$TransformStartTime' => 'Indicates when the transform job starts on ML instances. You are billed for the time interval between this time and the value of TransformEndTime.
Indicates when the transform job has been completed, or has stopped or failed. You are billed for the time interval between this time and the value of TransformStartTime.
A timestamp that shows when the transform Job was created.
', 'TransformJobSummary$TransformEndTime' => 'Indicates when the transform job ends on compute instances. For successful jobs and stopped jobs, this is the exact time recorded after the results are uploaded. For failed jobs, this is when Amazon SageMaker detected that the job failed.
', 'TransformJobSummary$LastModifiedTime' => 'Indicates when the transform job was last modified.
', 'Trial$CreationTime' => 'When the trial was created.
', 'Trial$LastModifiedTime' => 'Who last modified the trial.
', 'TrialComponent$StartTime' => 'When the component started.
', 'TrialComponent$EndTime' => 'When the component ended.
', 'TrialComponent$CreationTime' => 'When the component was created.
', 'TrialComponent$LastModifiedTime' => 'When the component was last modified.
', 'TrialComponentMetricSummary$TimeStamp' => 'When the metric was last updated.
', 'TrialComponentSimpleSummary$CreationTime' => 'When the component was created.
', 'TrialComponentSummary$StartTime' => 'When the component started.
', 'TrialComponentSummary$EndTime' => 'When the component ended.
', 'TrialComponentSummary$CreationTime' => 'When the component was created.
', 'TrialComponentSummary$LastModifiedTime' => 'When the component was last modified.
', 'TrialSummary$CreationTime' => 'When the trial was created.
', 'TrialSummary$LastModifiedTime' => 'When the trial was last modified.
', 'UpdateTrialComponentRequest$StartTime' => 'When the component started.
', 'UpdateTrialComponentRequest$EndTime' => 'When the component ended.
', 'Workforce$LastUpdatedDate' => 'The most recent date that UpdateWorkforce was used to successfully add one or more IP address ranges (CIDRs) to a private workforce\'s allow list.
', 'Workforce$CreateDate' => 'The date that the workforce is created.
', 'Workteam$CreateDate' => 'The date and time that the work team was created (timestamp).
', 'Workteam$LastUpdatedDate' => 'The date and time that the work team was last updated (timestamp).
', ], ], 'TimestampAttributeName' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesConfig$TimestampAttributeName' => 'The name of the column indicating a point in time at which the target value of a given item is recorded.
', ], ], 'TrafficDurationInSeconds' => [ 'base' => NULL, 'refs' => [ 'Phase$DurationInSeconds' => 'Specifies how long a traffic phase should be. For custom load tests, the value should be between 120 and 3600. This value should not exceed JobDurationInSeconds.
Defines how long each traffic step should be.
', ], ], 'TrafficPattern' => [ 'base' => 'Defines the traffic pattern of the load test.
', 'refs' => [ 'RecommendationJobInputConfig$TrafficPattern' => 'Specifies the traffic pattern of the job.
', ], ], 'TrafficRoutingConfig' => [ 'base' => 'Defines the traffic routing strategy during an endpoint deployment to shift traffic from the old fleet to the new fleet.
', 'refs' => [ 'BlueGreenUpdatePolicy$TrafficRoutingConfiguration' => 'Defines the traffic routing strategy to shift traffic from the old fleet to the new fleet during an endpoint deployment.
', ], ], 'TrafficRoutingConfigType' => [ 'base' => NULL, 'refs' => [ 'TrafficRoutingConfig$Type' => 'Traffic routing strategy type.
ALL_AT_ONCE: Endpoint traffic shifts to the new fleet in a single step.
CANARY: Endpoint traffic shifts to the new fleet in two steps. The first step is the canary, which is a small portion of the traffic. The second step is the remainder of the traffic.
LINEAR: Endpoint traffic shifts to the new fleet in n steps of a configurable size.
Defines the traffic patterns. Choose either PHASES or STAIRS.
The arguments for a container used to run a training job. See How Amazon SageMaker Runs Your Training Image for additional information.
', ], ], 'TrainingContainerEntrypoint' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSpecification$ContainerEntrypoint' => 'The entrypoint script for a Docker container used to run a training job. This script takes precedence over the default train processing instructions. See How Amazon SageMaker Runs Your Training Image for more information.
', ], ], 'TrainingContainerEntrypointString' => [ 'base' => NULL, 'refs' => [ 'TrainingContainerEntrypoint$member' => NULL, ], ], 'TrainingEnvironmentKey' => [ 'base' => NULL, 'refs' => [ 'TrainingEnvironmentMap$key' => NULL, ], ], 'TrainingEnvironmentMap' => [ 'base' => NULL, 'refs' => [ 'CreateTrainingJobRequest$Environment' => 'The environment variables to set in the Docker container.
', 'DescribeTrainingJobResponse$Environment' => 'The environment variables to set in the Docker container.
', 'TrainingJob$Environment' => 'The environment variables to set in the Docker container.
', ], ], 'TrainingEnvironmentValue' => [ 'base' => NULL, 'refs' => [ 'TrainingEnvironmentMap$value' => NULL, ], ], 'TrainingImageConfig' => [ 'base' => 'The configuration to use an image from a private Docker registry for a training job.
', 'refs' => [ 'AlgorithmSpecification$TrainingImageConfig' => 'The configuration to use an image from a private Docker registry for a training job.
', ], ], 'TrainingInputMode' => [ 'base' => 'The training input mode that the algorithm supports. For more information about input modes, see Algorithms.
Pipe mode
If an algorithm supports Pipe mode, Amazon SageMaker streams data directly from Amazon S3 to the container.
File mode
If an algorithm supports File mode, SageMaker downloads the training data from S3 to the provisioned ML storage volume, and mounts the directory to the Docker volume for the training container.
You must provision the ML storage volume with sufficient capacity to accommodate the data downloaded from S3. In addition to the training data, the ML storage volume also stores the output model. The algorithm container uses the ML storage volume to also store intermediate information, if any.
For distributed algorithms, training data is distributed uniformly. Your training duration is predictable if the input data objects sizes are approximately the same. SageMaker does not split the files any further for model training. If the object sizes are skewed, training won\'t be optimal as the data distribution is also skewed when one host in a training cluster is overloaded, thus becoming a bottleneck in training.
FastFile mode
If an algorithm supports FastFile mode, SageMaker streams data directly from S3 to the container with no code changes, and provides file system access to the data. Users can author their training script to interact with these files as if they were stored on disk.
FastFile mode works best when the data is read sequentially. Augmented manifest files aren\'t supported. The startup time is lower when there are fewer files in the S3 bucket provided.
(Optional) The input mode to use for the data channel in a training job. If you don\'t set a value for InputMode, SageMaker uses the value set for TrainingInputMode. Use this parameter to override the TrainingInputMode setting in a AlgorithmSpecification request when you have a channel that needs a different input mode from the training job\'s general setting. To download the data from Amazon Simple Storage Service (Amazon S3) to the provisioned ML storage volume, and mount the directory to a Docker volume, use File input mode. To stream data directly from Amazon S3 to the container, choose Pipe input mode.
To use a model for incremental training, choose File input model.
The number of instances of the type specified by InstanceType. Choose an instance count larger than 1 for distributed training algorithms. See Step 2: Launch a SageMaker Distributed Training Job Using the SageMaker Python SDK for more information.
The number of compute instances of type InstanceType to use. For distributed training, select a value greater than 1.
Specifies the number of instances of the instance group.
', 'ResourceConfig$InstanceCount' => 'The number of ML compute instances to use. For distributed training, provide a value greater than 1.
', ], ], 'TrainingInstanceType' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTuningInstanceConfig$InstanceType' => 'The instance type used for processing of hyperparameter optimization jobs. Choose from general purpose (no GPUs) instance types: ml.m5.xlarge, ml.m5.2xlarge, and ml.m5.4xlarge or compute optimized (no GPUs) instance types: ml.c5.xlarge and ml.c5.2xlarge. For more information about instance types, see instance type descriptions.
', 'HyperParameterTuningResourceConfig$InstanceType' => 'The instance type used to run hyperparameter optimization tuning jobs. See descriptions of instance types for more information.
', 'InstanceGroup$InstanceType' => 'Specifies the instance type of the instance group.
', 'ResourceConfig$InstanceType' => 'The ML compute instance type.
SageMaker Training on Amazon Elastic Compute Cloud (EC2) P4de instances is in preview release starting December 9th, 2022.
Amazon EC2 P4de instances (currently in preview) are powered by 8 NVIDIA A100 GPUs with 80GB high-performance HBM2e GPU memory, which accelerate the speed of training ML models that need to be trained on large datasets of high-resolution data. In this preview release, Amazon SageMaker supports ML training jobs on P4de instances (ml.p4de.24xlarge) to reduce model training time. The ml.p4de.24xlarge instances are available in the following Amazon Web Services Regions.
US East (N. Virginia) (us-east-1)
US West (Oregon) (us-west-2)
To request quota limit increase and start using P4de instances, contact the SageMaker Training service team through your account team.
A list of the instance types that this algorithm can use for training.
', ], ], 'TrainingJob' => [ 'base' => 'Contains information about a training job.
', 'refs' => [ 'SearchRecord$TrainingJob' => 'The properties of a training job.
', 'TrialComponentSourceDetail$TrainingJob' => 'Information about a training job that\'s the source of a trial component.
', ], ], 'TrainingJobArn' => [ 'base' => NULL, 'refs' => [ 'CreateTrainingJobResponse$TrainingJobArn' => 'The Amazon Resource Name (ARN) of the training job.
', 'DescribeProcessingJobResponse$TrainingJobArn' => 'The ARN of a training job associated with this processing job.
', 'DescribeTrainingJobResponse$TrainingJobArn' => 'The Amazon Resource Name (ARN) of the training job.
', 'HyperParameterTrainingJobSummary$TrainingJobArn' => 'The Amazon Resource Name (ARN) of the training job.
', 'ProcessingJob$TrainingJobArn' => 'The ARN of the training job associated with this processing job.
', 'TrainingJob$TrainingJobArn' => 'The Amazon Resource Name (ARN) of the training job.
', 'TrainingJobStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the training job that was run by this step execution.
', 'TrainingJobSummary$TrainingJobArn' => 'The Amazon Resource Name (ARN) of the training job.
', 'UpdateTrainingJobResponse$TrainingJobArn' => 'The Amazon Resource Name (ARN) of the training job.
', ], ], 'TrainingJobDefinition' => [ 'base' => 'Defines the input needed to run a training job using the algorithm.
', 'refs' => [ 'AlgorithmValidationProfile$TrainingJobDefinition' => 'The TrainingJobDefinition object that describes the training job that SageMaker runs to validate your algorithm.
Specifies whether to use early stopping for training jobs launched by the hyperparameter tuning job. Because the Hyperband strategy has its own advanced internal early stopping mechanism, TrainingJobEarlyStoppingType must be OFF to use Hyperband. This parameter can take on one of the following values (the default value is OFF):
Training jobs launched by the hyperparameter tuning job do not use early stopping.
SageMaker stops training jobs launched by the hyperparameter tuning job when they are unlikely to perform better than previously completed training jobs. For more information, see Stop Training Jobs Early.
The name of the training job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
', 'DescribeTrainingJobRequest$TrainingJobName' => 'The name of the training job.
', 'DescribeTrainingJobResponse$TrainingJobName' => 'Name of the model training job.
', 'HyperParameterTrainingJobSummary$TrainingJobName' => 'The name of the training job.
', 'StopTrainingJobRequest$TrainingJobName' => 'The name of the training job to stop.
', 'TrainingJob$TrainingJobName' => 'The name of the training job.
', 'TrainingJobSummary$TrainingJobName' => 'The name of the training job that you want a summary for.
', 'UpdateTrainingJobRequest$TrainingJobName' => 'The name of a training job to update the Debugger profiling configuration.
', 'WarmPoolStatus$ReusedByJob' => 'The name of the matching training job that reused the warm pool.
', ], ], 'TrainingJobSortByOptions' => [ 'base' => NULL, 'refs' => [ 'ListTrainingJobsForHyperParameterTuningJobRequest$SortBy' => 'The field to sort results by. The default is Name.
If the value of this field is FinalObjectiveMetricValue, any training jobs that did not return an objective metric are not listed.
The status of the training job.
SageMaker provides the following training job statuses:
InProgress - The training is in progress.
Completed - The training job has completed.
Failed - The training job has failed. To see the reason for the failure, see the FailureReason field in the response to a DescribeTrainingJobResponse call.
Stopping - The training job is stopping.
Stopped - The training job has stopped.
For more detailed information, see SecondaryStatus.
The status of the training job.
', 'ListTrainingJobsForHyperParameterTuningJobRequest$StatusEquals' => 'A filter that returns only training jobs with the specified status.
', 'ListTrainingJobsRequest$StatusEquals' => 'A filter that retrieves only training jobs with a specific status.
', 'TrainingJob$TrainingJobStatus' => 'The status of the training job.
Training job statuses are:
InProgress - The training is in progress.
Completed - The training job has completed.
Failed - The training job has failed. To see the reason for the failure, see the FailureReason field in the response to a DescribeTrainingJobResponse call.
Stopping - The training job is stopping.
Stopped - The training job has stopped.
For more detailed information, see SecondaryStatus.
The status of the training job.
', ], ], 'TrainingJobStatusCounter' => [ 'base' => NULL, 'refs' => [ 'TrainingJobStatusCounters$Completed' => 'The number of completed training jobs launched by the hyperparameter tuning job.
', 'TrainingJobStatusCounters$InProgress' => 'The number of in-progress training jobs launched by a hyperparameter tuning job.
', 'TrainingJobStatusCounters$RetryableError' => 'The number of training jobs that failed, but can be retried. A failed training job can be retried only if it failed because an internal service error occurred.
', 'TrainingJobStatusCounters$NonRetryableError' => 'The number of training jobs that failed and can\'t be retried. A failed training job can\'t be retried if it failed because a client error occurred.
', 'TrainingJobStatusCounters$Stopped' => 'The number of training jobs launched by a hyperparameter tuning job that were manually stopped.
', ], ], 'TrainingJobStatusCounters' => [ 'base' => 'The numbers of training jobs launched by a hyperparameter tuning job, categorized by status.
', 'refs' => [ 'DescribeHyperParameterTuningJobResponse$TrainingJobStatusCounters' => 'The TrainingJobStatusCounters object that specifies the number of training jobs, categorized by status, that this tuning job launched.
', 'HyperParameterTuningJobSearchEntity$TrainingJobStatusCounters' => NULL, 'HyperParameterTuningJobSummary$TrainingJobStatusCounters' => 'The TrainingJobStatusCounters object that specifies the numbers of training jobs, categorized by status, that this tuning job launched.
', ], ], 'TrainingJobStepMetadata' => [ 'base' => 'Metadata for a training job step.
', 'refs' => [ 'PipelineExecutionStepMetadata$TrainingJob' => 'The Amazon Resource Name (ARN) of the training job that was run by this step execution.
', ], ], 'TrainingJobSummaries' => [ 'base' => NULL, 'refs' => [ 'ListTrainingJobsResponse$TrainingJobSummaries' => 'An array of TrainingJobSummary objects, each listing a training job.
Provides summary information about a training job.
', 'refs' => [ 'TrainingJobSummaries$member' => NULL, ], ], 'TrainingRepositoryAccessMode' => [ 'base' => NULL, 'refs' => [ 'TrainingImageConfig$TrainingRepositoryAccessMode' => 'The method that your training job will use to gain access to the images in your private Docker registry. For access to an image in a private Docker registry, set to Vpc.
An object containing authentication information for a private Docker registry.
', 'refs' => [ 'TrainingImageConfig$TrainingRepositoryAuthConfig' => 'An object containing authentication information for a private Docker registry containing your training images.
', ], ], 'TrainingRepositoryCredentialsProviderArn' => [ 'base' => NULL, 'refs' => [ 'TrainingRepositoryAuthConfig$TrainingRepositoryCredentialsProviderArn' => 'The Amazon Resource Name (ARN) of an Amazon Web Services Lambda function used to give SageMaker access credentials to your private Docker registry.
', ], ], 'TrainingSpecification' => [ 'base' => 'Defines how the algorithm is used for a training job.
', 'refs' => [ 'CreateAlgorithmInput$TrainingSpecification' => 'Specifies details about training jobs run by this algorithm, including the following:
The Amazon ECR path of the container and the version digest of the algorithm.
The hyperparameters that the algorithm supports.
The instance types that the algorithm supports for training.
Whether the algorithm supports distributed training.
The metrics that the algorithm emits to Amazon CloudWatch.
Which metrics that the algorithm emits can be used as the objective metric for hyperparameter tuning jobs.
The input channels that the algorithm supports for training data. For example, an algorithm might support train, validation, and test channels.
Details about training jobs run by this algorithm.
', ], ], 'TrainingTimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'DescribeTrainingJobResponse$TrainingTimeInSeconds' => 'The training time in seconds.
', 'TrainingJob$TrainingTimeInSeconds' => 'The training time in seconds.
', ], ], 'TransformDataSource' => [ 'base' => 'Describes the location of the channel data.
', 'refs' => [ 'TransformInput$DataSource' => 'Describes the location of the channel data, which is, the S3 location of the input data that the model can consume.
', ], ], 'TransformEnvironmentKey' => [ 'base' => NULL, 'refs' => [ 'TransformEnvironmentMap$key' => NULL, ], ], 'TransformEnvironmentMap' => [ 'base' => NULL, 'refs' => [ 'CreateTransformJobRequest$Environment' => 'The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
', 'DescribeTransformJobResponse$Environment' => 'The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
', 'TransformJob$Environment' => 'The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
', 'TransformJobDefinition$Environment' => 'The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
', ], ], 'TransformEnvironmentValue' => [ 'base' => NULL, 'refs' => [ 'TransformEnvironmentMap$value' => NULL, ], ], 'TransformInput' => [ 'base' => 'Describes the input source of a transform job and the way the transform job consumes it.
', 'refs' => [ 'CreateTransformJobRequest$TransformInput' => 'Describes the input source and the way the transform job consumes it.
', 'DescribeTransformJobResponse$TransformInput' => 'Describes the dataset to be transformed and the Amazon S3 location where it is stored.
', 'TransformJob$TransformInput' => NULL, 'TransformJobDefinition$TransformInput' => 'A description of the input source and the way the transform job consumes it.
', ], ], 'TransformInstanceCount' => [ 'base' => NULL, 'refs' => [ 'TransformResources$InstanceCount' => 'The number of ML compute instances to use in the transform job. The default value is 1, and the maximum is 100. For distributed transform jobs, specify a value greater than 1.
The ML compute instance type for the transform job. If you are using built-in algorithms to transform moderately sized datasets, we recommend using ml.m4.xlarge or ml.m5.largeinstance types.
A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.
', 'InferenceSpecification$SupportedTransformInstanceTypes' => 'A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.
This parameter is required for unversioned models, and optional for versioned models.
', ], ], 'TransformJob' => [ 'base' => 'A batch transform job. For information about SageMaker batch transform, see Use Batch Transform.
', 'refs' => [ 'ModelDashboardModel$LastBatchTransformJob' => NULL, 'TrialComponentSourceDetail$TransformJob' => 'Information about a transform job that\'s the source of a trial component.
', ], ], 'TransformJobArn' => [ 'base' => NULL, 'refs' => [ 'CreateTransformJobResponse$TransformJobArn' => 'The Amazon Resource Name (ARN) of the transform job.
', 'DescribeTransformJobResponse$TransformJobArn' => 'The Amazon Resource Name (ARN) of the transform job.
', 'TransformJob$TransformJobArn' => 'The Amazon Resource Name (ARN) of the transform job.
', 'TransformJobStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the transform job that was run by this step execution.
', 'TransformJobSummary$TransformJobArn' => 'The Amazon Resource Name (ARN) of the transform job.
', ], ], 'TransformJobDefinition' => [ 'base' => 'Defines the input needed to run a transform job using the inference specification specified in the algorithm.
', 'refs' => [ 'AlgorithmValidationProfile$TransformJobDefinition' => 'The TransformJobDefinition object that describes the transform job that SageMaker runs to validate your algorithm.
The TransformJobDefinition object that describes the transform job used for the validation of the model package.
The name of the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
', 'DescribeTransformJobRequest$TransformJobName' => 'The name of the transform job that you want to view details of.
', 'DescribeTransformJobResponse$TransformJobName' => 'The name of the transform job.
', 'StopTransformJobRequest$TransformJobName' => 'The name of the batch transform job to stop.
', 'TransformJob$TransformJobName' => 'The name of the transform job.
', 'TransformJobSummary$TransformJobName' => 'The name of the transform job.
', ], ], 'TransformJobStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeTransformJobResponse$TransformJobStatus' => 'The status of the transform job. If the transform job failed, the reason is returned in the FailureReason field.
A filter that retrieves only transform jobs with a specific status.
', 'TransformJob$TransformJobStatus' => 'The status of the transform job.
Transform job statuses are:
InProgress - The job is in progress.
Completed - The job has completed.
Failed - The transform job has failed. To see the reason for the failure, see the FailureReason field in the response to a DescribeTransformJob call.
Stopping - The transform job is stopping.
Stopped - The transform job has stopped.
The status of the transform job.
', ], ], 'TransformJobStepMetadata' => [ 'base' => 'Metadata for a transform job step.
', 'refs' => [ 'PipelineExecutionStepMetadata$TransformJob' => 'The Amazon Resource Name (ARN) of the transform job that was run by this step execution.
', ], ], 'TransformJobSummaries' => [ 'base' => NULL, 'refs' => [ 'ListTransformJobsResponse$TransformJobSummaries' => 'An array of TransformJobSummary objects.
Provides a summary of a transform job. Multiple TransformJobSummary objects are returned as a list after in response to a ListTransformJobs call.
Describes the results of a transform job.
', 'refs' => [ 'CreateTransformJobRequest$TransformOutput' => 'Describes the results of the transform job.
', 'DescribeTransformJobResponse$TransformOutput' => 'Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
', 'TransformJob$TransformOutput' => NULL, 'TransformJobDefinition$TransformOutput' => 'Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
', ], ], 'TransformResources' => [ 'base' => 'Describes the resources, including ML instance types and ML instance count, to use for transform job.
', 'refs' => [ 'CreateTransformJobRequest$TransformResources' => 'Describes the resources, including ML instance types and ML instance count, to use for the transform job.
', 'DescribeTransformJobResponse$TransformResources' => 'Describes the resources, including ML instance types and ML instance count, to use for the transform job.
', 'TransformJob$TransformResources' => NULL, 'TransformJobDefinition$TransformResources' => 'Identifies the ML compute instances for the transform job.
', ], ], 'TransformS3DataSource' => [ 'base' => 'Describes the S3 data source.
', 'refs' => [ 'TransformDataSource$S3DataSource' => 'The S3 location of the data source that is associated with a channel.
', ], ], 'TransformationAttributeName' => [ 'base' => NULL, 'refs' => [ 'AggregationTransformations$key' => NULL, 'FillingTransformations$key' => NULL, ], ], 'Trial' => [ 'base' => 'The properties of a trial as returned by the Search API.
', 'refs' => [ 'SearchRecord$Trial' => 'The properties of a trial.
', ], ], 'TrialArn' => [ 'base' => NULL, 'refs' => [ 'AssociateTrialComponentResponse$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', 'CreateTrialResponse$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', 'DeleteTrialResponse$TrialArn' => 'The Amazon Resource Name (ARN) of the trial that is being deleted.
', 'DescribeTrialResponse$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', 'DisassociateTrialComponentResponse$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', 'Trial$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', 'TrialSummary$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', 'UpdateTrialResponse$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', ], ], 'TrialComponent' => [ 'base' => 'The properties of a trial component as returned by the Search API.
', 'refs' => [ 'SearchRecord$TrialComponent' => 'The properties of a trial component.
', ], ], 'TrialComponentArn' => [ 'base' => NULL, 'refs' => [ 'AssociateTrialComponentResponse$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'CreateTrialComponentResponse$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'DeleteTrialComponentResponse$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the component is being deleted.
', 'DescribeTrialComponentResponse$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'DisassociateTrialComponentResponse$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'TrialComponent$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'TrialComponentSimpleSummary$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'TrialComponentSummary$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'UpdateTrialComponentResponse$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', ], ], 'TrialComponentArtifact' => [ 'base' => 'Represents an input or output artifact of a trial component. You specify TrialComponentArtifact as part of the InputArtifacts and OutputArtifacts parameters in the CreateTrialComponent request.
Examples of input artifacts are datasets, algorithms, hyperparameters, source code, and instance types. Examples of output artifacts are metrics, snapshots, logs, and images.
', 'refs' => [ 'TrialComponentArtifacts$value' => NULL, ], ], 'TrialComponentArtifactValue' => [ 'base' => NULL, 'refs' => [ 'TrialComponentArtifact$Value' => 'The location of the artifact.
', ], ], 'TrialComponentArtifacts' => [ 'base' => NULL, 'refs' => [ 'CreateTrialComponentRequest$InputArtifacts' => 'The input artifacts for the component. Examples of input artifacts are datasets, algorithms, hyperparameters, source code, and instance types.
', 'CreateTrialComponentRequest$OutputArtifacts' => 'The output artifacts for the component. Examples of output artifacts are metrics, snapshots, logs, and images.
', 'DescribeTrialComponentResponse$InputArtifacts' => 'The input artifacts of the component.
', 'DescribeTrialComponentResponse$OutputArtifacts' => 'The output artifacts of the component.
', 'TrialComponent$InputArtifacts' => 'The input artifacts of the component.
', 'TrialComponent$OutputArtifacts' => 'The output artifacts of the component.
', 'UpdateTrialComponentRequest$InputArtifacts' => 'Replaces all of the component\'s input artifacts with the specified artifacts or adds new input artifacts. Existing input artifacts are replaced if the trial component is updated with an identical input artifact key.
', 'UpdateTrialComponentRequest$OutputArtifacts' => 'Replaces all of the component\'s output artifacts with the specified artifacts or adds new output artifacts. Existing output artifacts are replaced if the trial component is updated with an identical output artifact key.
', ], ], 'TrialComponentKey256' => [ 'base' => NULL, 'refs' => [ 'ListTrialComponentKey256$member' => NULL, 'TrialComponentParameters$key' => NULL, ], ], 'TrialComponentKey64' => [ 'base' => NULL, 'refs' => [ 'TrialComponentArtifacts$key' => NULL, ], ], 'TrialComponentMetricSummaries' => [ 'base' => NULL, 'refs' => [ 'DescribeTrialComponentResponse$Metrics' => 'The metrics for the component.
', 'TrialComponent$Metrics' => 'The metrics for the component.
', ], ], 'TrialComponentMetricSummary' => [ 'base' => 'A summary of the metrics of a trial component.
', 'refs' => [ 'TrialComponentMetricSummaries$member' => NULL, ], ], 'TrialComponentParameterValue' => [ 'base' => 'The value of a hyperparameter. Only one of NumberValue or StringValue can be specified.
This object is specified in the CreateTrialComponent request.
', 'refs' => [ 'TrialComponentParameters$value' => NULL, ], ], 'TrialComponentParameters' => [ 'base' => NULL, 'refs' => [ 'CreateTrialComponentRequest$Parameters' => 'The hyperparameters for the component.
', 'DescribeTrialComponentResponse$Parameters' => 'The hyperparameters of the component.
', 'TrialComponent$Parameters' => 'The hyperparameters of the component.
', 'UpdateTrialComponentRequest$Parameters' => 'Replaces all of the component\'s hyperparameters with the specified hyperparameters or add new hyperparameters. Existing hyperparameters are replaced if the trial component is updated with an identical hyperparameter key.
', ], ], 'TrialComponentPrimaryStatus' => [ 'base' => NULL, 'refs' => [ 'TrialComponentStatus$PrimaryStatus' => 'The status of the trial component.
', ], ], 'TrialComponentSimpleSummaries' => [ 'base' => NULL, 'refs' => [ 'Trial$TrialComponentSummaries' => 'A list of the components associated with the trial. For each component, a summary of the component\'s properties is included.
', ], ], 'TrialComponentSimpleSummary' => [ 'base' => 'A short summary of a trial component.
', 'refs' => [ 'TrialComponentSimpleSummaries$member' => NULL, ], ], 'TrialComponentSource' => [ 'base' => 'The Amazon Resource Name (ARN) and job type of the source of a trial component.
', 'refs' => [ 'DescribeTrialComponentResponse$Source' => 'The Amazon Resource Name (ARN) of the source and, optionally, the job type.
', 'TrialComponent$Source' => 'The Amazon Resource Name (ARN) and job type of the source of the component.
', 'TrialComponentSimpleSummary$TrialComponentSource' => NULL, 'TrialComponentSources$member' => NULL, 'TrialComponentSummary$TrialComponentSource' => NULL, ], ], 'TrialComponentSourceArn' => [ 'base' => NULL, 'refs' => [ 'TrialComponentMetricSummary$SourceArn' => 'The Amazon Resource Name (ARN) of the source.
', 'TrialComponentSource$SourceArn' => 'The source Amazon Resource Name (ARN).
', 'TrialComponentSourceDetail$SourceArn' => 'The Amazon Resource Name (ARN) of the source.
', ], ], 'TrialComponentSourceDetail' => [ 'base' => 'Detailed information about the source of a trial component. Either ProcessingJob or TrainingJob is returned.
Details of the source of the component.
', ], ], 'TrialComponentSources' => [ 'base' => NULL, 'refs' => [ 'DescribeTrialComponentResponse$Sources' => 'A list of ARNs and, if applicable, job types for multiple sources of an experiment run.
', ], ], 'TrialComponentStatus' => [ 'base' => 'The status of the trial component.
', 'refs' => [ 'CreateTrialComponentRequest$Status' => 'The status of the component. States include:
InProgress
Completed
Failed
The status of the component. States include:
InProgress
Completed
Failed
The status of the component. States include:
InProgress
Completed
Failed
The new status of the component.
', ], ], 'TrialComponentStatusMessage' => [ 'base' => NULL, 'refs' => [ 'TrialComponentStatus$Message' => 'If the component failed, a message describing why.
', ], ], 'TrialComponentSummaries' => [ 'base' => NULL, 'refs' => [ 'ListTrialComponentsResponse$TrialComponentSummaries' => 'A list of the summaries of your trial components.
', ], ], 'TrialComponentSummary' => [ 'base' => 'A summary of the properties of a trial component. To get all the properties, call the DescribeTrialComponent API and provide the TrialComponentName.
The source of the trial.
', 'refs' => [ 'DescribeTrialResponse$Source' => 'The Amazon Resource Name (ARN) of the source and, optionally, the job type.
', 'Trial$Source' => NULL, 'TrialSummary$TrialSource' => NULL, ], ], 'TrialSourceArn' => [ 'base' => NULL, 'refs' => [ 'TrialSource$SourceArn' => 'The Amazon Resource Name (ARN) of the source.
', ], ], 'TrialSummaries' => [ 'base' => NULL, 'refs' => [ 'ListTrialsResponse$TrialSummaries' => 'A list of the summaries of your trials.
', ], ], 'TrialSummary' => [ 'base' => 'A summary of the properties of a trial. To get the complete set of properties, call the DescribeTrial API and provide the TrialName.
Time to live duration, where the record is hard deleted after the expiration time is reached; ExpiresAt = EventTime + TtlDuration. For information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
Time to live duration, where the record is hard deleted after the expiration time is reached; ExpiresAt = EventTime + TtlDuration. For information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
Time to live duration, where the record is hard deleted after the expiration time is reached; ExpiresAt = EventTime + TtlDuration. For information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
TtlDuration time unit.
TtlDuration time value.
The job completion criteria.
', 'refs' => [ 'HyperParameterTuningJobConfig$TuningJobCompletionCriteria' => 'The tuning job\'s completion criteria.
', ], ], 'TuningJobStepMetaData' => [ 'base' => 'Metadata for a tuning step.
', 'refs' => [ 'PipelineExecutionStepMetadata$TuningJob' => 'The Amazon Resource Name (ARN) of the tuning job that was run by this step execution.
', ], ], 'USD' => [ 'base' => 'Represents an amount of money in United States dollars.
', 'refs' => [ 'PublicWorkforceTaskPrice$AmountInUsd' => 'Defines the amount of money paid to an Amazon Mechanical Turk worker in United States dollars.
', ], ], 'UiConfig' => [ 'base' => 'Provided configuration information for the worker UI for a labeling job. Provide either HumanTaskUiArn or UiTemplateS3Uri.
For named entity recognition, 3D point cloud and video frame labeling jobs, use HumanTaskUiArn.
For all other Ground Truth built-in task types and custom task types, use UiTemplateS3Uri to specify the location of a worker task template in Amazon S3.
Information about the user interface that workers use to complete the labeling task.
', ], ], 'UiTemplate' => [ 'base' => 'The Liquid template for the worker user interface.
', 'refs' => [ 'CreateHumanTaskUiRequest$UiTemplate' => NULL, 'RenderUiTemplateRequest$UiTemplate' => 'A Template object containing the worker UI template to render.
Container for user interface template information.
', 'refs' => [ 'DescribeHumanTaskUiResponse$UiTemplate' => NULL, ], ], 'UpdateActionRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateActionResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateAppImageConfigRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateAppImageConfigResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateArtifactRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateArtifactResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateCodeRepositoryInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateCodeRepositoryOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateContextRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateContextResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateDeviceFleetRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateDevicesRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateDomainRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateDomainResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateEndpointInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateEndpointOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateEndpointWeightsAndCapacitiesInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateEndpointWeightsAndCapacitiesOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateFeatureGroupRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateFeatureGroupResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateFeatureMetadataRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateHubRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateHubResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateImageRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateImageResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateImageVersionRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateImageVersionResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateInferenceExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateInferenceExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateModelCardRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateModelCardResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateModelPackageInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateModelPackageOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateMonitoringAlertRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateMonitoringAlertResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateMonitoringScheduleRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateMonitoringScheduleResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateNotebookInstanceInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateNotebookInstanceLifecycleConfigInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateNotebookInstanceLifecycleConfigOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateNotebookInstanceOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdatePipelineExecutionRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdatePipelineExecutionResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdatePipelineRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdatePipelineResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateProjectInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateProjectOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateSpaceRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateSpaceResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateTrainingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateTrainingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateTrialComponentRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateTrialComponentResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateTrialRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateTrialResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateUserProfileRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateUserProfileResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateWorkforceRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateWorkforceResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateWorkteamRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateWorkteamResponse' => [ 'base' => NULL, 'refs' => [], ], 'Url' => [ 'base' => NULL, 'refs' => [ 'AutoMLContainerDefinition$ModelDataUrl' => 'The location of the model artifacts. For more information, see ContainerDefinition.
', 'ClarifyShapBaselineConfig$ShapBaselineUri' => 'The uniform resource identifier (URI) of the S3 bucket where the SHAP baseline file is stored. The format of the SHAP baseline file should be the same format as the format of the training dataset. For example, if the training dataset is in CSV format, and each record in the training dataset has four features, and all features are numerical, then the baseline file should also have this same format. Each record should contain only the features. If you are using a virtual private cloud (VPC), the ShapBaselineUri should be accessible to the VPC. For more information about setting up endpoints with Amazon Virtual Private Cloud, see Give SageMaker access to Resources in your Amazon Virtual Private Cloud.
The S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix). The S3 path is required for SageMaker built-in algorithms, but not if you use your own algorithms. For more information on built-in algorithms, see Common Parameters.
The model artifacts must be in an S3 bucket that is in the same region as the model or endpoint you are creating.
If you provide a value for this parameter, SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you provide. Amazon Web Services STS is activated in your Amazon Web Services account by default. If you previously deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see Activating and Deactivating Amazon Web Services STS in an Amazon Web Services Region in the Amazon Web Services Identity and Access Management User Guide.
If you use a built-in algorithm to create a model, SageMaker requires that you provide a S3 path to the model artifacts in ModelDataUrl.
The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
The model artifacts must be in an S3 bucket that is in the same region as the model package.
The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
The model artifacts must be in an S3 bucket that is in the same Amazon Web Services region as the algorithm.
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
', 'refs' => [ 'AssociationSummary$CreatedBy' => NULL, 'DescribeActionResponse$CreatedBy' => NULL, 'DescribeActionResponse$LastModifiedBy' => NULL, 'DescribeArtifactResponse$CreatedBy' => NULL, 'DescribeArtifactResponse$LastModifiedBy' => NULL, 'DescribeContextResponse$CreatedBy' => NULL, 'DescribeContextResponse$LastModifiedBy' => NULL, 'DescribeExperimentResponse$CreatedBy' => 'Who created the experiment.
', 'DescribeExperimentResponse$LastModifiedBy' => 'Who last modified the experiment.
', 'DescribeLineageGroupResponse$CreatedBy' => NULL, 'DescribeLineageGroupResponse$LastModifiedBy' => NULL, 'DescribeModelCardResponse$CreatedBy' => NULL, 'DescribeModelCardResponse$LastModifiedBy' => NULL, 'DescribeModelPackageGroupOutput$CreatedBy' => NULL, 'DescribeModelPackageOutput$CreatedBy' => NULL, 'DescribeModelPackageOutput$LastModifiedBy' => NULL, 'DescribePipelineExecutionResponse$CreatedBy' => NULL, 'DescribePipelineExecutionResponse$LastModifiedBy' => NULL, 'DescribePipelineResponse$CreatedBy' => NULL, 'DescribePipelineResponse$LastModifiedBy' => NULL, 'DescribeProjectOutput$CreatedBy' => NULL, 'DescribeProjectOutput$LastModifiedBy' => NULL, 'DescribeTrialComponentResponse$CreatedBy' => 'Who created the trial component.
', 'DescribeTrialComponentResponse$LastModifiedBy' => 'Who last modified the component.
', 'DescribeTrialResponse$CreatedBy' => 'Who created the trial.
', 'DescribeTrialResponse$LastModifiedBy' => 'Who last modified the trial.
', 'Experiment$CreatedBy' => 'Who created the experiment.
', 'Experiment$LastModifiedBy' => NULL, 'ModelCard$CreatedBy' => NULL, 'ModelCard$LastModifiedBy' => NULL, 'ModelDashboardModelCard$CreatedBy' => NULL, 'ModelDashboardModelCard$LastModifiedBy' => NULL, 'ModelPackage$CreatedBy' => 'Information about the user who created or modified an experiment, trial, trial component, lineage group, or project.
', 'ModelPackage$LastModifiedBy' => 'Information about the user who created or modified an experiment, trial, trial component, lineage group, or project.
', 'ModelPackageGroup$CreatedBy' => NULL, 'Pipeline$CreatedBy' => NULL, 'Pipeline$LastModifiedBy' => NULL, 'PipelineExecution$CreatedBy' => NULL, 'PipelineExecution$LastModifiedBy' => NULL, 'Project$CreatedBy' => 'Who created the project.
', 'Project$LastModifiedBy' => NULL, 'Trial$CreatedBy' => 'Who created the trial.
', 'Trial$LastModifiedBy' => NULL, 'TrialComponent$CreatedBy' => 'Who created the trial component.
', 'TrialComponent$LastModifiedBy' => NULL, 'TrialComponentSimpleSummary$CreatedBy' => NULL, 'TrialComponentSummary$CreatedBy' => 'Who created the trial component.
', 'TrialComponentSummary$LastModifiedBy' => 'Who last modified the component.
', ], ], 'UserProfileArn' => [ 'base' => NULL, 'refs' => [ 'CreateUserProfileResponse$UserProfileArn' => 'The user profile Amazon Resource Name (ARN).
', 'DescribeUserProfileResponse$UserProfileArn' => 'The user profile Amazon Resource Name (ARN).
', 'UpdateUserProfileResponse$UserProfileArn' => 'The user profile Amazon Resource Name (ARN).
', ], ], 'UserProfileDetails' => [ 'base' => 'The user profile details.
', 'refs' => [ 'UserProfileList$member' => NULL, ], ], 'UserProfileList' => [ 'base' => NULL, 'refs' => [ 'ListUserProfilesResponse$UserProfiles' => 'The list of user profiles.
', ], ], 'UserProfileName' => [ 'base' => NULL, 'refs' => [ 'AppDetails$UserProfileName' => 'The user profile name.
', 'CreateAppRequest$UserProfileName' => 'The user profile name. If this value is not set, then SpaceName must be set.
The name of the UserProfile to sign-in as.
', 'CreateUserProfileRequest$UserProfileName' => 'A name for the UserProfile. This value is not case sensitive.
', 'DeleteAppRequest$UserProfileName' => 'The user profile name. If this value is not set, then SpaceName must be set.
The user profile name.
', 'DescribeAppRequest$UserProfileName' => 'The user profile name. If this value is not set, then SpaceName must be set.
The user profile name.
', 'DescribeUserProfileRequest$UserProfileName' => 'The user profile name. This value is not case sensitive.
', 'DescribeUserProfileResponse$UserProfileName' => 'The user profile name.
', 'ListAppsRequest$UserProfileNameEquals' => 'A parameter to search by user profile name. If SpaceNameEquals is set, then this value cannot be set.
A parameter by which to filter the results.
', 'UpdateUserProfileRequest$UserProfileName' => 'The user profile name.
', 'UserProfileDetails$UserProfileName' => 'The user profile name.
', ], ], 'UserProfileSortKey' => [ 'base' => NULL, 'refs' => [ 'ListUserProfilesRequest$SortBy' => 'The parameter by which to sort the results. The default is CreationTime.
', ], ], 'UserProfileStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeUserProfileResponse$Status' => 'The status.
', 'UserProfileDetails$Status' => 'The status.
', ], ], 'UserSettings' => [ 'base' => 'A collection of settings that apply to users of Amazon SageMaker Studio. These settings are specified when the CreateUserProfile API is called, and as DefaultUserSettings when the CreateDomain API is called.
SecurityGroups is aggregated when specified in both calls. For all other settings in UserSettings, the values specified in CreateUserProfile take precedence over those specified in CreateDomain.
The default settings to use to create a user profile when UserSettings isn\'t specified in the call to the CreateUserProfile API.
SecurityGroups is aggregated when specified in both calls. For all other settings in UserSettings, the values specified in CreateUserProfile take precedence over those specified in CreateDomain.
A collection of settings.
', 'DescribeDomainResponse$DefaultUserSettings' => 'Settings which are applied to UserProfiles in this domain if settings are not explicitly specified in a given UserProfile.
', 'DescribeUserProfileResponse$UserSettings' => 'A collection of settings.
', 'UpdateDomainRequest$DefaultUserSettings' => 'A collection of settings.
', 'UpdateUserProfileRequest$UserSettings' => 'A collection of settings.
', ], ], 'UsersPerStep' => [ 'base' => NULL, 'refs' => [ 'Stairs$UsersPerStep' => 'Specifies how many new users to spawn in each step.
', ], ], 'UtilizationMetric' => [ 'base' => NULL, 'refs' => [ 'RecommendationMetrics$CpuUtilization' => 'The expected CPU utilization at maximum invocations per minute for the instance.
NaN indicates that the value is not available.
The expected memory utilization at maximum invocations per minute for the instance.
NaN indicates that the value is not available.
The percentage of how much utilization you want an instance to use before autoscaling. The default value is 50%.
', 'GetScalingConfigurationRecommendationResponse$TargetCpuUtilizationPerCore' => 'The percentage of how much utilization you want an instance to use before autoscaling, which you specified in the request. The default value is 50%.
', ], ], 'ValidationFraction' => [ 'base' => NULL, 'refs' => [ 'AutoMLDataSplitConfig$ValidationFraction' => 'The validation fraction (optional) is a float that specifies the portion of the training dataset to be used for validation. The default value is 0.2, and values must be greater than 0 and less than 1. We recommend setting this value to be less than 0.5.
', ], ], 'VariantName' => [ 'base' => NULL, 'refs' => [ 'DesiredWeightAndCapacity$VariantName' => 'The name of the variant to update.
', 'PendingProductionVariantSummary$VariantName' => 'The name of the variant.
', 'ProductionVariant$VariantName' => 'The name of the production variant.
', 'ProductionVariantSummary$VariantName' => 'The name of the variant.
', ], ], 'VariantProperty' => [ 'base' => 'Specifies a production variant property type for an Endpoint.
If you are updating an endpoint with the RetainAllVariantProperties option of UpdateEndpointInput set to true, the VariantProperty objects listed in the ExcludeRetainedVariantProperties parameter of UpdateEndpointInput override the existing variant properties of the endpoint.
When you are updating endpoint resources with RetainAllVariantProperties, whose value is set to true, ExcludeRetainedVariantProperties specifies the list of type VariantProperty to override with the values provided by EndpointConfig. If you don\'t specify a value for ExcludeRetainedVariantProperties, no variant properties are overridden.
The type of variant property. The supported values are:
DesiredInstanceCount: Overrides the existing variant instance counts using the InitialInstanceCount values in the ProductionVariants of CreateEndpointConfig.
DesiredWeight: Overrides the existing variant weights using the InitialVariantWeight values in the ProductionVariants of CreateEndpointConfig.
DataCaptureConfig: (Not currently supported.)
The endpoint variant status which describes the current deployment stage status or operational status.
Creating: Creating inference resources for the production variant.
Deleting: Terminating inference resources for the production variant.
Updating: Updating capacity for the production variant.
ActivatingTraffic: Turning on traffic for the production variant.
Baking: Waiting period to monitor the CloudWatch alarms in the automatic rollback configuration.
A message that describes the status of the production variant.
', ], ], 'VariantWeight' => [ 'base' => NULL, 'refs' => [ 'DesiredWeightAndCapacity$DesiredWeight' => 'The variant\'s weight.
', 'PendingProductionVariantSummary$CurrentWeight' => 'The weight associated with the variant.
', 'PendingProductionVariantSummary$DesiredWeight' => 'The requested weight for the variant in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the CreateEndpointConfig operation.
', 'ProductionVariant$InitialVariantWeight' => 'Determines initial traffic distribution among all of the models that you specify in the endpoint configuration. The traffic to a production variant is determined by the ratio of the VariantWeight to the sum of all VariantWeight values across all ProductionVariants. If unspecified, it defaults to 1.0.
The weight associated with the variant.
', 'ProductionVariantSummary$DesiredWeight' => 'The requested weight, as specified in the UpdateEndpointWeightsAndCapacities request.
Configuration for your vector collection type.
', 'refs' => [ 'CollectionConfig$VectorConfig' => 'Configuration for your vector collection type.
Dimension: The number of elements in your vector.
The stability of the image version, specified by the maintainer.
NOT_PROVIDED: The maintainers did not provide a status for image version stability.
STABLE: The image version is stable.
TO_BE_ARCHIVED: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.
ARCHIVED: The image version is archived. Archived image versions are not searchable and are no longer actively supported.
The stability of the image version specified by the maintainer.
NOT_PROVIDED: The maintainers did not provide a status for image version stability.
STABLE: The image version is stable.
TO_BE_ARCHIVED: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.
ARCHIVED: The image version is archived. Archived image versions are not searchable and are no longer actively supported.
The availability of the image version specified by the maintainer.
NOT_PROVIDED: The maintainers did not provide a status for image version stability.
STABLE: The image version is stable.
TO_BE_ARCHIVED: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.
ARCHIVED: The image version is archived. Archived image versions are not searchable and are no longer actively supported.
Version Id of the pipeline definition file. If not specified, Amazon SageMaker will retrieve the latest version.
', ], ], 'VersionedArnOrName' => [ 'base' => NULL, 'refs' => [ 'ContainerDefinition$ModelPackageName' => 'The name or Amazon Resource Name (ARN) of the model package to use to create the model.
', 'DeleteModelPackageInput$ModelPackageName' => 'The name or Amazon Resource Name (ARN) of the model package to delete.
When you specify a name, the name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
', 'DescribeModelPackageInput$ModelPackageName' => 'The name or Amazon Resource Name (ARN) of the model package to describe.
When you specify a name, the name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
', ], ], 'Vertex' => [ 'base' => 'A lineage entity connected to the starting entity(ies).
', 'refs' => [ 'Vertices$member' => NULL, ], ], 'Vertices' => [ 'base' => NULL, 'refs' => [ 'QueryLineageResponse$Vertices' => 'A list of vertices connected to the start entity(ies) in the lineage graph.
', ], ], 'VolumeSizeInGB' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTuningInstanceConfig$VolumeSizeInGB' => 'The volume size in GB of the data to be processed for hyperparameter optimization (optional).
', 'ResourceConfig$VolumeSizeInGB' => 'The size of the ML storage volume that you want to provision.
ML storage volumes store model artifacts and incremental states. Training algorithms might also use the ML storage volume for scratch space. If you want to store the training data in the ML storage volume, choose File as the TrainingInputMode in the algorithm specification.
When using an ML instance with NVMe SSD volumes, SageMaker doesn\'t provision Amazon EBS General Purpose SSD (gp2) storage. Available storage is fixed to the NVMe-type instance\'s storage capacity. SageMaker configures storage paths for training datasets, checkpoints, model artifacts, and outputs to use the entire capacity of the instance storage. For example, ML instance families with the NVMe-type instance storage include ml.p4d, ml.g4dn, and ml.g5.
When using an ML instance with the EBS-only storage option and without instance storage, you must define the size of EBS volume through VolumeSizeInGB in the ResourceConfig API. For example, ML instance families that use EBS volumes include ml.c5 and ml.p2.
To look up instance types and their instance storage types and volumes, see Amazon EC2 Instance Types.
To find the default local paths defined by the SageMaker training platform, see Amazon SageMaker Training Storage Folders for Training Datasets, Checkpoints, Model Artifacts, and Outputs.
', ], ], 'VpcConfig' => [ 'base' => 'Specifies a VPC that your training jobs and hosted models have access to. Control access to and from your training and model containers by configuring the VPC. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud and Protect Training Jobs by Using an Amazon Virtual Private Cloud.
', 'refs' => [ 'AutoMLSecurityConfig$VpcConfig' => 'The VPC configuration.
', 'CreateModelInput$VpcConfig' => 'A VpcConfig object that specifies the VPC that you want your model to connect to. Control access to and from your model container by configuring the VPC. VpcConfig is used in hosting services and in batch transform. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud and Protect Data in Batch Transform Jobs by Using an Amazon Virtual Private Cloud.
A VpcConfig object that specifies the VPC that you want your training job to connect to. Control access to and from your training container by configuring the VPC. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
', 'DescribeModelOutput$VpcConfig' => 'A VpcConfig object that specifies the VPC that this model has access to. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud
', 'DescribeTrainingJobResponse$VpcConfig' => 'A VpcConfig object that specifies the VPC that this training job has access to. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
', 'HyperParameterTrainingJobDefinition$VpcConfig' => 'The VpcConfig object that specifies the VPC that you want the training jobs that this hyperparameter tuning job launches to connect to. Control access to and from your training container by configuring the VPC. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
', 'LabelingJobResourceConfig$VpcConfig' => NULL, 'Model$VpcConfig' => NULL, 'MonitoringNetworkConfig$VpcConfig' => NULL, 'NetworkConfig$VpcConfig' => NULL, 'TrainingJob$VpcConfig' => 'A VpcConfig object that specifies the VPC that this training job has access to. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
', ], ], 'VpcId' => [ 'base' => NULL, 'refs' => [ 'CreateDomainRequest$VpcId' => 'The ID of the Amazon Virtual Private Cloud (VPC) that Studio uses for communication.
', 'DescribeDomainResponse$VpcId' => 'The ID of the Amazon Virtual Private Cloud (VPC) that Studio uses for communication.
', ], ], 'VpcSecurityGroupIds' => [ 'base' => NULL, 'refs' => [ 'VpcConfig$SecurityGroupIds' => 'The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
The length of the baking period, during which SageMaker monitors alarms for each batch on the new fleet.
', 'TrafficRoutingConfig$WaitIntervalInSeconds' => 'The waiting time (in seconds) between incremental steps to turn on traffic on the new endpoint fleet.
', ], ], 'WarmPoolResourceStatus' => [ 'base' => NULL, 'refs' => [ 'ListTrainingJobsRequest$WarmPoolStatusEquals' => 'A filter that retrieves only training jobs with a specific warm pool status.
', 'WarmPoolStatus$Status' => 'The status of the warm pool.
InUse: The warm pool is in use for the training job.
Available: The warm pool is available to reuse for a matching training job.
Reused: The warm pool moved to a matching training job for reuse.
Terminated: The warm pool is no longer available. Warm pools are unavailable if they are terminated by a user, terminated for a patch update, or terminated for exceeding the specified KeepAlivePeriodInSeconds.
Status and billing information about the warm pool.
', 'refs' => [ 'DescribeTrainingJobResponse$WarmPoolStatus' => 'The status of the warm pool associated with the training job.
', 'TrainingJobSummary$WarmPoolStatus' => 'The status of the warm pool associated with the training job.
', ], ], 'Workforce' => [ 'base' => 'A single private workforce, which is automatically created when you create your first private work team. You can create one private work force in each Amazon Web Services Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
', 'refs' => [ 'DescribeWorkforceResponse$Workforce' => 'A single private workforce, which is automatically created when you create your first private work team. You can create one private work force in each Amazon Web Services Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
', 'UpdateWorkforceResponse$Workforce' => 'A single private workforce. You can create one private work force in each Amazon Web Services Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
', 'Workforces$member' => NULL, ], ], 'WorkforceArn' => [ 'base' => NULL, 'refs' => [ 'CreateWorkforceResponse$WorkforceArn' => 'The Amazon Resource Name (ARN) of the workforce.
', 'Workforce$WorkforceArn' => 'The Amazon Resource Name (ARN) of the private workforce.
', 'Workteam$WorkforceArn' => 'The Amazon Resource Name (ARN) of the workforce.
', ], ], 'WorkforceFailureReason' => [ 'base' => NULL, 'refs' => [ 'Workforce$FailureReason' => 'The reason your workforce failed.
', ], ], 'WorkforceName' => [ 'base' => NULL, 'refs' => [ 'CreateWorkforceRequest$WorkforceName' => 'The name of the private workforce.
', 'CreateWorkteamRequest$WorkforceName' => 'The name of the workforce.
', 'DeleteWorkforceRequest$WorkforceName' => 'The name of the workforce.
', 'DescribeWorkforceRequest$WorkforceName' => 'The name of the private workforce whose access you want to restrict. WorkforceName is automatically set to default when a workforce is created and cannot be modified.
A filter you can use to search for workforces using part of the workforce name.
', 'UpdateWorkforceRequest$WorkforceName' => 'The name of the private workforce that you want to update. You can find your workforce name by using the ListWorkforces operation.
', 'Workforce$WorkforceName' => 'The name of the private workforce.
', ], ], 'WorkforceSecurityGroupId' => [ 'base' => NULL, 'refs' => [ 'WorkforceSecurityGroupIds$member' => NULL, ], ], 'WorkforceSecurityGroupIds' => [ 'base' => NULL, 'refs' => [ 'WorkforceVpcConfigRequest$SecurityGroupIds' => 'The VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be for the same VPC as specified in the subnet.
', 'WorkforceVpcConfigResponse$SecurityGroupIds' => 'The VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be for the same VPC as specified in the subnet.
', ], ], 'WorkforceStatus' => [ 'base' => NULL, 'refs' => [ 'Workforce$Status' => 'The status of your workforce.
', ], ], 'WorkforceSubnetId' => [ 'base' => NULL, 'refs' => [ 'WorkforceSubnets$member' => NULL, ], ], 'WorkforceSubnets' => [ 'base' => NULL, 'refs' => [ 'WorkforceVpcConfigRequest$Subnets' => 'The ID of the subnets in the VPC that you want to connect.
', 'WorkforceVpcConfigResponse$Subnets' => 'The ID of the subnets in the VPC that you want to connect.
', ], ], 'WorkforceVpcConfigRequest' => [ 'base' => 'The VPC object you use to create or update a workforce.
', 'refs' => [ 'CreateWorkforceRequest$WorkforceVpcConfig' => 'Use this parameter to configure a workforce using VPC.
', 'UpdateWorkforceRequest$WorkforceVpcConfig' => 'Use this parameter to update your VPC configuration for a workforce.
', ], ], 'WorkforceVpcConfigResponse' => [ 'base' => 'A VpcConfig object that specifies the VPC that you want your workforce to connect to.
', 'refs' => [ 'Workforce$WorkforceVpcConfig' => 'The configuration of a VPC workforce.
', ], ], 'WorkforceVpcEndpointId' => [ 'base' => NULL, 'refs' => [ 'WorkforceVpcConfigResponse$VpcEndpointId' => 'The IDs for the VPC service endpoints of your VPC workforce when it is created and updated.
', ], ], 'WorkforceVpcId' => [ 'base' => NULL, 'refs' => [ 'WorkforceVpcConfigRequest$VpcId' => 'The ID of the VPC that the workforce uses for communication.
', 'WorkforceVpcConfigResponse$VpcId' => 'The ID of the VPC that the workforce uses for communication.
', ], ], 'Workforces' => [ 'base' => NULL, 'refs' => [ 'ListWorkforcesResponse$Workforces' => 'A list containing information about your workforce.
', ], ], 'WorkspaceSettings' => [ 'base' => 'The workspace settings for the SageMaker Canvas application.
', 'refs' => [ 'CanvasAppSettings$WorkspaceSettings' => 'The workspace settings for the SageMaker Canvas application.
', ], ], 'Workteam' => [ 'base' => 'Provides details about a labeling work team.
', 'refs' => [ 'DescribeWorkteamResponse$Workteam' => 'A Workteam instance that contains information about the work team.
A Workteam object that describes the updated work team.
The Amazon Resource Name (ARN) of the work team. You can use this ARN to identify the work team.
', 'DescribeSubscribedWorkteamRequest$WorkteamArn' => 'The Amazon Resource Name (ARN) of the subscribed work team to describe.
', 'HumanLoopConfig$WorkteamArn' => 'Amazon Resource Name (ARN) of a team of workers. To learn more about the types of workforces and work teams you can create and use with Amazon A2I, see Create and Manage Workforces.
', 'HumanTaskConfig$WorkteamArn' => 'The Amazon Resource Name (ARN) of the work team assigned to complete the tasks.
', 'LabelingJobSummary$WorkteamArn' => 'The Amazon Resource Name (ARN) of the work team assigned to the job.
', 'ListLabelingJobsForWorkteamRequest$WorkteamArn' => 'The Amazon Resource Name (ARN) of the work team for which you want to see labeling jobs for.
', 'SubscribedWorkteam$WorkteamArn' => 'The Amazon Resource Name (ARN) of the vendor that you have subscribed.
', 'Workteam$WorkteamArn' => 'The Amazon Resource Name (ARN) that identifies the work team.
', ], ], 'WorkteamName' => [ 'base' => NULL, 'refs' => [ 'CreateWorkteamRequest$WorkteamName' => 'The name of the work team. Use this name to identify the work team.
', 'DeleteWorkteamRequest$WorkteamName' => 'The name of the work team to delete.
', 'DescribeWorkteamRequest$WorkteamName' => 'The name of the work team to return a description of.
', 'ListSubscribedWorkteamsRequest$NameContains' => 'A string in the work team name. This filter returns only work teams whose name contains the specified string.
', 'ListWorkteamsRequest$NameContains' => 'A string in the work team\'s name. This filter returns only work teams whose name contains the specified string.
', 'UpdateWorkteamRequest$WorkteamName' => 'The name of the work team to update.
', 'Workteam$WorkteamName' => 'The name of the work team.
', ], ], 'Workteams' => [ 'base' => NULL, 'refs' => [ 'ListWorkteamsResponse$Workteams' => 'An array of Workteam objects, each describing a work team.
Provides APIs for creating and managing SageMaker resources.
Other Resources:
', 'operations' => [ 'AddAssociation' => 'Creates an association between the source and the destination. A source can be associated with multiple destinations, and a destination can be associated with multiple sources. An association is a lineage tracking entity. For more information, see Amazon SageMaker ML Lineage Tracking.
', 'AddTags' => 'Adds or overwrites one or more tags for the specified SageMaker resource. You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints.
Each tag consists of a key and an optional value. Tag keys must be unique per resource. For more information about tags, see For more information, see Amazon Web Services Tagging Strategies.
Tags that you add to a hyperparameter tuning job by calling this API are also added to any training jobs that the hyperparameter tuning job launches after you call this API, but not to training jobs that the hyperparameter tuning job launched before you called this API. To make sure that the tags associated with a hyperparameter tuning job are also added to all training jobs that the hyperparameter tuning job launches, add the tags when you first create the tuning job by specifying them in the Tags parameter of CreateHyperParameterTuningJob
Tags that you add to a SageMaker Studio Domain or User Profile by calling this API are also added to any Apps that the Domain or User Profile launches after you call this API, but not to Apps that the Domain or User Profile launched before you called this API. To make sure that the tags associated with a Domain or User Profile are also added to all Apps that the Domain or User Profile launches, add the tags when you first create the Domain or User Profile by specifying them in the Tags parameter of CreateDomain or CreateUserProfile.
Associates a trial component with a trial. A trial component can be associated with multiple trials. To disassociate a trial component from a trial, call the DisassociateTrialComponent API.
', 'BatchDescribeModelPackage' => 'This action batch describes a list of versioned model packages
', 'CreateAction' => 'Creates an action. An action is a lineage tracking entity that represents an action or activity. For example, a model deployment or an HPO job. Generally, an action involves at least one input or output artifact. For more information, see Amazon SageMaker ML Lineage Tracking.
', 'CreateAlgorithm' => 'Create a machine learning algorithm that you can use in SageMaker and list in the Amazon Web Services Marketplace.
', 'CreateApp' => 'Creates a running app for the specified UserProfile. This operation is automatically invoked by Amazon SageMaker Studio upon access to the associated Domain, and when new kernel configurations are selected by the user. A user may have multiple Apps active simultaneously.
', 'CreateAppImageConfig' => 'Creates a configuration for running a SageMaker image as a KernelGateway app. The configuration specifies the Amazon Elastic File System (EFS) storage volume on the image, and a list of the kernels in the image.
', 'CreateArtifact' => 'Creates an artifact. An artifact is a lineage tracking entity that represents a URI addressable object or data. Some examples are the S3 URI of a dataset and the ECR registry path of an image. For more information, see Amazon SageMaker ML Lineage Tracking.
', 'CreateAutoMLJob' => 'Creates an Autopilot job also referred to as Autopilot experiment or AutoML job.
We recommend using the new versions CreateAutoMLJobV2 and DescribeAutoMLJobV2, which offer backward compatibility.
CreateAutoMLJobV2 can manage tabular problem types identical to those of its previous version CreateAutoMLJob, as well as time-series forecasting, non-tabular problem types such as image or text classification, and text generation (LLMs fine-tuning).
Find guidelines about how to migrate a CreateAutoMLJob to CreateAutoMLJobV2 in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.
You can find the best-performing model after you run an AutoML job by calling DescribeAutoMLJobV2 (recommended) or DescribeAutoMLJob.
', 'CreateAutoMLJobV2' => 'Creates an Autopilot job also referred to as Autopilot experiment or AutoML job V2.
CreateAutoMLJobV2 and DescribeAutoMLJobV2 are new versions of CreateAutoMLJob and DescribeAutoMLJob which offer backward compatibility.
CreateAutoMLJobV2 can manage tabular problem types identical to those of its previous version CreateAutoMLJob, as well as time-series forecasting, non-tabular problem types such as image or text classification, and text generation (LLMs fine-tuning).
Find guidelines about how to migrate a CreateAutoMLJob to CreateAutoMLJobV2 in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.
For the list of available problem types supported by CreateAutoMLJobV2, see AutoMLProblemTypeConfig.
You can find the best-performing model after you run an AutoML job V2 by calling DescribeAutoMLJobV2.
', 'CreateCodeRepository' => 'Creates a Git repository as a resource in your SageMaker account. You can associate the repository with notebook instances so that you can use Git source control for the notebooks you create. The Git repository is a resource in your SageMaker account, so it can be associated with more than one notebook instance, and it persists independently from the lifecycle of any notebook instances it is associated with.
The repository can be hosted either in Amazon Web Services CodeCommit or in any other Git repository.
', 'CreateCompilationJob' => 'Starts a model compilation job. After the model has been compiled, Amazon SageMaker saves the resulting model artifacts to an Amazon Simple Storage Service (Amazon S3) bucket that you specify.
If you choose to host your model using Amazon SageMaker hosting services, you can use the resulting model artifacts as part of the model. You can also use the artifacts with Amazon Web Services IoT Greengrass. In that case, deploy them as an ML resource.
In the request body, you provide the following:
A name for the compilation job
Information about the input model artifacts
The output location for the compiled model and the device (target) that the model runs on
The Amazon Resource Name (ARN) of the IAM role that Amazon SageMaker assumes to perform the model compilation job.
You can also provide a Tag to track the model compilation job\'s resource use and costs. The response body contains the CompilationJobArn for the compiled job.
To stop a model compilation job, use StopCompilationJob. To get information about a particular model compilation job, use DescribeCompilationJob. To get information about multiple model compilation jobs, use ListCompilationJobs.
', 'CreateContext' => 'Creates a context. A context is a lineage tracking entity that represents a logical grouping of other tracking or experiment entities. Some examples are an endpoint and a model package. For more information, see Amazon SageMaker ML Lineage Tracking.
', 'CreateDataQualityJobDefinition' => 'Creates a definition for a job that monitors data quality and drift. For information about model monitor, see Amazon SageMaker Model Monitor.
', 'CreateDeviceFleet' => 'Creates a device fleet.
', 'CreateDomain' => 'Creates a Domain used by Amazon SageMaker Studio. A domain consists of an associated Amazon Elastic File System (EFS) volume, a list of authorized users, and a variety of security, application, policy, and Amazon Virtual Private Cloud (VPC) configurations. Users within a domain can share notebook files and other artifacts with each other.
EFS storage
When a domain is created, an EFS volume is created for use by all of the users within the domain. Each user receives a private home directory within the EFS volume for notebooks, Git repositories, and data files.
SageMaker uses the Amazon Web Services Key Management Service (Amazon Web Services KMS) to encrypt the EFS volume attached to the domain with an Amazon Web Services managed key by default. For more control, you can specify a customer managed key. For more information, see Protect Data at Rest Using Encryption.
VPC configuration
All SageMaker Studio traffic between the domain and the EFS volume is through the specified VPC and subnets. For other Studio traffic, you can specify the AppNetworkAccessType parameter. AppNetworkAccessType corresponds to the network access type that you choose when you onboard to Studio. The following options are available:
PublicInternetOnly - Non-EFS traffic goes through a VPC managed by Amazon SageMaker, which allows internet access. This is the default value.
VpcOnly - All Studio traffic is through the specified VPC and subnets. Internet access is disabled by default. To allow internet access, you must specify a NAT gateway.
When internet access is disabled, you won\'t be able to run a Studio notebook or to train or host models unless your VPC has an interface endpoint to the SageMaker API and runtime or a NAT gateway and your security groups allow outbound connections.
NFS traffic over TCP on port 2049 needs to be allowed in both inbound and outbound rules in order to launch a SageMaker Studio app successfully.
For more information, see Connect SageMaker Studio Notebooks to Resources in a VPC.
', 'CreateEdgeDeploymentPlan' => 'Creates an edge deployment plan, consisting of multiple stages. Each stage may have a different deployment configuration and devices.
', 'CreateEdgeDeploymentStage' => 'Creates a new stage in an existing edge deployment plan.
', 'CreateEdgePackagingJob' => 'Starts a SageMaker Edge Manager model packaging job. Edge Manager will use the model artifacts from the Amazon Simple Storage Service bucket that you specify. After the model has been packaged, Amazon SageMaker saves the resulting artifacts to an S3 bucket that you specify.
', 'CreateEndpoint' => 'Creates an endpoint using the endpoint configuration specified in the request. SageMaker uses the endpoint to provision resources and deploy models. You create the endpoint configuration with the CreateEndpointConfig API.
Use this API to deploy models using SageMaker hosting services.
You must not delete an EndpointConfig that is in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. To update an endpoint, you must create a new EndpointConfig.
The endpoint name must be unique within an Amazon Web Services Region in your Amazon Web Services account.
When it receives the request, SageMaker creates the endpoint, launches the resources (ML compute instances), and deploys the model(s) on them.
When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads , the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read.
When SageMaker receives the request, it sets the endpoint status to Creating. After it creates the endpoint, it sets the status to InService. SageMaker can then process incoming requests for inferences. To check the status of an endpoint, use the DescribeEndpoint API.
If any of the models hosted at this endpoint get model data from an Amazon S3 location, SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you provided. Amazon Web Services STS is activated in your Amazon Web Services account by default. If you previously deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see Activating and Deactivating Amazon Web Services STS in an Amazon Web Services Region in the Amazon Web Services Identity and Access Management User Guide.
To add the IAM role policies for using this API operation, go to the IAM console, and choose Roles in the left navigation pane. Search the IAM role that you want to grant access to use the CreateEndpoint and CreateEndpointConfig API operations, add the following policies to the role.
Option 1: For a full SageMaker access, search and attach the AmazonSageMakerFullAccess policy.
Option 2: For granting a limited access to an IAM role, paste the following Action elements manually into the JSON file of the IAM role:
"Action": ["sagemaker:CreateEndpoint", "sagemaker:CreateEndpointConfig"]
"Resource": [
"arn:aws:sagemaker:region:account-id:endpoint/endpointName"
"arn:aws:sagemaker:region:account-id:endpoint-config/endpointConfigName"
]
For more information, see SageMaker API Permissions: Actions, Permissions, and Resources Reference.
Creates an endpoint configuration that SageMaker hosting services uses to deploy models. In the configuration, you identify one or more models, created using the CreateModel API, to deploy and the resources that you want SageMaker to provision. Then you call the CreateEndpoint API.
Use this API if you want to use SageMaker hosting services to deploy models into production.
In the request, you define a ProductionVariant, for each model that you want to deploy. Each ProductionVariant parameter also describes the resources that you want SageMaker to provision. This includes the number and type of ML compute instances to deploy.
If you are hosting multiple models, you also assign a VariantWeight to specify how much traffic you want to allocate to each model. For example, suppose that you want to host two models, A and B, and you assign traffic weight 2 for model A and 1 for model B. SageMaker distributes two-thirds of the traffic to Model A, and one-third to model B.
When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads , the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read.
Creates a SageMaker experiment. An experiment is a collection of trials that are observed, compared and evaluated as a group. A trial is a set of steps, called trial components, that produce a machine learning model.
In the Studio UI, trials are referred to as run groups and trial components are referred to as runs.
The goal of an experiment is to determine the components that produce the best model. Multiple trials are performed, each one isolating and measuring the impact of a change to one or more inputs, while keeping the remaining inputs constant.
When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided by the SDK.
You can add tags to experiments, trials, trial components and then use the Search API to search for the tags.
To add a description to an experiment, specify the optional Description parameter. To add a description later, or to change the description, call the UpdateExperiment API.
To get a list of all your experiments, call the ListExperiments API. To view an experiment\'s properties, call the DescribeExperiment API. To get a list of all the trials associated with an experiment, call the ListTrials API. To create a trial call the CreateTrial API.
', 'CreateFeatureGroup' => 'Create a new FeatureGroup. A FeatureGroup is a group of Features defined in the FeatureStore to describe a Record.
The FeatureGroup defines the schema and features contained in the FeatureGroup. A FeatureGroup definition is composed of a list of Features, a RecordIdentifierFeatureName, an EventTimeFeatureName and configurations for its OnlineStore and OfflineStore. Check Amazon Web Services service quotas to see the FeatureGroups quota for your Amazon Web Services account.
Note that it can take approximately 10-15 minutes to provision an OnlineStore FeatureGroup with the InMemory StorageType.
You must include at least one of OnlineStoreConfig and OfflineStoreConfig to create a FeatureGroup.
Creates a flow definition.
', 'CreateHub' => 'Create a hub.
Hub APIs are only callable through SageMaker Studio.
Defines the settings you will use for the human review workflow user interface. Reviewers will see a three-panel interface with an instruction area, the item to review, and an input area.
', 'CreateHyperParameterTuningJob' => 'Starts a hyperparameter tuning job. A hyperparameter tuning job finds the best version of a model by running many training jobs on your dataset using the algorithm you choose and values for hyperparameters within ranges that you specify. It then chooses the hyperparameter values that result in a model that performs the best, as measured by an objective metric that you choose.
A hyperparameter tuning job automatically creates Amazon SageMaker experiments, trials, and trial components for each training job that it runs. You can view these entities in Amazon SageMaker Studio. For more information, see View Experiments, Trials, and Trial Components.
Do not include any security-sensitive information including account access IDs, secrets or tokens in any hyperparameter field. If the use of security-sensitive credentials are detected, SageMaker will reject your training job request and return an exception error.
Creates a custom SageMaker image. A SageMaker image is a set of image versions. Each image version represents a container image stored in Amazon Elastic Container Registry (ECR). For more information, see Bring your own SageMaker image.
', 'CreateImageVersion' => 'Creates a version of the SageMaker image specified by ImageName. The version represents the Amazon Elastic Container Registry (ECR) container image specified by BaseImage.
Creates an inference experiment using the configurations specified in the request.
Use this API to setup and schedule an experiment to compare model variants on a Amazon SageMaker inference endpoint. For more information about inference experiments, see Shadow tests.
Amazon SageMaker begins your experiment at the scheduled time and routes traffic to your endpoint\'s model variants based on your specified configuration.
While the experiment is in progress or after it has concluded, you can view metrics that compare your model variants. For more information, see View, monitor, and edit shadow tests.
', 'CreateInferenceRecommendationsJob' => 'Starts a recommendation job. You can create either an instance recommendation or load test job.
', 'CreateLabelingJob' => 'Creates a job that uses workers to label the data objects in your input dataset. You can use the labeled data to train machine learning models.
You can select your workforce from one of three providers:
A private workforce that you create. It can include employees, contractors, and outside experts. Use a private workforce when want the data to stay within your organization or when a specific set of skills is required.
One or more vendors that you select from the Amazon Web Services Marketplace. Vendors provide expertise in specific areas.
The Amazon Mechanical Turk workforce. This is the largest workforce, but it should only be used for public data or data that has been stripped of any personally identifiable information.
You can also use automated data labeling to reduce the number of data objects that need to be labeled by a human. Automated data labeling uses active learning to determine if a data object can be labeled by machine or if it needs to be sent to a human worker. For more information, see Using Automated Data Labeling.
The data objects to be labeled are contained in an Amazon S3 bucket. You create a manifest file that describes the location of each object. For more information, see Using Input and Output Data.
The output can be used as the manifest file for another labeling job or as training data for your machine learning models.
You can use this operation to create a static labeling job or a streaming labeling job. A static labeling job stops if all data objects in the input manifest file identified in ManifestS3Uri have been labeled. A streaming labeling job runs perpetually until it is manually stopped, or remains idle for 10 days. You can send new data objects to an active (InProgress) streaming labeling job in real time. To learn how to create a static labeling job, see Create a Labeling Job (API) in the Amazon SageMaker Developer Guide. To learn how to create a streaming labeling job, see Create a Streaming Labeling Job.
Creates a model in SageMaker. In the request, you name the model and describe a primary container. For the primary container, you specify the Docker image that contains inference code, artifacts (from prior training), and a custom environment map that the inference code uses when you deploy the model for predictions.
Use this API to create a model if you want to use SageMaker hosting services or run a batch transform job.
To host your model, you create an endpoint configuration with the CreateEndpointConfig API, and then create an endpoint with the CreateEndpoint API. SageMaker then deploys all of the containers that you defined for the model in the hosting environment.
For an example that calls this method when deploying a model to SageMaker hosting services, see Create a Model (Amazon Web Services SDK for Python (Boto 3)).
To run a batch transform using your model, you start a job with the CreateTransformJob API. SageMaker uses your model and your dataset to get inferences which are then saved to a specified S3 location.
In the request, you also provide an IAM role that SageMaker can assume to access model artifacts and docker image for deployment on ML compute hosting instances or for batch transform jobs. In addition, you also use the IAM role to manage permissions the inference code needs. For example, if the inference code access any other Amazon Web Services resources, you grant necessary permissions via this role.
', 'CreateModelBiasJobDefinition' => 'Creates the definition for a model bias job.
', 'CreateModelCard' => 'Creates an Amazon SageMaker Model Card.
For information about how to use model cards, see Amazon SageMaker Model Card.
', 'CreateModelCardExportJob' => 'Creates an Amazon SageMaker Model Card export job.
', 'CreateModelExplainabilityJobDefinition' => 'Creates the definition for a model explainability job.
', 'CreateModelPackage' => 'Creates a model package that you can use to create SageMaker models or list on Amazon Web Services Marketplace, or a versioned model that is part of a model group. Buyers can subscribe to model packages listed on Amazon Web Services Marketplace to create models in SageMaker.
To create a model package by specifying a Docker container that contains your inference code and the Amazon S3 location of your model artifacts, provide values for InferenceSpecification. To create a model from an algorithm resource that you created or subscribed to in Amazon Web Services Marketplace, provide a value for SourceAlgorithmSpecification.
There are two types of model packages:
Versioned - a model that is part of a model group in the model registry.
Unversioned - a model package that is not part of a model group.
Creates a model group. A model group contains a group of model versions.
', 'CreateModelQualityJobDefinition' => 'Creates a definition for a job that monitors model quality and drift. For information about model monitor, see Amazon SageMaker Model Monitor.
', 'CreateMonitoringSchedule' => 'Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to monitor the data captured for an Amazon SageMaker Endpoint.
', 'CreateNotebookInstance' => 'Creates an SageMaker notebook instance. A notebook instance is a machine learning (ML) compute instance running on a Jupyter notebook.
In a CreateNotebookInstance request, specify the type of ML compute instance that you want to run. SageMaker launches the instance, installs common libraries that you can use to explore datasets for model training, and attaches an ML storage volume to the notebook instance.
SageMaker also provides a set of example notebooks. Each notebook demonstrates how to use SageMaker with a specific algorithm or with a machine learning framework.
After receiving the request, SageMaker does the following:
Creates a network interface in the SageMaker VPC.
(Option) If you specified SubnetId, SageMaker creates a network interface in your own VPC, which is inferred from the subnet ID that you provide in the input. When creating this network interface, SageMaker attaches the security group that you specified in the request to the network interface that it creates in your VPC.
Launches an EC2 instance of the type specified in the request in the SageMaker VPC. If you specified SubnetId of your VPC, SageMaker specifies both network interfaces when launching this instance. This enables inbound traffic from your own VPC to the notebook instance, assuming that the security groups allow it.
After creating the notebook instance, SageMaker returns its Amazon Resource Name (ARN). You can\'t change the name of a notebook instance after you create it.
After SageMaker creates the notebook instance, you can connect to the Jupyter server and work in Jupyter notebooks. For example, you can write code to explore a dataset that you can use for model training, train a model, host models by creating SageMaker endpoints, and validate hosted models.
For more information, see How It Works.
', 'CreateNotebookInstanceLifecycleConfig' => 'Creates a lifecycle configuration that you can associate with a notebook instance. A lifecycle configuration is a collection of shell scripts that run when you create or start a notebook instance.
Each lifecycle configuration script has a limit of 16384 characters.
The value of the $PATH environment variable that is available to both scripts is /sbin:bin:/usr/sbin:/usr/bin.
View CloudWatch Logs for notebook instance lifecycle configurations in log group /aws/sagemaker/NotebookInstances in log stream [notebook-instance-name]/[LifecycleConfigHook].
Lifecycle configuration scripts cannot run for longer than 5 minutes. If a script runs for longer than 5 minutes, it fails and the notebook instance is not created or started.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
', 'CreatePipeline' => 'Creates a pipeline using a JSON pipeline definition.
', 'CreatePresignedDomainUrl' => 'Creates a URL for a specified UserProfile in a Domain. When accessed in a web browser, the user will be automatically signed in to Amazon SageMaker Studio, and granted access to all of the Apps and files associated with the Domain\'s Amazon Elastic File System (EFS) volume. This operation can only be called when the authentication mode equals IAM.
The IAM role or user passed to this API defines the permissions to access the app. Once the presigned URL is created, no additional permission is required to access this URL. IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that attempts to connect to the app.
You can restrict access to this API and to the URL that it returns to a list of IP addresses, Amazon VPCs or Amazon VPC Endpoints that you specify. For more information, see Connect to SageMaker Studio Through an Interface VPC Endpoint .
The URL that you get from a call to CreatePresignedDomainUrl has a default timeout of 5 minutes. You can configure this value using ExpiresInSeconds. If you try to use the URL after the timeout limit expires, you are directed to the Amazon Web Services console sign-in page.
Returns a URL that you can use to connect to the Jupyter server from a notebook instance. In the SageMaker console, when you choose Open next to a notebook instance, SageMaker opens a new tab showing the Jupyter server home page from the notebook instance. The console uses this API to get the URL and show the page.
The IAM role or user used to call this API defines the permissions to access the notebook instance. Once the presigned URL is created, no additional permission is required to access this URL. IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that attempts to connect to the notebook instance.
You can restrict access to this API and to the URL that it returns to a list of IP addresses that you specify. Use the NotIpAddress condition operator and the aws:SourceIP condition context key to specify the list of IP addresses that you want to have access to the notebook instance. For more information, see Limit Access to a Notebook Instance by IP Address.
The URL that you get from a call to CreatePresignedNotebookInstanceUrl is valid only for 5 minutes. If you try to use the URL after the 5-minute limit expires, you are directed to the Amazon Web Services console sign-in page.
Creates a processing job.
', 'CreateProject' => 'Creates a machine learning (ML) project that can contain one or more templates that set up an ML pipeline from training to deploying an approved model.
', 'CreateSpace' => 'Creates a space used for real time collaboration in a Domain.
', 'CreateStudioLifecycleConfig' => 'Creates a new Studio Lifecycle Configuration.
', 'CreateTrainingJob' => 'Starts a model training job. After training completes, SageMaker saves the resulting model artifacts to an Amazon S3 location that you specify.
If you choose to host your model using SageMaker hosting services, you can use the resulting model artifacts as part of the model. You can also use the artifacts in a machine learning service other than SageMaker, provided that you know how to use them for inference.
In the request body, you provide the following:
AlgorithmSpecification - Identifies the training algorithm to use.
HyperParameters - Specify these algorithm-specific parameters to enable the estimation of model parameters during training. Hyperparameters can be tuned to optimize this learning process. For a list of hyperparameters for each training algorithm provided by SageMaker, see Algorithms.
Do not include any security-sensitive information including account access IDs, secrets or tokens in any hyperparameter field. If the use of security-sensitive credentials are detected, SageMaker will reject your training job request and return an exception error.
InputDataConfig - Describes the input required by the training job and the Amazon S3, EFS, or FSx location where it is stored.
OutputDataConfig - Identifies the Amazon S3 bucket where you want SageMaker to save the results of model training.
ResourceConfig - Identifies the resources, ML compute instances, and ML storage volumes to deploy for model training. In distributed training, you specify more than one instance.
EnableManagedSpotTraining - Optimize the cost of training machine learning models by up to 80% by using Amazon EC2 Spot instances. For more information, see Managed Spot Training.
RoleArn - The Amazon Resource Name (ARN) that SageMaker assumes to perform tasks on your behalf during model training. You must grant this role the necessary permissions so that SageMaker can successfully complete model training.
StoppingCondition - To help cap training costs, use MaxRuntimeInSeconds to set a time limit for training. Use MaxWaitTimeInSeconds to specify how long a managed spot training job has to complete.
Environment - The environment variables to set in the Docker container.
RetryStrategy - The number of times to retry the job when the job fails due to an InternalServerError.
For more information about SageMaker, see How It Works.
', 'CreateTransformJob' => 'Starts a transform job. A transform job uses a trained model to get inferences on a dataset and saves these results to an Amazon S3 location that you specify.
To perform batch transformations, you create a transform job and use the data that you have readily available.
In the request body, you provide the following:
TransformJobName - Identifies the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
ModelName - Identifies the model to use. ModelName must be the name of an existing Amazon SageMaker model in the same Amazon Web Services Region and Amazon Web Services account. For information on creating a model, see CreateModel.
TransformInput - Describes the dataset to be transformed and the Amazon S3 location where it is stored.
TransformOutput - Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
TransformResources - Identifies the ML compute instances for the transform job.
For more information about how batch transformation works, see Batch Transform.
', 'CreateTrial' => 'Creates an SageMaker trial. A trial is a set of steps called trial components that produce a machine learning model. A trial is part of a single SageMaker experiment.
When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided by the SDK.
You can add tags to a trial and then use the Search API to search for the tags.
To get a list of all your trials, call the ListTrials API. To view a trial\'s properties, call the DescribeTrial API. To create a trial component, call the CreateTrialComponent API.
', 'CreateTrialComponent' => 'Creates a trial component, which is a stage of a machine learning trial. A trial is composed of one or more trial components. A trial component can be used in multiple trials.
Trial components include pre-processing jobs, training jobs, and batch transform jobs.
When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided by the SDK.
You can add tags to a trial component and then use the Search API to search for the tags.
', 'CreateUserProfile' => 'Creates a user profile. A user profile represents a single user within a domain, and is the main way to reference a "person" for the purposes of sharing, reporting, and other user-oriented features. This entity is created when a user onboards to Amazon SageMaker Studio. If an administrator invites a person by email or imports them from IAM Identity Center, a user profile is automatically created. A user profile is the primary holder of settings for an individual user and has a reference to the user\'s private Amazon Elastic File System (EFS) home directory.
', 'CreateWorkforce' => 'Use this operation to create a workforce. This operation will return an error if a workforce already exists in the Amazon Web Services Region that you specify. You can only create one workforce in each Amazon Web Services Region per Amazon Web Services account.
If you want to create a new workforce in an Amazon Web Services Region where a workforce already exists, use the DeleteWorkforce API operation to delete the existing workforce and then use CreateWorkforce to create a new workforce.
To create a private workforce using Amazon Cognito, you must specify a Cognito user pool in CognitoConfig. You can also create an Amazon Cognito workforce using the Amazon SageMaker console. For more information, see Create a Private Workforce (Amazon Cognito).
To create a private workforce using your own OIDC Identity Provider (IdP), specify your IdP configuration in OidcConfig. Your OIDC IdP must support groups because groups are used by Ground Truth and Amazon A2I to create work teams. For more information, see Create a Private Workforce (OIDC IdP).
Creates a new work team for labeling your data. A work team is defined by one or more Amazon Cognito user pools. You must first create the user pools before you can create a work team.
You cannot create more than 25 work teams in an account and region.
', 'DeleteAction' => 'Deletes an action.
', 'DeleteAlgorithm' => 'Removes the specified algorithm from your account.
', 'DeleteApp' => 'Used to stop and delete an app.
', 'DeleteAppImageConfig' => 'Deletes an AppImageConfig.
', 'DeleteArtifact' => 'Deletes an artifact. Either ArtifactArn or Source must be specified.
Deletes an association.
', 'DeleteCodeRepository' => 'Deletes the specified Git repository from your account.
', 'DeleteContext' => 'Deletes an context.
', 'DeleteDataQualityJobDefinition' => 'Deletes a data quality monitoring job definition.
', 'DeleteDeviceFleet' => 'Deletes a fleet.
', 'DeleteDomain' => 'Used to delete a domain. If you onboarded with IAM mode, you will need to delete your domain to onboard again using IAM Identity Center. Use with caution. All of the members of the domain will lose access to their EFS volume, including data, notebooks, and other artifacts.
', 'DeleteEdgeDeploymentPlan' => 'Deletes an edge deployment plan if (and only if) all the stages in the plan are inactive or there are no stages in the plan.
', 'DeleteEdgeDeploymentStage' => 'Delete a stage in an edge deployment plan if (and only if) the stage is inactive.
', 'DeleteEndpoint' => 'Deletes an endpoint. SageMaker frees up all of the resources that were deployed when the endpoint was created.
SageMaker retires any custom KMS key grants associated with the endpoint, meaning you don\'t need to use the RevokeGrant API call.
When you delete your endpoint, SageMaker asynchronously deletes associated endpoint resources such as KMS key grants. You might still see these resources in your account for a few minutes after deleting your endpoint. Do not delete or revoke the permissions for your ExecutionRoleArn , otherwise SageMaker cannot delete these resources.
Deletes an endpoint configuration. The DeleteEndpointConfig API deletes only the specified configuration. It does not delete endpoints created using the configuration.
You must not delete an EndpointConfig in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. If you delete the EndpointConfig of an endpoint that is active or being created or updated you may lose visibility into the instance type the endpoint is using. The endpoint must be deleted in order to stop incurring charges.
Deletes an SageMaker experiment. All trials associated with the experiment must be deleted first. Use the ListTrials API to get a list of the trials associated with the experiment.
', 'DeleteFeatureGroup' => 'Delete the FeatureGroup and any data that was written to the OnlineStore of the FeatureGroup. Data cannot be accessed from the OnlineStore immediately after DeleteFeatureGroup is called.
Data written into the OfflineStore will not be deleted. The Amazon Web Services Glue database and tables that are automatically created for your OfflineStore are not deleted.
Note that it can take approximately 10-15 minutes to delete an OnlineStore FeatureGroup with the InMemory StorageType.
Deletes the specified flow definition.
', 'DeleteHub' => 'Delete a hub.
Hub APIs are only callable through SageMaker Studio.
Delete the contents of a hub.
Hub APIs are only callable through SageMaker Studio.
Use this operation to delete a human task user interface (worker task template).
To see a list of human task user interfaces (work task templates) in your account, use ListHumanTaskUis. When you delete a worker task template, it no longer appears when you call ListHumanTaskUis.
Deletes a SageMaker image and all versions of the image. The container images aren\'t deleted.
', 'DeleteImageVersion' => 'Deletes a version of a SageMaker image. The container image the version represents isn\'t deleted.
', 'DeleteInferenceExperiment' => 'Deletes an inference experiment.
This operation does not delete your endpoint, variants, or any underlying resources. This operation only deletes the metadata of your experiment.
Deletes a model. The DeleteModel API deletes only the model entry that was created in SageMaker when you called the CreateModel API. It does not delete model artifacts, inference code, or the IAM role that you specified when creating the model.
Deletes an Amazon SageMaker model bias job definition.
', 'DeleteModelCard' => 'Deletes an Amazon SageMaker Model Card.
', 'DeleteModelExplainabilityJobDefinition' => 'Deletes an Amazon SageMaker model explainability job definition.
', 'DeleteModelPackage' => 'Deletes a model package.
A model package is used to create SageMaker models or list on Amazon Web Services Marketplace. Buyers can subscribe to model packages listed on Amazon Web Services Marketplace to create models in SageMaker.
', 'DeleteModelPackageGroup' => 'Deletes the specified model group.
', 'DeleteModelPackageGroupPolicy' => 'Deletes a model group resource policy.
', 'DeleteModelQualityJobDefinition' => 'Deletes the secified model quality monitoring job definition.
', 'DeleteMonitoringSchedule' => 'Deletes a monitoring schedule. Also stops the schedule had not already been stopped. This does not delete the job execution history of the monitoring schedule.
', 'DeleteNotebookInstance' => ' Deletes an SageMaker notebook instance. Before you can delete a notebook instance, you must call the StopNotebookInstance API.
When you delete a notebook instance, you lose all of your data. SageMaker removes the ML compute instance, and deletes the ML storage volume and the network interface associated with the notebook instance.
Deletes a notebook instance lifecycle configuration.
', 'DeletePipeline' => 'Deletes a pipeline if there are no running instances of the pipeline. To delete a pipeline, you must stop all running instances of the pipeline using the StopPipelineExecution API. When you delete a pipeline, all instances of the pipeline are deleted.
Delete the specified project.
', 'DeleteSpace' => 'Used to delete a space.
', 'DeleteStudioLifecycleConfig' => 'Deletes the Studio Lifecycle Configuration. In order to delete the Lifecycle Configuration, there must be no running apps using the Lifecycle Configuration. You must also remove the Lifecycle Configuration from UserSettings in all Domains and UserProfiles.
', 'DeleteTags' => 'Deletes the specified tags from an SageMaker resource.
To list a resource\'s tags, use the ListTags API.
When you call this API to delete tags from a hyperparameter tuning job, the deleted tags are not removed from training jobs that the hyperparameter tuning job launched before you called this API.
When you call this API to delete tags from a SageMaker Studio Domain or User Profile, the deleted tags are not removed from Apps that the SageMaker Studio Domain or User Profile launched before you called this API.
Deletes the specified trial. All trial components that make up the trial must be deleted first. Use the DescribeTrialComponent API to get the list of trial components.
', 'DeleteTrialComponent' => 'Deletes the specified trial component. A trial component must be disassociated from all trials before the trial component can be deleted. To disassociate a trial component from a trial, call the DisassociateTrialComponent API.
', 'DeleteUserProfile' => 'Deletes a user profile. When a user profile is deleted, the user loses access to their EFS volume, including data, notebooks, and other artifacts.
', 'DeleteWorkforce' => 'Use this operation to delete a workforce.
If you want to create a new workforce in an Amazon Web Services Region where a workforce already exists, use this operation to delete the existing workforce and then use CreateWorkforce to create a new workforce.
If a private workforce contains one or more work teams, you must use the DeleteWorkteam operation to delete all work teams before you delete the workforce. If you try to delete a workforce that contains one or more work teams, you will recieve a ResourceInUse error.
Deletes an existing work team. This operation can\'t be undone.
', 'DeregisterDevices' => 'Deregisters the specified devices. After you deregister a device, you will need to re-register the devices.
', 'DescribeAction' => 'Describes an action.
', 'DescribeAlgorithm' => 'Returns a description of the specified algorithm that is in your account.
', 'DescribeApp' => 'Describes the app.
', 'DescribeAppImageConfig' => 'Describes an AppImageConfig.
', 'DescribeArtifact' => 'Describes an artifact.
', 'DescribeAutoMLJob' => 'Returns information about an AutoML job created by calling CreateAutoMLJob.
AutoML jobs created by calling CreateAutoMLJobV2 cannot be described by DescribeAutoMLJob.
Returns information about an AutoML job created by calling CreateAutoMLJobV2 or CreateAutoMLJob.
', 'DescribeCodeRepository' => 'Gets details about the specified Git repository.
', 'DescribeCompilationJob' => 'Returns information about a model compilation job.
To create a model compilation job, use CreateCompilationJob. To get information about multiple model compilation jobs, use ListCompilationJobs.
', 'DescribeContext' => 'Describes a context.
', 'DescribeDataQualityJobDefinition' => 'Gets the details of a data quality monitoring job definition.
', 'DescribeDevice' => 'Describes the device.
', 'DescribeDeviceFleet' => 'A description of the fleet the device belongs to.
', 'DescribeDomain' => 'The description of the domain.
', 'DescribeEdgeDeploymentPlan' => 'Describes an edge deployment plan with deployment status per stage.
', 'DescribeEdgePackagingJob' => 'A description of edge packaging jobs.
', 'DescribeEndpoint' => 'Returns the description of an endpoint.
', 'DescribeEndpointConfig' => 'Returns the description of an endpoint configuration created using the CreateEndpointConfig API.
Provides a list of an experiment\'s properties.
', 'DescribeFeatureGroup' => 'Use this operation to describe a FeatureGroup. The response includes information on the creation time, FeatureGroup name, the unique identifier for each FeatureGroup, and more.
Shows the metadata for a feature within a feature group.
', 'DescribeFlowDefinition' => 'Returns information about the specified flow definition.
', 'DescribeHub' => 'Describe a hub.
Hub APIs are only callable through SageMaker Studio.
Describe the content of a hub.
Hub APIs are only callable through SageMaker Studio.
Returns information about the requested human task user interface (worker task template).
', 'DescribeHyperParameterTuningJob' => 'Returns a description of a hyperparameter tuning job, depending on the fields selected. These fields can include the name, Amazon Resource Name (ARN), job status of your tuning job and more.
', 'DescribeImage' => 'Describes a SageMaker image.
', 'DescribeImageVersion' => 'Describes a version of a SageMaker image.
', 'DescribeInferenceExperiment' => 'Returns details about an inference experiment.
', 'DescribeInferenceRecommendationsJob' => 'Provides the results of the Inference Recommender job. One or more recommendation jobs are returned.
', 'DescribeLabelingJob' => 'Gets information about a labeling job.
', 'DescribeLineageGroup' => 'Provides a list of properties for the requested lineage group. For more information, see Cross-Account Lineage Tracking in the Amazon SageMaker Developer Guide.
', 'DescribeModel' => 'Describes a model that you created using the CreateModel API.
Returns a description of a model bias job definition.
', 'DescribeModelCard' => 'Describes the content, creation time, and security configuration of an Amazon SageMaker Model Card.
', 'DescribeModelCardExportJob' => 'Describes an Amazon SageMaker Model Card export job.
', 'DescribeModelExplainabilityJobDefinition' => 'Returns a description of a model explainability job definition.
', 'DescribeModelPackage' => 'Returns a description of the specified model package, which is used to create SageMaker models or list them on Amazon Web Services Marketplace.
To create models in SageMaker, buyers can subscribe to model packages listed on Amazon Web Services Marketplace.
', 'DescribeModelPackageGroup' => 'Gets a description for the specified model group.
', 'DescribeModelQualityJobDefinition' => 'Returns a description of a model quality job definition.
', 'DescribeMonitoringSchedule' => 'Describes the schedule for a monitoring job.
', 'DescribeNotebookInstance' => 'Returns information about a notebook instance.
', 'DescribeNotebookInstanceLifecycleConfig' => 'Returns a description of a notebook instance lifecycle configuration.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
', 'DescribePipeline' => 'Describes the details of a pipeline.
', 'DescribePipelineDefinitionForExecution' => 'Describes the details of an execution\'s pipeline definition.
', 'DescribePipelineExecution' => 'Describes the details of a pipeline execution.
', 'DescribeProcessingJob' => 'Returns a description of a processing job.
', 'DescribeProject' => 'Describes the details of a project.
', 'DescribeSpace' => 'Describes the space.
', 'DescribeStudioLifecycleConfig' => 'Describes the Studio Lifecycle Configuration.
', 'DescribeSubscribedWorkteam' => 'Gets information about a work team provided by a vendor. It returns details about the subscription with a vendor in the Amazon Web Services Marketplace.
', 'DescribeTrainingJob' => 'Returns information about a training job.
Some of the attributes below only appear if the training job successfully starts. If the training job fails, TrainingJobStatus is Failed and, depending on the FailureReason, attributes like TrainingStartTime, TrainingTimeInSeconds, TrainingEndTime, and BillableTimeInSeconds may not be present in the response.
Returns information about a transform job.
', 'DescribeTrial' => 'Provides a list of a trial\'s properties.
', 'DescribeTrialComponent' => 'Provides a list of a trials component\'s properties.
', 'DescribeUserProfile' => 'Describes a user profile. For more information, see CreateUserProfile.
Lists private workforce information, including workforce name, Amazon Resource Name (ARN), and, if applicable, allowed IP address ranges (CIDRs). Allowable IP address ranges are the IP addresses that workers can use to access tasks.
This operation applies only to private workforces.
Gets information about a specific work team. You can see information such as the create date, the last updated date, membership information, and the work team\'s Amazon Resource Name (ARN).
', 'DisableSagemakerServicecatalogPortfolio' => 'Disables using Service Catalog in SageMaker. Service Catalog is used to create SageMaker projects.
', 'DisassociateTrialComponent' => 'Disassociates a trial component from a trial. This doesn\'t effect other trials the component is associated with. Before you can delete a component, you must disassociate the component from all trials it is associated with. To associate a trial component with a trial, call the AssociateTrialComponent API.
To get a list of the trials a component is associated with, use the Search API. Specify ExperimentTrialComponent for the Resource parameter. The list appears in the response under Results.TrialComponent.Parents.
Enables using Service Catalog in SageMaker. Service Catalog is used to create SageMaker projects.
', 'GetDeviceFleetReport' => 'Describes a fleet.
', 'GetLineageGroupPolicy' => 'The resource policy for the lineage group.
', 'GetModelPackageGroupPolicy' => 'Gets a resource policy that manages access for a model group. For information about resource policies, see Identity-based policies and resource-based policies in the Amazon Web Services Identity and Access Management User Guide..
', 'GetSagemakerServicecatalogPortfolioStatus' => 'Gets the status of Service Catalog in SageMaker. Service Catalog is used to create SageMaker projects.
', 'GetScalingConfigurationRecommendation' => 'Starts an Amazon SageMaker Inference Recommender autoscaling recommendation job. Returns recommendations for autoscaling policies that you can apply to your SageMaker endpoint.
', 'GetSearchSuggestions' => 'An auto-complete API for the search functionality in the SageMaker console. It returns suggestions of possible matches for the property name to use in Search queries. Provides suggestions for HyperParameters, Tags, and Metrics.
Import hub content.
Hub APIs are only callable through SageMaker Studio.
Lists the actions in your account and their properties.
', 'ListAlgorithms' => 'Lists the machine learning algorithms that have been created.
', 'ListAliases' => 'Lists the aliases of a specified image or image version.
', 'ListAppImageConfigs' => 'Lists the AppImageConfigs in your account and their properties. The list can be filtered by creation time or modified time, and whether the AppImageConfig name contains a specified string.
', 'ListApps' => 'Lists apps.
', 'ListArtifacts' => 'Lists the artifacts in your account and their properties.
', 'ListAssociations' => 'Lists the associations in your account and their properties.
', 'ListAutoMLJobs' => 'Request a list of jobs.
', 'ListCandidatesForAutoMLJob' => 'List the candidates created for the job.
', 'ListCodeRepositories' => 'Gets a list of the Git repositories in your account.
', 'ListCompilationJobs' => 'Lists model compilation jobs that satisfy various filters.
To create a model compilation job, use CreateCompilationJob. To get information about a particular model compilation job you have created, use DescribeCompilationJob.
', 'ListContexts' => 'Lists the contexts in your account and their properties.
', 'ListDataQualityJobDefinitions' => 'Lists the data quality job definitions in your account.
', 'ListDeviceFleets' => 'Returns a list of devices in the fleet.
', 'ListDevices' => 'A list of devices.
', 'ListDomains' => 'Lists the domains.
', 'ListEdgeDeploymentPlans' => 'Lists all edge deployment plans.
', 'ListEdgePackagingJobs' => 'Returns a list of edge packaging jobs.
', 'ListEndpointConfigs' => 'Lists endpoint configurations.
', 'ListEndpoints' => 'Lists endpoints.
', 'ListExperiments' => 'Lists all the experiments in your account. The list can be filtered to show only experiments that were created in a specific time range. The list can be sorted by experiment name or creation time.
', 'ListFeatureGroups' => 'List FeatureGroups based on given filter and order.
Returns information about the flow definitions in your account.
', 'ListHubContentVersions' => 'List hub content versions.
Hub APIs are only callable through SageMaker Studio.
List the contents of a hub.
Hub APIs are only callable through SageMaker Studio.
List all existing hubs.
Hub APIs are only callable through SageMaker Studio.
Returns information about the human task user interfaces in your account.
', 'ListHyperParameterTuningJobs' => 'Gets a list of HyperParameterTuningJobSummary objects that describe the hyperparameter tuning jobs launched in your account.
', 'ListImageVersions' => 'Lists the versions of a specified image and their properties. The list can be filtered by creation time or modified time.
', 'ListImages' => 'Lists the images in your account and their properties. The list can be filtered by creation time or modified time, and whether the image name contains a specified string.
', 'ListInferenceExperiments' => 'Returns the list of all inference experiments.
', 'ListInferenceRecommendationsJobSteps' => 'Returns a list of the subtasks for an Inference Recommender job.
The supported subtasks are benchmarks, which evaluate the performance of your model on different instance types.
', 'ListInferenceRecommendationsJobs' => 'Lists recommendation jobs that satisfy various filters.
', 'ListLabelingJobs' => 'Gets a list of labeling jobs.
', 'ListLabelingJobsForWorkteam' => 'Gets a list of labeling jobs assigned to a specified work team.
', 'ListLineageGroups' => 'A list of lineage groups shared with your Amazon Web Services account. For more information, see Cross-Account Lineage Tracking in the Amazon SageMaker Developer Guide.
', 'ListModelBiasJobDefinitions' => 'Lists model bias jobs definitions that satisfy various filters.
', 'ListModelCardExportJobs' => 'List the export jobs for the Amazon SageMaker Model Card.
', 'ListModelCardVersions' => 'List existing versions of an Amazon SageMaker Model Card.
', 'ListModelCards' => 'List existing model cards.
', 'ListModelExplainabilityJobDefinitions' => 'Lists model explainability job definitions that satisfy various filters.
', 'ListModelMetadata' => 'Lists the domain, framework, task, and model name of standard machine learning models found in common model zoos.
', 'ListModelPackageGroups' => 'Gets a list of the model groups in your Amazon Web Services account.
', 'ListModelPackages' => 'Lists the model packages that have been created.
', 'ListModelQualityJobDefinitions' => 'Gets a list of model quality monitoring job definitions in your account.
', 'ListModels' => 'Lists models created with the CreateModel API.
Gets a list of past alerts in a model monitoring schedule.
', 'ListMonitoringAlerts' => 'Gets the alerts for a single monitoring schedule.
', 'ListMonitoringExecutions' => 'Returns list of all monitoring job executions.
', 'ListMonitoringSchedules' => 'Returns list of all monitoring schedules.
', 'ListNotebookInstanceLifecycleConfigs' => 'Lists notebook instance lifestyle configurations created with the CreateNotebookInstanceLifecycleConfig API.
', 'ListNotebookInstances' => 'Returns a list of the SageMaker notebook instances in the requester\'s account in an Amazon Web Services Region.
', 'ListPipelineExecutionSteps' => 'Gets a list of PipeLineExecutionStep objects.
Gets a list of the pipeline executions.
', 'ListPipelineParametersForExecution' => 'Gets a list of parameters for a pipeline execution.
', 'ListPipelines' => 'Gets a list of pipelines.
', 'ListProcessingJobs' => 'Lists processing jobs that satisfy various filters.
', 'ListProjects' => 'Gets a list of the projects in an Amazon Web Services account.
', 'ListResourceCatalogs' => ' Lists Amazon SageMaker Catalogs based on given filters and orders. The maximum number of ResourceCatalogs viewable is 1000.
Lists spaces.
', 'ListStageDevices' => 'Lists devices allocated to the stage, containing detailed device information and deployment status.
', 'ListStudioLifecycleConfigs' => 'Lists the Studio Lifecycle Configurations in your Amazon Web Services Account.
', 'ListSubscribedWorkteams' => 'Gets a list of the work teams that you are subscribed to in the Amazon Web Services Marketplace. The list may be empty if no work team satisfies the filter specified in the NameContains parameter.
Returns the tags for the specified SageMaker resource.
', 'ListTrainingJobs' => 'Lists training jobs.
When StatusEquals and MaxResults are set at the same time, the MaxResults number of training jobs are first retrieved ignoring the StatusEquals parameter and then they are filtered by the StatusEquals parameter, which is returned as a response.
For example, if ListTrainingJobs is invoked with the following parameters:
{ ... MaxResults: 100, StatusEquals: InProgress ... }
First, 100 trainings jobs with any status, including those other than InProgress, are selected (sorted according to the creation time, from the most current to the oldest). Next, those with a status of InProgress are returned.
You can quickly test the API using the following Amazon Web Services CLI code.
aws sagemaker list-training-jobs --max-results 100 --status-equals InProgress
Gets a list of TrainingJobSummary objects that describe the training jobs that a hyperparameter tuning job launched.
', 'ListTransformJobs' => 'Lists transform jobs.
', 'ListTrialComponents' => 'Lists the trial components in your account. You can sort the list by trial component name or creation time. You can filter the list to show only components that were created in a specific time range. You can also filter on one of the following:
ExperimentName
SourceArn
TrialName
Lists the trials in your account. Specify an experiment name to limit the list to the trials that are part of that experiment. Specify a trial component name to limit the list to the trials that associated with that trial component. The list can be filtered to show only trials that were created in a specific time range. The list can be sorted by trial name or creation time.
', 'ListUserProfiles' => 'Lists user profiles.
', 'ListWorkforces' => 'Use this operation to list all private and vendor workforces in an Amazon Web Services Region. Note that you can only have one private workforce per Amazon Web Services Region.
', 'ListWorkteams' => 'Gets a list of private work teams that you have defined in a region. The list may be empty if no work team satisfies the filter specified in the NameContains parameter.
Adds a resouce policy to control access to a model group. For information about resoure policies, see Identity-based policies and resource-based policies in the Amazon Web Services Identity and Access Management User Guide..
', 'QueryLineage' => 'Use this action to inspect your lineage and discover relationships between entities. For more information, see Querying Lineage Entities in the Amazon SageMaker Developer Guide.
', 'RegisterDevices' => 'Register devices.
', 'RenderUiTemplate' => 'Renders the UI template so that you can preview the worker\'s experience.
', 'RetryPipelineExecution' => 'Retry the execution of the pipeline.
', 'Search' => 'Finds SageMaker resources that match a search query. Matching resources are returned as a list of SearchRecord objects in the response. You can sort the search results by any resource property in a ascending or descending order.
You can query against the following value types: numeric, text, Boolean, and timestamp.
The Search API may provide access to otherwise restricted data. See Amazon SageMaker API Permissions: Actions, Permissions, and Resources Reference for more information.
Notifies the pipeline that the execution of a callback step failed, along with a message describing why. When a callback step is run, the pipeline generates a callback token and includes the token in a message sent to Amazon Simple Queue Service (Amazon SQS).
', 'SendPipelineExecutionStepSuccess' => 'Notifies the pipeline that the execution of a callback step succeeded and provides a list of the step\'s output parameters. When a callback step is run, the pipeline generates a callback token and includes the token in a message sent to Amazon Simple Queue Service (Amazon SQS).
', 'StartEdgeDeploymentStage' => 'Starts a stage in an edge deployment plan.
', 'StartInferenceExperiment' => 'Starts an inference experiment.
', 'StartMonitoringSchedule' => 'Starts a previously stopped monitoring schedule.
By default, when you successfully create a new schedule, the status of a monitoring schedule is scheduled.
Launches an ML compute instance with the latest version of the libraries and attaches your ML storage volume. After configuring the notebook instance, SageMaker sets the notebook instance status to InService. A notebook instance\'s status must be InService before you can connect to your Jupyter notebook.
Starts a pipeline execution.
', 'StopAutoMLJob' => 'A method for forcing a running job to shut down.
', 'StopCompilationJob' => 'Stops a model compilation job.
To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal. This gracefully shuts the job down. If the job hasn\'t stopped, it sends the SIGKILL signal.
When it receives a StopCompilationJob request, Amazon SageMaker changes the CompilationJobStatus of the job to Stopping. After Amazon SageMaker stops the job, it sets the CompilationJobStatus to Stopped.
Stops a stage in an edge deployment plan.
', 'StopEdgePackagingJob' => 'Request to stop an edge packaging job.
', 'StopHyperParameterTuningJob' => 'Stops a running hyperparameter tuning job and all running training jobs that the tuning job launched.
All model artifacts output from the training jobs are stored in Amazon Simple Storage Service (Amazon S3). All data that the training jobs write to Amazon CloudWatch Logs are still available in CloudWatch. After the tuning job moves to the Stopped state, it releases all reserved resources for the tuning job.
Stops an inference experiment.
', 'StopInferenceRecommendationsJob' => 'Stops an Inference Recommender job.
', 'StopLabelingJob' => 'Stops a running labeling job. A job that is stopped cannot be restarted. Any results obtained before the job is stopped are placed in the Amazon S3 output bucket.
', 'StopMonitoringSchedule' => 'Stops a previously started monitoring schedule.
', 'StopNotebookInstance' => 'Terminates the ML compute instance. Before terminating the instance, SageMaker disconnects the ML storage volume from it. SageMaker preserves the ML storage volume. SageMaker stops charging you for the ML compute instance when you call StopNotebookInstance.
To access data on the ML storage volume for a notebook instance that has been terminated, call the StartNotebookInstance API. StartNotebookInstance launches another ML compute instance, configures it, and attaches the preserved ML storage volume so you can continue your work.
Stops a pipeline execution.
Callback Step
A pipeline execution won\'t stop while a callback step is running. When you call StopPipelineExecution on a pipeline execution with a running callback step, SageMaker Pipelines sends an additional Amazon SQS message to the specified SQS queue. The body of the SQS message contains a "Status" field which is set to "Stopping".
You should add logic to your Amazon SQS message consumer to take any needed action (for example, resource cleanup) upon receipt of the message followed by a call to SendPipelineExecutionStepSuccess or SendPipelineExecutionStepFailure.
Only when SageMaker Pipelines receives one of these calls will it stop the pipeline execution.
Lambda Step
A pipeline execution can\'t be stopped while a lambda step is running because the Lambda function invoked by the lambda step can\'t be stopped. If you attempt to stop the execution while the Lambda function is running, the pipeline waits for the Lambda function to finish or until the timeout is hit, whichever occurs first, and then stops. If the Lambda function finishes, the pipeline execution status is Stopped. If the timeout is hit the pipeline execution status is Failed.
Stops a processing job.
', 'StopTrainingJob' => 'Stops a training job. To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms might use this 120-second window to save the model artifacts, so the results of the training is not lost.
When it receives a StopTrainingJob request, SageMaker changes the status of the job to Stopping. After SageMaker stops the job, it sets the status to Stopped.
Stops a batch transform job.
When Amazon SageMaker receives a StopTransformJob request, the status of the job changes to Stopping. After Amazon SageMaker stops the job, the status is set to Stopped. When you stop a batch transform job before it is completed, Amazon SageMaker doesn\'t store the job\'s output in Amazon S3.
Updates an action.
', 'UpdateAppImageConfig' => 'Updates the properties of an AppImageConfig.
', 'UpdateArtifact' => 'Updates an artifact.
', 'UpdateCodeRepository' => 'Updates the specified Git repository with the specified values.
', 'UpdateContext' => 'Updates a context.
', 'UpdateDeviceFleet' => 'Updates a fleet of devices.
', 'UpdateDevices' => 'Updates one or more devices in a fleet.
', 'UpdateDomain' => 'Updates the default settings for new user profiles in the domain.
', 'UpdateEndpoint' => 'Deploys the new EndpointConfig specified in the request, switches to using newly created endpoint, and then deletes resources provisioned for the endpoint using the previous EndpointConfig (there is no availability loss).
When SageMaker receives the request, it sets the endpoint status to Updating. After updating the endpoint, it sets the status to InService. To check the status of an endpoint, use the DescribeEndpoint API.
You must not delete an EndpointConfig in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. To update an endpoint, you must create a new EndpointConfig.
If you delete the EndpointConfig of an endpoint that is active or being created or updated you may lose visibility into the instance type the endpoint is using. The endpoint must be deleted in order to stop incurring charges.
Updates variant weight of one or more variants associated with an existing endpoint, or capacity of one variant associated with an existing endpoint. When it receives the request, SageMaker sets the endpoint status to Updating. After updating the endpoint, it sets the status to InService. To check the status of an endpoint, use the DescribeEndpoint API.
Adds, updates, or removes the description of an experiment. Updates the display name of an experiment.
', 'UpdateFeatureGroup' => 'Updates the feature group by either adding features or updating the online store configuration. Use one of the following request parameters at a time while using the UpdateFeatureGroup API.
You can add features for your feature group using the FeatureAdditions request parameter. Features cannot be removed from a feature group.
You can update the online store configuration by using the OnlineStoreConfig request parameter. If a TtlDuration is specified, the default TtlDuration applies for all records added to the feature group after the feature group is updated. If a record level TtlDuration exists from using the PutRecord API, the record level TtlDuration applies to that record instead of the default TtlDuration.
Updates the description and parameters of the feature group.
', 'UpdateHub' => 'Update a hub.
Hub APIs are only callable through SageMaker Studio.
Updates the properties of a SageMaker image. To change the image\'s tags, use the AddTags and DeleteTags APIs.
', 'UpdateImageVersion' => 'Updates the properties of a SageMaker image version.
', 'UpdateInferenceExperiment' => ' Updates an inference experiment that you created. The status of the inference experiment has to be either Created, Running. For more information on the status of an inference experiment, see DescribeInferenceExperiment.
Update an Amazon SageMaker Model Card.
You cannot update both model card content and model card status in a single call.
Updates a versioned model.
', 'UpdateMonitoringAlert' => 'Update the parameters of a model monitor alert.
', 'UpdateMonitoringSchedule' => 'Updates a previously created schedule.
', 'UpdateNotebookInstance' => 'Updates a notebook instance. NotebookInstance updates include upgrading or downgrading the ML compute instance used for your notebook instance to accommodate changes in your workload requirements.
', 'UpdateNotebookInstanceLifecycleConfig' => 'Updates a notebook instance lifecycle configuration created with the CreateNotebookInstanceLifecycleConfig API.
', 'UpdatePipeline' => 'Updates a pipeline.
', 'UpdatePipelineExecution' => 'Updates a pipeline execution.
', 'UpdateProject' => 'Updates a machine learning (ML) project that is created from a template that sets up an ML pipeline from training to deploying an approved model.
You must not update a project that is in use. If you update the ServiceCatalogProvisioningUpdateDetails of a project that is active or being created, or updated, you may lose resources already created by the project.
Updates the settings of a space.
', 'UpdateTrainingJob' => 'Update a model training job to request a new Debugger profiling configuration or to change warm pool retention length.
', 'UpdateTrial' => 'Updates the display name of a trial.
', 'UpdateTrialComponent' => 'Updates one or more properties of a trial component.
', 'UpdateUserProfile' => 'Updates a user profile.
', 'UpdateWorkforce' => 'Use this operation to update your workforce. You can use this operation to require that workers use specific IP addresses to work on tasks and to update your OpenID Connect (OIDC) Identity Provider (IdP) workforce configuration.
The worker portal is now supported in VPC and public internet.
Use SourceIpConfig to restrict worker access to tasks to a specific range of IP addresses. You specify allowed IP addresses by creating a list of up to ten CIDRs. By default, a workforce isn\'t restricted to specific IP addresses. If you specify a range of IP addresses, workers who attempt to access tasks using any IP address outside the specified range are denied and get a Not Found error message on the worker portal.
To restrict access to all the workers in public internet, add the SourceIpConfig CIDR value as "10.0.0.0/16".
Amazon SageMaker does not support Source Ip restriction for worker portals in VPC.
Use OidcConfig to update the configuration of a workforce created using your own OIDC IdP.
You can only update your OIDC IdP configuration when there are no work teams associated with your workforce. You can delete work teams using the DeleteWorkteam operation.
After restricting access to a range of IP addresses or updating your OIDC IdP configuration with this operation, you can view details about your update workforce using the DescribeWorkforce operation.
This operation only applies to private workforces.
Updates an existing work team with new member definitions or description.
', ], 'shapes' => [ 'Accept' => [ 'base' => NULL, 'refs' => [ 'TransformOutput$Accept' => 'The MIME type used to specify the output data. Amazon SageMaker uses the MIME type with each http call to transfer data from the transform job.
', ], ], 'AcceptEula' => [ 'base' => NULL, 'refs' => [ 'ModelAccessConfig$AcceptEula' => 'Specifies agreement to the model end-user license agreement (EULA). The AcceptEula value must be explicitly defined as True in order to accept the EULA that this model requires. You are responsible for reviewing and complying with any applicable license terms and making sure they are acceptable for your use case before downloading or using a model.
The Amazon Web Services account ID of the account used to start the labeling job.
', ], ], 'ActionArn' => [ 'base' => NULL, 'refs' => [ 'ActionSummary$ActionArn' => 'The Amazon Resource Name (ARN) of the action.
', 'CreateActionResponse$ActionArn' => 'The Amazon Resource Name (ARN) of the action.
', 'DeleteActionResponse$ActionArn' => 'The Amazon Resource Name (ARN) of the action.
', 'DescribeActionResponse$ActionArn' => 'The Amazon Resource Name (ARN) of the action.
', 'UpdateActionResponse$ActionArn' => 'The Amazon Resource Name (ARN) of the action.
', ], ], 'ActionSource' => [ 'base' => 'A structure describing the source of an action.
', 'refs' => [ 'ActionSummary$Source' => 'The source of the action.
', 'CreateActionRequest$Source' => 'The source type, ID, and URI.
', 'DescribeActionResponse$Source' => 'The source of the action.
', ], ], 'ActionStatus' => [ 'base' => NULL, 'refs' => [ 'ActionSummary$Status' => 'The status of the action.
', 'CreateActionRequest$Status' => 'The status of the action.
', 'DescribeActionResponse$Status' => 'The status of the action.
', 'UpdateActionRequest$Status' => 'The new status for the action.
', ], ], 'ActionSummaries' => [ 'base' => NULL, 'refs' => [ 'ListActionsResponse$ActionSummaries' => 'A list of actions and their properties.
', ], ], 'ActionSummary' => [ 'base' => 'Lists the properties of an action. An action represents an action or activity. Some examples are a workflow step and a model deployment. Generally, an action involves at least one input artifact or output artifact.
', 'refs' => [ 'ActionSummaries$member' => NULL, ], ], 'AddAssociationRequest' => [ 'base' => NULL, 'refs' => [], ], 'AddAssociationResponse' => [ 'base' => NULL, 'refs' => [], ], 'AddTagsInput' => [ 'base' => NULL, 'refs' => [], ], 'AddTagsOutput' => [ 'base' => NULL, 'refs' => [], ], 'AdditionalCodeRepositoryNamesOrUrls' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$AdditionalCodeRepositories' => 'An array of up to three Git repositories to associate with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', 'DescribeNotebookInstanceOutput$AdditionalCodeRepositories' => 'An array of up to three Git repositories associated with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', 'NotebookInstanceSummary$AdditionalCodeRepositories' => 'An array of up to three Git repositories associated with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', 'UpdateNotebookInstanceInput$AdditionalCodeRepositories' => 'An array of up to three Git repositories to associate with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', ], ], 'AdditionalInferenceSpecificationDefinition' => [ 'base' => 'A structure of additional Inference Specification. Additional Inference Specification specifies details about inference jobs that can be run with models based on this model package
', 'refs' => [ 'AdditionalInferenceSpecifications$member' => NULL, ], ], 'AdditionalInferenceSpecifications' => [ 'base' => NULL, 'refs' => [ 'CreateModelPackageInput$AdditionalInferenceSpecifications' => 'An array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
', 'DescribeModelPackageOutput$AdditionalInferenceSpecifications' => 'An array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
', 'ModelPackage$AdditionalInferenceSpecifications' => 'An array of additional Inference Specification objects.
', 'UpdateModelPackageInput$AdditionalInferenceSpecificationsToAdd' => 'An array of additional Inference Specification objects to be added to the existing array additional Inference Specification. Total number of additional Inference Specifications can not exceed 15. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
', ], ], 'AdditionalS3DataSource' => [ 'base' => 'A data source used for training or inference that is in addition to the input dataset or model data.
', 'refs' => [ 'ModelPackageContainerDefinition$AdditionalS3DataSource' => 'The additional data source that is used during inference in the Docker container for your model package.
', 'TrainingSpecification$AdditionalS3DataSource' => 'The additional data source used during the training job.
', ], ], 'AdditionalS3DataSourceDataType' => [ 'base' => NULL, 'refs' => [ 'AdditionalS3DataSource$S3DataType' => 'The data type of the additional data source that you specify for use in inference or training.
', ], ], 'AgentVersion' => [ 'base' => 'Edge Manager agent version.
', 'refs' => [ 'AgentVersions$member' => NULL, ], ], 'AgentVersions' => [ 'base' => NULL, 'refs' => [ 'GetDeviceFleetReportResponse$AgentVersions' => 'The versions of Edge Manager agent deployed on the fleet.
', ], ], 'AggregationTransformationValue' => [ 'base' => NULL, 'refs' => [ 'AggregationTransformations$value' => NULL, ], ], 'AggregationTransformations' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesTransformations$Aggregation' => 'A key value pair defining the aggregation method for a column, where the key is the column name and the value is the aggregation method.
The supported aggregation methods are sum (default), avg, first, min, max.
Aggregation is only supported for the target column.
An Amazon CloudWatch alarm configured to monitor metrics on an endpoint.
', 'refs' => [ 'AlarmList$member' => NULL, ], ], 'AlarmList' => [ 'base' => NULL, 'refs' => [ 'AutoRollbackConfig$Alarms' => 'List of CloudWatch alarms in your account that are configured to monitor metrics on an endpoint. If any alarms are tripped during a deployment, SageMaker rolls back the deployment.
', ], ], 'AlarmName' => [ 'base' => NULL, 'refs' => [ 'Alarm$AlarmName' => 'The name of a CloudWatch alarm in your account.
', ], ], 'AlgorithmArn' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSummary$AlgorithmArn' => 'The Amazon Resource Name (ARN) of the algorithm.
', 'CreateAlgorithmOutput$AlgorithmArn' => 'The Amazon Resource Name (ARN) of the new algorithm.
', 'DescribeAlgorithmOutput$AlgorithmArn' => 'The Amazon Resource Name (ARN) of the algorithm.
', ], ], 'AlgorithmImage' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSpecification$TrainingImage' => 'The registry path of the Docker image that contains the training algorithm. For information about docker registry paths for SageMaker built-in algorithms, see Docker Registry Paths and Example Code in the Amazon SageMaker developer guide. SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information about using your custom training container, see Using Your Own Algorithms with Amazon SageMaker.
You must specify either the algorithm name to the AlgorithmName parameter or the image URI of the algorithm container to the TrainingImage parameter.
For more information, see the note in the AlgorithmName parameter description.
The Amazon Elastic Container (ECR) Image for the managed rule evaluation.
', 'HyperParameterAlgorithmSpecification$TrainingImage' => ' The registry path of the Docker image that contains the training algorithm. For information about Docker registry paths for built-in algorithms, see Algorithms Provided by Amazon SageMaker: Common Parameters. SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.
The Amazon Elastic Container Registry Image for the managed rule evaluation.
', ], ], 'AlgorithmSortBy' => [ 'base' => NULL, 'refs' => [ 'ListAlgorithmsInput$SortBy' => 'The parameter by which to sort the results. The default is CreationTime.
Specifies the training algorithm to use in a CreateTrainingJob request.
For more information about algorithms provided by SageMaker, see Algorithms. For information about using your own algorithms, see Using Your Own Algorithms with Amazon SageMaker.
', 'refs' => [ 'CreateTrainingJobRequest$AlgorithmSpecification' => 'The registry path of the Docker image that contains the training algorithm and algorithm-specific metadata, including the input mode. For more information about algorithms provided by SageMaker, see Algorithms. For information about providing your own algorithms, see Using Your Own Algorithms with Amazon SageMaker.
', 'DescribeTrainingJobResponse$AlgorithmSpecification' => 'Information about the algorithm used for training, and algorithm metadata.
', 'TrainingJob$AlgorithmSpecification' => 'Information about the algorithm used for training, and algorithm metadata.
', ], ], 'AlgorithmStatus' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSummary$AlgorithmStatus' => 'The overall status of the algorithm.
', 'DescribeAlgorithmOutput$AlgorithmStatus' => 'The current status of the algorithm.
', ], ], 'AlgorithmStatusDetails' => [ 'base' => 'Specifies the validation and image scan statuses of the algorithm.
', 'refs' => [ 'DescribeAlgorithmOutput$AlgorithmStatusDetails' => 'Details about the current status of the algorithm.
', ], ], 'AlgorithmStatusItem' => [ 'base' => 'Represents the overall status of an algorithm.
', 'refs' => [ 'AlgorithmStatusItemList$member' => NULL, ], ], 'AlgorithmStatusItemList' => [ 'base' => NULL, 'refs' => [ 'AlgorithmStatusDetails$ValidationStatuses' => 'The status of algorithm validation.
', 'AlgorithmStatusDetails$ImageScanStatuses' => 'The status of the scan of the algorithm\'s Docker image container.
', ], ], 'AlgorithmSummary' => [ 'base' => 'Provides summary information about an algorithm.
', 'refs' => [ 'AlgorithmSummaryList$member' => NULL, ], ], 'AlgorithmSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListAlgorithmsOutput$AlgorithmSummaryList' => '>An array of AlgorithmSummary objects, each of which lists an algorithm.
Defines a training job and a batch transform job that SageMaker runs to validate your algorithm.
The data provided in the validation profile is made available to your buyers on Amazon Web Services Marketplace.
', 'refs' => [ 'AlgorithmValidationProfiles$member' => NULL, ], ], 'AlgorithmValidationProfiles' => [ 'base' => NULL, 'refs' => [ 'AlgorithmValidationSpecification$ValidationProfiles' => 'An array of AlgorithmValidationProfile objects, each of which specifies a training job and batch transform job that SageMaker runs to validate your algorithm.
Specifies configurations for one or more training jobs that SageMaker runs to test the algorithm.
', 'refs' => [ 'CreateAlgorithmInput$ValidationSpecification' => 'Specifies configurations for one or more training jobs and that SageMaker runs to test the algorithm\'s training code and, optionally, one or more batch transform jobs that SageMaker runs to test the algorithm\'s inference code.
', 'DescribeAlgorithmOutput$ValidationSpecification' => 'Details about configurations for one or more training jobs that SageMaker runs to test the algorithm.
', ], ], 'AnnotationConsolidationConfig' => [ 'base' => 'Configures how labels are consolidated across human workers and processes output data.
', 'refs' => [ 'HumanTaskConfig$AnnotationConsolidationConfig' => 'Configures how labels are consolidated across human workers.
', ], ], 'AppArn' => [ 'base' => NULL, 'refs' => [ 'CreateAppResponse$AppArn' => 'The Amazon Resource Name (ARN) of the app.
', 'DescribeAppResponse$AppArn' => 'The Amazon Resource Name (ARN) of the app.
', ], ], 'AppDetails' => [ 'base' => 'Details about an Amazon SageMaker app.
', 'refs' => [ 'AppList$member' => NULL, ], ], 'AppImageConfigArn' => [ 'base' => NULL, 'refs' => [ 'AppImageConfigDetails$AppImageConfigArn' => 'The Amazon Resource Name (ARN) of the AppImageConfig.
', 'CreateAppImageConfigResponse$AppImageConfigArn' => 'The Amazon Resource Name (ARN) of the AppImageConfig.
', 'DescribeAppImageConfigResponse$AppImageConfigArn' => 'The Amazon Resource Name (ARN) of the AppImageConfig.
', 'UpdateAppImageConfigResponse$AppImageConfigArn' => 'The Amazon Resource Name (ARN) for the AppImageConfig.
', ], ], 'AppImageConfigDetails' => [ 'base' => 'The configuration for running a SageMaker image as a KernelGateway app.
', 'refs' => [ 'AppImageConfigList$member' => NULL, ], ], 'AppImageConfigList' => [ 'base' => NULL, 'refs' => [ 'ListAppImageConfigsResponse$AppImageConfigs' => 'A list of AppImageConfigs and their properties.
', ], ], 'AppImageConfigName' => [ 'base' => NULL, 'refs' => [ 'AppImageConfigDetails$AppImageConfigName' => 'The name of the AppImageConfig. Must be unique to your account.
', 'CreateAppImageConfigRequest$AppImageConfigName' => 'The name of the AppImageConfig. Must be unique to your account.
', 'CustomImage$AppImageConfigName' => 'The name of the AppImageConfig.
', 'DeleteAppImageConfigRequest$AppImageConfigName' => 'The name of the AppImageConfig to delete.
', 'DescribeAppImageConfigRequest$AppImageConfigName' => 'The name of the AppImageConfig to describe.
', 'DescribeAppImageConfigResponse$AppImageConfigName' => 'The name of the AppImageConfig.
', 'ListAppImageConfigsRequest$NameContains' => 'A filter that returns only AppImageConfigs whose name contains the specified string.
', 'UpdateAppImageConfigRequest$AppImageConfigName' => 'The name of the AppImageConfig to update.
', ], ], 'AppImageConfigSortKey' => [ 'base' => NULL, 'refs' => [ 'ListAppImageConfigsRequest$SortBy' => 'The property used to sort results. The default value is CreationTime.
The instance type that the image version runs on.
JupyterServer apps only support the system value.
For KernelGateway apps, the system value is translated to ml.t3.medium. KernelGateway apps also support all other values for available instance types.
The list of apps.
', ], ], 'AppManaged' => [ 'base' => NULL, 'refs' => [ 'ProcessingInput$AppManaged' => 'When True, input operations such as data download are managed natively by the processing job application. When False (default), input operations are managed by Amazon SageMaker.
When True, output operations such as data upload are managed natively by the processing job application. When False (default), output operations are managed by Amazon SageMaker.
The name of the app.
', 'CreateAppRequest$AppName' => 'The name of the app.
', 'DeleteAppRequest$AppName' => 'The name of the app.
', 'DescribeAppRequest$AppName' => 'The name of the app.
', 'DescribeAppResponse$AppName' => 'The name of the app.
', ], ], 'AppNetworkAccessType' => [ 'base' => NULL, 'refs' => [ 'CreateDomainRequest$AppNetworkAccessType' => 'Specifies the VPC used for non-EFS traffic. The default value is PublicInternetOnly.
PublicInternetOnly - Non-EFS traffic is through a VPC managed by Amazon SageMaker, which allows direct internet access
VpcOnly - All Studio traffic is through the specified VPC and subnets
Specifies the VPC used for non-EFS traffic. The default value is PublicInternetOnly.
PublicInternetOnly - Non-EFS traffic is through a VPC managed by Amazon SageMaker, which allows direct internet access
VpcOnly - All Studio traffic is through the specified VPC and subnets
The entity that creates and manages the required security groups for inter-app communication in VPCOnly mode. Required when CreateDomain.AppNetworkAccessType is VPCOnly and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided. If setting up the domain for use with RStudio, this value must be set to Service.
The entity that creates and manages the required security groups for inter-app communication in VPCOnly mode. Required when CreateDomain.AppNetworkAccessType is VPCOnly and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided.
The entity that creates and manages the required security groups for inter-app communication in VPCOnly mode. Required when CreateDomain.AppNetworkAccessType is VPCOnly and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided. If setting up the domain for use with RStudio, this value must be set to Service.
The parameter by which to sort the results. The default is CreationTime.
', ], ], 'AppSpecification' => [ 'base' => 'Configuration to run a processing job in a specified container image.
', 'refs' => [ 'CreateProcessingJobRequest$AppSpecification' => 'Configures the processing job to run a specified Docker container image.
', 'DescribeProcessingJobResponse$AppSpecification' => 'Configures the processing job to run a specified container image.
', 'ProcessingJob$AppSpecification' => NULL, ], ], 'AppStatus' => [ 'base' => NULL, 'refs' => [ 'AppDetails$Status' => 'The status.
', 'DescribeAppResponse$Status' => 'The status.
', ], ], 'AppType' => [ 'base' => NULL, 'refs' => [ 'AppDetails$AppType' => 'The type of app.
', 'CreateAppRequest$AppType' => 'The type of app.
', 'DeleteAppRequest$AppType' => 'The type of app.
', 'DescribeAppRequest$AppType' => 'The type of app.
', 'DescribeAppResponse$AppType' => 'The type of app.
', ], ], 'ApprovalDescription' => [ 'base' => NULL, 'refs' => [ 'DescribeModelPackageOutput$ApprovalDescription' => 'A description provided for the model approval.
', 'ModelPackage$ApprovalDescription' => 'A description provided when the model approval is set.
', 'UpdateModelPackageInput$ApprovalDescription' => 'A description for the approval status of the model.
', ], ], 'ArnOrName' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSpecification$AlgorithmName' => 'The name of the algorithm resource to use for the training job. This must be an algorithm resource that you created or subscribe to on Amazon Web Services Marketplace.
You must specify either the algorithm name to the AlgorithmName parameter or the image URI of the algorithm container to the TrainingImage parameter.
Note that the AlgorithmName parameter is mutually exclusive with the TrainingImage parameter. If you specify a value for the AlgorithmName parameter, you can\'t specify a value for TrainingImage, and vice versa.
If you specify values for both parameters, the training job might break; if you don\'t specify any value for both parameters, the training job might raise a null error.
The name or Amazon Resource Name (ARN) of the model package group that this model version belongs to.
This parameter is required for versioned models, and does not apply to unversioned models.
', 'DeleteModelPackageGroupInput$ModelPackageGroupName' => 'The name of the model group to delete.
', 'DescribeAlgorithmInput$AlgorithmName' => 'The name of the algorithm to describe.
', 'DescribeModelPackageGroupInput$ModelPackageGroupName' => 'The name of gthe model group to describe.
', 'HyperParameterAlgorithmSpecification$AlgorithmName' => 'The name of the resource algorithm to use for the hyperparameter tuning job. If you specify a value for this parameter, do not specify a value for TrainingImage.
A filter that returns only model versions that belong to the specified model group.
', 'SourceAlgorithm$AlgorithmName' => 'The name of an algorithm that was used to create the model package. The algorithm must be either an algorithm resource in your SageMaker account or an algorithm in Amazon Web Services Marketplace that you are subscribed to.
', ], ], 'ArtifactArn' => [ 'base' => NULL, 'refs' => [ 'ArtifactSummary$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact.
', 'CreateArtifactResponse$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact.
', 'DeleteArtifactRequest$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact to delete.
', 'DeleteArtifactResponse$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact.
', 'DescribeArtifactRequest$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact to describe.
', 'DescribeArtifactResponse$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact.
', 'UpdateArtifactRequest$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact to update.
', 'UpdateArtifactResponse$ArtifactArn' => 'The Amazon Resource Name (ARN) of the artifact.
', ], ], 'ArtifactDigest' => [ 'base' => NULL, 'refs' => [ 'ModelDigests$ArtifactDigest' => 'Provides a hash value that uniquely identifies the stored model artifacts.
', ], ], 'ArtifactSource' => [ 'base' => 'A structure describing the source of an artifact.
', 'refs' => [ 'ArtifactSummary$Source' => 'The source of the artifact.
', 'CreateArtifactRequest$Source' => 'The ID, ID type, and URI of the source.
', 'DeleteArtifactRequest$Source' => 'The URI of the source.
', 'DescribeArtifactResponse$Source' => 'The source of the artifact.
', ], ], 'ArtifactSourceIdType' => [ 'base' => NULL, 'refs' => [ 'ArtifactSourceType$SourceIdType' => 'The type of ID.
', ], ], 'ArtifactSourceType' => [ 'base' => 'The ID and ID type of an artifact source.
', 'refs' => [ 'ArtifactSourceTypes$member' => NULL, ], ], 'ArtifactSourceTypes' => [ 'base' => NULL, 'refs' => [ 'ArtifactSource$SourceTypes' => 'A list of source types.
', ], ], 'ArtifactSummaries' => [ 'base' => NULL, 'refs' => [ 'ListArtifactsResponse$ArtifactSummaries' => 'A list of artifacts and their properties.
', ], ], 'ArtifactSummary' => [ 'base' => 'Lists a summary of the properties of an artifact. An artifact represents a URI addressable object or data. Some examples are a dataset and a model.
', 'refs' => [ 'ArtifactSummaries$member' => NULL, ], ], 'AssemblyType' => [ 'base' => NULL, 'refs' => [ 'TransformOutput$AssembleWith' => 'Defines how to assemble the results of the transform job as a single S3 object. Choose a format that is most convenient to you. To concatenate the results in binary format, specify None. To add a newline character at the end of every transformed record, specify Line.
The type of association. The following are suggested uses for each type. Amazon SageMaker places no restrictions on their use.
ContributedTo - The source contributed to the destination or had a part in enabling the destination. For example, the training data contributed to the training job.
AssociatedWith - The source is connected to the destination. For example, an approval workflow is associated with a model deployment.
DerivedFrom - The destination is a modification of the source. For example, a digest output of a channel input for a processing job is derived from the original inputs.
Produced - The source generated the destination. For example, a training job produced a model artifact.
The type of the association.
', 'Edge$AssociationType' => 'The type of the Association(Edge) between the source and destination. For example ContributedTo, Produced, or DerivedFrom.
A filter that returns only associations of the specified type.
', ], ], 'AssociationEntityArn' => [ 'base' => NULL, 'refs' => [ 'AddAssociationRequest$SourceArn' => 'The ARN of the source.
', 'AddAssociationRequest$DestinationArn' => 'The Amazon Resource Name (ARN) of the destination.
', 'AddAssociationResponse$SourceArn' => 'The ARN of the source.
', 'AddAssociationResponse$DestinationArn' => 'The Amazon Resource Name (ARN) of the destination.
', 'AssociationSummary$SourceArn' => 'The ARN of the source.
', 'AssociationSummary$DestinationArn' => 'The Amazon Resource Name (ARN) of the destination.
', 'DeleteAssociationRequest$SourceArn' => 'The ARN of the source.
', 'DeleteAssociationRequest$DestinationArn' => 'The Amazon Resource Name (ARN) of the destination.
', 'DeleteAssociationResponse$SourceArn' => 'The ARN of the source.
', 'DeleteAssociationResponse$DestinationArn' => 'The Amazon Resource Name (ARN) of the destination.
', 'Edge$SourceArn' => 'The Amazon Resource Name (ARN) of the source lineage entity of the directed edge.
', 'Edge$DestinationArn' => 'The Amazon Resource Name (ARN) of the destination lineage entity of the directed edge.
', 'ListAssociationsRequest$SourceArn' => 'A filter that returns only associations with the specified source ARN.
', 'ListAssociationsRequest$DestinationArn' => 'A filter that returns only associations with the specified destination Amazon Resource Name (ARN).
', 'QueryLineageStartArns$member' => NULL, 'Vertex$Arn' => 'The Amazon Resource Name (ARN) of the lineage entity resource.
', ], ], 'AssociationSummaries' => [ 'base' => NULL, 'refs' => [ 'ListAssociationsResponse$AssociationSummaries' => 'A list of associations and their properties.
', ], ], 'AssociationSummary' => [ 'base' => 'Lists a summary of the properties of an association. An association is an entity that links other lineage or experiment entities. An example would be an association between a training job and a model.
', 'refs' => [ 'AssociationSummaries$member' => NULL, ], ], 'AsyncInferenceClientConfig' => [ 'base' => 'Configures the behavior of the client used by SageMaker to interact with the model container during asynchronous inference.
', 'refs' => [ 'AsyncInferenceConfig$ClientConfig' => 'Configures the behavior of the client used by SageMaker to interact with the model container during asynchronous inference.
', ], ], 'AsyncInferenceConfig' => [ 'base' => 'Specifies configuration for how an endpoint performs asynchronous inference.
', 'refs' => [ 'CreateEndpointConfigInput$AsyncInferenceConfig' => 'Specifies configuration for how an endpoint performs asynchronous inference. This is a required field in order for your Endpoint to be invoked using InvokeEndpointAsync.
', 'DescribeEndpointConfigOutput$AsyncInferenceConfig' => 'Returns the description of an endpoint configuration created using the CreateEndpointConfig API.
Returns the description of an endpoint configuration created using the CreateEndpointConfig API.
Specifies the configuration for notifications of inference results for asynchronous inference.
', 'refs' => [ 'AsyncInferenceOutputConfig$NotificationConfig' => 'Specifies the configuration for notifications of inference results for asynchronous inference.
', ], ], 'AsyncInferenceOutputConfig' => [ 'base' => 'Specifies the configuration for asynchronous inference invocation outputs.
', 'refs' => [ 'AsyncInferenceConfig$OutputConfig' => 'Specifies the configuration for asynchronous inference invocation outputs.
', ], ], 'AsyncNotificationTopicTypeList' => [ 'base' => NULL, 'refs' => [ 'AsyncInferenceNotificationConfig$IncludeInferenceResponseIn' => 'The Amazon SNS topics where you want the inference response to be included.
The inference response is included only if the response size is less than or equal to 128 KB.
The name of the data catalog used in Athena query execution.
', 'refs' => [ 'AthenaDatasetDefinition$Catalog' => NULL, ], ], 'AthenaDatabase' => [ 'base' => 'The name of the database used in the Athena query execution.
', 'refs' => [ 'AthenaDatasetDefinition$Database' => NULL, ], ], 'AthenaDatasetDefinition' => [ 'base' => 'Configuration for Athena Dataset Definition input.
', 'refs' => [ 'DatasetDefinition$AthenaDatasetDefinition' => NULL, ], ], 'AthenaQueryString' => [ 'base' => 'The SQL query statements, to be executed.
', 'refs' => [ 'AthenaDatasetDefinition$QueryString' => NULL, ], ], 'AthenaResultCompressionType' => [ 'base' => 'The compression used for Athena query results.
', 'refs' => [ 'AthenaDatasetDefinition$OutputCompression' => NULL, ], ], 'AthenaResultFormat' => [ 'base' => 'The data storage format for Athena query results.
', 'refs' => [ 'AthenaDatasetDefinition$OutputFormat' => NULL, ], ], 'AthenaWorkGroup' => [ 'base' => 'The name of the workgroup in which the Athena query is being started.
', 'refs' => [ 'AthenaDatasetDefinition$WorkGroup' => NULL, ], ], 'AttributeName' => [ 'base' => NULL, 'refs' => [ 'AttributeNames$member' => NULL, ], ], 'AttributeNames' => [ 'base' => NULL, 'refs' => [ 'S3DataSource$AttributeNames' => 'A list of one or more attribute names to use that are found in a specified augmented manifest file.
', ], ], 'AuthMode' => [ 'base' => NULL, 'refs' => [ 'CreateDomainRequest$AuthMode' => 'The mode of authentication that members use to access the domain.
', 'DescribeDomainResponse$AuthMode' => 'The domain\'s authentication mode.
', ], ], 'AutoGenerateEndpointName' => [ 'base' => NULL, 'refs' => [ 'ModelDeployConfig$AutoGenerateEndpointName' => 'Set to True to automatically generate an endpoint name for a one-click Autopilot model deployment; set to False otherwise. The default value is False.
If you set AutoGenerateEndpointName to True, do not specify the EndpointName; otherwise a 400 error is thrown.
The collection of algorithms run on a dataset for training the model candidates of an Autopilot job.
', 'refs' => [ 'AutoMLAlgorithmsConfig$member' => NULL, ], ], 'AutoMLAlgorithms' => [ 'base' => NULL, 'refs' => [ 'AutoMLAlgorithmConfig$AutoMLAlgorithms' => 'The selection of algorithms run on a dataset to train the model candidates of an Autopilot job.
Selected algorithms must belong to the list corresponding to the training mode set in AutoMLJobConfig.Mode (ENSEMBLING or HYPERPARAMETER_TUNING). Choose a minimum of 1 algorithm.
In ENSEMBLING mode:
"catboost"
"extra-trees"
"fastai"
"lightgbm"
"linear-learner"
"nn-torch"
"randomforest"
"xgboost"
In HYPERPARAMETER_TUNING mode:
"linear-learner"
"mlp"
"xgboost"
Stores the configuration information for the selection of algorithms used to train the model candidates.
The list of available algorithms to choose from depends on the training mode set in AutoMLJobConfig.Mode .
AlgorithmsConfig should not be set in AUTO training mode.
When AlgorithmsConfig is provided, one AutoMLAlgorithms attribute must be set and one only.
If the list of algorithms provided as values for AutoMLAlgorithms is empty, AutoMLCandidateGenerationConfig uses the full set of algorithms for the given training mode.
When AlgorithmsConfig is not provided, AutoMLCandidateGenerationConfig uses the full set of algorithms for the given training mode.
For the list of all algorithms per training mode, see AutoMLAlgorithmConfig.
For more information on each algorithm, see the Algorithm support section in Autopilot developer guide.
', 'CandidateGenerationConfig$AlgorithmsConfig' => 'Stores the configuration information for the selection of algorithms used to train model candidates on tabular data.
The list of available algorithms to choose from depends on the training mode set in TabularJobConfig.Mode .
AlgorithmsConfig should not be set in AUTO training mode.
When AlgorithmsConfig is provided, one AutoMLAlgorithms attribute must be set and one only.
If the list of algorithms provided as values for AutoMLAlgorithms is empty, CandidateGenerationConfig uses the full set of algorithms for the given training mode.
When AlgorithmsConfig is not provided, CandidateGenerationConfig uses the full set of algorithms for the given training mode.
For the list of all algorithms per problem type and training mode, see AutoMLAlgorithmConfig.
For more information on each algorithm, see the Algorithm support section in Autopilot developer guide.
', ], ], 'AutoMLCandidate' => [ 'base' => 'Information about a candidate produced by an AutoML training job, including its status, steps, and other properties.
', 'refs' => [ 'AutoMLCandidates$member' => NULL, 'DescribeAutoMLJobResponse$BestCandidate' => 'The best model candidate selected by SageMaker Autopilot using both the best objective metric and lowest InferenceLatency for an experiment.
', 'DescribeAutoMLJobV2Response$BestCandidate' => 'Information about the candidate produced by an AutoML training job V2, including its status, steps, and other properties.
', ], ], 'AutoMLCandidateGenerationConfig' => [ 'base' => 'Stores the configuration information for how a candidate is generated (optional).
', 'refs' => [ 'AutoMLJobConfig$CandidateGenerationConfig' => 'The configuration for generating a candidate for an AutoML job (optional).
', ], ], 'AutoMLCandidateStep' => [ 'base' => 'Information about the steps for a candidate and what step it is working on.
', 'refs' => [ 'CandidateSteps$member' => NULL, ], ], 'AutoMLCandidates' => [ 'base' => NULL, 'refs' => [ 'ListCandidatesForAutoMLJobResponse$Candidates' => 'Summaries about the AutoMLCandidates.
A channel is a named input source that training algorithms can consume. The validation dataset size is limited to less than 2 GB. The training dataset size must be less than 100 GB. For more information, see Channel.
A validation dataset must contain the same headers as the training dataset.
The channel type (optional) is an enum string. The default value is training. Channels for training and validation must share the same ContentType and TargetAttributeName. For information on specifying training and validation channel types, see How to specify training and validation datasets.
The type of channel. Defines whether the data are used for training or validation. The default value is training. Channels for training and validation must share the same ContentType
The type of channel defaults to training for the time-series forecasting problem type.
A list of container definitions that describe the different containers that make up an AutoML candidate. For more information, see ContainerDefinition.
', 'refs' => [ 'AutoMLContainerDefinitions$member' => NULL, ], ], 'AutoMLContainerDefinitions' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidate$InferenceContainers' => 'Information about the recommended inference container definitions.
', 'AutoMLInferenceContainerDefinitions$value' => 'Information about the recommended inference container definitions.
', ], ], 'AutoMLDataSource' => [ 'base' => 'The data source for the Autopilot job.
', 'refs' => [ 'AutoMLChannel$DataSource' => 'The data source for an AutoML channel.
', 'AutoMLJobChannel$DataSource' => 'The data source for an AutoML channel (Required).
', ], ], 'AutoMLDataSplitConfig' => [ 'base' => 'This structure specifies how to split the data into train and validation datasets.
The validation and training datasets must contain the same headers. For jobs created by calling CreateAutoMLJob, the validation dataset must be less than 2 GB in size.
The configuration for splitting the input training dataset.
Type: AutoMLDataSplitConfig
', 'CreateAutoMLJobV2Request$DataSplitConfig' => 'This structure specifies how to split the data into train and validation datasets.
The validation and training datasets must contain the same headers. For jobs created by calling CreateAutoMLJob, the validation dataset must be less than 2 GB in size.
This attribute must not be set for the time-series forecasting problem type, as Autopilot automatically splits the input dataset into training and validation sets.
Returns the configuration settings of how the data are split into train and validation datasets.
', ], ], 'AutoMLFailureReason' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidate$FailureReason' => 'The failure reason.
', 'AutoMLJobSummary$FailureReason' => 'The failure reason of an AutoML job.
', 'AutoMLPartialFailureReason$PartialFailureMessage' => 'The message containing the reason for a partial failure of an AutoML job.
', 'DescribeAutoMLJobResponse$FailureReason' => 'Returns the failure reason for an AutoML job, when applicable.
', 'DescribeAutoMLJobV2Response$FailureReason' => 'Returns the reason for the failure of the AutoML job V2, when applicable.
', ], ], 'AutoMLInferenceContainerDefinitions' => [ 'base' => 'The mapping of all supported processing unit (CPU, GPU, etc...) to inference container definitions for the candidate. This field is populated for the V2 API only (for example, for jobs created by calling CreateAutoMLJobV2).
The mapping of all supported processing unit (CPU, GPU, etc...) to inference container definitions for the candidate. This field is populated for the AutoML jobs V2 (for example, for jobs created by calling CreateAutoMLJobV2) related to image or text classification problem types only.
An array of channel objects that describes the input data and its location. Each channel is a named input source. Similar to InputDataConfig supported by HyperParameterTrainingJobDefinition. Format(s) supported: CSV, Parquet. A minimum of 500 rows is required for the training dataset. There is not a minimum number of rows required for the validation dataset.
Returns the input data configuration for the AutoML job.
', ], ], 'AutoMLJobArn' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the AutoML job.
', 'AutoMLJobSummary$AutoMLJobArn' => 'The ARN of the AutoML job.
', 'CreateAutoMLJobResponse$AutoMLJobArn' => 'The unique ARN assigned to the AutoML job when it is created.
', 'CreateAutoMLJobV2Response$AutoMLJobArn' => 'The unique ARN assigned to the AutoMLJob when it is created.
', 'DescribeAutoMLJobResponse$AutoMLJobArn' => 'Returns the ARN of the AutoML job.
', 'DescribeAutoMLJobV2Response$AutoMLJobArn' => 'Returns the Amazon Resource Name (ARN) of the AutoML job V2.
', 'DescribeProcessingJobResponse$AutoMLJobArn' => 'The ARN of an AutoML job associated with this processing job.
', 'DescribeTrainingJobResponse$AutoMLJobArn' => 'The Amazon Resource Name (ARN) of an AutoML job.
', 'DescribeTransformJobResponse$AutoMLJobArn' => 'The Amazon Resource Name (ARN) of the AutoML transform job.
', 'ProcessingJob$AutoMLJobArn' => 'The Amazon Resource Name (ARN) of the AutoML job associated with this processing job.
', 'TrainingJob$AutoMLJobArn' => 'The Amazon Resource Name (ARN) of the job.
', 'TransformJob$AutoMLJobArn' => 'The Amazon Resource Name (ARN) of the AutoML job that created the transform job.
', ], ], 'AutoMLJobArtifacts' => [ 'base' => 'The artifacts that are generated during an AutoML job.
', 'refs' => [ 'DescribeAutoMLJobResponse$AutoMLJobArtifacts' => 'Returns information on the job\'s artifacts found in AutoMLJobArtifacts.
A channel is a named input source that training algorithms can consume. This channel is used for AutoML jobs V2 (jobs created by calling CreateAutoMLJobV2).
', 'refs' => [ 'AutoMLJobInputDataConfig$member' => NULL, ], ], 'AutoMLJobCompletionCriteria' => [ 'base' => 'How long a job is allowed to run, or how many candidates a job is allowed to generate.
', 'refs' => [ 'AutoMLJobConfig$CompletionCriteria' => 'How long an AutoML job is allowed to run, or how many candidates a job is allowed to generate.
', 'AutoMLResolvedAttributes$CompletionCriteria' => NULL, 'ImageClassificationJobConfig$CompletionCriteria' => 'How long a job is allowed to run, or how many candidates a job is allowed to generate.
', 'ResolvedAttributes$CompletionCriteria' => NULL, 'TabularJobConfig$CompletionCriteria' => NULL, 'TextClassificationJobConfig$CompletionCriteria' => 'How long a job is allowed to run, or how many candidates a job is allowed to generate.
', 'TextGenerationJobConfig$CompletionCriteria' => NULL, 'TimeSeriesForecastingJobConfig$CompletionCriteria' => NULL, ], ], 'AutoMLJobConfig' => [ 'base' => 'A collection of settings used for an AutoML job.
', 'refs' => [ 'CreateAutoMLJobRequest$AutoMLJobConfig' => 'A collection of settings used to configure an AutoML job.
', 'DescribeAutoMLJobResponse$AutoMLJobConfig' => 'Returns the configuration for the AutoML job.
', ], ], 'AutoMLJobInputDataConfig' => [ 'base' => NULL, 'refs' => [ 'CreateAutoMLJobV2Request$AutoMLJobInputDataConfig' => 'An array of channel objects describing the input data and their location. Each channel is a named input source. Similar to the InputDataConfig attribute in the CreateAutoMLJob input parameters. The supported formats depend on the problem type:
For tabular problem types: S3Prefix, ManifestFile.
For image classification: S3Prefix, ManifestFile, AugmentedManifestFile.
For text classification: S3Prefix.
For time-series forecasting: S3Prefix.
For text generation (LLMs fine-tuning): S3Prefix.
Returns an array of channel objects describing the input data and their location.
', ], ], 'AutoMLJobName' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobSummary$AutoMLJobName' => 'The name of the AutoML job you are requesting.
', 'CreateAutoMLJobRequest$AutoMLJobName' => 'Identifies an Autopilot job. The name must be unique to your account and is case insensitive.
', 'CreateAutoMLJobV2Request$AutoMLJobName' => 'Identifies an Autopilot job. The name must be unique to your account and is case insensitive.
', 'DescribeAutoMLJobRequest$AutoMLJobName' => 'Requests information about an AutoML job using its unique name.
', 'DescribeAutoMLJobResponse$AutoMLJobName' => 'Returns the name of the AutoML job.
', 'DescribeAutoMLJobV2Request$AutoMLJobName' => 'Requests information about an AutoML job V2 using its unique name.
', 'DescribeAutoMLJobV2Response$AutoMLJobName' => 'Returns the name of the AutoML job V2.
', 'ListCandidatesForAutoMLJobRequest$AutoMLJobName' => 'List the candidates created for the job by providing the job\'s name.
', 'StopAutoMLJobRequest$AutoMLJobName' => 'The name of the object you are requesting.
', ], ], 'AutoMLJobObjective' => [ 'base' => 'Specifies a metric to minimize or maximize as the objective of an AutoML job.
', 'refs' => [ 'AutoMLResolvedAttributes$AutoMLJobObjective' => NULL, 'CreateAutoMLJobRequest$AutoMLJobObjective' => 'Specifies a metric to minimize or maximize as the objective of a job. If not specified, the default objective metric depends on the problem type. See AutoMLJobObjective for the default values.
', 'CreateAutoMLJobV2Request$AutoMLJobObjective' => 'Specifies a metric to minimize or maximize as the objective of a job. If not specified, the default objective metric depends on the problem type. For the list of default values per problem type, see AutoMLJobObjective.
For tabular problem types: You must either provide both the AutoMLJobObjective and indicate the type of supervised learning problem in AutoMLProblemTypeConfig (TabularJobConfig.ProblemType), or none at all.
For text generation problem types (LLMs fine-tuning): Fine-tuning language models in Autopilot does not require setting the AutoMLJobObjective field. Autopilot fine-tunes LLMs without requiring multiple candidates to be trained and evaluated. Instead, using your dataset, Autopilot directly fine-tunes your target model to enhance a default objective metric, the cross-entropy loss. After fine-tuning a language model, you can evaluate the quality of its generated text using different metrics. For a list of the available metrics, see Metrics for fine-tuning LLMs in Autopilot.
Returns the job\'s objective.
', 'DescribeAutoMLJobV2Response$AutoMLJobObjective' => 'Returns the job\'s objective.
', 'ResolvedAttributes$AutoMLJobObjective' => NULL, ], ], 'AutoMLJobObjectiveType' => [ 'base' => NULL, 'refs' => [ 'FinalAutoMLJobObjectiveMetric$Type' => 'The type of metric with the best result.
', ], ], 'AutoMLJobSecondaryStatus' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobSummary$AutoMLJobSecondaryStatus' => 'The secondary status of the AutoML job.
', 'DescribeAutoMLJobResponse$AutoMLJobSecondaryStatus' => 'Returns the secondary status of the AutoML job.
', 'DescribeAutoMLJobV2Response$AutoMLJobSecondaryStatus' => 'Returns the secondary status of the AutoML job V2.
', ], ], 'AutoMLJobStatus' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobSummary$AutoMLJobStatus' => 'The status of the AutoML job.
', 'DescribeAutoMLJobResponse$AutoMLJobStatus' => 'Returns the status of the AutoML job.
', 'DescribeAutoMLJobV2Response$AutoMLJobStatus' => 'Returns the status of the AutoML job V2.
', 'ListAutoMLJobsRequest$StatusEquals' => 'Request a list of jobs, using a filter for status.
', ], ], 'AutoMLJobStepMetadata' => [ 'base' => 'Metadata for an AutoML job step.
', 'refs' => [ 'PipelineExecutionStepMetadata$AutoMLJob' => 'The Amazon Resource Name (ARN) of the AutoML job that was run by this step.
', ], ], 'AutoMLJobSummaries' => [ 'base' => NULL, 'refs' => [ 'ListAutoMLJobsResponse$AutoMLJobSummaries' => 'Returns a summary list of jobs.
', ], ], 'AutoMLJobSummary' => [ 'base' => 'Provides a summary about an AutoML job.
', 'refs' => [ 'AutoMLJobSummaries$member' => NULL, ], ], 'AutoMLMaxResults' => [ 'base' => NULL, 'refs' => [ 'ListAutoMLJobsRequest$MaxResults' => 'Request a list of jobs up to a specified limit.
', 'ListCandidatesForAutoMLJobRequest$MaxResults' => 'List the job\'s candidates up to a specified limit.
', ], ], 'AutoMLMetricEnum' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobObjective$MetricName' => 'The name of the objective metric used to measure the predictive quality of a machine learning system. During training, the model\'s parameters are updated iteratively to optimize its performance based on the feedback provided by the objective metric when evaluating the model on the validation dataset.
The list of available metrics supported by Autopilot and the default metric applied when you do not specify a metric name explicitly depend on the problem type.
For tabular problem types:
List of available metrics:
Regression: InferenceLatency, MAE, MSE, R2, RMSE
Binary classification: Accuracy, AUC, BalancedAccuracy, F1, InferenceLatency, LogLoss, Precision, Recall
Multiclass classification: Accuracy, BalancedAccuracy, F1macro, InferenceLatency, LogLoss, PrecisionMacro, RecallMacro
For a description of each metric, see Autopilot metrics for classification and regression.
Default objective metrics:
Regression: MSE.
Binary classification: F1.
Multiclass classification: Accuracy.
For image or text classification problem types:
List of available metrics: Accuracy
For a description of each metric, see Autopilot metrics for text and image classification.
Default objective metrics: Accuracy
For time-series forecasting problem types:
List of available metrics: RMSE, wQL, Average wQL, MASE, MAPE, WAPE
For a description of each metric, see Autopilot metrics for time-series forecasting.
Default objective metrics: AverageWeightedQuantileLoss
For text generation problem types (LLMs fine-tuning): Fine-tuning language models in Autopilot does not require setting the AutoMLJobObjective field. Autopilot fine-tunes LLMs without requiring multiple candidates to be trained and evaluated. Instead, using your dataset, Autopilot directly fine-tunes your target model to enhance a default objective metric, the cross-entropy loss. After fine-tuning a language model, you can evaluate the quality of its generated text using different metrics. For a list of the available metrics, see Metrics for fine-tuning LLMs in Autopilot.
The name of the metric with the best result. For a description of the possible objective metrics, see AutoMLJobObjective$MetricName.
', 'FinalAutoMLJobObjectiveMetric$StandardMetricName' => 'The name of the standard metric. For a description of the standard metrics, see Autopilot candidate metrics.
', 'MetricDatum$MetricName' => 'The name of the metric.
', ], ], 'AutoMLMetricExtendedEnum' => [ 'base' => NULL, 'refs' => [ 'MetricDatum$StandardMetricName' => 'The name of the standard metric.
For definitions of the standard metrics, see Autopilot candidate metrics .
The method that Autopilot uses to train the data. You can either specify the mode manually or let Autopilot choose for you based on the dataset size by selecting AUTO. In AUTO mode, Autopilot chooses ENSEMBLING for datasets smaller than 100 MB, and HYPERPARAMETER_TUNING for larger ones.
The ENSEMBLING mode uses a multi-stack ensemble model to predict classification and regression tasks directly from your dataset. This machine learning mode combines several base models to produce an optimal predictive model. It then uses a stacking ensemble method to combine predictions from contributing members. A multi-stack ensemble model can provide better performance over a single model by combining the predictive capabilities of multiple models. See Autopilot algorithm support for a list of algorithms supported by ENSEMBLING mode.
The HYPERPARAMETER_TUNING (HPO) mode uses the best hyperparameters to train the best version of a model. HPO automatically selects an algorithm for the type of problem you want to solve. Then HPO finds the best hyperparameters according to your objective metric. See Autopilot algorithm support for a list of algorithms supported by HYPERPARAMETER_TUNING mode.
The method that Autopilot uses to train the data. You can either specify the mode manually or let Autopilot choose for you based on the dataset size by selecting AUTO. In AUTO mode, Autopilot chooses ENSEMBLING for datasets smaller than 100 MB, and HYPERPARAMETER_TUNING for larger ones.
The ENSEMBLING mode uses a multi-stack ensemble model to predict classification and regression tasks directly from your dataset. This machine learning mode combines several base models to produce an optimal predictive model. It then uses a stacking ensemble method to combine predictions from contributing members. A multi-stack ensemble model can provide better performance over a single model by combining the predictive capabilities of multiple models. See Autopilot algorithm support for a list of algorithms supported by ENSEMBLING mode.
The HYPERPARAMETER_TUNING (HPO) mode uses the best hyperparameters to train the best version of a model. HPO automatically selects an algorithm for the type of problem you want to solve. Then HPO finds the best hyperparameters according to your objective metric. See Autopilot algorithm support for a list of algorithms supported by HYPERPARAMETER_TUNING mode.
Request a list of jobs, using a search filter for name.
', ], ], 'AutoMLOutputDataConfig' => [ 'base' => 'The output data configuration.
', 'refs' => [ 'CreateAutoMLJobRequest$OutputDataConfig' => 'Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job. Format(s) supported: CSV.
', 'CreateAutoMLJobV2Request$OutputDataConfig' => 'Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job.
', 'DescribeAutoMLJobResponse$OutputDataConfig' => 'Returns the job\'s output data config.
', 'DescribeAutoMLJobV2Response$OutputDataConfig' => 'Returns the job\'s output data config.
', ], ], 'AutoMLPartialFailureReason' => [ 'base' => 'The reason for a partial failure of an AutoML job.
', 'refs' => [ 'AutoMLPartialFailureReasons$member' => NULL, ], ], 'AutoMLPartialFailureReasons' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobSummary$PartialFailureReasons' => 'The list of reasons for partial failures within an AutoML job.
', 'DescribeAutoMLJobResponse$PartialFailureReasons' => 'Returns a list of reasons for partial failures within an AutoML job.
', 'DescribeAutoMLJobV2Response$PartialFailureReasons' => 'Returns a list of reasons for partial failures within an AutoML job V2.
', ], ], 'AutoMLProblemTypeConfig' => [ 'base' => 'A collection of settings specific to the problem type used to configure an AutoML job V2. There must be one and only one config of the following type.
', 'refs' => [ 'CreateAutoMLJobV2Request$AutoMLProblemTypeConfig' => 'Defines the configuration settings of one of the supported problem types.
', 'DescribeAutoMLJobV2Response$AutoMLProblemTypeConfig' => 'Returns the configuration settings of the problem type set for the AutoML job V2.
', ], ], 'AutoMLProblemTypeConfigName' => [ 'base' => NULL, 'refs' => [ 'DescribeAutoMLJobV2Response$AutoMLProblemTypeConfigName' => 'Returns the name of the problem type configuration set for the AutoML job V2.
', ], ], 'AutoMLProblemTypeResolvedAttributes' => [ 'base' => 'Stores resolved attributes specific to the problem type of an AutoML job V2.
', 'refs' => [ 'AutoMLResolvedAttributes$AutoMLProblemTypeResolvedAttributes' => 'Defines the resolved attributes specific to a problem type.
', ], ], 'AutoMLProcessingUnit' => [ 'base' => NULL, 'refs' => [ 'AutoMLInferenceContainerDefinitions$key' => 'Processing unit for an inference container. Currently Autopilot only supports CPU or GPU.
The resolved attributes used to configure an AutoML job V2.
', 'refs' => [ 'DescribeAutoMLJobV2Response$ResolvedAttributes' => 'Returns the resolved attributes used by the AutoML job V2.
', ], ], 'AutoMLS3DataSource' => [ 'base' => 'Describes the Amazon S3 data source.
', 'refs' => [ 'AutoMLDataSource$S3DataSource' => 'The Amazon S3 location of the input data.
', ], ], 'AutoMLS3DataType' => [ 'base' => NULL, 'refs' => [ 'AutoMLS3DataSource$S3DataType' => 'The data type.
If you choose S3Prefix, S3Uri identifies a key name prefix. SageMaker uses all objects that match the specified key name prefix for model training.
The S3Prefix should have the following format:
s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER-OR-FILE
If you choose ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want SageMaker to use for model training.
A ManifestFile should have the format shown below:
[ {"prefix": "s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER/DOC-EXAMPLE-PREFIX/"},
"DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-1",
"DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-2",
... "DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-N" ]
If you choose AugmentedManifestFile, S3Uri identifies an object that is an augmented manifest file in JSON lines format. This file contains the data you want to use for model training. AugmentedManifestFile is available for V2 API jobs only (for example, for jobs created by calling CreateAutoMLJobV2).
Here is a minimal, single-record example of an AugmentedManifestFile:
{"source-ref": "s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER/cats/cat.jpg",
"label-metadata": {"class-name": "cat" }
For more information on AugmentedManifestFile, see Provide Dataset Metadata to Training Jobs with an Augmented Manifest File.
Security options.
', 'refs' => [ 'AutoMLJobConfig$SecurityConfig' => 'The security configuration for traffic encryption or Amazon VPC settings.
', 'CreateAutoMLJobV2Request$SecurityConfig' => 'The security configuration for traffic encryption or Amazon VPC settings.
', 'DescribeAutoMLJobV2Response$SecurityConfig' => 'Returns the security configuration for traffic encryption or Amazon VPC settings.
', ], ], 'AutoMLSortBy' => [ 'base' => NULL, 'refs' => [ 'ListAutoMLJobsRequest$SortBy' => 'The parameter by which to sort the results. The default is Name.
The sort order for the results. The default is Descending.
The sort order for the results. The default is Ascending.
The name and an example value of the hyperparameter that you want to use in Autotune. If Automatic model tuning (AMT) determines that your hyperparameter is eligible for Autotune, an optimal hyperparameter range is selected for you.
', 'refs' => [ 'AutoParameters$member' => NULL, ], ], 'AutoParameters' => [ 'base' => NULL, 'refs' => [ 'ParameterRanges$AutoParameters' => 'A list containing hyperparameter names and example values to be used by Autotune to determine optimal ranges for your tuning job.
', ], ], 'AutoRollbackConfig' => [ 'base' => 'Automatic rollback configuration for handling endpoint deployment failures and recovery.
', 'refs' => [ 'DeploymentConfig$AutoRollbackConfiguration' => 'Automatic rollback configuration for handling endpoint deployment failures and recovery.
', ], ], 'Autotune' => [ 'base' => 'A flag to indicate if you want to use Autotune to automatically find optimal values for the following fields:
ParameterRanges: The names and ranges of parameters that a hyperparameter tuning job can optimize.
ResourceLimits: The maximum resources that can be used for a training job. These resources include the maximum number of training jobs, the maximum runtime of a tuning job, and the maximum number of training jobs to run at the same time.
TrainingJobEarlyStoppingType: A flag that specifies whether or not to use early stopping for training jobs launched by a hyperparameter tuning job.
RetryStrategy: The number of times to retry a training job.
Strategy: Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training jobs that it launches.
ConvergenceDetected: A flag to indicate that Automatic model tuning (AMT) has detected model convergence.
Configures SageMaker Automatic model tuning (AMT) to automatically find optimal parameters for the following fields:
ParameterRanges: The names and ranges of parameters that a hyperparameter tuning job can optimize.
ResourceLimits: The maximum resources that can be used for a training job. These resources include the maximum number of training jobs, the maximum runtime of a tuning job, and the maximum number of training jobs to run at the same time.
TrainingJobEarlyStoppingType: A flag that specifies whether or not to use early stopping for training jobs launched by a hyperparameter tuning job.
RetryStrategy: The number of times to retry a training job.
Strategy: Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training jobs that it launches.
ConvergenceDetected: A flag to indicate that Automatic model tuning (AMT) has detected model convergence.
A flag to indicate if autotune is enabled for the hyperparameter tuning job.
', ], ], 'AutotuneMode' => [ 'base' => NULL, 'refs' => [ 'Autotune$Mode' => 'Set Mode to Enabled if you want to use Autotune.
Specifies whether Amazon Rekognition or Amazon Textract are used as the integration source. The default field settings and JSON parsing rules are different based on the integration source. Valid values:
', ], ], 'BacktestResultsLocation' => [ 'base' => NULL, 'refs' => [ 'CandidateArtifactLocations$BacktestResults' => 'The Amazon S3 prefix to the accuracy metrics and the inference results observed over the testing window. Available only for the time-series forecasting problem type.
', ], ], 'BaseModelName' => [ 'base' => NULL, 'refs' => [ 'TextGenerationJobConfig$BaseModelName' => 'The name of the base model to fine-tune. Autopilot supports fine-tuning a variety of large language models. For information on the list of supported models, see Text generation models supporting fine-tuning in Autopilot. If no BaseModelName is provided, the default model used is Falcon-7B-Instruct.
The name of the base model to fine-tune.
', ], ], 'BatchDataCaptureConfig' => [ 'base' => 'Configuration to control how SageMaker captures inference data for batch transform jobs.
', 'refs' => [ 'CreateTransformJobRequest$DataCaptureConfig' => 'Configuration to control how SageMaker captures inference data.
', 'DescribeTransformJobResponse$DataCaptureConfig' => 'Configuration to control how SageMaker captures inference data.
', 'TransformJob$DataCaptureConfig' => NULL, ], ], 'BatchDescribeModelPackageError' => [ 'base' => 'The error code and error description associated with the resource.
', 'refs' => [ 'BatchDescribeModelPackageErrorMap$value' => NULL, ], ], 'BatchDescribeModelPackageErrorMap' => [ 'base' => NULL, 'refs' => [ 'BatchDescribeModelPackageOutput$BatchDescribeModelPackageErrorMap' => 'A map of the resource and BatchDescribeModelPackageError objects reporting the error associated with describing the model package.
', ], ], 'BatchDescribeModelPackageInput' => [ 'base' => NULL, 'refs' => [], ], 'BatchDescribeModelPackageOutput' => [ 'base' => NULL, 'refs' => [], ], 'BatchDescribeModelPackageSummary' => [ 'base' => 'Provides summary information about the model package.
', 'refs' => [ 'ModelPackageSummaries$value' => NULL, ], ], 'BatchStrategy' => [ 'base' => NULL, 'refs' => [ 'CreateTransformJobRequest$BatchStrategy' => 'Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.
To enable the batch strategy, you must set the SplitType property to Line, RecordIO, or TFRecord.
To use only one record when making an HTTP invocation request to a container, set BatchStrategy to SingleRecord and SplitType to Line.
To fit as many records in a mini-batch as can fit within the MaxPayloadInMB limit, set BatchStrategy to MultiRecord and SplitType to Line.
Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.
To enable the batch strategy, you must set SplitType to Line, RecordIO, or TFRecord.
Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.
', 'TransformJobDefinition$BatchStrategy' => 'A string that determines the number of records included in a single mini-batch.
SingleRecord means only one record is used per mini-batch. MultiRecord means a mini-batch is set to contain as many records that can fit within the MaxPayloadInMB limit.
Input object for the batch transform job.
', 'refs' => [ 'DataQualityJobInput$BatchTransformInput' => 'Input object for the batch transform job.
', 'ModelBiasJobInput$BatchTransformInput' => 'Input object for the batch transform job.
', 'ModelDashboardMonitoringSchedule$BatchTransformInput' => NULL, 'ModelExplainabilityJobInput$BatchTransformInput' => 'Input object for the batch transform job.
', 'ModelQualityJobInput$BatchTransformInput' => 'Input object for the batch transform job.
', 'MonitoringInput$BatchTransformInput' => 'Input object for the batch transform job.
', ], ], 'BestObjectiveNotImproving' => [ 'base' => 'A structure that keeps track of which training jobs launched by your hyperparameter tuning job are not improving model performance as evaluated against an objective function.
', 'refs' => [ 'TuningJobCompletionCriteria$BestObjectiveNotImproving' => 'A flag to stop your hyperparameter tuning job if model performance fails to improve as evaluated against an objective function.
', ], ], 'Bias' => [ 'base' => 'Contains bias metrics for a model.
', 'refs' => [ 'ModelMetrics$Bias' => 'Metrics that measure bais in a model.
', ], ], 'BillableTimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'DescribeTrainingJobResponse$BillableTimeInSeconds' => 'The billable time in seconds. Billable time refers to the absolute wall-clock time.
Multiply BillableTimeInSeconds by the number of instances (InstanceCount) in your training cluster to get the total compute time SageMaker bills you if you run distributed training. The formula is as follows: BillableTimeInSeconds * InstanceCount .
You can calculate the savings from using managed spot training using the formula (1 - BillableTimeInSeconds / TrainingTimeInSeconds) * 100. For example, if BillableTimeInSeconds is 100 and TrainingTimeInSeconds is 500, the savings is 80%.
The billable time in seconds.
', ], ], 'BlockedReason' => [ 'base' => NULL, 'refs' => [ 'OfflineStoreStatus$BlockedReason' => 'The justification for why the OfflineStoreStatus is Blocked (if applicable).
', ], ], 'BlueGreenUpdatePolicy' => [ 'base' => 'Update policy for a blue/green deployment. If this update policy is specified, SageMaker creates a new fleet during the deployment while maintaining the old fleet. SageMaker flips traffic to the new fleet according to the specified traffic routing configuration. Only one update policy should be used in the deployment configuration. If no update policy is specified, SageMaker uses a blue/green deployment strategy with all at once traffic shifting by default.
', 'refs' => [ 'DeploymentConfig$BlueGreenUpdatePolicy' => 'Update policy for a blue/green deployment. If this update policy is specified, SageMaker creates a new fleet during the deployment while maintaining the old fleet. SageMaker flips traffic to the new fleet according to the specified traffic routing configuration. Only one update policy should be used in the deployment configuration. If no update policy is specified, SageMaker uses a blue/green deployment strategy with all at once traffic shifting by default.
', ], ], 'Boolean' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSpecification$EnableSageMakerMetricsTimeSeries' => 'To generate and save time-series metrics during training, set to true. The default is false and time-series metrics aren\'t generated except in the following cases:
You use one of the SageMaker built-in algorithms
You use one of the following Prebuilt SageMaker Docker Images:
Tensorflow (version >= 1.15)
MXNet (version >= 1.6)
PyTorch (version >= 1.3)
You specify at least one MetricDefinition
Whether to use traffic encryption between the container layers.
', 'BatchDataCaptureConfig$GenerateInferenceId' => 'Flag that indicates whether to append inference id to the output.
', 'ChannelSpecification$IsRequired' => 'Indicates whether the channel is required by the algorithm.
', 'ClarifyCheckStepMetadata$SkipCheck' => 'This flag indicates if the drift check against the previous baseline will be skipped or not. If it is set to False, the previous baseline of the configured check type must be available.
This flag indicates if a newly calculated baseline can be accessed through step properties BaselineUsedForDriftCheckConstraints and BaselineUsedForDriftCheckStatistics. If it is set to False, the previous baseline of the configured check type must also be available. These can be accessed through the BaselineUsedForDriftCheckConstraints property.
Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
', 'CreateTrainingJobRequest$EnableNetworkIsolation' => 'Isolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If you enable network isolation for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.
', 'CreateTrainingJobRequest$EnableInterContainerTrafficEncryption' => 'To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training. For more information, see Protect Communications Between ML Compute Instances in a Distributed Training Job.
To train models using managed spot training, choose True. Managed spot training provides a fully managed and scalable infrastructure for training machine learning models. this option is useful when training jobs can be interrupted and when there is flexibility when the training job is run.
The complete and intermediate results of jobs are stored in an Amazon S3 bucket, and can be used as a starting point to train models incrementally. Amazon SageMaker provides metrics and logs in CloudWatch. They can be used to see when managed spot training jobs are running, interrupted, resumed, or completed.
', 'DescribeModelOutput$EnableNetworkIsolation' => 'If True, no inbound or outbound network calls can be made to or from the model container.
If you want to allow inbound or outbound network calls, except for calls between peers within a training cluster for distributed training, choose True. If you enable network isolation for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.
To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithms in distributed training.
A Boolean indicating whether managed spot training is enabled (True) or not (False).
Indicates whether this hyperparameter is tunable in a hyperparameter tuning job.
', 'HyperParameterSpecification$IsRequired' => 'Indicates whether this hyperparameter is required.
', 'HyperParameterTrainingJobDefinition$EnableNetworkIsolation' => 'Isolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If network isolation is used for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.
', 'HyperParameterTrainingJobDefinition$EnableInterContainerTrafficEncryption' => 'To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training.
A Boolean indicating whether managed spot training is enabled (True) or not (False).
Toggle for excluding devices deployed in other stages.
', 'Model$EnableNetworkIsolation' => 'Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
', 'ModelDashboardIndicatorAction$Enabled' => 'Indicates whether the alert action is turned on.
', 'MonitoringCsvDatasetFormat$Header' => 'Indicates if the CSV data has a header.
', 'MonitoringJsonDatasetFormat$Line' => 'Indicates if the file should be read as a JSON object per line.
', 'MonitoringNetworkConfig$EnableInterContainerTrafficEncryption' => 'Whether to encrypt all communications between the instances used for the monitoring jobs. Choose True to encrypt communications. Encryption provides greater security for distributed jobs, but the processing might take longer.
Whether to allow inbound and outbound network calls to and from the containers used for the monitoring job.
', 'NetworkConfig$EnableInterContainerTrafficEncryption' => 'Whether to encrypt all communications between distributed processing jobs. Choose True to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.
Whether to allow inbound and outbound network calls to and from the containers used for the processing job.
', 'OfflineStoreConfig$DisableGlueTableCreation' => 'Set to True to disable the automatic creation of an Amazon Web Services Glue table when configuring an OfflineStore. If set to False, Feature Store will name the OfflineStore Glue table following Athena\'s naming recommendations.
The default value is False.
Turn OnlineStore off by specifying False for the EnableOnlineStore flag. Turn OnlineStore on by specifying True for the EnableOnlineStore flag.
The default value is False.
This flag indicates if the drift check against the previous baseline will be skipped or not. If it is set to False, the previous baseline of the configured check type must be available.
This flag indicates if a newly calculated baseline can be accessed through step properties BaselineUsedForDriftCheckConstraints and BaselineUsedForDriftCheckStatistics. If it is set to False, the previous baseline of the configured check type must also be available. These can be accessed through the BaselineUsedForDriftCheckConstraints and BaselineUsedForDriftCheckStatistics properties.
Setting this value to True retrieves not only the entities of interest but also the Associations and lineage entities on the path. Set to False to only return lineage entities that match your query.
If the TrainingJob was created with network isolation, the value is set to true. If network isolation is enabled, nodes can\'t communicate beyond the VPC they run in.
To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training.
When true, enables managed spot training using Amazon EC2 Spot instances to run training jobs instead of on-demand instances. For more information, see Managed Spot Training.
', 'TrainingSpecification$SupportsDistributedTraining' => 'Indicates whether the algorithm supports distributed training. If set to false, buyers can\'t request more than one instance during training.
', 'UpdateEndpointInput$RetainAllVariantProperties' => 'When updating endpoint resources, enables or disables the retention of variant properties, such as the instance count or the variant weight. To retain the variant properties of an endpoint when updating it, set RetainAllVariantProperties to true. To use the variant properties specified in a new EndpointConfig call when updating an endpoint, set RetainAllVariantProperties to false. The default is false.
Specifies whether to reuse the last deployment configuration. The default value is false (the configuration is not reused).
', ], ], 'BooleanOperator' => [ 'base' => NULL, 'refs' => [ 'SearchExpression$Operator' => 'A Boolean operator used to evaluate the search expression. If you want every conditional statement in all lists to be satisfied for the entire search expression to be true, specify And. If only a single conditional statement needs to be true for the entire search expression to be true, specify Or. The default value is And.
The default branch for the Git repository.
', ], ], 'BucketName' => [ 'base' => NULL, 'refs' => [ 'PipelineDefinitionS3Location$Bucket' => 'Name of the S3 bucket.
', ], ], 'CacheHitResult' => [ 'base' => 'Details on the cache hit of a pipeline execution step.
', 'refs' => [ 'PipelineExecutionStep$CacheHitResult' => 'If this pipeline execution step was cached, details on the cache hit.
', ], ], 'CallbackStepMetadata' => [ 'base' => 'Metadata about a callback step.
', 'refs' => [ 'PipelineExecutionStepMetadata$Callback' => 'The URL of the Amazon SQS queue used by this step execution, the pipeline generated token, and a list of output parameters.
', ], ], 'CallbackToken' => [ 'base' => NULL, 'refs' => [ 'CallbackStepMetadata$CallbackToken' => 'The pipeline generated token from the Amazon SQS queue.
', 'SendPipelineExecutionStepFailureRequest$CallbackToken' => 'The pipeline generated token from the Amazon SQS queue.
', 'SendPipelineExecutionStepSuccessRequest$CallbackToken' => 'The pipeline generated token from the Amazon SQS queue.
', ], ], 'CandidateArtifactLocations' => [ 'base' => 'The location of artifacts for an AutoML candidate job.
', 'refs' => [ 'CandidateProperties$CandidateArtifactLocations' => 'The Amazon S3 prefix to the artifacts generated for an AutoML candidate.
', ], ], 'CandidateDefinitionNotebookLocation' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobArtifacts$CandidateDefinitionNotebookLocation' => 'The URL of the notebook location.
', ], ], 'CandidateGenerationConfig' => [ 'base' => 'Stores the configuration information for how model candidates are generated using an AutoML job V2.
', 'refs' => [ 'TabularJobConfig$CandidateGenerationConfig' => 'The configuration information of how model candidates are generated.
', ], ], 'CandidateName' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidate$CandidateName' => 'The name of the candidate.
', 'ListCandidatesForAutoMLJobRequest$CandidateNameEquals' => 'List the candidates for the job and filter by candidate name.
', ], ], 'CandidateProperties' => [ 'base' => 'The properties of an AutoML candidate job.
', 'refs' => [ 'AutoMLCandidate$CandidateProperties' => 'The properties of an AutoML candidate job.
', ], ], 'CandidateSortBy' => [ 'base' => NULL, 'refs' => [ 'ListCandidatesForAutoMLJobRequest$SortBy' => 'The parameter by which to sort the results. The default is Descending.
The candidate\'s status.
', 'ListCandidatesForAutoMLJobRequest$StatusEquals' => 'List the candidates for the job and filter by status.
', ], ], 'CandidateStepArn' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidateStep$CandidateStepArn' => 'The ARN for the candidate\'s step.
', ], ], 'CandidateStepName' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidateStep$CandidateStepName' => 'The name for the candidate\'s step.
', ], ], 'CandidateStepType' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidateStep$CandidateStepType' => 'Whether the candidate is at the transform, training, or processing step.
', ], ], 'CandidateSteps' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidate$CandidateSteps' => 'Information about the candidate\'s steps.
', ], ], 'CanvasAppSettings' => [ 'base' => 'The SageMaker Canvas application settings.
', 'refs' => [ 'UserSettings$CanvasAppSettings' => 'The Canvas app settings.
', ], ], 'CapacitySize' => [ 'base' => 'Specifies the type and size of the endpoint capacity to activate for a blue/green deployment, a rolling deployment, or a rollback strategy. You can specify your batches as either instance count or the overall percentage or your fleet.
For a rollback strategy, if you don\'t specify the fields in this object, or if you set the Value to 100%, then SageMaker uses a blue/green rollback strategy and rolls all traffic back to the blue fleet.
Batch size for each rolling step to provision capacity and turn on traffic on the new endpoint fleet, and terminate capacity on the old endpoint fleet. Value must be between 5% to 50% of the variant\'s total instance count.
', 'RollingUpdatePolicy$RollbackMaximumBatchSize' => 'Batch size for rollback to the old endpoint fleet. Each rolling step to provision capacity and turn on traffic on the old endpoint fleet, and terminate capacity on the new endpoint fleet. If this field is absent, the default value will be set to 100% of total capacity which means to bring up the whole capacity of the old fleet at once during rollback.
', 'TrafficRoutingConfig$CanarySize' => 'Batch size for the first step to turn on traffic on the new endpoint fleet. Value must be less than or equal to 50% of the variant\'s total instance count.
Batch size for each step to turn on traffic on the new endpoint fleet. Value must be 10-50% of the variant\'s total instance count.
Specifies the endpoint capacity type.
INSTANCE_COUNT: The endpoint activates based on the number of instances.
CAPACITY_PERCENT: The endpoint activates based on the specified percentage of capacity.
Defines the capacity size, either as a number of instances or a capacity percentage.
', ], ], 'CaptureContentTypeHeader' => [ 'base' => 'Configuration specifying how to treat different headers. If no headers are specified Amazon SageMaker will by default base64 encode when capturing the data.
', 'refs' => [ 'DataCaptureConfig$CaptureContentTypeHeader' => 'Configuration specifying how to treat different headers. If no headers are specified SageMaker will by default base64 encode when capturing the data.
', 'InferenceExperimentDataStorageConfig$ContentType' => NULL, ], ], 'CaptureMode' => [ 'base' => NULL, 'refs' => [ 'CaptureOption$CaptureMode' => 'Specify the boundary of data to capture.
', ], ], 'CaptureOption' => [ 'base' => 'Specifies data Model Monitor will capture.
', 'refs' => [ 'CaptureOptionList$member' => NULL, ], ], 'CaptureOptionList' => [ 'base' => NULL, 'refs' => [ 'DataCaptureConfig$CaptureOptions' => 'Specifies data Model Monitor will capture. You can configure whether to collect only input, only output, or both
', ], ], 'CaptureStatus' => [ 'base' => NULL, 'refs' => [ 'DataCaptureConfigSummary$CaptureStatus' => 'Whether data capture is currently functional.
', ], ], 'Catalog' => [ 'base' => NULL, 'refs' => [ 'DataCatalogConfig$Catalog' => 'The name of the Glue table catalog.
', ], ], 'CategoricalParameter' => [ 'base' => 'Environment parameters you want to benchmark your load test against.
', 'refs' => [ 'CategoricalParameters$member' => NULL, ], ], 'CategoricalParameterRange' => [ 'base' => 'A list of categorical hyperparameters to tune.
', 'refs' => [ 'CategoricalParameterRanges$member' => NULL, ], ], 'CategoricalParameterRangeSpecification' => [ 'base' => 'Defines the possible values for a categorical hyperparameter.
', 'refs' => [ 'ParameterRange$CategoricalParameterRangeSpecification' => 'A CategoricalParameterRangeSpecification object that defines the possible values for a categorical hyperparameter.
The list of values you can pass.
', ], ], 'CategoricalParameterRanges' => [ 'base' => NULL, 'refs' => [ 'ParameterRanges$CategoricalParameterRanges' => 'The array of CategoricalParameterRange objects that specify ranges of categorical hyperparameters that a hyperparameter tuning job searches.
', ], ], 'CategoricalParameters' => [ 'base' => NULL, 'refs' => [ 'EnvironmentParameterRanges$CategoricalParameterRanges' => 'Specified a list of parameters for each category.
', ], ], 'Cents' => [ 'base' => NULL, 'refs' => [ 'USD$Cents' => 'The fractional portion, in cents, of the amount.
', ], ], 'CertifyForMarketplace' => [ 'base' => NULL, 'refs' => [ 'CreateAlgorithmInput$CertifyForMarketplace' => 'Whether to certify the algorithm so that it can be listed in Amazon Web Services Marketplace.
', 'CreateModelPackageInput$CertifyForMarketplace' => 'Whether to certify the model package for listing on Amazon Web Services Marketplace.
This parameter is optional for unversioned models, and does not apply to versioned models.
', 'DescribeAlgorithmOutput$CertifyForMarketplace' => 'Whether the algorithm is certified to be listed in Amazon Web Services Marketplace.
', 'DescribeModelPackageOutput$CertifyForMarketplace' => 'Whether the model package is certified for listing on Amazon Web Services Marketplace.
', 'ModelPackage$CertifyForMarketplace' => 'Whether the model package is to be certified to be listed on Amazon Web Services Marketplace. For information about listing model packages on Amazon Web Services Marketplace, see List Your Algorithm or Model Package on Amazon Web Services Marketplace.
', ], ], 'Channel' => [ 'base' => 'A channel is a named input source that training algorithms can consume.
', 'refs' => [ 'InputDataConfig$member' => NULL, ], ], 'ChannelName' => [ 'base' => NULL, 'refs' => [ 'Channel$ChannelName' => 'The name of the channel.
', 'ChannelSpecification$Name' => 'The name of the channel.
', ], ], 'ChannelSpecification' => [ 'base' => 'Defines a named input source, called a channel, to be used by an algorithm.
', 'refs' => [ 'ChannelSpecifications$member' => NULL, ], ], 'ChannelSpecifications' => [ 'base' => NULL, 'refs' => [ 'TrainingSpecification$TrainingChannels' => 'A list of ChannelSpecification objects, which specify the input sources to be used by the algorithm.
Contains information about the output location for managed spot training checkpoint data.
', 'refs' => [ 'CreateTrainingJobRequest$CheckpointConfig' => 'Contains information about the output location for managed spot training checkpoint data.
', 'DescribeTrainingJobResponse$CheckpointConfig' => NULL, 'HyperParameterTrainingJobDefinition$CheckpointConfig' => NULL, 'TrainingJob$CheckpointConfig' => NULL, ], ], 'Cidr' => [ 'base' => NULL, 'refs' => [ 'Cidrs$member' => NULL, ], ], 'Cidrs' => [ 'base' => NULL, 'refs' => [ 'SourceIpConfig$Cidrs' => 'A list of one to ten Classless Inter-Domain Routing (CIDR) values.
Maximum: Ten CIDR values
The following Length Constraints apply to individual CIDR values in the CIDR value list.
The container for the metadata for the ClarifyCheck step. For more information, see the topic on ClarifyCheck step in the Amazon SageMaker Developer Guide.
', 'refs' => [ 'PipelineExecutionStepMetadata$ClarifyCheck' => 'Container for the metadata for a Clarify check step. The configurations and outcomes of the check step execution. This includes:
The type of the check conducted,
The Amazon S3 URIs of baseline constraints and statistics files to be used for the drift check.
The Amazon S3 URIs of newly calculated baseline constraints and statistics.
The model package group name provided.
The Amazon S3 URI of the violation report if violations detected.
The Amazon Resource Name (ARN) of check processing job initiated by the step execution.
The boolean flags indicating if the drift check is skipped.
If step property BaselineUsedForDriftCheck is set the same as CalculatedBaseline.
A template string used to format a JSON record into an acceptable model container input. For example, a ContentTemplate string \'{"myfeatures":$features}\' will format a list of features [1,2,3] into the record string \'{"myfeatures":[1,2,3]}\'. Required only when the model container input is in JSON Lines format.
A JMESPath boolean expression used to filter which records to explain. Explanations are activated by default. See EnableExplanations for additional information.
The configuration parameters for the SageMaker Clarify explainer.
', 'refs' => [ 'ExplainerConfig$ClarifyExplainerConfig' => 'A member of ExplainerConfig that contains configuration parameters for the SageMaker Clarify explainer.
The names of the features. If provided, these are included in the endpoint response payload to help readability of the InvokeEndpoint output. See the Response section under Invoke the endpoint in the Developer Guide for more information.
A list of data types of the features (optional). Applicable only to NLP explainability. If provided, FeatureTypes must have at least one \'text\' string (for example, [\'text\']). If FeatureTypes is not provided, the explainer infers the feature types based on the baseline data. The feature types are included in the endpoint response payload. For additional information see the response section under Invoke the endpoint in the Developer Guide for more information.
Provides the JMESPath expression to extract the features from a model container input in JSON Lines format. For example, if FeaturesAttribute is the JMESPath expression \'myfeatures\', it extracts a list of features [1,2,3] from request data \'{"myfeatures":[1,2,3]}\'.
The inference configuration parameter for the model container.
', 'refs' => [ 'ClarifyExplainerConfig$InferenceConfig' => 'The inference configuration parameter for the model container.
', ], ], 'ClarifyLabelAttribute' => [ 'base' => NULL, 'refs' => [ 'ClarifyInferenceConfig$LabelAttribute' => 'A JMESPath expression used to locate the list of label headers in the model container output.
Example: If the model container output of a batch request is \'{"labels":["cat","dog","fish"],"probability":[0.6,0.3,0.1]}\', then set LabelAttribute to \'labels\' to extract the list of label headers ["cat","dog","fish"]
For multiclass classification problems, the label headers are the names of the classes. Otherwise, the label header is the name of the predicted label. These are used to help readability for the output of the InvokeEndpoint API. See the response section under Invoke the endpoint in the Developer Guide for more information. If there are no label headers in the model container output, provide them manually using this parameter.
A zero-based index used to extract a label header or list of label headers from model container output in CSV format.
Example for a multiclass model: If the model container output consists of label headers followed by probabilities: \'"[\\\'cat\\\',\\\'dog\\\',\\\'fish\\\']","[0.1,0.6,0.3]"\', set LabelIndex to 0 to select the label headers [\'cat\',\'dog\',\'fish\'].
The maximum payload size (MB) allowed of a request from the explainer to the model container. Defaults to 6 MB.
The maximum number of records in a request that the model container can process when querying the model container for the predictions of a synthetic dataset. A record is a unit of input data that inference can be made on, for example, a single line in CSV data. If MaxRecordCount is 1, the model container expects one record per request. A value of 2 or greater means that the model expects batch requests, which can reduce overhead and speed up the inferencing process. If this parameter is not provided, the explainer will tune the record count per request according to the model container\'s capacity at runtime.
The MIME type of the baseline data. Choose from \'text/csv\' or \'application/jsonlines\'. Defaults to \'text/csv\'.
A JMESPath expression used to extract the probability (or score) from the model container output if the model container is in JSON Lines format.
Example: If the model container output of a single request is \'{"predicted_label":1,"probability":0.6}\', then set ProbabilityAttribute to \'probability\'.
A zero-based index used to extract a probability value (score) or list from model container output in CSV format. If this value is not provided, the entire model container output will be treated as a probability value (score) or list.
Example for a single class model: If the model container output consists of a string-formatted prediction label followed by its probability: \'1,0.6\', set ProbabilityIndex to 1 to select the probability value 0.6.
Example for a multiclass model: If the model container output consists of a string-formatted prediction label followed by its probability: \'"[\\\'cat\\\',\\\'dog\\\',\\\'fish\\\']","[0.1,0.6,0.3]"\', set ProbabilityIndex to 1 to select the probability values [0.1,0.6,0.3].
The inline SHAP baseline data in string format. ShapBaseline can have one or multiple records to be used as the baseline dataset. The format of the SHAP baseline file should be the same format as the training dataset. For example, if the training dataset is in CSV format and each record contains four features, and all features are numerical, then the format of the baseline data should also share these characteristics. For natural language processing (NLP) of text columns, the baseline value should be the value used to replace the unit of text specified by the Granularity of the TextConfig parameter. The size limit for ShapBasline is 4 KB. Use the ShapBaselineUri parameter if you want to provide more than 4 KB of baseline data.
The configuration for the SHAP baseline (also called the background or reference dataset) of the Kernal SHAP algorithm.
The number of records in the baseline data determines the size of the synthetic dataset, which has an impact on latency of explainability requests. For more information, see the Synthetic data of Configure and create an endpoint.
ShapBaseline and ShapBaselineUri are mutually exclusive parameters. One or the either is required to configure a SHAP baseline.
The configuration for the SHAP baseline of the Kernal SHAP algorithm.
', ], ], 'ClarifyShapConfig' => [ 'base' => 'The configuration for SHAP analysis using SageMaker Clarify Explainer.
', 'refs' => [ 'ClarifyExplainerConfig$ShapConfig' => 'The configuration for SHAP analysis.
', ], ], 'ClarifyShapNumberOfSamples' => [ 'base' => NULL, 'refs' => [ 'ClarifyShapConfig$NumberOfSamples' => 'The number of samples to be used for analysis by the Kernal SHAP algorithm.
The number of samples determines the size of the synthetic dataset, which has an impact on latency of explainability requests. For more information, see the Synthetic data of Configure and create an endpoint.
The starting value used to initialize the random number generator in the explainer. Provide a value for this parameter to obtain a deterministic SHAP result.
', ], ], 'ClarifyShapUseLogit' => [ 'base' => NULL, 'refs' => [ 'ClarifyShapConfig$UseLogit' => 'A Boolean toggle to indicate if you want to use the logit function (true) or log-odds units (false) for model predictions. Defaults to false.
', ], ], 'ClarifyTextConfig' => [ 'base' => 'A parameter used to configure the SageMaker Clarify explainer to treat text features as text so that explanations are provided for individual units of text. Required only for natural language processing (NLP) explainability.
', 'refs' => [ 'ClarifyShapConfig$TextConfig' => 'A parameter that indicates if text features are treated as text and explanations are provided for individual units of text. Required for natural language processing (NLP) explainability only.
', ], ], 'ClarifyTextGranularity' => [ 'base' => NULL, 'refs' => [ 'ClarifyTextConfig$Granularity' => 'The unit of granularity for the analysis of text features. For example, if the unit is \'token\', then each token (like a word in English) of the text is treated as a feature. SHAP values are computed for each unit/feature.
Specifies the language of the text features in ISO 639-1 or ISO 639-3 code of a supported language.
For a mix of multiple languages, use code \'xx\'.
The client ID for your Amazon Cognito user pool.
', 'CognitoMemberDefinition$ClientId' => 'An identifier for an application client. You must create the app client ID using Amazon Cognito.
', 'OidcConfig$ClientId' => 'The OIDC IdP client ID used to configure your private workforce.
', 'OidcConfigForResponse$ClientId' => 'The OIDC IdP client ID used to configure your private workforce.
', ], ], 'ClientSecret' => [ 'base' => NULL, 'refs' => [ 'OidcConfig$ClientSecret' => 'The OIDC IdP client secret used to configure your private workforce.
', ], ], 'ClientToken' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$ClientToken' => 'A unique ID. If not specified, the Amazon Web Services CLI and Amazon Web Services SDKs, such as the SDK for Python (Boto3), add a unique value to the call.
', 'CreateModelPackageInput$ClientToken' => 'A unique token that guarantees that the call to this API is idempotent.
', ], ], 'CodeRepositories' => [ 'base' => NULL, 'refs' => [ 'JupyterServerAppSettings$CodeRepositories' => 'A list of Git repositories that SageMaker automatically displays to users for cloning in the JupyterServer application.
', ], ], 'CodeRepository' => [ 'base' => 'A Git repository that SageMaker automatically displays to users for cloning in the JupyterServer application.
', 'refs' => [ 'CodeRepositories$member' => NULL, ], ], 'CodeRepositoryArn' => [ 'base' => NULL, 'refs' => [ 'CodeRepositorySummary$CodeRepositoryArn' => 'The Amazon Resource Name (ARN) of the Git repository.
', 'CreateCodeRepositoryOutput$CodeRepositoryArn' => 'The Amazon Resource Name (ARN) of the new repository.
', 'DescribeCodeRepositoryOutput$CodeRepositoryArn' => 'The Amazon Resource Name (ARN) of the Git repository.
', 'UpdateCodeRepositoryOutput$CodeRepositoryArn' => 'The ARN of the Git repository.
', ], ], 'CodeRepositoryContains' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstancesInput$DefaultCodeRepositoryContains' => 'A string in the name or URL of a Git repository associated with this notebook instance. This filter returns only notebook instances associated with a git repository with a name that contains the specified string.
', ], ], 'CodeRepositoryNameContains' => [ 'base' => NULL, 'refs' => [ 'ListCodeRepositoriesInput$NameContains' => 'A string in the Git repositories name. This filter returns only repositories whose name contains the specified string.
', ], ], 'CodeRepositoryNameOrUrl' => [ 'base' => NULL, 'refs' => [ 'AdditionalCodeRepositoryNamesOrUrls$member' => NULL, 'CreateNotebookInstanceInput$DefaultCodeRepository' => 'A Git repository to associate with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', 'DescribeNotebookInstanceOutput$DefaultCodeRepository' => 'The Git repository associated with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', 'ListNotebookInstancesInput$AdditionalCodeRepositoryEquals' => 'A filter that returns only notebook instances with associated with the specified git repository.
', 'NotebookInstanceSummary$DefaultCodeRepository' => 'The Git repository associated with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', 'UpdateNotebookInstanceInput$DefaultCodeRepository' => 'The Git repository to associate with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker Notebook Instances.
', ], ], 'CodeRepositorySortBy' => [ 'base' => NULL, 'refs' => [ 'ListCodeRepositoriesInput$SortBy' => 'The field to sort results by. The default is Name.
The sort order for results. The default is Ascending.
Specifies summary information about a Git repository.
', 'refs' => [ 'CodeRepositorySummaryList$member' => NULL, ], ], 'CodeRepositorySummaryList' => [ 'base' => NULL, 'refs' => [ 'ListCodeRepositoriesOutput$CodeRepositorySummaryList' => 'Gets a list of summaries of the Git repositories. Each summary specifies the following values for the repository:
Name
Amazon Resource Name (ARN)
Creation time
Last modified time
Configuration information, including the URL location of the repository and the ARN of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository.
Use this parameter to configure your Amazon Cognito workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.
', 'refs' => [ 'CreateWorkforceRequest$CognitoConfig' => 'Use this parameter to configure an Amazon Cognito private workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.
Do not use OidcConfig if you specify values for CognitoConfig.
The configuration of an Amazon Cognito workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.
', ], ], 'CognitoMemberDefinition' => [ 'base' => 'Identifies a Amazon Cognito user group. A user group can be used in on or more work teams.
', 'refs' => [ 'MemberDefinition$CognitoMemberDefinition' => 'The Amazon Cognito user group that is part of the work team.
', ], ], 'CognitoUserGroup' => [ 'base' => NULL, 'refs' => [ 'CognitoMemberDefinition$UserGroup' => 'An identifier for a user group.
', ], ], 'CognitoUserPool' => [ 'base' => NULL, 'refs' => [ 'CognitoConfig$UserPool' => 'A user pool is a user directory in Amazon Cognito. With a user pool, your users can sign in to your web or mobile app through Amazon Cognito. Your users can also sign in through social identity providers like Google, Facebook, Amazon, or Apple, and through SAML identity providers.
', 'CognitoMemberDefinition$UserPool' => 'An identifier for a user pool. The user pool must be in the same region as the service that you are calling.
', ], ], 'CollectionConfig' => [ 'base' => 'Configuration for your collection.
', 'refs' => [ 'FeatureDefinition$CollectionConfig' => 'Configuration for your collection.
', ], ], 'CollectionConfiguration' => [ 'base' => 'Configuration information for the Amazon SageMaker Debugger output tensor collections.
', 'refs' => [ 'CollectionConfigurations$member' => NULL, ], ], 'CollectionConfigurations' => [ 'base' => NULL, 'refs' => [ 'DebugHookConfig$CollectionConfigurations' => 'Configuration information for Amazon SageMaker Debugger tensor collections. To learn more about how to configure the CollectionConfiguration parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
The name of the tensor collection. The name must be unique relative to other rule configuration names.
', ], ], 'CollectionParameters' => [ 'base' => NULL, 'refs' => [ 'CollectionConfiguration$CollectionParameters' => 'Parameter values for the tensor collection. The allowed parameters are "name", "include_regex", "reduction_config", "save_config", "tensor_names", and "save_histogram".
A grouping of elements where each element within the collection must have the same feature type (String, Integral, or Fractional).
List: An ordered collection of elements.
Set: An unordered collection of unique elements.
Vector: A specialized list that represents a fixed-size array of elements. The vector dimension is determined by you. Must have elements with fractional feature types.
The Amazon Resource Name (ARN) of the model compilation job.
', 'CreateCompilationJobResponse$CompilationJobArn' => 'If the action is successful, the service sends back an HTTP 200 response. Amazon SageMaker returns the following data in JSON format:
CompilationJobArn: The Amazon Resource Name (ARN) of the compiled job.
The Amazon Resource Name (ARN) of the model compilation job.
', ], ], 'CompilationJobStatus' => [ 'base' => NULL, 'refs' => [ 'CompilationJobSummary$CompilationJobStatus' => 'The status of the model compilation job.
', 'DescribeCompilationJobResponse$CompilationJobStatus' => 'The status of the model compilation job.
', 'ListCompilationJobsRequest$StatusEquals' => 'A filter that retrieves model compilation jobs with a specific CompilationJobStatus status.
An array of CompilationJobSummary objects, each describing a model compilation job.
', ], ], 'CompilationJobSummary' => [ 'base' => 'A summary of a model compilation job.
', 'refs' => [ 'CompilationJobSummaries$member' => NULL, ], ], 'CompilerOptions' => [ 'base' => NULL, 'refs' => [ 'OutputConfig$CompilerOptions' => 'Specifies additional parameters for compiler options in JSON format. The compiler options are TargetPlatform specific. It is required for NVIDIA accelerators and highly recommended for CPU compilations. For any other cases, it is optional to specify CompilerOptions.
DTYPE: Specifies the data type for the input. When compiling for ml_* (except for ml_inf) instances using PyTorch framework, provide the data type (dtype) of the model\'s input. "float32" is used if "DTYPE" is not specified. Options for data type are:
float32: Use either "float" or "float32".
int64: Use either "int64" or "long".
For example, {"dtype" : "float32"}.
CPU: Compilation for CPU supports the following compiler options.
mcpu: CPU micro-architecture. For example, {\'mcpu\': \'skylake-avx512\'}
mattr: CPU flags. For example, {\'mattr\': [\'+neon\', \'+vfpv4\']}
ARM: Details of ARM CPU compilations.
NEON: NEON is an implementation of the Advanced SIMD extension used in ARMv7 processors.
For example, add {\'mattr\': [\'+neon\']} to the compiler options if compiling for ARM 32-bit platform with the NEON support.
NVIDIA: Compilation for NVIDIA GPU supports the following compiler options.
gpu_code: Specifies the targeted architecture.
trt-ver: Specifies the TensorRT versions in x.y.z. format.
cuda-ver: Specifies the CUDA version in x.y format.
For example, {\'gpu-code\': \'sm_72\', \'trt-ver\': \'6.0.1\', \'cuda-ver\': \'10.1\'}
ANDROID: Compilation for the Android OS supports the following compiler options:
ANDROID_PLATFORM: Specifies the Android API levels. Available levels range from 21 to 29. For example, {\'ANDROID_PLATFORM\': 28}.
mattr: Add {\'mattr\': [\'+neon\']} to compiler options if compiling for ARM 32-bit platform with NEON support.
INFERENTIA: Compilation for target ml_inf1 uses compiler options passed in as a JSON string. For example, "CompilerOptions": "\\"--verbose 1 --num-neuroncores 2 -O2\\"".
For information about supported compiler options, see Neuron Compiler CLI Reference Guide.
CoreML: Compilation for the CoreML OutputConfig TargetDevice supports the following compiler options:
class_labels: Specifies the classification labels file name inside input tar.gz file. For example, {"class_labels": "imagenet_labels_1000.txt"}. Labels inside the txt file should be separated by newlines.
EIA: Compilation for the Elastic Inference Accelerator supports the following compiler options:
precision_mode: Specifies the precision of compiled artifacts. Supported values are "FP16" and "FP32". Default is "FP32".
signature_def_key: Specifies the signature to use for models in SavedModel format. Defaults is TensorFlow\'s default signature def key.
output_names: Specifies a list of output tensor names for models in FrozenGraph format. Set at most one API field, either: signature_def_key or output_names.
For example: {"precision_mode": "FP32", "output_names": ["output:0"]}
A flag to stop a tuning job once AMT has detected that the job has converged.
', ], ], 'CompressionType' => [ 'base' => NULL, 'refs' => [ 'AdditionalS3DataSource$CompressionType' => 'The type of compression used for an additional data source used in inference or training. Specify None if your additional data source is not compressed.
You can use Gzip or None. The default value is None.
The allowed compression types depend on the input format and problem type. We allow the compression type Gzip for S3Prefix inputs on tabular data only. For all other inputs, the compression type should be None. If no compression type is provided, we default to None.
If training data is compressed, the compression type. The default value is None. CompressionType is used only in Pipe input mode. In File mode, leave this field unset or set it to None.
If your transform data is compressed, specify the compression type. Amazon SageMaker automatically decompresses the data for the transform job accordingly. The default value is None.
The allowed compression types, if data compression is used.
', ], ], 'ConditionOutcome' => [ 'base' => NULL, 'refs' => [ 'ConditionStepMetadata$Outcome' => 'The outcome of the Condition step evaluation.
', ], ], 'ConditionStepMetadata' => [ 'base' => 'Metadata for a Condition step.
', 'refs' => [ 'PipelineExecutionStepMetadata$Condition' => 'The outcome of the condition evaluation that was run by this step execution.
', ], ], 'ConfigKey' => [ 'base' => NULL, 'refs' => [ 'CollectionParameters$key' => NULL, 'HookParameters$key' => NULL, 'ProfilingParameters$key' => NULL, 'RuleParameters$key' => NULL, ], ], 'ConfigValue' => [ 'base' => NULL, 'refs' => [ 'CollectionParameters$value' => NULL, 'HookParameters$value' => NULL, 'ProfilingParameters$value' => NULL, 'RuleParameters$value' => NULL, ], ], 'ConflictException' => [ 'base' => 'There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
The arguments for a container used to run a processing job.
', ], ], 'ContainerDefinition' => [ 'base' => 'Describes the container, as part of model definition.
', 'refs' => [ 'ContainerDefinitionList$member' => NULL, 'CreateModelInput$PrimaryContainer' => 'The location of the primary docker image containing inference code, associated artifacts, and custom environment map that the inference code uses when the model is deployed for predictions.
', 'DescribeModelOutput$PrimaryContainer' => 'The location of the primary inference code, associated artifacts, and custom environment map that the inference code uses when it is deployed in production.
', 'Model$PrimaryContainer' => NULL, ], ], 'ContainerDefinitionList' => [ 'base' => NULL, 'refs' => [ 'CreateModelInput$Containers' => 'Specifies the containers in the inference pipeline.
', 'DescribeModelOutput$Containers' => 'The containers in the inference pipeline.
', 'Model$Containers' => 'The containers in the inference pipeline.
', ], ], 'ContainerEntrypoint' => [ 'base' => NULL, 'refs' => [ 'AppSpecification$ContainerEntrypoint' => 'The entrypoint for a container used to run a processing job.
', 'DataQualityAppSpecification$ContainerEntrypoint' => 'The entrypoint for a container used to run a monitoring job.
', 'ModelQualityAppSpecification$ContainerEntrypoint' => 'Specifies the entrypoint for a container that the monitoring job runs.
', 'MonitoringAppSpecification$ContainerEntrypoint' => 'Specifies the entrypoint for a container used to run the monitoring job.
', ], ], 'ContainerEntrypointString' => [ 'base' => NULL, 'refs' => [ 'ContainerEntrypoint$member' => NULL, ], ], 'ContainerHostname' => [ 'base' => NULL, 'refs' => [ 'ContainerDefinition$ContainerHostname' => 'This parameter is ignored for models that contain only a PrimaryContainer.
When a ContainerDefinition is part of an inference pipeline, the value of the parameter uniquely identifies the container for the purposes of logging and metrics. For information, see Use Logs and Metrics to Monitor an Inference Pipeline. If you don\'t specify a value for this parameter for a ContainerDefinition that is part of an inference pipeline, a unique name is automatically assigned based on the position of the ContainerDefinition in the pipeline. If you specify a value for the ContainerHostName for any ContainerDefinition that is part of an inference pipeline, you must specify a value for the ContainerHostName parameter of every ContainerDefinition in that pipeline.
The DNS host name for the Docker container.
', ], ], 'ContainerImage' => [ 'base' => NULL, 'refs' => [ 'AutoMLContainerDefinition$Image' => 'The Amazon Elastic Container Registry (Amazon ECR) path of the container. For more information, see ContainerDefinition.
', 'ContainerDefinition$Image' => 'The path where inference code is stored. This can be either in Amazon EC2 Container Registry or in a Docker registry that is accessible from the same VPC that you configure for your endpoint. If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference code must meet SageMaker requirements. SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.
The model artifacts in an Amazon S3 bucket and the Docker image for inference container in Amazon EC2 Container Registry must be in the same region as the model or endpoint you are creating.
The image path you specified when you created the model.
', 'DeployedImage$ResolvedImage' => 'The specific digest path of the image hosted in this ProductionVariant.
The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.
If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference code must meet SageMaker requirements. SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.
The Amazon ECR registry path of the Docker image that contains the training algorithm.
', ], ], 'ContainerMode' => [ 'base' => NULL, 'refs' => [ 'ContainerDefinition$Mode' => 'Whether the container hosts a single model or multiple models.
', ], ], 'ContentClassifier' => [ 'base' => NULL, 'refs' => [ 'ContentClassifiers$member' => NULL, ], ], 'ContentClassifiers' => [ 'base' => NULL, 'refs' => [ 'LabelingJobDataAttributes$ContentClassifiers' => 'Declares that your content is free of personally identifiable information or adult content. SageMaker may restrict the Amazon Mechanical Turk workers that can view your task based on this information.
', ], ], 'ContentColumn' => [ 'base' => NULL, 'refs' => [ 'TextClassificationJobConfig$ContentColumn' => 'The name of the column used to provide the sentences to be classified. It should not be the same as the target column.
', ], ], 'ContentDigest' => [ 'base' => NULL, 'refs' => [ 'FileSource$ContentDigest' => 'The digest of the file source.
', 'MetricsSource$ContentDigest' => 'The hash key used for the metrics source.
', ], ], 'ContentType' => [ 'base' => NULL, 'refs' => [ 'AutoMLChannel$ContentType' => 'The content type of the data from the input source. You can use text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
The content type of the data from the input source. The following are the allowed content types for different problems:
For tabular problem types: text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
For image classification: image/png, image/jpeg, or image/*. The default value is image/*.
For text classification: text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
For time-series forecasting: text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
For text generation (LLMs fine-tuning): text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
The MIME type of the data.
', 'ContentTypes$member' => NULL, 'FileSource$ContentType' => 'The type of content stored in the file source.
', 'MetricsSource$ContentType' => 'The metric source content type.
', 'TransformInput$ContentType' => 'The multipurpose internet mail extension (MIME) type of the data. Amazon SageMaker uses the MIME type with each http call to transfer data to the transform job.
', ], ], 'ContentTypes' => [ 'base' => NULL, 'refs' => [ 'AdditionalInferenceSpecificationDefinition$SupportedContentTypes' => 'The supported MIME types for the input data.
', 'ChannelSpecification$SupportedContentTypes' => 'The supported MIME types for the data.
', 'InferenceSpecification$SupportedContentTypes' => 'The supported MIME types for the input data.
', ], ], 'ContextArn' => [ 'base' => NULL, 'refs' => [ 'ContextSummary$ContextArn' => 'The Amazon Resource Name (ARN) of the context.
', 'CreateContextResponse$ContextArn' => 'The Amazon Resource Name (ARN) of the context.
', 'DeleteContextResponse$ContextArn' => 'The Amazon Resource Name (ARN) of the context.
', 'DescribeContextResponse$ContextArn' => 'The Amazon Resource Name (ARN) of the context.
', 'UpdateContextResponse$ContextArn' => 'The Amazon Resource Name (ARN) of the context.
', ], ], 'ContextSource' => [ 'base' => 'A structure describing the source of a context.
', 'refs' => [ 'ContextSummary$Source' => 'The source of the context.
', 'CreateContextRequest$Source' => 'The source type, ID, and URI.
', 'DescribeContextResponse$Source' => 'The source of the context.
', ], ], 'ContextSummaries' => [ 'base' => NULL, 'refs' => [ 'ListContextsResponse$ContextSummaries' => 'A list of contexts and their properties.
', ], ], 'ContextSummary' => [ 'base' => 'Lists a summary of the properties of a context. A context provides a logical grouping of other entities.
', 'refs' => [ 'ContextSummaries$member' => NULL, ], ], 'ContinuousParameterRange' => [ 'base' => 'A list of continuous hyperparameters to tune.
', 'refs' => [ 'ContinuousParameterRanges$member' => NULL, ], ], 'ContinuousParameterRangeSpecification' => [ 'base' => 'Defines the possible values for a continuous hyperparameter.
', 'refs' => [ 'ParameterRange$ContinuousParameterRangeSpecification' => 'A ContinuousParameterRangeSpecification object that defines the possible values for a continuous hyperparameter.
The array of ContinuousParameterRange objects that specify ranges of continuous hyperparameters that a hyperparameter tuning job searches.
', ], ], 'ConvergenceDetected' => [ 'base' => 'A flag to indicating that automatic model tuning (AMT) has detected model convergence, defined as a lack of significant improvement (1% or less) against an objective metric.
', 'refs' => [ 'TuningJobCompletionCriteria$ConvergenceDetected' => 'A flag to top your hyperparameter tuning job if automatic model tuning (AMT) has detected that your model has converged as evaluated against your objective function.
', ], ], 'CountryCode' => [ 'base' => NULL, 'refs' => [ 'HolidayConfigAttributes$CountryCode' => 'The country code for the holiday calendar.
For the list of public holiday calendars supported by AutoML job V2, see Country Codes. Use the country code corresponding to the country of your choice.
', ], ], 'CreateActionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateActionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateAlgorithmInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateAlgorithmOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateAppImageConfigRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateAppImageConfigResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateAppRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateAppResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateArtifactRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateArtifactResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateAutoMLJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateAutoMLJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateAutoMLJobV2Request' => [ 'base' => NULL, 'refs' => [], ], 'CreateAutoMLJobV2Response' => [ 'base' => NULL, 'refs' => [], ], 'CreateCodeRepositoryInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateCodeRepositoryOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateCompilationJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateCompilationJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateContextRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateContextResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateDataQualityJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateDataQualityJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateDeviceFleetRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateDomainRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateDomainResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateEdgeDeploymentPlanRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateEdgeDeploymentPlanResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateEdgeDeploymentStageRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateEdgePackagingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateEndpointConfigInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateEndpointConfigOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateEndpointInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateEndpointOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateFeatureGroupRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateFeatureGroupResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateFlowDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateFlowDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateHubRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateHubResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateHumanTaskUiRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateHumanTaskUiResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateHyperParameterTuningJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateHyperParameterTuningJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateImageRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateImageResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateImageVersionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateImageVersionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateInferenceExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateInferenceExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateInferenceRecommendationsJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateInferenceRecommendationsJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateLabelingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateLabelingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelBiasJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelBiasJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelCardExportJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelCardExportJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelCardRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelCardResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelExplainabilityJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelExplainabilityJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelPackageGroupInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelPackageGroupOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelPackageInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelPackageOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelQualityJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateModelQualityJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateMonitoringScheduleRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateMonitoringScheduleResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateNotebookInstanceInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateNotebookInstanceLifecycleConfigInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateNotebookInstanceLifecycleConfigOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateNotebookInstanceOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreatePipelineRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreatePipelineResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreatePresignedDomainUrlRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreatePresignedDomainUrlResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreatePresignedNotebookInstanceUrlInput' => [ 'base' => NULL, 'refs' => [], ], 'CreatePresignedNotebookInstanceUrlOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateProcessingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateProcessingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateProjectInput' => [ 'base' => NULL, 'refs' => [], ], 'CreateProjectOutput' => [ 'base' => NULL, 'refs' => [], ], 'CreateSpaceRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateSpaceResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateStudioLifecycleConfigRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateStudioLifecycleConfigResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateTrainingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateTrainingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateTransformJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateTransformJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateTrialComponentRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateTrialComponentResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateTrialRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateTrialResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateUserProfileRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateUserProfileResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateWorkforceRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateWorkforceResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreateWorkteamRequest' => [ 'base' => NULL, 'refs' => [], ], 'CreateWorkteamResponse' => [ 'base' => NULL, 'refs' => [], ], 'CreationTime' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSummary$CreationTime' => 'A timestamp that shows when the algorithm was created.
', 'AppDetails$CreationTime' => 'The creation time.
', 'BatchDescribeModelPackageSummary$CreationTime' => 'The creation time of the mortgage package summary.
', 'CodeRepositorySummary$CreationTime' => 'The date and time that the Git repository was created.
', 'CompilationJobSummary$CreationTime' => 'The time when the model compilation job was created.
', 'DescribeAlgorithmOutput$CreationTime' => 'A timestamp specifying when the algorithm was created.
', 'DescribeAppResponse$CreationTime' => 'The creation time.
', 'DescribeCodeRepositoryOutput$CreationTime' => 'The date and time that the repository was created.
', 'DescribeCompilationJobResponse$CreationTime' => 'The time that the model compilation job was created.
', 'DescribeDomainResponse$CreationTime' => 'The creation time.
', 'DescribeFeatureGroupResponse$CreationTime' => 'A timestamp indicating when SageMaker created the FeatureGroup.
A timestamp indicating when the feature was created.
', 'DescribeInferenceRecommendationsJobResponse$CreationTime' => 'A timestamp that shows when the job was created.
', 'DescribeModelPackageGroupOutput$CreationTime' => 'The time that the model group was created.
', 'DescribeModelPackageOutput$CreationTime' => 'A timestamp specifying when the model package was created.
', 'DescribeNotebookInstanceLifecycleConfigOutput$CreationTime' => 'A timestamp that tells when the lifecycle configuration was created.
', 'DescribeNotebookInstanceOutput$CreationTime' => 'A timestamp. Use this parameter to return the time when the notebook instance was created
', 'DescribeSpaceResponse$CreationTime' => 'The creation time.
', 'DescribeUserProfileResponse$CreationTime' => 'The creation time.
', 'DomainDetails$CreationTime' => 'The creation time.
', 'FeatureGroup$CreationTime' => 'The time a FeatureGroup was created.
A timestamp indicating when the feature was created.
', 'InferenceRecommendationsJob$CreationTime' => 'A timestamp that shows when the job was created.
', 'ListAlgorithmsInput$CreationTimeAfter' => 'A filter that returns only algorithms created after the specified time (timestamp).
', 'ListAlgorithmsInput$CreationTimeBefore' => 'A filter that returns only algorithms created before the specified time (timestamp).
', 'ListCodeRepositoriesInput$CreationTimeAfter' => 'A filter that returns only Git repositories that were created after the specified time.
', 'ListCodeRepositoriesInput$CreationTimeBefore' => 'A filter that returns only Git repositories that were created before the specified time.
', 'ListCompilationJobsRequest$CreationTimeAfter' => 'A filter that returns the model compilation jobs that were created after a specified time.
', 'ListCompilationJobsRequest$CreationTimeBefore' => 'A filter that returns the model compilation jobs that were created before a specified time.
', 'ListFeatureGroupsRequest$CreationTimeAfter' => 'Use this parameter to search for FeatureGroupss created after a specific date and time.
Use this parameter to search for FeatureGroupss created before a specific date and time.
A filter that returns only jobs created after the specified time (timestamp).
', 'ListInferenceRecommendationsJobsRequest$CreationTimeBefore' => 'A filter that returns only jobs created before the specified time (timestamp).
', 'ListModelPackageGroupsInput$CreationTimeAfter' => 'A filter that returns only model groups created after the specified time.
', 'ListModelPackageGroupsInput$CreationTimeBefore' => 'A filter that returns only model groups created before the specified time.
', 'ListModelPackagesInput$CreationTimeAfter' => 'A filter that returns only model packages created after the specified time (timestamp).
', 'ListModelPackagesInput$CreationTimeBefore' => 'A filter that returns only model packages created before the specified time (timestamp).
', 'ListNotebookInstanceLifecycleConfigsInput$CreationTimeBefore' => 'A filter that returns only lifecycle configurations that were created before the specified time (timestamp).
', 'ListNotebookInstanceLifecycleConfigsInput$CreationTimeAfter' => 'A filter that returns only lifecycle configurations that were created after the specified time (timestamp).
', 'ListNotebookInstancesInput$CreationTimeBefore' => 'A filter that returns only notebook instances that were created before the specified time (timestamp).
', 'ListNotebookInstancesInput$CreationTimeAfter' => 'A filter that returns only notebook instances that were created after the specified time (timestamp).
', 'ModelPackage$CreationTime' => 'The time that the model package was created.
', 'ModelPackageGroup$CreationTime' => 'The time that the model group was created.
', 'ModelPackageGroupSummary$CreationTime' => 'The time that the model group was created.
', 'ModelPackageSummary$CreationTime' => 'A timestamp that shows when the model package was created.
', 'NotebookInstanceLifecycleConfigSummary$CreationTime' => 'A timestamp that tells when the lifecycle configuration was created.
', 'NotebookInstanceSummary$CreationTime' => 'A timestamp that shows when the notebook instance was created.
', 'SpaceDetails$CreationTime' => 'The creation time.
', 'UserProfileDetails$CreationTime' => 'The creation time.
', ], ], 'CrossAccountFilterOption' => [ 'base' => NULL, 'refs' => [ 'SearchRequest$CrossAccountFilterOption' => ' A cross account filter option. When the value is "CrossAccount" the search results will only include resources made discoverable to you from other accounts. When the value is "SameAccount" or null the search results will only include resources from your account. Default is null. For more information on searching for resources made discoverable to your account, see Search discoverable resources in the SageMaker Developer Guide. The maximum number of ResourceCatalogs viewable is 1000.
The list of all content type headers that Amazon SageMaker will treat as CSV and capture accordingly.
', ], ], 'CustomImage' => [ 'base' => 'A custom SageMaker image. For more information, see Bring your own SageMaker image.
', 'refs' => [ 'CustomImages$member' => NULL, ], ], 'CustomImages' => [ 'base' => NULL, 'refs' => [ 'KernelGatewayAppSettings$CustomImages' => 'A list of custom SageMaker images that are configured to run as a KernelGateway app.
', 'RSessionAppSettings$CustomImages' => 'A list of custom SageMaker images that are configured to run as a RSession app.
', ], ], 'CustomerMetadataKey' => [ 'base' => NULL, 'refs' => [ 'CustomerMetadataKeyList$member' => NULL, 'CustomerMetadataMap$key' => NULL, ], ], 'CustomerMetadataKeyList' => [ 'base' => NULL, 'refs' => [ 'UpdateModelPackageInput$CustomerMetadataPropertiesToRemove' => 'The metadata properties associated with the model package versions to remove.
', ], ], 'CustomerMetadataMap' => [ 'base' => NULL, 'refs' => [ 'CreateModelPackageInput$CustomerMetadataProperties' => 'The metadata properties associated with the model package versions.
', 'DescribeModelPackageOutput$CustomerMetadataProperties' => 'The metadata properties associated with the model package versions.
', 'ModelPackage$CustomerMetadataProperties' => 'The metadata properties for the model package.
', 'UpdateModelPackageInput$CustomerMetadataProperties' => 'The metadata properties associated with the model package versions.
', ], ], 'CustomerMetadataValue' => [ 'base' => NULL, 'refs' => [ 'CustomerMetadataMap$value' => NULL, ], ], 'CustomizedMetricSpecification' => [ 'base' => 'A customized metric.
', 'refs' => [ 'MetricSpecification$Customized' => 'Information about a customized metric.
', ], ], 'DataCaptureConfig' => [ 'base' => 'Configuration to control how SageMaker captures inference data.
', 'refs' => [ 'CreateEndpointConfigInput$DataCaptureConfig' => NULL, 'DescribeEndpointConfigOutput$DataCaptureConfig' => NULL, ], ], 'DataCaptureConfigSummary' => [ 'base' => 'The currently active data capture configuration used by your Endpoint.
', 'refs' => [ 'DescribeEndpointOutput$DataCaptureConfig' => NULL, 'Endpoint$DataCaptureConfig' => NULL, ], ], 'DataCatalogConfig' => [ 'base' => 'The meta data of the Glue table which serves as data catalog for the OfflineStore.
The meta data of the Glue table that is autogenerated when an OfflineStore is created.
Whether the generated dataset is FullyReplicated or ShardedByS3Key (default).
The URL of the notebook location.
', ], ], 'DataInputConfig' => [ 'base' => NULL, 'refs' => [ 'DerivedInformation$DerivedDataInputConfig' => 'The data input configuration that SageMaker Neo automatically derived for the model. When SageMaker Neo derives this information, you don\'t need to specify the data input configuration when you create a compilation job.
', 'InputConfig$DataInputConfig' => 'Specifies the name and shape of the expected data inputs for your trained model with a JSON dictionary form. The data inputs are Framework specific.
TensorFlow: You must specify the name and shape (NHWC format) of the expected data inputs using a dictionary format for your trained model. The dictionary formats required for the console and CLI are different.
Examples for one input:
If using the console, {"input":[1,1024,1024,3]}
If using the CLI, {\\"input\\":[1,1024,1024,3]}
Examples for two inputs:
If using the console, {"data1": [1,28,28,1], "data2":[1,28,28,1]}
If using the CLI, {\\"data1\\": [1,28,28,1], \\"data2\\":[1,28,28,1]}
KERAS: You must specify the name and shape (NCHW format) of expected data inputs using a dictionary format for your trained model. Note that while Keras model artifacts should be uploaded in NHWC (channel-last) format, DataInputConfig should be specified in NCHW (channel-first) format. The dictionary formats required for the console and CLI are different.
Examples for one input:
If using the console, {"input_1":[1,3,224,224]}
If using the CLI, {\\"input_1\\":[1,3,224,224]}
Examples for two inputs:
If using the console, {"input_1": [1,3,224,224], "input_2":[1,3,224,224]}
If using the CLI, {\\"input_1\\": [1,3,224,224], \\"input_2\\":[1,3,224,224]}
MXNET/ONNX/DARKNET: You must specify the name and shape (NCHW format) of the expected data inputs in order using a dictionary format for your trained model. The dictionary formats required for the console and CLI are different.
Examples for one input:
If using the console, {"data":[1,3,1024,1024]}
If using the CLI, {\\"data\\":[1,3,1024,1024]}
Examples for two inputs:
If using the console, {"var1": [1,1,28,28], "var2":[1,1,28,28]}
If using the CLI, {\\"var1\\": [1,1,28,28], \\"var2\\":[1,1,28,28]}
PyTorch: You can either specify the name and shape (NCHW format) of expected data inputs in order using a dictionary format for your trained model or you can specify the shape only using a list format. The dictionary formats required for the console and CLI are different. The list formats for the console and CLI are the same.
Examples for one input in dictionary format:
If using the console, {"input0":[1,3,224,224]}
If using the CLI, {\\"input0\\":[1,3,224,224]}
Example for one input in list format: [[1,3,224,224]]
Examples for two inputs in dictionary format:
If using the console, {"input0":[1,3,224,224], "input1":[1,3,224,224]}
If using the CLI, {\\"input0\\":[1,3,224,224], \\"input1\\":[1,3,224,224]}
Example for two inputs in list format: [[1,3,224,224], [1,3,224,224]]
XGBOOST: input data name and shape are not needed.
DataInputConfig supports the following parameters for CoreML TargetDevice (ML Model format):
shape: Input shape, for example {"input_1": {"shape": [1,224,224,3]}}. In addition to static input shapes, CoreML converter supports Flexible input shapes:
Range Dimension. You can use the Range Dimension feature if you know the input shape will be within some specific interval in that dimension, for example: {"input_1": {"shape": ["1..10", 224, 224, 3]}}
Enumerated shapes. Sometimes, the models are trained to work only on a select set of inputs. You can enumerate all supported input shapes, for example: {"input_1": {"shape": [[1, 224, 224, 3], [1, 160, 160, 3]]}}
default_shape: Default input shape. You can set a default shape during conversion for both Range Dimension and Enumerated Shapes. For example {"input_1": {"shape": ["1..10", 224, 224, 3], "default_shape": [1, 224, 224, 3]}}
type: Input type. Allowed values: Image and Tensor. By default, the converter generates an ML Model with inputs of type Tensor (MultiArray). User can set input type to be Image. Image input type requires additional input parameters such as bias and scale.
bias: If the input type is an Image, you need to provide the bias vector.
scale: If the input type is an Image, you need to provide a scale factor.
CoreML ClassifierConfig parameters can be specified using OutputConfig CompilerOptions. CoreML converter supports Tensorflow and PyTorch models. CoreML conversion examples:
Tensor type input:
"DataInputConfig": {"input_1": {"shape": [[1,224,224,3], [1,160,160,3]], "default_shape": [1,224,224,3]}}
Tensor type input without input name (PyTorch):
"DataInputConfig": [{"shape": [[1,3,224,224], [1,3,160,160]], "default_shape": [1,3,224,224]}]
Image type input:
"DataInputConfig": {"input_1": {"shape": [[1,224,224,3], [1,160,160,3]], "default_shape": [1,224,224,3], "type": "Image", "bias": [-1,-1,-1], "scale": 0.007843137255}}
"CompilerOptions": {"class_labels": "imagenet_labels_1000.txt"}
Image type input without input name (PyTorch):
"DataInputConfig": [{"shape": [[1,3,224,224], [1,3,160,160]], "default_shape": [1,3,224,224], "type": "Image", "bias": [-1,-1,-1], "scale": 0.007843137255}]
"CompilerOptions": {"class_labels": "imagenet_labels_1000.txt"}
Depending on the model format, DataInputConfig requires the following parameters for ml_eia2 OutputConfig:TargetDevice.
For TensorFlow models saved in the SavedModel format, specify the input names from signature_def_key and the input model shapes for DataInputConfig. Specify the signature_def_key in OutputConfig:CompilerOptions if the model does not use TensorFlow\'s default signature def key. For example:
"DataInputConfig": {"inputs": [1, 224, 224, 3]}
"CompilerOptions": {"signature_def_key": "serving_custom"}
For TensorFlow models saved as a frozen graph, specify the input tensor names and shapes in DataInputConfig and the output tensor names for output_names in OutputConfig:CompilerOptions . For example:
"DataInputConfig": {"input_tensor:0": [1, 224, 224, 3]}
"CompilerOptions": {"output_names": ["output_tensor:0"]}
The input configuration object for the model.
', ], ], 'DataProcessing' => [ 'base' => 'The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see Associate Prediction Results with their Corresponding Input Records.
', 'refs' => [ 'CreateTransformJobRequest$DataProcessing' => 'The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see Associate Prediction Results with their Corresponding Input Records.
', 'DescribeTransformJobResponse$DataProcessing' => NULL, 'TransformJob$DataProcessing' => NULL, ], ], 'DataQualityAppSpecification' => [ 'base' => 'Information about the container that a data quality monitoring job runs.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$DataQualityAppSpecification' => 'Specifies the container that runs the monitoring job.
', 'DescribeDataQualityJobDefinitionResponse$DataQualityAppSpecification' => 'Information about the container that runs the data quality monitoring job.
', ], ], 'DataQualityBaselineConfig' => [ 'base' => 'Configuration for monitoring constraints and monitoring statistics. These baseline resources are compared against the results of the current job from the series of jobs scheduled to collect data periodically.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$DataQualityBaselineConfig' => 'Configures the constraints and baselines for the monitoring job.
', 'DescribeDataQualityJobDefinitionResponse$DataQualityBaselineConfig' => 'The constraints and baselines for the data quality monitoring job definition.
', ], ], 'DataQualityJobInput' => [ 'base' => 'The input for the data quality monitoring job. Currently endpoints are supported for input.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$DataQualityJobInput' => 'A list of inputs for the monitoring job. Currently endpoints are supported as monitoring inputs.
', 'DescribeDataQualityJobDefinitionResponse$DataQualityJobInput' => 'The list of inputs for the data quality monitoring job. Currently endpoints are supported.
', ], ], 'DataSource' => [ 'base' => 'Describes the location of the channel data.
', 'refs' => [ 'Channel$DataSource' => 'The location of the channel data.
', ], ], 'DataSourceName' => [ 'base' => NULL, 'refs' => [ 'IdentityProviderOAuthSetting$DataSourceName' => 'The name of the data source that you\'re connecting to. Canvas currently supports OAuth for Snowflake and Salesforce Data Cloud.
', ], ], 'Database' => [ 'base' => NULL, 'refs' => [ 'DataCatalogConfig$Database' => 'The name of the Glue table database.
', ], ], 'DatasetDefinition' => [ 'base' => 'Configuration for Dataset Definition inputs. The Dataset Definition input must specify exactly one of either AthenaDatasetDefinition or RedshiftDatasetDefinition types.
Configuration for a Dataset Definition input.
', ], ], 'DebugHookConfig' => [ 'base' => 'Configuration information for the Amazon SageMaker Debugger hook parameters, metric and tensor collections, and storage paths. To learn more about how to configure the DebugHookConfig parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Configuration information for SageMaker Debugger rules for debugging. To learn more about how to configure the DebugRuleConfiguration parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.
', 'DescribeTrainingJobResponse$DebugRuleConfigurations' => 'Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.
', 'TrainingJob$DebugRuleConfigurations' => 'Information about the debug rule configuration.
', ], ], 'DebugRuleEvaluationStatus' => [ 'base' => 'Information about the status of the rule evaluation.
', 'refs' => [ 'DebugRuleEvaluationStatuses$member' => NULL, ], ], 'DebugRuleEvaluationStatuses' => [ 'base' => NULL, 'refs' => [ 'DescribeTrainingJobResponse$DebugRuleEvaluationStatuses' => 'Evaluation status of Amazon SageMaker Debugger rules for debugging on a training job.
', 'TrainingJob$DebugRuleEvaluationStatuses' => 'Information about the evaluation status of the rules for the training job.
', ], ], 'DefaultGid' => [ 'base' => NULL, 'refs' => [ 'FileSystemConfig$DefaultGid' => 'The default POSIX group ID (GID). If not specified, defaults to 100.
A collection of settings that apply to spaces created in the Domain.
', 'refs' => [ 'CreateDomainRequest$DefaultSpaceSettings' => 'The default settings used to create a space.
', 'DescribeDomainResponse$DefaultSpaceSettings' => 'The default settings used to create a space.
', 'UpdateDomainRequest$DefaultSpaceSettings' => 'The default settings used to create a space within the Domain.
', ], ], 'DefaultUid' => [ 'base' => NULL, 'refs' => [ 'FileSystemConfig$DefaultUid' => 'The default POSIX user ID (UID). If not specified, defaults to 1000.
The hub content dependency copy path.
', ], ], 'DependencyOriginPath' => [ 'base' => NULL, 'refs' => [ 'HubContentDependency$DependencyOriginPath' => 'The hub content dependency origin path.
', ], ], 'DeployedImage' => [ 'base' => 'Gets the Amazon EC2 Container Registry path of the docker image of the model that is hosted in this ProductionVariant.
If you used the registry/repository[:tag] form to specify the image path of the primary container when you created the model hosted in this ProductionVariant, the path resolves to a path of the form registry/repository[@digest]. A digest is a hash value that identifies a specific version of an image. For information about Amazon ECR paths, see Pulling an Image in the Amazon ECR User Guide.
An array of DeployedImage objects that specify the Amazon EC2 Container Registry paths of the inference images deployed on instances of this ProductionVariant.
An array of DeployedImage objects that specify the Amazon EC2 Container Registry paths of the inference images deployed on instances of this ProductionVariant.
The deployment configuration for an endpoint, which contains the desired deployment strategy and rollback configurations.
', 'refs' => [ 'CreateEndpointInput$DeploymentConfig' => NULL, 'DescribeEndpointOutput$LastDeploymentConfig' => 'The most recent deployment configuration for the endpoint.
', 'UpdateEndpointInput$DeploymentConfig' => 'The deployment configuration for an endpoint, which contains the desired deployment strategy and rollback configurations.
', ], ], 'DeploymentRecommendation' => [ 'base' => 'A set of recommended deployment configurations for the model. To get more advanced recommendations, see CreateInferenceRecommendationsJob to create an inference recommendation job.
', 'refs' => [ 'DescribeModelOutput$DeploymentRecommendation' => 'A set of recommended deployment configurations for the model.
', 'Model$DeploymentRecommendation' => 'A set of recommended deployment configurations for the model.
', ], ], 'DeploymentStage' => [ 'base' => 'Contains information about a stage in an edge deployment plan.
', 'refs' => [ 'DeploymentStages$member' => NULL, ], ], 'DeploymentStageMaxResults' => [ 'base' => NULL, 'refs' => [ 'DescribeEdgeDeploymentPlanRequest$MaxResults' => 'The maximum number of results to select (50 by default).
', ], ], 'DeploymentStageStatusSummaries' => [ 'base' => NULL, 'refs' => [ 'DescribeEdgeDeploymentPlanResponse$Stages' => 'List of stages in the edge deployment plan.
', ], ], 'DeploymentStageStatusSummary' => [ 'base' => 'Contains information summarizing the deployment stage results.
', 'refs' => [ 'DeploymentStageStatusSummaries$member' => NULL, ], ], 'DeploymentStages' => [ 'base' => NULL, 'refs' => [ 'CreateEdgeDeploymentPlanRequest$Stages' => 'List of stages of the edge deployment plan. The number of stages is limited to 10 per deployment.
', 'CreateEdgeDeploymentStageRequest$Stages' => 'List of stages to be added to the edge deployment plan.
', ], ], 'DeregisterDevicesRequest' => [ 'base' => NULL, 'refs' => [], ], 'DerivedInformation' => [ 'base' => 'Information that SageMaker Neo automatically derived about the model.
', 'refs' => [ 'DescribeCompilationJobResponse$DerivedInformation' => 'Information that SageMaker Neo automatically derived about the model.
', ], ], 'DescribeActionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeActionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAlgorithmInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAlgorithmOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAppImageConfigRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAppImageConfigResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAppRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAppResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeArtifactRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeArtifactResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAutoMLJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAutoMLJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAutoMLJobV2Request' => [ 'base' => NULL, 'refs' => [], ], 'DescribeAutoMLJobV2Response' => [ 'base' => NULL, 'refs' => [], ], 'DescribeCodeRepositoryInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeCodeRepositoryOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeCompilationJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeCompilationJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeContextRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeContextResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDataQualityJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDataQualityJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDeviceFleetRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDeviceFleetResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDeviceRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDeviceResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDomainRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeDomainResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEdgeDeploymentPlanRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEdgeDeploymentPlanResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEdgePackagingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEdgePackagingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEndpointConfigInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEndpointConfigOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEndpointInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeEndpointOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeFeatureGroupRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeFeatureGroupResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeFeatureMetadataRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeFeatureMetadataResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeFlowDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeFlowDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHubContentRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHubContentResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHubRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHubResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHumanTaskUiRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHumanTaskUiResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHyperParameterTuningJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeHyperParameterTuningJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeImageRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeImageResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeImageVersionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeImageVersionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeInferenceExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeInferenceExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeInferenceRecommendationsJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeInferenceRecommendationsJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeLabelingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeLabelingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeLineageGroupRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeLineageGroupResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelBiasJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelBiasJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelCardExportJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelCardExportJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelCardRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelCardResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelExplainabilityJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelExplainabilityJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelPackageGroupInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelPackageGroupOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelPackageInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelPackageOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelQualityJobDefinitionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeModelQualityJobDefinitionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeMonitoringScheduleRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeMonitoringScheduleResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeNotebookInstanceInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeNotebookInstanceLifecycleConfigInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeNotebookInstanceLifecycleConfigOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeNotebookInstanceOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribePipelineDefinitionForExecutionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribePipelineDefinitionForExecutionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribePipelineExecutionRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribePipelineExecutionResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribePipelineRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribePipelineResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeProcessingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeProcessingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeProjectInput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeProjectOutput' => [ 'base' => NULL, 'refs' => [], ], 'DescribeSpaceRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeSpaceResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeStudioLifecycleConfigRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeStudioLifecycleConfigResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeSubscribedWorkteamRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeSubscribedWorkteamResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTrainingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTrainingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTransformJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTransformJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTrialComponentRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTrialComponentResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTrialRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeTrialResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeUserProfileRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeUserProfileResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeWorkforceRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeWorkforceResponse' => [ 'base' => NULL, 'refs' => [], ], 'DescribeWorkteamRequest' => [ 'base' => NULL, 'refs' => [], ], 'DescribeWorkteamResponse' => [ 'base' => NULL, 'refs' => [], ], 'Description' => [ 'base' => NULL, 'refs' => [ 'CreateFeatureGroupRequest$Description' => 'A free-form description of a FeatureGroup.
A free form description of the feature group.
', 'FeatureGroup$Description' => 'A free form description of a FeatureGroup.
Specifies weight and capacity values for a production variant.
', 'refs' => [ 'DesiredWeightAndCapacityList$member' => NULL, ], ], 'DesiredWeightAndCapacityList' => [ 'base' => NULL, 'refs' => [ 'UpdateEndpointWeightsAndCapacitiesInput$DesiredWeightsAndCapacities' => 'An object that provides new capacity and weight values for a variant.
', ], ], 'DestinationS3Uri' => [ 'base' => NULL, 'refs' => [ 'AsyncInferenceOutputConfig$S3OutputPath' => 'The Amazon S3 location to upload inference responses to.
', 'AsyncInferenceOutputConfig$S3FailurePath' => 'The Amazon S3 location to upload failure inference responses to.
', 'BatchTransformInput$DataCapturedDestinationS3Uri' => 'The Amazon S3 location being used to capture the data.
', 'DataCaptureConfig$DestinationS3Uri' => 'The Amazon S3 location used to capture the data.
', 'DataCaptureConfigSummary$DestinationS3Uri' => 'The Amazon S3 location being used to capture the data.
', 'InferenceExperimentDataStorageConfig$Destination' => 'The Amazon S3 bucket where the inference request and response data is stored.
', 'ProductionVariantCoreDumpConfig$DestinationS3Uri' => 'The Amazon S3 bucket to send the core dump to.
', ], ], 'DetailedAlgorithmStatus' => [ 'base' => NULL, 'refs' => [ 'AlgorithmStatusItem$Status' => 'The current status.
', ], ], 'DetailedModelPackageStatus' => [ 'base' => NULL, 'refs' => [ 'ModelPackageStatusItem$Status' => 'The current status.
', ], ], 'Device' => [ 'base' => 'Information of a particular device.
', 'refs' => [ 'Devices$member' => NULL, ], ], 'DeviceArn' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceResponse$DeviceArn' => 'The Amazon Resource Name (ARN) of the device.
', 'DeviceDeploymentSummary$DeviceArn' => 'The ARN of the device.
', 'DeviceSummary$DeviceArn' => 'Amazon Resource Name (ARN) of the device.
', ], ], 'DeviceDeploymentStatus' => [ 'base' => NULL, 'refs' => [ 'DeviceDeploymentSummary$DeviceDeploymentStatus' => 'The deployment status of the device.
', ], ], 'DeviceDeploymentSummaries' => [ 'base' => NULL, 'refs' => [ 'ListStageDevicesResponse$DeviceDeploymentSummaries' => 'List of summaries of devices allocated to the stage.
', ], ], 'DeviceDeploymentSummary' => [ 'base' => 'Contains information summarizing device details and deployment status.
', 'refs' => [ 'DeviceDeploymentSummaries$member' => NULL, ], ], 'DeviceDescription' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceResponse$Description' => 'A description of the device.
', 'Device$Description' => 'Description of the device.
', 'DeviceDeploymentSummary$Description' => 'The description of the device.
', 'DeviceSummary$Description' => 'A description of the device.
', ], ], 'DeviceFleetArn' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceFleetResponse$DeviceFleetArn' => 'The The Amazon Resource Name (ARN) of the fleet.
', 'DeviceFleetSummary$DeviceFleetArn' => 'Amazon Resource Name (ARN) of the device fleet.
', 'GetDeviceFleetReportResponse$DeviceFleetArn' => 'The Amazon Resource Name (ARN) of the device.
', ], ], 'DeviceFleetDescription' => [ 'base' => NULL, 'refs' => [ 'CreateDeviceFleetRequest$Description' => 'A description of the fleet.
', 'DescribeDeviceFleetResponse$Description' => 'A description of the fleet.
', 'GetDeviceFleetReportResponse$Description' => 'Description of the fleet.
', 'UpdateDeviceFleetRequest$Description' => 'Description of the fleet.
', ], ], 'DeviceFleetSummaries' => [ 'base' => NULL, 'refs' => [ 'ListDeviceFleetsResponse$DeviceFleetSummaries' => 'Summary of the device fleet.
', ], ], 'DeviceFleetSummary' => [ 'base' => 'Summary of the device fleet.
', 'refs' => [ 'DeviceFleetSummaries$member' => NULL, ], ], 'DeviceName' => [ 'base' => NULL, 'refs' => [ 'Device$DeviceName' => 'The name of the device.
', 'DeviceDeploymentSummary$DeviceName' => 'The name of the device.
', 'DeviceNames$member' => NULL, 'DeviceSelectionConfig$DeviceNameContains' => 'A filter to select devices with names containing this name.
', ], ], 'DeviceNames' => [ 'base' => NULL, 'refs' => [ 'DeregisterDevicesRequest$DeviceNames' => 'The unique IDs of the devices.
', 'DeviceSelectionConfig$DeviceNames' => 'List of devices chosen to deploy.
', ], ], 'DeviceSelectionConfig' => [ 'base' => 'Contains information about the configurations of selected devices.
', 'refs' => [ 'DeploymentStage$DeviceSelectionConfig' => 'Configuration of the devices in the stage.
', 'DeploymentStageStatusSummary$DeviceSelectionConfig' => 'Configuration of the devices in the stage.
', ], ], 'DeviceStats' => [ 'base' => 'Status of devices.
', 'refs' => [ 'GetDeviceFleetReportResponse$DeviceStats' => 'Status of devices.
', ], ], 'DeviceSubsetType' => [ 'base' => NULL, 'refs' => [ 'DeviceSelectionConfig$DeviceSubsetType' => 'Type of device subsets to deploy to the current stage.
', ], ], 'DeviceSummaries' => [ 'base' => NULL, 'refs' => [ 'ListDevicesResponse$DeviceSummaries' => 'Summary of devices.
', ], ], 'DeviceSummary' => [ 'base' => 'Summary of the device.
', 'refs' => [ 'DeviceSummaries$member' => NULL, ], ], 'Devices' => [ 'base' => NULL, 'refs' => [ 'RegisterDevicesRequest$Devices' => 'A list of devices to register with SageMaker Edge Manager.
', 'UpdateDevicesRequest$Devices' => 'List of devices to register with Edge Manager agent.
', ], ], 'Dimension' => [ 'base' => NULL, 'refs' => [ 'VectorConfig$Dimension' => 'The number of elements in your vector.
', ], ], 'DirectDeploySettings' => [ 'base' => 'The model deployment settings for the SageMaker Canvas application.
In order to enable model deployment for Canvas, the SageMaker Domain\'s or user profile\'s Amazon Web Services IAM execution role must have the AmazonSageMakerCanvasDirectDeployAccess policy attached. You can also turn on model deployment permissions through the SageMaker Domain\'s or user profile\'s settings in the SageMaker console.
The model deployment settings for the SageMaker Canvas application.
', ], ], 'DirectInternetAccess' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$DirectInternetAccess' => 'Sets whether SageMaker provides internet access to the notebook instance. If you set this to Disabled this notebook instance is able to access resources only in your VPC, and is not be able to connect to SageMaker training and endpoint services unless you configure a NAT Gateway in your VPC.
For more information, see Notebook Instances Are Internet-Enabled by Default. You can set the value of this parameter to Disabled only if you set a value for the SubnetId parameter.
Describes whether SageMaker provides internet access to the notebook instance. If this value is set to Disabled, the notebook instance does not have internet access, and cannot connect to SageMaker training and endpoint services.
For more information, see Notebook Instances Are Internet-Enabled by Default.
', ], ], 'Direction' => [ 'base' => NULL, 'refs' => [ 'QueryLineageRequest$Direction' => 'Associations between lineage entities have a direction. This parameter determines the direction from the StartArn(s) that the query traverses.
', ], ], 'DirectoryPath' => [ 'base' => NULL, 'refs' => [ 'CheckpointConfig$LocalPath' => '(Optional) The local directory where checkpoints are written. The default directory is /opt/ml/checkpoints/.
Path to local storage location for metrics and tensors. Defaults to /opt/ml/output/tensors/.
Path to local storage location for output of rules. Defaults to /opt/ml/processing/output/rule/.
The full path to the directory to associate with the channel.
', 'ProfilerRuleConfiguration$LocalPath' => 'Path to local storage location for output of rules. Defaults to /opt/ml/processing/output/rule/.
Path to local storage location for tensorBoard output. Defaults to /opt/ml/output/tensorboard.
Configuration to turn off Amazon SageMaker Debugger\'s system monitoring and profiling functionality. To turn it off, set to True.
To turn off Amazon SageMaker Debugger monitoring and profiling while a training job is in progress, set to True.
A list of names or URLs of the default Git repositories to remove from this notebook instance. This operation is idempotent. If you specify a Git repository that is not associated with the notebook instance when you call this method, it does not throw an error.
', ], ], 'DisassociateDefaultCodeRepository' => [ 'base' => NULL, 'refs' => [ 'UpdateNotebookInstanceInput$DisassociateDefaultCodeRepository' => 'The name or URL of the default Git repository to remove from this notebook instance. This operation is idempotent. If you specify a Git repository that is not associated with the notebook instance when you call this method, it does not throw an error.
', ], ], 'DisassociateNotebookInstanceAcceleratorTypes' => [ 'base' => NULL, 'refs' => [ 'UpdateNotebookInstanceInput$DisassociateAcceleratorTypes' => 'A list of the Elastic Inference (EI) instance types to remove from this notebook instance. This operation is idempotent. If you specify an accelerator type that is not associated with the notebook instance when you call this method, it does not throw an error.
', ], ], 'DisassociateNotebookInstanceLifecycleConfig' => [ 'base' => NULL, 'refs' => [ 'UpdateNotebookInstanceInput$DisassociateLifecycleConfig' => 'Set to true to remove the notebook instance lifecycle configuration currently associated with the notebook instance. This operation is idempotent. If you specify a lifecycle configuration that is not associated with the notebook instance when you call this method, it does not throw an error.
The document schema version for the hub content.
', 'HubContentInfo$DocumentSchemaVersion' => 'The version of the hub content document schema.
', 'ImportHubContentRequest$DocumentSchemaVersion' => 'The version of the hub content schema to import.
', 'ListHubContentVersionsRequest$MaxSchemaVersion' => 'The upper bound of the hub content schema version.
', 'ListHubContentsRequest$MaxSchemaVersion' => 'The upper bound of the hub content schema verion.
', ], ], 'Dollars' => [ 'base' => NULL, 'refs' => [ 'USD$Dollars' => 'The whole number of dollars in the amount.
', ], ], 'DomainArn' => [ 'base' => NULL, 'refs' => [ 'CreateDomainResponse$DomainArn' => 'The Amazon Resource Name (ARN) of the created domain.
', 'DescribeDomainResponse$DomainArn' => 'The domain\'s Amazon Resource Name (ARN).
', 'DomainDetails$DomainArn' => 'The domain\'s Amazon Resource Name (ARN).
', 'UpdateDomainResponse$DomainArn' => 'The Amazon Resource Name (ARN) of the domain.
', ], ], 'DomainDetails' => [ 'base' => 'The domain\'s details.
', 'refs' => [ 'DomainList$member' => NULL, ], ], 'DomainId' => [ 'base' => NULL, 'refs' => [ 'AppDetails$DomainId' => 'The domain ID.
', 'CreateAppRequest$DomainId' => 'The domain ID.
', 'CreatePresignedDomainUrlRequest$DomainId' => 'The domain ID.
', 'CreateSpaceRequest$DomainId' => 'The ID of the associated Domain.
', 'CreateUserProfileRequest$DomainId' => 'The ID of the associated Domain.
', 'DeleteAppRequest$DomainId' => 'The domain ID.
', 'DeleteDomainRequest$DomainId' => 'The domain ID.
', 'DeleteSpaceRequest$DomainId' => 'The ID of the associated Domain.
', 'DeleteUserProfileRequest$DomainId' => 'The domain ID.
', 'DescribeAppRequest$DomainId' => 'The domain ID.
', 'DescribeAppResponse$DomainId' => 'The domain ID.
', 'DescribeDomainRequest$DomainId' => 'The domain ID.
', 'DescribeDomainResponse$DomainId' => 'The domain ID.
', 'DescribeSpaceRequest$DomainId' => 'The ID of the associated Domain.
', 'DescribeSpaceResponse$DomainId' => 'The ID of the associated Domain.
', 'DescribeUserProfileRequest$DomainId' => 'The domain ID.
', 'DescribeUserProfileResponse$DomainId' => 'The ID of the domain that contains the profile.
', 'DomainDetails$DomainId' => 'The domain ID.
', 'ListAppsRequest$DomainIdEquals' => 'A parameter to search for the domain ID.
', 'ListSpacesRequest$DomainIdEquals' => 'A parameter to search for the Domain ID.
', 'ListUserProfilesRequest$DomainIdEquals' => 'A parameter by which to filter the results.
', 'SpaceDetails$DomainId' => 'The ID of the associated Domain.
', 'UpdateDomainRequest$DomainId' => 'The ID of the domain to be updated.
', 'UpdateSpaceRequest$DomainId' => 'The ID of the associated Domain.
', 'UpdateUserProfileRequest$DomainId' => 'The domain ID.
', 'UserProfileDetails$DomainId' => 'The domain ID.
', ], ], 'DomainList' => [ 'base' => NULL, 'refs' => [ 'ListDomainsResponse$Domains' => 'The list of domains.
', ], ], 'DomainName' => [ 'base' => NULL, 'refs' => [ 'CreateDomainRequest$DomainName' => 'A name for the domain.
', 'DescribeDomainResponse$DomainName' => 'The domain name.
', 'DomainDetails$DomainName' => 'The domain name.
', ], ], 'DomainSecurityGroupIds' => [ 'base' => NULL, 'refs' => [ 'DomainSettings$SecurityGroupIds' => 'The security groups for the Amazon Virtual Private Cloud that the Domain uses for communication between Domain-level apps and user apps.
The security groups for the Amazon Virtual Private Cloud that the Domain uses for communication between Domain-level apps and user apps.
A collection of settings that apply to the SageMaker Domain. These settings are specified through the CreateDomain API call.
A collection of Domain settings.
A collection of Domain settings.
A collection of Domain configuration settings to update.
A collection of DomainSettings configuration values to update.
The status.
', 'DomainDetails$Status' => 'The status.
', ], ], 'Double' => [ 'base' => NULL, 'refs' => [ 'TargetTrackingScalingPolicyConfiguration$TargetValue' => 'The recommended target value to specify for the metric when creating a scaling policy.
', ], ], 'DoubleParameterValue' => [ 'base' => NULL, 'refs' => [ 'TrialComponentParameterValue$NumberValue' => 'The numeric value of a numeric hyperparameter. If you specify a value for this parameter, you can\'t specify the StringValue parameter.
Represents the drift check baselines that can be used when the model monitor is set using the model package.
', 'refs' => [ 'CreateModelPackageInput$DriftCheckBaselines' => 'Represents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on Drift Detection against Previous Baselines in SageMaker Pipelines in the Amazon SageMaker Developer Guide.
', 'DescribeModelPackageOutput$DriftCheckBaselines' => 'Represents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on Drift Detection against Previous Baselines in SageMaker Pipelines in the Amazon SageMaker Developer Guide.
', 'ModelPackage$DriftCheckBaselines' => 'Represents the drift check baselines that can be used when the model monitor is set using the model package.
', ], ], 'DriftCheckBias' => [ 'base' => 'Represents the drift check bias baselines that can be used when the model monitor is set using the model package.
', 'refs' => [ 'DriftCheckBaselines$Bias' => 'Represents the drift check bias baselines that can be used when the model monitor is set using the model package.
', ], ], 'DriftCheckExplainability' => [ 'base' => 'Represents the drift check explainability baselines that can be used when the model monitor is set using the model package.
', 'refs' => [ 'DriftCheckBaselines$Explainability' => 'Represents the drift check explainability baselines that can be used when the model monitor is set using the model package.
', ], ], 'DriftCheckModelDataQuality' => [ 'base' => 'Represents the drift check data quality baselines that can be used when the model monitor is set using the model package.
', 'refs' => [ 'DriftCheckBaselines$ModelDataQuality' => 'Represents the drift check model data quality baselines that can be used when the model monitor is set using the model package.
', ], ], 'DriftCheckModelQuality' => [ 'base' => 'Represents the drift check model quality baselines that can be used when the model monitor is set using the model package.
', 'refs' => [ 'DriftCheckBaselines$ModelQuality' => 'Represents the drift check model quality baselines that can be used when the model monitor is set using the model package.
', ], ], 'DynamicScalingConfiguration' => [ 'base' => 'An object with the recommended values for you to specify when creating an autoscaling policy.
', 'refs' => [ 'GetScalingConfigurationRecommendationResponse$DynamicScalingConfiguration' => 'An object with the recommended values for you to specify when creating an autoscaling policy.
', ], ], 'EMRStepMetadata' => [ 'base' => 'The configurations and outcomes of an Amazon EMR step execution.
', 'refs' => [ 'PipelineExecutionStepMetadata$EMR' => 'The configurations and outcomes of an Amazon EMR step execution.
', ], ], 'Edge' => [ 'base' => 'A directed edge connecting two lineage entities.
', 'refs' => [ 'Edges$member' => NULL, ], ], 'EdgeDeploymentConfig' => [ 'base' => 'Contains information about the configuration of a deployment.
', 'refs' => [ 'DeploymentStage$DeploymentConfig' => 'Configuration of the deployment details.
', 'DeploymentStageStatusSummary$DeploymentConfig' => 'Configuration of the deployment details.
', ], ], 'EdgeDeploymentModelConfig' => [ 'base' => 'Contains information about the configuration of a model in a deployment.
', 'refs' => [ 'EdgeDeploymentModelConfigs$member' => NULL, ], ], 'EdgeDeploymentModelConfigs' => [ 'base' => NULL, 'refs' => [ 'CreateEdgeDeploymentPlanRequest$ModelConfigs' => 'List of models associated with the edge deployment plan.
', 'DescribeEdgeDeploymentPlanResponse$ModelConfigs' => 'List of models associated with the edge deployment plan.
', ], ], 'EdgeDeploymentPlanArn' => [ 'base' => NULL, 'refs' => [ 'CreateEdgeDeploymentPlanResponse$EdgeDeploymentPlanArn' => 'The ARN of the edge deployment plan.
', 'DescribeEdgeDeploymentPlanResponse$EdgeDeploymentPlanArn' => 'The ARN of edge deployment plan.
', 'DeviceDeploymentSummary$EdgeDeploymentPlanArn' => 'The ARN of the edge deployment plan.
', 'EdgeDeploymentPlanSummary$EdgeDeploymentPlanArn' => 'The ARN of the edge deployment plan.
', ], ], 'EdgeDeploymentPlanSummaries' => [ 'base' => NULL, 'refs' => [ 'ListEdgeDeploymentPlansResponse$EdgeDeploymentPlanSummaries' => 'List of summaries of edge deployment plans.
', ], ], 'EdgeDeploymentPlanSummary' => [ 'base' => 'Contains information summarizing an edge deployment plan.
', 'refs' => [ 'EdgeDeploymentPlanSummaries$member' => NULL, ], ], 'EdgeDeploymentStatus' => [ 'base' => 'Contains information summarizing the deployment stage results.
', 'refs' => [ 'DeploymentStageStatusSummary$DeploymentStatus' => 'General status of the current state.
', ], ], 'EdgeModel' => [ 'base' => 'The model on the edge device.
', 'refs' => [ 'EdgeModels$member' => NULL, ], ], 'EdgeModelStat' => [ 'base' => 'Status of edge devices with this model.
', 'refs' => [ 'EdgeModelStats$member' => NULL, ], ], 'EdgeModelStats' => [ 'base' => NULL, 'refs' => [ 'GetDeviceFleetReportResponse$ModelStats' => 'Status of model on device.
', ], ], 'EdgeModelSummaries' => [ 'base' => NULL, 'refs' => [ 'DeviceSummary$Models' => 'Models on the device.
', ], ], 'EdgeModelSummary' => [ 'base' => 'Summary of model on edge device.
', 'refs' => [ 'EdgeModelSummaries$member' => NULL, ], ], 'EdgeModels' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceResponse$Models' => 'Models on the device.
', ], ], 'EdgeOutputConfig' => [ 'base' => 'The output configuration.
', 'refs' => [ 'CreateDeviceFleetRequest$OutputConfig' => 'The output configuration for storing sample data collected by the fleet.
', 'CreateEdgePackagingJobRequest$OutputConfig' => 'Provides information about the output location for the packaged model.
', 'DescribeDeviceFleetResponse$OutputConfig' => 'The output configuration for storing sampled data.
', 'DescribeEdgePackagingJobResponse$OutputConfig' => 'The output configuration for the edge packaging job.
', 'GetDeviceFleetReportResponse$OutputConfig' => 'The output configuration for storing sample data collected by the fleet.
', 'UpdateDeviceFleetRequest$OutputConfig' => 'Output configuration for storing sample data collected by the fleet.
', ], ], 'EdgePackagingJobArn' => [ 'base' => NULL, 'refs' => [ 'DescribeEdgePackagingJobResponse$EdgePackagingJobArn' => 'The Amazon Resource Name (ARN) of the edge packaging job.
', 'EdgePackagingJobSummary$EdgePackagingJobArn' => 'The Amazon Resource Name (ARN) of the edge packaging job.
', ], ], 'EdgePackagingJobStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeEdgePackagingJobResponse$EdgePackagingJobStatus' => 'The current status of the packaging job.
', 'EdgePackagingJobSummary$EdgePackagingJobStatus' => 'The status of the edge packaging job.
', 'ListEdgePackagingJobsRequest$StatusEquals' => 'The job status to filter for.
', ], ], 'EdgePackagingJobSummaries' => [ 'base' => NULL, 'refs' => [ 'ListEdgePackagingJobsResponse$EdgePackagingJobSummaries' => 'Summaries of edge packaging jobs.
', ], ], 'EdgePackagingJobSummary' => [ 'base' => 'Summary of edge packaging job.
', 'refs' => [ 'EdgePackagingJobSummaries$member' => NULL, ], ], 'EdgePresetDeploymentArtifact' => [ 'base' => NULL, 'refs' => [ 'EdgePresetDeploymentOutput$Artifact' => 'The Amazon Resource Name (ARN) of the generated deployable resource.
', ], ], 'EdgePresetDeploymentOutput' => [ 'base' => 'The output of a SageMaker Edge Manager deployable resource.
', 'refs' => [ 'DescribeEdgePackagingJobResponse$PresetDeploymentOutput' => 'The output of a SageMaker Edge Manager deployable resource.
', ], ], 'EdgePresetDeploymentStatus' => [ 'base' => NULL, 'refs' => [ 'EdgePresetDeploymentOutput$Status' => 'The status of the deployable resource.
', ], ], 'EdgePresetDeploymentType' => [ 'base' => NULL, 'refs' => [ 'EdgeOutputConfig$PresetDeploymentType' => 'The deployment type SageMaker Edge Manager will create. Currently only supports Amazon Web Services IoT Greengrass Version 2 components.
', 'EdgePresetDeploymentOutput$Type' => 'The deployment type created by SageMaker Edge Manager. Currently only supports Amazon Web Services IoT Greengrass Version 2 components.
', ], ], 'EdgeVersion' => [ 'base' => NULL, 'refs' => [ 'AgentVersion$Version' => 'Version of the agent.
', 'CreateEdgePackagingJobRequest$ModelVersion' => 'The version of the model.
', 'DescribeDeviceResponse$AgentVersion' => 'Edge Manager agent version.
', 'DescribeEdgePackagingJobResponse$ModelVersion' => 'The version of the model.
', 'DeviceSummary$AgentVersion' => 'Edge Manager agent version.
', 'EdgeModel$ModelVersion' => 'The model version.
', 'EdgeModelStat$ModelVersion' => 'The model version.
', 'EdgeModelSummary$ModelVersion' => 'The version model.
', 'EdgePackagingJobSummary$ModelVersion' => 'The version of the model.
', ], ], 'Edges' => [ 'base' => NULL, 'refs' => [ 'QueryLineageResponse$Edges' => 'A list of edges that connect vertices in the response.
', ], ], 'EfsUid' => [ 'base' => NULL, 'refs' => [ 'DescribeSpaceResponse$HomeEfsFileSystemUid' => 'The ID of the space\'s profile in the Amazon Elastic File System volume.
', 'DescribeUserProfileResponse$HomeEfsFileSystemUid' => 'The ID of the user\'s profile in the Amazon Elastic File System (EFS) volume.
', ], ], 'EnableCapture' => [ 'base' => NULL, 'refs' => [ 'DataCaptureConfig$EnableCapture' => 'Whether data capture should be enabled or disabled (defaults to enabled).
', 'DataCaptureConfigSummary$EnableCapture' => 'Whether data capture is enabled or disabled.
', ], ], 'EnableIotRoleAlias' => [ 'base' => NULL, 'refs' => [ 'CreateDeviceFleetRequest$EnableIotRoleAlias' => 'Whether to create an Amazon Web Services IoT Role Alias during device fleet creation. The name of the role alias generated will match this pattern: "SageMakerEdge-{DeviceFleetName}".
For example, if your device fleet is called "demo-fleet", the name of the role alias will be "SageMakerEdge-demo-fleet".
', 'UpdateDeviceFleetRequest$EnableIotRoleAlias' => 'Whether to create an Amazon Web Services IoT Role Alias during device fleet creation. The name of the role alias generated will match this pattern: "SageMakerEdge-{DeviceFleetName}".
For example, if your device fleet is called "demo-fleet", the name of the role alias will be "SageMakerEdge-demo-fleet".
', ], ], 'EnableSagemakerServicecatalogPortfolioInput' => [ 'base' => NULL, 'refs' => [], ], 'EnableSagemakerServicecatalogPortfolioOutput' => [ 'base' => NULL, 'refs' => [], ], 'Endpoint' => [ 'base' => 'A hosted endpoint for real-time inference.
', 'refs' => [ 'SearchRecord$Endpoint' => NULL, ], ], 'EndpointArn' => [ 'base' => NULL, 'refs' => [ 'CreateEndpointOutput$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint.
', 'DescribeEndpointOutput$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint.
', 'Endpoint$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint.
', 'EndpointSummary$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint.
', 'ModelDashboardEndpoint$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint.
', 'UpdateEndpointOutput$EndpointArn' => 'The Amazon Resource Name (ARN) of the endpoint.
', 'UpdateEndpointWeightsAndCapacitiesOutput$EndpointArn' => 'The Amazon Resource Name (ARN) of the updated endpoint.
', ], ], 'EndpointConfigArn' => [ 'base' => NULL, 'refs' => [ 'CreateEndpointConfigOutput$EndpointConfigArn' => 'The Amazon Resource Name (ARN) of the endpoint configuration.
', 'DescribeEndpointConfigOutput$EndpointConfigArn' => 'The Amazon Resource Name (ARN) of the endpoint configuration.
', 'EndpointConfigSummary$EndpointConfigArn' => 'The Amazon Resource Name (ARN) of the endpoint configuration.
', ], ], 'EndpointConfigName' => [ 'base' => NULL, 'refs' => [ 'CreateEndpointConfigInput$EndpointConfigName' => 'The name of the endpoint configuration. You specify this name in a CreateEndpoint request.
', 'CreateEndpointInput$EndpointConfigName' => 'The name of an endpoint configuration. For more information, see CreateEndpointConfig.
', 'DeleteEndpointConfigInput$EndpointConfigName' => 'The name of the endpoint configuration that you want to delete.
', 'DescribeEndpointConfigInput$EndpointConfigName' => 'The name of the endpoint configuration.
', 'DescribeEndpointConfigOutput$EndpointConfigName' => 'Name of the SageMaker endpoint configuration.
', 'DescribeEndpointOutput$EndpointConfigName' => 'The name of the endpoint configuration associated with this endpoint.
', 'Endpoint$EndpointConfigName' => 'The endpoint configuration associated with the endpoint.
', 'EndpointConfigSummary$EndpointConfigName' => 'The name of the endpoint configuration.
', 'EndpointMetadata$EndpointConfigName' => 'The name of the endpoint configuration.
', 'PendingDeploymentSummary$EndpointConfigName' => 'The name of the endpoint configuration used in the deployment.
', 'UpdateEndpointInput$EndpointConfigName' => 'The name of the new endpoint configuration.
', ], ], 'EndpointConfigNameContains' => [ 'base' => NULL, 'refs' => [ 'ListEndpointConfigsInput$NameContains' => 'A string in the endpoint configuration name. This filter returns only endpoint configurations whose name contains the specified string.
', ], ], 'EndpointConfigSortKey' => [ 'base' => NULL, 'refs' => [ 'ListEndpointConfigsInput$SortBy' => 'The field to sort results by. The default is CreationTime.
Provides summary information for an endpoint configuration.
', 'refs' => [ 'EndpointConfigSummaryList$member' => NULL, ], ], 'EndpointConfigSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListEndpointConfigsOutput$EndpointConfigs' => 'An array of endpoint configurations.
', ], ], 'EndpointInfo' => [ 'base' => 'Details about a customer endpoint that was compared in an Inference Recommender job.
', 'refs' => [ 'EndpointPerformance$EndpointInfo' => NULL, 'Endpoints$member' => NULL, ], ], 'EndpointInput' => [ 'base' => 'Input object for the endpoint
', 'refs' => [ 'DataQualityJobInput$EndpointInput' => NULL, 'ModelBiasJobInput$EndpointInput' => NULL, 'ModelExplainabilityJobInput$EndpointInput' => NULL, 'ModelQualityJobInput$EndpointInput' => NULL, 'MonitoringInput$EndpointInput' => 'The endpoint for a monitoring job.
', ], ], 'EndpointInputConfiguration' => [ 'base' => 'The endpoint configuration for the load test.
', 'refs' => [ 'EndpointInputConfigurations$member' => NULL, ], ], 'EndpointInputConfigurations' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobInputConfig$EndpointConfigurations' => 'Specifies the endpoint configuration to use for a job.
', ], ], 'EndpointMetadata' => [ 'base' => 'The metadata of the endpoint.
', 'refs' => [ 'DescribeInferenceExperimentResponse$EndpointMetadata' => 'The metadata of the endpoint on which the inference experiment ran.
', ], ], 'EndpointName' => [ 'base' => NULL, 'refs' => [ 'CreateEndpointInput$EndpointName' => 'The name of the endpoint.The name must be unique within an Amazon Web Services Region in your Amazon Web Services account. The name is case-insensitive in CreateEndpoint, but the case is preserved and must be matched in InvokeEndpoint.
The name of the Amazon SageMaker endpoint on which you want to run the inference experiment.
', 'DeleteEndpointInput$EndpointName' => 'The name of the endpoint that you want to delete.
', 'DescribeEndpointInput$EndpointName' => 'The name of the endpoint.
', 'DescribeEndpointOutput$EndpointName' => 'Name of the endpoint.
', 'DescribeMonitoringScheduleResponse$EndpointName' => 'The name of the endpoint for the monitoring job.
', 'Endpoint$EndpointName' => 'The name of the endpoint.
', 'EndpointInfo$EndpointName' => 'The name of a customer\'s endpoint.
', 'EndpointInput$EndpointName' => 'An endpoint in customer\'s account which has enabled DataCaptureConfig enabled.
The name of the endpoint.
', 'EndpointSummary$EndpointName' => 'The name of the endpoint.
', 'GetScalingConfigurationRecommendationRequest$EndpointName' => 'The name of an endpoint benchmarked during a previously completed inference recommendation job. This name should come from one of the recommendations returned by the job specified in the InferenceRecommendationsJobName field.
Specify either this field or the RecommendationId field.
The name of an endpoint benchmarked during a previously completed Inference Recommender job.
', 'ListDataQualityJobDefinitionsRequest$EndpointName' => 'A filter that lists the data quality job definitions associated with the specified endpoint.
', 'ListModelBiasJobDefinitionsRequest$EndpointName' => 'Name of the endpoint to monitor for model bias.
', 'ListModelExplainabilityJobDefinitionsRequest$EndpointName' => 'Name of the endpoint to monitor for model explainability.
', 'ListModelQualityJobDefinitionsRequest$EndpointName' => 'A filter that returns only model quality monitoring job definitions that are associated with the specified endpoint.
', 'ListMonitoringExecutionsRequest$EndpointName' => 'Name of a specific endpoint to fetch jobs for.
', 'ListMonitoringSchedulesRequest$EndpointName' => 'Name of a specific endpoint to fetch schedules for.
', 'ModelDashboardEndpoint$EndpointName' => 'The endpoint name.
', 'ModelDashboardMonitoringSchedule$EndpointName' => 'The endpoint which is monitored.
', 'ModelDeployConfig$EndpointName' => 'Specifies the endpoint name to use for a one-click Autopilot model deployment if the endpoint name is not generated automatically.
Specify the EndpointName if and only if you set AutoGenerateEndpointName to False; otherwise a 400 error is thrown.
The name of the endpoint to which the model has been deployed.
If model deployment fails, this field is omitted from the response.
The name of the endpoint used to run the monitoring job.
', 'MonitoringJobDefinitionSummary$EndpointName' => 'The name of the endpoint that the job monitors.
', 'MonitoringSchedule$EndpointName' => 'The endpoint that hosts the model being monitored.
', 'MonitoringScheduleSummary$EndpointName' => 'The name of the endpoint using the monitoring schedule.
', 'UpdateEndpointInput$EndpointName' => 'The name of the endpoint whose configuration you want to update.
', 'UpdateEndpointWeightsAndCapacitiesInput$EndpointName' => 'The name of an existing SageMaker endpoint.
', ], ], 'EndpointNameContains' => [ 'base' => NULL, 'refs' => [ 'ListEndpointsInput$NameContains' => 'A string in endpoint names. This filter returns only endpoints whose name contains the specified string.
', ], ], 'EndpointOutputConfiguration' => [ 'base' => 'The endpoint configuration made by Inference Recommender during a recommendation job.
', 'refs' => [ 'InferenceRecommendation$EndpointConfiguration' => 'Defines the endpoint configuration parameters.
', 'RecommendationJobInferenceBenchmark$EndpointConfiguration' => NULL, ], ], 'EndpointPerformance' => [ 'base' => 'The performance results from running an Inference Recommender job on an existing endpoint.
', 'refs' => [ 'EndpointPerformances$member' => NULL, ], ], 'EndpointPerformances' => [ 'base' => NULL, 'refs' => [ 'DescribeInferenceRecommendationsJobResponse$EndpointPerformances' => 'The performance results from running an Inference Recommender job on an existing endpoint.
', ], ], 'EndpointSortKey' => [ 'base' => NULL, 'refs' => [ 'ListEndpointsInput$SortBy' => 'Sorts the list of results. The default is CreationTime.
The status of the endpoint.
OutOfService: Endpoint is not available to take incoming requests.
Creating: CreateEndpoint is executing.
Updating: UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing.
SystemUpdating: Endpoint is undergoing maintenance and cannot be updated or deleted or re-scaled until it has completed. This maintenance operation does not change any customer-specified values such as VPC config, KMS encryption, model, instance type, or instance count.
RollingBack: Endpoint fails to scale up or down or change its variant weight and is in the process of rolling back to its previous configuration. Once the rollback completes, endpoint returns to an InService status. This transitional status only applies to an endpoint that has autoscaling enabled and is undergoing variant weight or capacity changes as part of an UpdateEndpointWeightsAndCapacities call or when the UpdateEndpointWeightsAndCapacities operation is called explicitly.
InService: Endpoint is available to process incoming requests.
Deleting: DeleteEndpoint is executing.
Failed: Endpoint could not be created, updated, or re-scaled. Use the FailureReason value returned by DescribeEndpoint for information about the failure. DeleteEndpoint is the only operation that can be performed on a failed endpoint.
UpdateRollbackFailed: Both the rolling deployment and auto-rollback failed. Your endpoint is in service with a mix of the old and new endpoint configurations. For information about how to remedy this issue and restore the endpoint\'s status to InService, see Rolling Deployments.
The status of the endpoint.
', 'EndpointMetadata$EndpointStatus' => 'The status of the endpoint. For possible values of the status of an endpoint, see EndpointSummary.
', 'EndpointSummary$EndpointStatus' => 'The status of the endpoint.
OutOfService: Endpoint is not available to take incoming requests.
Creating: CreateEndpoint is executing.
Updating: UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing.
SystemUpdating: Endpoint is undergoing maintenance and cannot be updated or deleted or re-scaled until it has completed. This maintenance operation does not change any customer-specified values such as VPC config, KMS encryption, model, instance type, or instance count.
RollingBack: Endpoint fails to scale up or down or change its variant weight and is in the process of rolling back to its previous configuration. Once the rollback completes, endpoint returns to an InService status. This transitional status only applies to an endpoint that has autoscaling enabled and is undergoing variant weight or capacity changes as part of an UpdateEndpointWeightsAndCapacities call or when the UpdateEndpointWeightsAndCapacities operation is called explicitly.
InService: Endpoint is available to process incoming requests.
Deleting: DeleteEndpoint is executing.
Failed: Endpoint could not be created, updated, or re-scaled. Use DescribeEndpointOutput$FailureReason for information about the failure. DeleteEndpoint is the only operation that can be performed on a failed endpoint.
To get a list of endpoints with a specified status, use the StatusEquals filter with a call to ListEndpoints.
A filter that returns only endpoints with the specified status.
', 'ModelDashboardEndpoint$EndpointStatus' => 'The endpoint status.
', ], ], 'EndpointSummary' => [ 'base' => 'Provides summary information for an endpoint.
', 'refs' => [ 'EndpointSummaryList$member' => NULL, ], ], 'EndpointSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListEndpointsOutput$Endpoints' => 'An array or endpoint objects.
', ], ], 'Endpoints' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobInputConfig$Endpoints' => 'Existing customer endpoints on which to run an Inference Recommender job.
', ], ], 'EntityDescription' => [ 'base' => NULL, 'refs' => [ 'AdditionalInferenceSpecificationDefinition$Description' => 'A description of the additional Inference specification
', 'AlgorithmSummary$AlgorithmDescription' => 'A brief description of the algorithm.
', 'BatchDescribeModelPackageSummary$ModelPackageDescription' => 'The description of the model package.
', 'ChannelSpecification$Description' => 'A brief description of the channel.
', 'CreateAlgorithmInput$AlgorithmDescription' => 'A description of the algorithm.
', 'CreateModelPackageGroupInput$ModelPackageGroupDescription' => 'A description for the model group.
', 'CreateModelPackageInput$ModelPackageDescription' => 'A description of the model package.
', 'CreateProjectInput$ProjectDescription' => 'A description for the project.
', 'DescribeAlgorithmOutput$AlgorithmDescription' => 'A brief summary about the algorithm.
', 'DescribeModelPackageGroupOutput$ModelPackageGroupDescription' => 'A description of the model group.
', 'DescribeModelPackageOutput$ModelPackageDescription' => 'A brief summary of the model package.
', 'DescribeProjectOutput$ProjectDescription' => 'The description of the project.
', 'HyperParameterSpecification$Description' => 'A brief description of the hyperparameter.
', 'ModelPackage$ModelPackageDescription' => 'The description of the model package.
', 'ModelPackageGroup$ModelPackageGroupDescription' => 'The description for the model group.
', 'ModelPackageGroupSummary$ModelPackageGroupDescription' => 'A description of the model group.
', 'ModelPackageSummary$ModelPackageDescription' => 'A brief description of the model package.
', 'Project$ProjectDescription' => 'The description of the project.
', 'ProjectSummary$ProjectDescription' => 'The description of the project.
', 'UpdateProjectInput$ProjectDescription' => 'The description for the project.
', ], ], 'EntityName' => [ 'base' => NULL, 'refs' => [ 'AdditionalInferenceSpecificationDefinition$Name' => 'A unique name to identify the additional inference specification. The name must be unique within the list of your additional inference specifications for a particular model package.
', 'AlgorithmStatusItem$Name' => 'The name of the algorithm for which the overall status is being reported.
', 'AlgorithmSummary$AlgorithmName' => 'The name of the algorithm that is described by the summary.
', 'AlgorithmValidationProfile$ProfileName' => 'The name of the profile for the algorithm. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
', 'BatchDescribeModelPackageSummary$ModelPackageGroupName' => 'The group name for the model package
', 'CodeRepositorySummary$CodeRepositoryName' => 'The name of the Git repository.
', 'CompilationJobSummary$CompilationJobName' => 'The name of the model compilation job that you want a summary for.
', 'CreateAlgorithmInput$AlgorithmName' => 'The name of the algorithm.
', 'CreateCodeRepositoryInput$CodeRepositoryName' => 'The name of the Git repository. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
', 'CreateCompilationJobRequest$CompilationJobName' => 'A name for the model compilation job. The name must be unique within the Amazon Web Services Region and within your Amazon Web Services account.
', 'CreateDeviceFleetRequest$DeviceFleetName' => 'The name of the fleet that the device belongs to.
', 'CreateEdgeDeploymentPlanRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan.
', 'CreateEdgeDeploymentPlanRequest$DeviceFleetName' => 'The device fleet used for this edge deployment plan.
', 'CreateEdgeDeploymentStageRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan.
', 'CreateEdgePackagingJobRequest$EdgePackagingJobName' => 'The name of the edge packaging job.
', 'CreateEdgePackagingJobRequest$CompilationJobName' => 'The name of the SageMaker Neo compilation job that will be used to locate model artifacts for packaging.
', 'CreateEdgePackagingJobRequest$ModelName' => 'The name of the model.
', 'CreateModelCardExportJobRequest$ModelCardExportJobName' => 'The name of the model card export job.
', 'CreateModelCardRequest$ModelCardName' => 'The unique name of the model card.
', 'CreateModelPackageGroupInput$ModelPackageGroupName' => 'The name of the model group.
', 'CreateModelPackageInput$ModelPackageName' => 'The name of the model package. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
This parameter is required for unversioned models. It is not applicable to versioned models.
', 'DeleteAlgorithmInput$AlgorithmName' => 'The name of the algorithm to delete.
', 'DeleteCodeRepositoryInput$CodeRepositoryName' => 'The name of the Git repository to delete.
', 'DeleteDeviceFleetRequest$DeviceFleetName' => 'The name of the fleet to delete.
', 'DeleteEdgeDeploymentPlanRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan to delete.
', 'DeleteEdgeDeploymentStageRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan from which the stage will be deleted.
', 'DeleteEdgeDeploymentStageRequest$StageName' => 'The name of the stage.
', 'DeleteModelCardRequest$ModelCardName' => 'The name of the model card to delete.
', 'DeleteModelPackageGroupPolicyInput$ModelPackageGroupName' => 'The name of the model group for which to delete the policy.
', 'DeploymentStage$StageName' => 'The name of the stage.
', 'DeploymentStageStatusSummary$StageName' => 'The name of the stage.
', 'DeregisterDevicesRequest$DeviceFleetName' => 'The name of the fleet the devices belong to.
', 'DescribeAlgorithmOutput$AlgorithmName' => 'The name of the algorithm being described.
', 'DescribeCodeRepositoryInput$CodeRepositoryName' => 'The name of the Git repository to describe.
', 'DescribeCodeRepositoryOutput$CodeRepositoryName' => 'The name of the Git repository.
', 'DescribeCompilationJobRequest$CompilationJobName' => 'The name of the model compilation job that you want information about.
', 'DescribeCompilationJobResponse$CompilationJobName' => 'The name of the model compilation job.
', 'DescribeDeviceFleetRequest$DeviceFleetName' => 'The name of the fleet.
', 'DescribeDeviceFleetResponse$DeviceFleetName' => 'The name of the fleet.
', 'DescribeDeviceRequest$DeviceName' => 'The unique ID of the device.
', 'DescribeDeviceRequest$DeviceFleetName' => 'The name of the fleet the devices belong to.
', 'DescribeDeviceResponse$DeviceName' => 'The unique identifier of the device.
', 'DescribeDeviceResponse$DeviceFleetName' => 'The name of the fleet the device belongs to.
', 'DescribeEdgeDeploymentPlanRequest$EdgeDeploymentPlanName' => 'The name of the deployment plan to describe.
', 'DescribeEdgeDeploymentPlanResponse$EdgeDeploymentPlanName' => 'The name of the edge deployment plan.
', 'DescribeEdgeDeploymentPlanResponse$DeviceFleetName' => 'The device fleet used for this edge deployment plan.
', 'DescribeEdgePackagingJobRequest$EdgePackagingJobName' => 'The name of the edge packaging job.
', 'DescribeEdgePackagingJobResponse$EdgePackagingJobName' => 'The name of the edge packaging job.
', 'DescribeEdgePackagingJobResponse$CompilationJobName' => 'The name of the SageMaker Neo compilation job that is used to locate model artifacts that are being packaged.
', 'DescribeEdgePackagingJobResponse$ModelName' => 'The name of the model.
', 'DescribeModelCardExportJobResponse$ModelCardExportJobName' => 'The name of the model card export job to describe.
', 'DescribeModelCardExportJobResponse$ModelCardName' => 'The name or Amazon Resource Name (ARN) of the model card that the model export job exports.
', 'DescribeModelCardResponse$ModelCardName' => 'The name of the model card.
', 'DescribeModelPackageGroupOutput$ModelPackageGroupName' => 'The name of the model group.
', 'DescribeModelPackageOutput$ModelPackageName' => 'The name of the model package being described.
', 'DescribeModelPackageOutput$ModelPackageGroupName' => 'If the model is a versioned model, the name of the model group that the versioned model belongs to.
', 'DeviceDeploymentSummary$EdgeDeploymentPlanName' => 'The name of the edge deployment plan.
', 'DeviceDeploymentSummary$StageName' => 'The name of the stage in the edge deployment plan.
', 'DeviceDeploymentSummary$DeployedStageName' => 'The name of the deployed stage.
', 'DeviceDeploymentSummary$DeviceFleetName' => 'The name of the fleet to which the device belongs to.
', 'DeviceFleetSummary$DeviceFleetName' => 'Name of the device fleet.
', 'DeviceSummary$DeviceName' => 'The unique identifier of the device.
', 'DeviceSummary$DeviceFleetName' => 'The name of the fleet the device belongs to.
', 'EdgeDeploymentModelConfig$ModelHandle' => 'The name the device application uses to reference this model.
', 'EdgeDeploymentModelConfig$EdgePackagingJobName' => 'The edge packaging job associated with this deployment.
', 'EdgeDeploymentPlanSummary$EdgeDeploymentPlanName' => 'The name of the edge deployment plan.
', 'EdgeDeploymentPlanSummary$DeviceFleetName' => 'The name of the device fleet used for the deployment.
', 'EdgeModel$ModelName' => 'The name of the model.
', 'EdgeModelStat$ModelName' => 'The name of the model.
', 'EdgeModelSummary$ModelName' => 'The name of the model.
', 'EdgePackagingJobSummary$EdgePackagingJobName' => 'The name of the edge packaging job.
', 'EdgePackagingJobSummary$CompilationJobName' => 'The name of the SageMaker Neo compilation job.
', 'EdgePackagingJobSummary$ModelName' => 'The name of the model.
', 'GetDeviceFleetReportRequest$DeviceFleetName' => 'The name of the fleet.
', 'GetDeviceFleetReportResponse$DeviceFleetName' => 'The name of the fleet.
', 'GetModelPackageGroupPolicyInput$ModelPackageGroupName' => 'The name of the model group for which to get the resource policy.
', 'ListDevicesRequest$ModelName' => 'A filter that searches devices that contains this name in any of their models.
', 'ListDevicesRequest$DeviceFleetName' => 'Filter for fleets containing this name in their device fleet name.
', 'ListModelCardExportJobsRequest$ModelCardName' => 'List export jobs for the model card with the specified name.
', 'ListModelCardExportJobsRequest$ModelCardExportJobNameContains' => 'Only list model card export jobs with names that contain the specified string.
', 'ListModelCardsRequest$NameContains' => 'Only list model cards with names that contain the specified string.
', 'ListStageDevicesRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan.
', 'ListStageDevicesRequest$StageName' => 'The name of the stage in the deployment.
', 'ModelCard$ModelCardName' => 'The unique name of the model card.
', 'ModelCardExportJobSummary$ModelCardExportJobName' => 'The name of the model card export job.
', 'ModelCardExportJobSummary$ModelCardName' => 'The name of the model card that the export job exports.
', 'ModelCardSummary$ModelCardName' => 'The name of the model card.
', 'ModelCardVersionSummary$ModelCardName' => 'The name of the model card.
', 'ModelDashboardModelCard$ModelCardName' => 'The name of a model card.
', 'ModelPackage$ModelPackageName' => 'The name of the model.
', 'ModelPackage$ModelPackageGroupName' => 'The model group to which the model belongs.
', 'ModelPackageGroup$ModelPackageGroupName' => 'The name of the model group.
', 'ModelPackageGroupSummary$ModelPackageGroupName' => 'The name of the model group.
', 'ModelPackageStatusItem$Name' => 'The name of the model package for which the overall status is being reported.
', 'ModelPackageSummary$ModelPackageName' => 'The name of the model package.
', 'ModelPackageSummary$ModelPackageGroupName' => 'If the model package is a versioned model, the model group that the versioned model belongs to.
', 'ModelPackageValidationProfile$ProfileName' => 'The name of the profile for the model package.
', 'PutModelPackageGroupPolicyInput$ModelPackageGroupName' => 'The name of the model group to add a resource policy to.
', 'RegisterDevicesRequest$DeviceFleetName' => 'The name of the fleet.
', 'StartEdgeDeploymentStageRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan to start.
', 'StartEdgeDeploymentStageRequest$StageName' => 'The name of the stage to start.
', 'StopCompilationJobRequest$CompilationJobName' => 'The name of the model compilation job to stop.
', 'StopEdgeDeploymentStageRequest$EdgeDeploymentPlanName' => 'The name of the edge deployment plan to stop.
', 'StopEdgeDeploymentStageRequest$StageName' => 'The name of the stage to stop.
', 'StopEdgePackagingJobRequest$EdgePackagingJobName' => 'The name of the edge packaging job.
', 'UpdateCodeRepositoryInput$CodeRepositoryName' => 'The name of the Git repository to update.
', 'UpdateDeviceFleetRequest$DeviceFleetName' => 'The name of the fleet.
', 'UpdateDevicesRequest$DeviceFleetName' => 'The name of the fleet the devices belong to.
', ], ], 'EnvironmentKey' => [ 'base' => NULL, 'refs' => [ 'EnvironmentMap$key' => NULL, ], ], 'EnvironmentMap' => [ 'base' => NULL, 'refs' => [ 'AutoMLContainerDefinition$Environment' => 'The environment variables to set in the container. For more information, see ContainerDefinition.
', 'ContainerDefinition$Environment' => 'The environment variables to set in the Docker container. Each key and value in the Environment string to string map can have length of up to 1024. We support up to 16 entries in the map.
The environment variables to set in the Docker container. Each key and value in the Environment string to string map can have length of up to 1024. We support up to 16 entries in the map.
The recommended environment variables to set in the model container for Real-Time Inference.
', ], ], 'EnvironmentParameter' => [ 'base' => 'A list of environment parameters suggested by the Amazon SageMaker Inference Recommender.
', 'refs' => [ 'EnvironmentParameters$member' => NULL, ], ], 'EnvironmentParameterRanges' => [ 'base' => 'Specifies the range of environment parameters
', 'refs' => [ 'EndpointInputConfiguration$EnvironmentParameterRanges' => 'The parameter you want to benchmark against.
', ], ], 'EnvironmentParameters' => [ 'base' => NULL, 'refs' => [ 'ModelConfiguration$EnvironmentParameters' => 'Defines the environment parameters that includes key, value types, and values.
', ], ], 'EnvironmentValue' => [ 'base' => NULL, 'refs' => [ 'EnvironmentMap$value' => NULL, ], ], 'ExcludeFeaturesAttribute' => [ 'base' => NULL, 'refs' => [ 'BatchTransformInput$ExcludeFeaturesAttribute' => 'The attributes of the input data to exclude from the analysis.
', 'EndpointInput$ExcludeFeaturesAttribute' => 'The attributes of the input data to exclude from the analysis.
', ], ], 'ExecutionRoleIdentityConfig' => [ 'base' => NULL, 'refs' => [ 'DomainSettings$ExecutionRoleIdentityConfig' => 'The configuration for attaching a SageMaker user profile name to the execution role as a sts:SourceIdentity key.
', 'DomainSettingsForUpdate$ExecutionRoleIdentityConfig' => 'The configuration for attaching a SageMaker user profile name to the execution role as a sts:SourceIdentity key. This configuration can only be modified if there are no apps in the InService or Pending state.
A filter that retrieves only jobs with a specific status.
', 'MonitoringExecutionSummary$MonitoringExecutionStatus' => 'The status of the monitoring job.
', ], ], 'ExitMessage' => [ 'base' => NULL, 'refs' => [ 'DescribeProcessingJobResponse$ExitMessage' => 'An optional string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
', 'ProcessingJob$ExitMessage' => 'A string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
', 'ProcessingJobSummary$ExitMessage' => 'An optional string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
', ], ], 'Experiment' => [ 'base' => 'The properties of an experiment as returned by the Search API.
', 'refs' => [ 'SearchRecord$Experiment' => 'The properties of an experiment.
', ], ], 'ExperimentArn' => [ 'base' => NULL, 'refs' => [ 'CreateExperimentResponse$ExperimentArn' => 'The Amazon Resource Name (ARN) of the experiment.
', 'DeleteExperimentResponse$ExperimentArn' => 'The Amazon Resource Name (ARN) of the experiment that is being deleted.
', 'DescribeExperimentResponse$ExperimentArn' => 'The Amazon Resource Name (ARN) of the experiment.
', 'Experiment$ExperimentArn' => 'The Amazon Resource Name (ARN) of the experiment.
', 'ExperimentSummary$ExperimentArn' => 'The Amazon Resource Name (ARN) of the experiment.
', 'UpdateExperimentResponse$ExperimentArn' => 'The Amazon Resource Name (ARN) of the experiment.
', ], ], 'ExperimentConfig' => [ 'base' => 'Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
', 'refs' => [ 'CreateProcessingJobRequest$ExperimentConfig' => NULL, 'CreateTrainingJobRequest$ExperimentConfig' => NULL, 'CreateTransformJobRequest$ExperimentConfig' => NULL, 'DescribeProcessingJobResponse$ExperimentConfig' => 'The configuration information used to create an experiment.
', 'DescribeTrainingJobResponse$ExperimentConfig' => NULL, 'DescribeTransformJobResponse$ExperimentConfig' => NULL, 'ProcessingJob$ExperimentConfig' => NULL, 'TrainingJob$ExperimentConfig' => NULL, 'TransformJob$ExperimentConfig' => NULL, ], ], 'ExperimentDescription' => [ 'base' => NULL, 'refs' => [ 'CreateActionRequest$Description' => 'The description of the action.
', 'CreateContextRequest$Description' => 'The description of the context.
', 'CreateExperimentRequest$Description' => 'The description of the experiment.
', 'DescribeActionResponse$Description' => 'The description of the action.
', 'DescribeContextResponse$Description' => 'The description of the context.
', 'DescribeExperimentResponse$Description' => 'The description of the experiment.
', 'DescribeLineageGroupResponse$Description' => 'The description of the lineage group.
', 'Experiment$Description' => 'The description of the experiment.
', 'UpdateActionRequest$Description' => 'The new description for the action.
', 'UpdateContextRequest$Description' => 'The new description for the context.
', 'UpdateExperimentRequest$Description' => 'The description of the experiment.
', ], ], 'ExperimentEntityName' => [ 'base' => NULL, 'refs' => [ 'ActionSummary$ActionName' => 'The name of the action.
', 'ArtifactSummary$ArtifactName' => 'The name of the artifact.
', 'AssociateTrialComponentRequest$TrialComponentName' => 'The name of the component to associated with the trial.
', 'AssociateTrialComponentRequest$TrialName' => 'The name of the trial to associate with.
', 'AssociationSummary$SourceName' => 'The name of the source.
', 'AssociationSummary$DestinationName' => 'The name of the destination.
', 'ContextSummary$ContextName' => 'The name of the context.
', 'CreateActionRequest$ActionName' => 'The name of the action. Must be unique to your account in an Amazon Web Services Region.
', 'CreateArtifactRequest$ArtifactName' => 'The name of the artifact. Must be unique to your account in an Amazon Web Services Region.
', 'CreateContextRequest$ContextName' => 'The name of the context. Must be unique to your account in an Amazon Web Services Region.
', 'CreateExperimentRequest$ExperimentName' => 'The name of the experiment. The name must be unique in your Amazon Web Services account and is not case-sensitive.
', 'CreateExperimentRequest$DisplayName' => 'The name of the experiment as displayed. The name doesn\'t need to be unique. If you don\'t specify DisplayName, the value in ExperimentName is displayed.
The name of the component. The name must be unique in your Amazon Web Services account and is not case-sensitive.
', 'CreateTrialComponentRequest$DisplayName' => 'The name of the component as displayed. The name doesn\'t need to be unique. If DisplayName isn\'t specified, TrialComponentName is displayed.
The name of the trial. The name must be unique in your Amazon Web Services account and is not case-sensitive.
', 'CreateTrialRequest$DisplayName' => 'The name of the trial as displayed. The name doesn\'t need to be unique. If DisplayName isn\'t specified, TrialName is displayed.
The name of the experiment to associate the trial with.
', 'DeleteActionRequest$ActionName' => 'The name of the action to delete.
', 'DeleteContextRequest$ContextName' => 'The name of the context to delete.
', 'DeleteExperimentRequest$ExperimentName' => 'The name of the experiment to delete.
', 'DeleteTrialComponentRequest$TrialComponentName' => 'The name of the component to delete.
', 'DeleteTrialRequest$TrialName' => 'The name of the trial to delete.
', 'DescribeActionRequest$ActionName' => 'The name of the action to describe.
', 'DescribeContextResponse$ContextName' => 'The name of the context.
', 'DescribeExperimentRequest$ExperimentName' => 'The name of the experiment to describe.
', 'DescribeExperimentResponse$ExperimentName' => 'The name of the experiment.
', 'DescribeExperimentResponse$DisplayName' => 'The name of the experiment as displayed. If DisplayName isn\'t specified, ExperimentName is displayed.
The name of the lineage group.
', 'DescribeLineageGroupResponse$LineageGroupName' => 'The name of the lineage group.
', 'DescribeLineageGroupResponse$DisplayName' => 'The display name of the lineage group.
', 'DescribeTrialComponentResponse$TrialComponentName' => 'The name of the trial component.
', 'DescribeTrialComponentResponse$DisplayName' => 'The name of the component as displayed. If DisplayName isn\'t specified, TrialComponentName is displayed.
The name of the trial to describe.
', 'DescribeTrialResponse$TrialName' => 'The name of the trial.
', 'DescribeTrialResponse$DisplayName' => 'The name of the trial as displayed. If DisplayName isn\'t specified, TrialName is displayed.
The name of the experiment the trial is part of.
', 'DisassociateTrialComponentRequest$TrialComponentName' => 'The name of the component to disassociate from the trial.
', 'DisassociateTrialComponentRequest$TrialName' => 'The name of the trial to disassociate from.
', 'Experiment$ExperimentName' => 'The name of the experiment.
', 'Experiment$DisplayName' => 'The name of the experiment as displayed. If DisplayName isn\'t specified, ExperimentName is displayed.
The name of an existing experiment to associate with the trial component.
', 'ExperimentConfig$TrialName' => 'The name of an existing trial to associate the trial component with. If not specified, a new trial is created.
', 'ExperimentConfig$TrialComponentDisplayName' => 'The display name for the trial component. If this key isn\'t specified, the display name is the trial component name.
', 'ExperimentConfig$RunName' => 'The name of the experiment run to associate with the trial component.
', 'ExperimentSummary$ExperimentName' => 'The name of the experiment.
', 'ExperimentSummary$DisplayName' => 'The name of the experiment as displayed. If DisplayName isn\'t specified, ExperimentName is displayed.
The name or Amazon Resource Name (ARN) of the lineage group.
', 'LineageGroupSummary$DisplayName' => 'The display name of the lineage group summary.
', 'ListTrialComponentsRequest$ExperimentName' => 'A filter that returns only components that are part of the specified experiment. If you specify ExperimentName, you can\'t filter by SourceArn or TrialName.
A filter that returns only components that are part of the specified trial. If you specify TrialName, you can\'t filter by ExperimentName or SourceArn.
A filter that returns only trials that are part of the specified experiment.
', 'ListTrialsRequest$TrialComponentName' => 'A filter that returns only trials that are associated with the specified trial component.
', 'Parent$TrialName' => 'The name of the trial.
', 'Parent$ExperimentName' => 'The name of the experiment.
', 'PipelineExperimentConfig$ExperimentName' => 'The name of the experiment.
', 'PipelineExperimentConfig$TrialName' => 'The name of the trial.
', 'Trial$TrialName' => 'The name of the trial.
', 'Trial$DisplayName' => 'The name of the trial as displayed. If DisplayName isn\'t specified, TrialName is displayed.
The name of the experiment the trial is part of.
', 'TrialComponent$TrialComponentName' => 'The name of the trial component.
', 'TrialComponent$DisplayName' => 'The name of the component as displayed. If DisplayName isn\'t specified, TrialComponentName is displayed.
The name of the experiment run.
', 'TrialComponentSimpleSummary$TrialComponentName' => 'The name of the trial component.
', 'TrialComponentSummary$TrialComponentName' => 'The name of the trial component.
', 'TrialComponentSummary$DisplayName' => 'The name of the component as displayed. If DisplayName isn\'t specified, TrialComponentName is displayed.
The name of the trial.
', 'TrialSummary$DisplayName' => 'The name of the trial as displayed. If DisplayName isn\'t specified, TrialName is displayed.
The name of the action to update.
', 'UpdateArtifactRequest$ArtifactName' => 'The new name for the artifact.
', 'UpdateContextRequest$ContextName' => 'The name of the context to update.
', 'UpdateExperimentRequest$ExperimentName' => 'The name of the experiment to update.
', 'UpdateExperimentRequest$DisplayName' => 'The name of the experiment as displayed. The name doesn\'t need to be unique. If DisplayName isn\'t specified, ExperimentName is displayed.
The name of the component to update.
', 'UpdateTrialComponentRequest$DisplayName' => 'The name of the component as displayed. The name doesn\'t need to be unique. If DisplayName isn\'t specified, TrialComponentName is displayed.
The name of the trial to update.
', 'UpdateTrialRequest$DisplayName' => 'The name of the trial as displayed. The name doesn\'t need to be unique. If DisplayName isn\'t specified, TrialName is displayed.
The name of the action.
', 'DescribeArtifactResponse$ArtifactName' => 'The name of the artifact.
', 'DescribeContextRequest$ContextName' => 'The name of the context to describe.
', 'DescribeTrialComponentRequest$TrialComponentName' => 'The name of the trial component to describe.
', ], ], 'ExperimentSource' => [ 'base' => 'The source of the experiment.
', 'refs' => [ 'DescribeExperimentResponse$Source' => 'The Amazon Resource Name (ARN) of the source and, optionally, the type.
', 'Experiment$Source' => NULL, 'ExperimentSummary$ExperimentSource' => NULL, ], ], 'ExperimentSourceArn' => [ 'base' => NULL, 'refs' => [ 'ExperimentSource$SourceArn' => 'The Amazon Resource Name (ARN) of the source.
', ], ], 'ExperimentSummaries' => [ 'base' => NULL, 'refs' => [ 'ListExperimentsResponse$ExperimentSummaries' => 'A list of the summaries of your experiments.
', ], ], 'ExperimentSummary' => [ 'base' => 'A summary of the properties of an experiment. To get the complete set of properties, call the DescribeExperiment API and provide the ExperimentName.
The number of seconds until the pre-signed URL expires. This value defaults to 300.
', ], ], 'Explainability' => [ 'base' => 'Contains explainability metrics for a model.
', 'refs' => [ 'ModelMetrics$Explainability' => 'Metrics that help explain a model.
', ], ], 'ExplainabilityLocation' => [ 'base' => NULL, 'refs' => [ 'CandidateArtifactLocations$Explainability' => 'The Amazon S3 prefix to the explainability artifacts generated for the AutoML candidate.
', ], ], 'ExplainerConfig' => [ 'base' => 'A parameter to activate explainers.
', 'refs' => [ 'CreateEndpointConfigInput$ExplainerConfig' => 'A member of CreateEndpointConfig that enables explainers.
The configuration parameters for an explainer.
', 'DescribeEndpointOutput$ExplainerConfig' => 'The configuration parameters for an explainer.
', ], ], 'FailStepMetadata' => [ 'base' => 'The container for the metadata for Fail step.
', 'refs' => [ 'PipelineExecutionStepMetadata$Fail' => 'The configurations and outcomes of a Fail step execution.
', ], ], 'FailureHandlingPolicy' => [ 'base' => NULL, 'refs' => [ 'EdgeDeploymentConfig$FailureHandlingPolicy' => 'Toggle that determines whether to rollback to previous configuration if the current deployment fails. By default this is turned on. You may turn this off if you want to investigate the errors yourself.
', ], ], 'FailureReason' => [ 'base' => NULL, 'refs' => [ 'ConflictException$Message' => NULL, 'DescribeAppResponse$FailureReason' => 'The failure reason.
', 'DescribeCompilationJobResponse$FailureReason' => 'If a model compilation job failed, the reason it failed.
', 'DescribeDomainResponse$FailureReason' => 'The failure reason.
', 'DescribeEndpointOutput$FailureReason' => 'If the status of the endpoint is Failed, the reason why it failed.
The reason that the FeatureGroup failed to be replicated in the OfflineStore. This is failure can occur because:
The FeatureGroup could not be created in the OfflineStore.
The FeatureGroup could not be deleted from the OfflineStore.
The reason your flow definition failed.
', 'DescribeHubContentResponse$FailureReason' => 'The failure reason if importing hub content failed.
', 'DescribeHubResponse$FailureReason' => 'The failure reason if importing hub content failed.
', 'DescribeHyperParameterTuningJobResponse$FailureReason' => 'If the tuning job failed, the reason it failed.
', 'DescribeImageResponse$FailureReason' => 'When a create, update, or delete operation fails, the reason for the failure.
', 'DescribeImageVersionResponse$FailureReason' => 'When a create or delete operation fails, the reason for the failure.
', 'DescribeInferenceRecommendationsJobResponse$FailureReason' => 'If the job fails, provides information why the job failed.
', 'DescribeLabelingJobResponse$FailureReason' => 'If the job failed, the reason that it failed.
', 'DescribeModelCardExportJobResponse$FailureReason' => 'The failure reason if the model export job fails.
', 'DescribeMonitoringScheduleResponse$FailureReason' => 'A string, up to one KB in size, that contains the reason a monitoring job failed, if it failed.
', 'DescribeNotebookInstanceOutput$FailureReason' => 'If status is Failed, the reason it failed.
A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
', 'DescribeSpaceResponse$FailureReason' => 'The failure reason.
', 'DescribeTrainingJobResponse$FailureReason' => 'If the training job failed, the reason it failed.
', 'DescribeTransformJobResponse$FailureReason' => 'If the transform job failed, FailureReason describes why it failed. A transform job creates a log file, which includes error messages, and stores it as an Amazon S3 object. For more information, see Log Amazon SageMaker Events with Amazon CloudWatch.
The failure reason.
', 'Endpoint$FailureReason' => 'If the endpoint failed, the reason it failed.
', 'EndpointMetadata$FailureReason' => ' If the status of the endpoint is Failed, or the status is InService but update operation fails, this provides the reason why it failed.
The reason that the FeatureGroup failed to be replicated in the OfflineStore. This is failure may be due to a failure to create a FeatureGroup in or delete a FeatureGroup from the OfflineStore.
The reason why the flow definition creation failed. A failure reason is returned only when the flow definition status is Failed.
The reason that the training job failed.
', 'HyperParameterTuningJobSearchEntity$FailureReason' => 'The error that was created when a hyperparameter tuning job failed.
', 'Image$FailureReason' => 'When a create, update, or delete operation fails, the reason for the failure.
', 'ImageVersion$FailureReason' => 'When a create or delete operation fails, the reason for the failure.
', 'InferenceRecommendationsJob$FailureReason' => 'If the job fails, provides information why the job failed.
', 'LabelingJobSummary$FailureReason' => 'If the LabelingJobStatus field is Failed, this field contains a description of the error.
If the update wasn\'t successful, indicates the reason why it failed.
', 'ModelDashboardMonitoringSchedule$FailureReason' => 'If a monitoring job failed, provides the reason.
', 'MonitoringExecutionSummary$FailureReason' => 'Contains the reason a monitoring job failed, if it failed.
', 'MonitoringSchedule$FailureReason' => 'If the monitoring schedule failed, the reason it failed.
', 'PipelineExecutionStep$FailureReason' => 'The reason why the step failed execution. This is only returned if the step failed its execution.
', 'ProcessingJob$FailureReason' => 'A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
', 'ProcessingJobSummary$FailureReason' => 'A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
', 'ResourceInUse$Message' => NULL, 'ResourceLimitExceeded$Message' => NULL, 'ResourceNotFound$Message' => NULL, 'TrainingJob$FailureReason' => 'If the training job failed, the reason it failed.
', 'TransformJob$FailureReason' => 'If the transform job failed, the reason it failed.
', 'TransformJobSummary$FailureReason' => 'If the transform job failed, the reason it failed.
', ], ], 'FeatureAdditions' => [ 'base' => NULL, 'refs' => [ 'UpdateFeatureGroupRequest$FeatureAdditions' => 'Updates the feature group. Updating a feature group is an asynchronous operation. When you get an HTTP 200 response, you\'ve made a valid request. It takes some time after you\'ve made a valid request for Feature Store to update the feature group.
', ], ], 'FeatureDefinition' => [ 'base' => 'A list of features. You must include FeatureName and FeatureType. Valid feature FeatureTypes are Integral, Fractional and String.
A list of Feature names and types. Name and Type is compulsory per Feature.
Valid feature FeatureTypes are Integral, Fractional and String.
FeatureNames cannot be any of the following: is_deleted, write_time, api_invocation_time
You can create up to 2,500 FeatureDefinitions per FeatureGroup.
A list of the Features in the FeatureGroup. Each feature is defined by a FeatureName and FeatureType.
A list of Features. Each Feature must include a FeatureName and a FeatureType.
Valid FeatureTypes are Integral, Fractional and String.
FeatureNames cannot be any of the following: is_deleted, write_time, api_invocation_time.
You can create up to 2,500 FeatureDefinitions per FeatureGroup.
The description you added to describe the feature.
', 'FeatureMetadata$Description' => 'An optional description that you specify to better describe the feature.
', 'UpdateFeatureMetadataRequest$Description' => 'A description that you can write to better describe the feature.
', ], ], 'FeatureGroup' => [ 'base' => 'Amazon SageMaker Feature Store stores features in a collection called Feature Group. A Feature Group can be visualized as a table which has rows, with a unique identifier for each row where each column in the table is a feature. In principle, a Feature Group is composed of features and values per features.
', 'refs' => [ 'SearchRecord$FeatureGroup' => NULL, ], ], 'FeatureGroupArn' => [ 'base' => NULL, 'refs' => [ 'CreateFeatureGroupResponse$FeatureGroupArn' => 'The Amazon Resource Name (ARN) of the FeatureGroup. This is a unique identifier for the feature group.
The Amazon Resource Name (ARN) of the FeatureGroup.
The Amazon Resource Number (ARN) of the feature group that contains the feature.
', 'FeatureGroup$FeatureGroupArn' => 'The Amazon Resource Name (ARN) of a FeatureGroup.
Unique identifier for the FeatureGroup.
The Amazon Resource Number (ARN) of the feature group.
', 'UpdateFeatureGroupResponse$FeatureGroupArn' => 'The Amazon Resource Number (ARN) of the feature group that you\'re updating.
', ], ], 'FeatureGroupMaxResults' => [ 'base' => NULL, 'refs' => [ 'ListFeatureGroupsRequest$MaxResults' => 'The maximum number of results returned by ListFeatureGroups.
The name of the FeatureGroup. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account. The name:
Must start and end with an alphanumeric character.
Can only contain alphanumeric character and hyphens. Spaces are not allowed.
The name of the FeatureGroup you want to delete. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
he name of the FeatureGroup.
The name of the feature group that you\'ve specified.
', 'FeatureGroup$FeatureGroupName' => 'The name of the FeatureGroup.
The name of FeatureGroup.
The name of the feature group containing the feature.
', 'ProcessingFeatureStoreOutput$FeatureGroupName' => 'The name of the Amazon SageMaker FeatureGroup to use as the destination for processing job output. Note that your processing script is responsible for putting records into your Feature Store.
', ], ], 'FeatureGroupNameContains' => [ 'base' => NULL, 'refs' => [ 'ListFeatureGroupsRequest$NameContains' => 'A string that partially matches one or more FeatureGroups names. Filters FeatureGroups by name.
The name or Amazon Resource Name (ARN) of the FeatureGroup you want described.
The name or Amazon Resource Name (ARN) of the feature group containing the feature.
', 'UpdateFeatureGroupRequest$FeatureGroupName' => 'The name or Amazon Resource Name (ARN) of the feature group that you\'re updating.
', 'UpdateFeatureMetadataRequest$FeatureGroupName' => 'The name or Amazon Resource Name (ARN) of the feature group containing the feature that you\'re updating.
', ], ], 'FeatureGroupSortBy' => [ 'base' => NULL, 'refs' => [ 'ListFeatureGroupsRequest$SortBy' => 'The value on which the feature group list is sorted.
', ], ], 'FeatureGroupSortOrder' => [ 'base' => NULL, 'refs' => [ 'ListFeatureGroupsRequest$SortOrder' => 'The order in which feature groups are listed.
', ], ], 'FeatureGroupStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeFeatureGroupResponse$FeatureGroupStatus' => 'The status of the feature group.
', 'FeatureGroup$FeatureGroupStatus' => 'A FeatureGroup status.
The status of a FeatureGroup. The status can be any of the following: Creating, Created, CreateFail, Deleting or DetailFail.
A FeatureGroup status. Filters by FeatureGroup status.
A summary of feature groups.
', ], ], 'FeatureGroupSummary' => [ 'base' => 'The name, ARN, CreationTime, FeatureGroup values, LastUpdatedTime and EnableOnlineStorage status of a FeatureGroup.
The metadata for a feature. It can either be metadata that you specify, or metadata that is updated automatically.
', 'refs' => [ 'SearchRecord$FeatureMetadata' => 'The feature metadata used to search through the features.
', ], ], 'FeatureName' => [ 'base' => NULL, 'refs' => [ 'CreateFeatureGroupRequest$RecordIdentifierFeatureName' => 'The name of the Feature whose value uniquely identifies a Record defined in the FeatureStore. Only the latest record per identifier value will be stored in the OnlineStore. RecordIdentifierFeatureName must be one of feature definitions\' names.
You use the RecordIdentifierFeatureName to access data in a FeatureStore.
This name:
Must start and end with an alphanumeric character.
Can only contains alphanumeric characters, hyphens, underscores. Spaces are not allowed.
The name of the feature that stores the EventTime of a Record in a FeatureGroup.
An EventTime is a point in time when a new event occurs that corresponds to the creation or update of a Record in a FeatureGroup. All Records in the FeatureGroup must have a corresponding EventTime.
An EventTime can be a String or Fractional.
Fractional: EventTime feature values must be a Unix timestamp in seconds.
String: EventTime feature values must be an ISO-8601 string in the format. The following formats are supported yyyy-MM-dd\'T\'HH:mm:ssZ and yyyy-MM-dd\'T\'HH:mm:ss.SSSZ where yyyy, MM, and dd represent the year, month, and day respectively and HH, mm, ss, and if applicable, SSS represent the hour, month, second and milliseconds respsectively. \'T\' and Z are constants.
The name of the Feature used for RecordIdentifier, whose value uniquely identifies a record stored in the feature store.
The name of the feature that stores the EventTime of a Record in a FeatureGroup.
An EventTime is a point in time when a new event occurs that corresponds to the creation or update of a Record in a FeatureGroup. All Records in the FeatureGroup have a corresponding EventTime.
The name of the feature.
', 'DescribeFeatureMetadataResponse$FeatureName' => 'The name of the feature that you\'ve specified.
', 'FeatureDefinition$FeatureName' => 'The name of a feature. The type must be a string. FeatureName cannot be any of the following: is_deleted, write_time, api_invocation_time.
The name of the Feature whose value uniquely identifies a Record defined in the FeatureGroup FeatureDefinitions.
The name of the feature that stores the EventTime of a Record in a FeatureGroup.
A EventTime is point in time when a new event occurs that corresponds to the creation or update of a Record in FeatureGroup. All Records in the FeatureGroup must have a corresponding EventTime.
The name of feature.
', 'UpdateFeatureMetadataRequest$FeatureName' => 'The name of the feature that you\'re updating.
', ], ], 'FeatureParameter' => [ 'base' => 'A key-value pair that you specify to describe the feature.
', 'refs' => [ 'FeatureParameterAdditions$member' => NULL, 'FeatureParameters$member' => NULL, ], ], 'FeatureParameterAdditions' => [ 'base' => NULL, 'refs' => [ 'UpdateFeatureMetadataRequest$ParameterAdditions' => 'A list of key-value pairs that you can add to better describe the feature.
', ], ], 'FeatureParameterKey' => [ 'base' => NULL, 'refs' => [ 'FeatureParameter$Key' => 'A key that must contain a value to describe the feature.
', 'FeatureParameterRemovals$member' => NULL, ], ], 'FeatureParameterRemovals' => [ 'base' => NULL, 'refs' => [ 'UpdateFeatureMetadataRequest$ParameterRemovals' => 'A list of parameter keys that you can specify to remove parameters that describe your feature.
', ], ], 'FeatureParameterValue' => [ 'base' => NULL, 'refs' => [ 'FeatureParameter$Value' => 'The value that belongs to a key.
', ], ], 'FeatureParameters' => [ 'base' => NULL, 'refs' => [ 'DescribeFeatureMetadataResponse$Parameters' => 'The key-value pairs that you added to describe the feature.
', 'FeatureMetadata$Parameters' => 'Optional key-value pairs that you specify to better describe the feature.
', ], ], 'FeatureStatus' => [ 'base' => NULL, 'refs' => [ 'DirectDeploySettings$Status' => 'Describes whether model deployment permissions are enabled or disabled in the Canvas application.
', 'IdentityProviderOAuthSetting$Status' => 'Describes whether OAuth for a data source is enabled or disabled in the Canvas application.
', 'KendraSettings$Status' => 'Describes whether the document querying feature is enabled or disabled in the Canvas application.
', 'ModelRegisterSettings$Status' => 'Describes whether the integration to the model registry is enabled or disabled in the Canvas application.
', 'TimeSeriesForecastingSettings$Status' => 'Describes whether time series forecasting is enabled or disabled in the Canvas application.
', ], ], 'FeatureType' => [ 'base' => NULL, 'refs' => [ 'DescribeFeatureMetadataResponse$FeatureType' => 'The data type of the feature.
', 'FeatureDefinition$FeatureType' => 'The value type of a feature. Valid values are Integral, Fractional, or String.
', 'FeatureMetadata$FeatureType' => 'The data type of the feature.
', ], ], 'FileSource' => [ 'base' => 'Contains details regarding the file source.
', 'refs' => [ 'DriftCheckBias$ConfigFile' => 'The bias config file for a model.
', 'DriftCheckExplainability$ConfigFile' => 'The explainability config file for the model.
', ], ], 'FileSystemAccessMode' => [ 'base' => NULL, 'refs' => [ 'FileSystemDataSource$FileSystemAccessMode' => 'The access mode of the mount of the directory associated with the channel. A directory can be mounted either in ro (read-only) or rw (read-write) mode.
The Amazon Elastic File System (EFS) storage configuration for a SageMaker image.
', 'refs' => [ 'KernelGatewayImageConfig$FileSystemConfig' => 'The Amazon Elastic File System (EFS) storage configuration for a SageMaker image.
', ], ], 'FileSystemDataSource' => [ 'base' => 'Specifies a file system data source for a channel.
', 'refs' => [ 'DataSource$FileSystemDataSource' => 'The file system that is associated with a channel.
', ], ], 'FileSystemId' => [ 'base' => NULL, 'refs' => [ 'FileSystemDataSource$FileSystemId' => 'The file system id.
', ], ], 'FileSystemType' => [ 'base' => NULL, 'refs' => [ 'FileSystemDataSource$FileSystemType' => 'The file system type.
', ], ], 'FillingTransformationMap' => [ 'base' => NULL, 'refs' => [ 'FillingTransformations$value' => NULL, ], ], 'FillingTransformationValue' => [ 'base' => NULL, 'refs' => [ 'FillingTransformationMap$value' => NULL, ], ], 'FillingTransformations' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesTransformations$Filling' => 'A key value pair defining the filling method for a column, where the key is the column name and the value is an object which defines the filling logic. You can specify multiple filling methods for a single column.
The supported filling methods and their corresponding options are:
frontfill: none (Supported only for target column)
middlefill: zero, value, median, mean, min, max
backfill: zero, value, median, mean, min, max
futurefill: zero, value, median, mean, min, max
To set a filling method to a specific value, set the fill parameter to the chosen filling method value (for example "backfill" : "value"), and define the filling value in an additional parameter prefixed with "_value". For example, to set backfill to a value of 2, you must include two parameters: "backfill": "value" and "backfill_value":"2".
A conditional statement for a search expression that includes a resource property, a Boolean operator, and a value. Resources that match the statement are returned in the results from the Search API.
If you specify a Value, but not an Operator, SageMaker uses the equals operator.
In search, there are several property types:
To define a metric filter, enter a value using the form "Metrics.<name>", where <name> is a metric name. For example, the following filter searches for training jobs with an "accuracy" metric greater than "0.9":
{
"Name": "Metrics.accuracy",
"Operator": "GreaterThan",
"Value": "0.9"
}
To define a hyperparameter filter, enter a value with the form "HyperParameters.<name>". Decimal hyperparameter values are treated as a decimal in a comparison if the specified Value is also a decimal value. If the specified Value is an integer, the decimal hyperparameter values are treated as integers. For example, the following filter is satisfied by training jobs with a "learning_rate" hyperparameter that is less than "0.5":
{
"Name": "HyperParameters.learning_rate",
"Operator": "LessThan",
"Value": "0.5"
}
To define a tag filter, enter a value with the form Tags.<key>.
A list of filters. Each filter acts on a property. Filters must contain at least one Filters value. For example, a NestedFilters call might include a filter on the PropertyName parameter of the InputDataConfig property: InputDataConfig.DataSource.S3DataSource.S3Uri.
A list of filter objects.
', ], ], 'FilterValue' => [ 'base' => NULL, 'refs' => [ 'Filter$Value' => 'A value used with Name and Operator to determine which resources satisfy the filter\'s condition. For numerical properties, Value must be an integer or floating-point decimal. For timestamp properties, Value must be an ISO 8601 date-time string of the following format: YYYY-mm-dd\'T\'HH:MM:SS.
The best candidate result from an AutoML training job.
', 'refs' => [ 'AutoMLCandidate$FinalAutoMLJobObjectiveMetric' => NULL, ], ], 'FinalHyperParameterTuningJobObjectiveMetric' => [ 'base' => 'Shows the latest objective metric emitted by a training job that was launched by a hyperparameter tuning job. You define the objective metric in the HyperParameterTuningJobObjective parameter of HyperParameterTuningJobConfig.
The FinalHyperParameterTuningJobObjectiveMetric object that specifies the value of the objective metric of the tuning job that launched this training job.
', ], ], 'FinalMetricDataList' => [ 'base' => NULL, 'refs' => [ 'DescribeTrainingJobResponse$FinalMetricDataList' => 'A collection of MetricData objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.
A list of final metric values that are set when the training job completes. Used only if the training job was configured to use metrics.
', ], ], 'FlatInvocations' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobStoppingConditions$FlatInvocations' => 'Stops a load test when the number of invocations (TPS) peaks and flattens, which means that the instance has reached capacity. The default value is Stop. If you want the load test to continue after invocations have flattened, set the value to Continue.
The value of the metric.
', 'MetricDatum$Value' => 'The value of the metric.
', 'RecommendationMetrics$CostPerHour' => 'Defines the cost per hour for the instance.
', 'RecommendationMetrics$CostPerInference' => 'Defines the cost per inference for the instance .
', ], ], 'FlowDefinitionArn' => [ 'base' => NULL, 'refs' => [ 'CreateFlowDefinitionResponse$FlowDefinitionArn' => 'The Amazon Resource Name (ARN) of the flow definition you create.
', 'DescribeFlowDefinitionResponse$FlowDefinitionArn' => 'The Amazon Resource Name (ARN) of the flow defintion.
', 'FlowDefinitionSummary$FlowDefinitionArn' => 'The Amazon Resource Name (ARN) of the flow definition.
', ], ], 'FlowDefinitionName' => [ 'base' => NULL, 'refs' => [ 'CreateFlowDefinitionRequest$FlowDefinitionName' => 'The name of your flow definition.
', 'DeleteFlowDefinitionRequest$FlowDefinitionName' => 'The name of the flow definition you are deleting.
', 'DescribeFlowDefinitionRequest$FlowDefinitionName' => 'The name of the flow definition.
', 'DescribeFlowDefinitionResponse$FlowDefinitionName' => 'The Amazon Resource Name (ARN) of the flow definition.
', 'FlowDefinitionSummary$FlowDefinitionName' => 'The name of the flow definition.
', ], ], 'FlowDefinitionOutputConfig' => [ 'base' => 'Contains information about where human output will be stored.
', 'refs' => [ 'CreateFlowDefinitionRequest$OutputConfig' => 'An object containing information about where the human review results will be uploaded.
', 'DescribeFlowDefinitionResponse$OutputConfig' => 'An object containing information about the output file.
', ], ], 'FlowDefinitionStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeFlowDefinitionResponse$FlowDefinitionStatus' => 'The status of the flow definition. Valid values are listed below.
', 'FlowDefinitionSummary$FlowDefinitionStatus' => 'The status of the flow definition. Valid values:
', ], ], 'FlowDefinitionSummaries' => [ 'base' => NULL, 'refs' => [ 'ListFlowDefinitionsResponse$FlowDefinitionSummaries' => 'An array of objects describing the flow definitions.
', ], ], 'FlowDefinitionSummary' => [ 'base' => 'Contains summary information about the flow definition.
', 'refs' => [ 'FlowDefinitionSummaries$member' => NULL, ], ], 'FlowDefinitionTaskAvailabilityLifetimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'HumanLoopConfig$TaskAvailabilityLifetimeInSeconds' => 'The length of time that a task remains available for review by human workers.
', ], ], 'FlowDefinitionTaskCount' => [ 'base' => NULL, 'refs' => [ 'HumanLoopConfig$TaskCount' => 'The number of distinct workers who will perform the same task on each object. For example, if TaskCount is set to 3 for an image classification labeling job, three workers will classify each input image. Increasing TaskCount can improve label accuracy.
A description for the human worker task.
', ], ], 'FlowDefinitionTaskKeyword' => [ 'base' => NULL, 'refs' => [ 'FlowDefinitionTaskKeywords$member' => NULL, ], ], 'FlowDefinitionTaskKeywords' => [ 'base' => NULL, 'refs' => [ 'HumanLoopConfig$TaskKeywords' => 'Keywords used to describe the task so that workers can discover the task.
', ], ], 'FlowDefinitionTaskTimeLimitInSeconds' => [ 'base' => NULL, 'refs' => [ 'HumanLoopConfig$TaskTimeLimitInSeconds' => 'The amount of time that a worker has to complete a task. The default value is 3,600 seconds (1 hour).
', ], ], 'FlowDefinitionTaskTitle' => [ 'base' => NULL, 'refs' => [ 'HumanLoopConfig$TaskTitle' => 'A title for the human worker task.
', ], ], 'ForecastFrequency' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesForecastingJobConfig$ForecastFrequency' => 'The frequency of predictions in a forecast.
Valid intervals are an integer followed by Y (Year), M (Month), W (Week), D (Day), H (Hour), and min (Minute). For example, 1D indicates every day and 15min indicates every 15 minutes. The value of a frequency must not overlap with the next larger frequency. For example, you must use a frequency of 1H instead of 60min.
The valid values for each frequency are the following:
Minute - 1-59
Hour - 1-23
Day - 1-6
Week - 1-4
Month - 1-11
Year - 1
The number of time-steps that the model predicts. The forecast horizon is also called the prediction length. The maximum forecast horizon is the lesser of 500 time-steps or 1/4 of the time-steps in the dataset.
', ], ], 'ForecastQuantile' => [ 'base' => NULL, 'refs' => [ 'ForecastQuantiles$member' => NULL, ], ], 'ForecastQuantiles' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesForecastingJobConfig$ForecastQuantiles' => 'The quantiles used to train the model for forecasts at a specified quantile. You can specify quantiles from 0.01 (p1) to 0.99 (p99), by increments of 0.01 or higher. Up to five forecast quantiles can be specified. When ForecastQuantiles is not provided, the AutoML job uses the quantiles p10, p50, and p90 as default.
Identifies the framework in which the model was trained. For example: TENSORFLOW.
', ], ], 'FrameworkVersion' => [ 'base' => NULL, 'refs' => [ 'InputConfig$FrameworkVersion' => 'Specifies the framework version to use. This API field is only supported for the MXNet, PyTorch, TensorFlow and TensorFlow Lite frameworks.
For information about framework versions supported for cloud targets and edge devices, see Cloud Supported Instance Types and Frameworks and Edge Supported Frameworks.
', ], ], 'GenerateCandidateDefinitionsOnly' => [ 'base' => NULL, 'refs' => [ 'CreateAutoMLJobRequest$GenerateCandidateDefinitionsOnly' => 'Generates possible candidates without training the models. A candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings.
', 'DescribeAutoMLJobResponse$GenerateCandidateDefinitionsOnly' => 'Indicates whether the output for an AutoML job generates candidate definitions only.
', 'TabularJobConfig$GenerateCandidateDefinitionsOnly' => 'Generates possible candidates without training the models. A model candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings.
', ], ], 'GetDeviceFleetReportRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetDeviceFleetReportResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetLineageGroupPolicyRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetLineageGroupPolicyResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetModelPackageGroupPolicyInput' => [ 'base' => NULL, 'refs' => [], ], 'GetModelPackageGroupPolicyOutput' => [ 'base' => NULL, 'refs' => [], ], 'GetSagemakerServicecatalogPortfolioStatusInput' => [ 'base' => NULL, 'refs' => [], ], 'GetSagemakerServicecatalogPortfolioStatusOutput' => [ 'base' => NULL, 'refs' => [], ], 'GetScalingConfigurationRecommendationRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetScalingConfigurationRecommendationResponse' => [ 'base' => NULL, 'refs' => [], ], 'GetSearchSuggestionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'GetSearchSuggestionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'GitConfig' => [ 'base' => 'Specifies configuration details for a Git repository in your Amazon Web Services account.
', 'refs' => [ 'CodeRepositorySummary$GitConfig' => 'Configuration details for the Git repository, including the URL where it is located and the ARN of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository.
', 'CreateCodeRepositoryInput$GitConfig' => 'Specifies details about the repository, including the URL where the repository is located, the default branch, and credentials to use to access the repository.
', 'DescribeCodeRepositoryOutput$GitConfig' => 'Configuration details about the repository, including the URL where the repository is located, the default branch, and the Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository.
', ], ], 'GitConfigForUpdate' => [ 'base' => 'Specifies configuration details for a Git repository when the repository is updated.
', 'refs' => [ 'UpdateCodeRepositoryInput$GitConfig' => 'The configuration of the git repository, including the URL and the Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository. The secret must have a staging label of AWSCURRENT and must be in the following format:
{"username": UserName, "password": Password}
The URL where the Git repository is located.
', ], ], 'Group' => [ 'base' => NULL, 'refs' => [ 'Groups$member' => NULL, ], ], 'GroupingAttributeName' => [ 'base' => NULL, 'refs' => [ 'GroupingAttributeNames$member' => NULL, ], ], 'GroupingAttributeNames' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesConfig$GroupingAttributeNames' => 'A set of columns names that can be grouped with the item identifier column to create a composite key for which a target value is predicted.
', ], ], 'Groups' => [ 'base' => NULL, 'refs' => [ 'OidcMemberDefinition$Groups' => 'A list of comma seperated strings that identifies user groups in your OIDC IdP. Each user group is made up of a group of private workers.
', ], ], 'HolidayConfig' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesForecastingJobConfig$HolidayConfig' => 'The collection of holiday featurization attributes used to incorporate national holiday information into your forecasting model.
', ], ], 'HolidayConfigAttributes' => [ 'base' => 'Stores the holiday featurization attributes applicable to each item of time-series datasets during the training of a forecasting model. This allows the model to identify patterns associated with specific holidays.
', 'refs' => [ 'HolidayConfig$member' => NULL, ], ], 'HookParameters' => [ 'base' => NULL, 'refs' => [ 'DebugHookConfig$HookParameters' => 'Configuration information for the Amazon SageMaker Debugger hook parameters.
', ], ], 'Horovod' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$Horovod' => 'Indicates Horovod compatibility.
', 'DescribeImageVersionResponse$Horovod' => 'Indicates Horovod compatibility.
', 'UpdateImageVersionRequest$Horovod' => 'Indicates Horovod compatibility.
', ], ], 'HubArn' => [ 'base' => NULL, 'refs' => [ 'CreateHubResponse$HubArn' => 'The Amazon Resource Name (ARN) of the hub.
', 'DescribeHubContentResponse$HubArn' => 'The Amazon Resource Name (ARN) of the hub that contains the content.
', 'DescribeHubResponse$HubArn' => 'The Amazon Resource Name (ARN) of the hub.
', 'HubInfo$HubArn' => 'The Amazon Resource Name (ARN) of the hub.
', 'ImportHubContentResponse$HubArn' => 'The ARN of the hub that the content was imported into.
', 'UpdateHubResponse$HubArn' => 'The Amazon Resource Name (ARN) of the updated hub.
', ], ], 'HubContentArn' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentArn' => 'The Amazon Resource Name (ARN) of the hub content.
', 'HubContentInfo$HubContentArn' => 'The Amazon Resource Name (ARN) of the hub content.
', 'ImportHubContentResponse$HubContentArn' => 'The ARN of the hub content that was imported.
', ], ], 'HubContentDependency' => [ 'base' => 'Any dependencies related to hub content, such as scripts, model artifacts, datasets, or notebooks.
', 'refs' => [ 'HubContentDependencyList$member' => NULL, ], ], 'HubContentDependencyList' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentDependencies' => 'The location of any dependencies that the hub content has, such as scripts, model artifacts, datasets, or notebooks.
', ], ], 'HubContentDescription' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentDescription' => 'A description of the hub content.
', 'HubContentInfo$HubContentDescription' => 'A description of the hub content.
', 'ImportHubContentRequest$HubContentDescription' => 'A description of the hub content to import.
', ], ], 'HubContentDisplayName' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentDisplayName' => 'The display name of the hub content.
', 'HubContentInfo$HubContentDisplayName' => 'The display name of the hub content.
', 'ImportHubContentRequest$HubContentDisplayName' => 'The display name of the hub content to import.
', ], ], 'HubContentDocument' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentDocument' => 'The hub content document that describes information about the hub content such as type, associated containers, scripts, and more.
', 'ImportHubContentRequest$HubContentDocument' => 'The hub content document that describes information about the hub content such as type, associated containers, scripts, and more.
', ], ], 'HubContentInfo' => [ 'base' => 'Information about hub content.
', 'refs' => [ 'HubContentInfoList$member' => NULL, ], ], 'HubContentInfoList' => [ 'base' => NULL, 'refs' => [ 'ListHubContentVersionsResponse$HubContentSummaries' => 'The summaries of the listed hub content versions.
', 'ListHubContentsResponse$HubContentSummaries' => 'The summaries of the listed hub content.
', ], ], 'HubContentMarkdown' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentMarkdown' => 'A string that provides a description of the hub content. This string can include links, tables, and standard markdown formating.
', 'ImportHubContentRequest$HubContentMarkdown' => 'A string that provides a description of the hub content. This string can include links, tables, and standard markdown formating.
', ], ], 'HubContentName' => [ 'base' => NULL, 'refs' => [ 'DeleteHubContentRequest$HubContentName' => 'The name of the content that you want to delete from a hub.
', 'DescribeHubContentRequest$HubContentName' => 'The name of the content to describe.
', 'DescribeHubContentResponse$HubContentName' => 'The name of the hub content.
', 'HubContentInfo$HubContentName' => 'The name of the hub content.
', 'ImportHubContentRequest$HubContentName' => 'The name of the hub content to import.
', 'ListHubContentVersionsRequest$HubContentName' => 'The name of the hub content.
', ], ], 'HubContentSearchKeywordList' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentSearchKeywords' => 'The searchable keywords for the hub content.
', 'HubContentInfo$HubContentSearchKeywords' => 'The searchable keywords for the hub content.
', 'ImportHubContentRequest$HubContentSearchKeywords' => 'The searchable keywords of the hub content.
', ], ], 'HubContentSortBy' => [ 'base' => NULL, 'refs' => [ 'ListHubContentVersionsRequest$SortBy' => 'Sort hub content versions by either name or creation time.
', 'ListHubContentsRequest$SortBy' => 'Sort hub content versions by either name or creation time.
', ], ], 'HubContentStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeHubContentResponse$HubContentStatus' => 'The status of the hub content.
', 'HubContentInfo$HubContentStatus' => 'The status of the hub content.
', ], ], 'HubContentType' => [ 'base' => NULL, 'refs' => [ 'DeleteHubContentRequest$HubContentType' => 'The type of content that you want to delete from a hub.
', 'DescribeHubContentRequest$HubContentType' => 'The type of content in the hub.
', 'DescribeHubContentResponse$HubContentType' => 'The type of hub content.
', 'HubContentInfo$HubContentType' => 'The type of hub content.
', 'ImportHubContentRequest$HubContentType' => 'The type of hub content to import.
', 'ListHubContentVersionsRequest$HubContentType' => 'The type of hub content to list versions of.
', 'ListHubContentsRequest$HubContentType' => 'The type of hub content to list.
', ], ], 'HubContentVersion' => [ 'base' => NULL, 'refs' => [ 'DeleteHubContentRequest$HubContentVersion' => 'The version of the content that you want to delete from a hub.
', 'DescribeHubContentRequest$HubContentVersion' => 'The version of the content to describe.
', 'DescribeHubContentResponse$HubContentVersion' => 'The version of the hub content.
', 'HubContentInfo$HubContentVersion' => 'The version of the hub content.
', 'ImportHubContentRequest$HubContentVersion' => 'The version of the hub content to import.
', 'ListHubContentVersionsRequest$MinVersion' => 'The lower bound of the hub content versions to list.
', ], ], 'HubDescription' => [ 'base' => NULL, 'refs' => [ 'CreateHubRequest$HubDescription' => 'A description of the hub.
', 'DescribeHubResponse$HubDescription' => 'A description of the hub.
', 'HubInfo$HubDescription' => 'A description of the hub.
', 'UpdateHubRequest$HubDescription' => 'A description of the updated hub.
', ], ], 'HubDisplayName' => [ 'base' => NULL, 'refs' => [ 'CreateHubRequest$HubDisplayName' => 'The display name of the hub.
', 'DescribeHubResponse$HubDisplayName' => 'The display name of the hub.
', 'HubInfo$HubDisplayName' => 'The display name of the hub.
', 'UpdateHubRequest$HubDisplayName' => 'The display name of the hub.
', ], ], 'HubInfo' => [ 'base' => 'Information about a hub.
', 'refs' => [ 'HubInfoList$member' => NULL, ], ], 'HubInfoList' => [ 'base' => NULL, 'refs' => [ 'ListHubsResponse$HubSummaries' => 'The summaries of the listed hubs.
', ], ], 'HubName' => [ 'base' => NULL, 'refs' => [ 'CreateHubRequest$HubName' => 'The name of the hub to create.
', 'DeleteHubContentRequest$HubName' => 'The name of the hub that you want to delete content in.
', 'DeleteHubRequest$HubName' => 'The name of the hub to delete.
', 'DescribeHubContentRequest$HubName' => 'The name of the hub that contains the content to describe.
', 'DescribeHubContentResponse$HubName' => 'The name of the hub that contains the content.
', 'DescribeHubRequest$HubName' => 'The name of the hub to describe.
', 'DescribeHubResponse$HubName' => 'The name of the hub.
', 'HubInfo$HubName' => 'The name of the hub.
', 'ImportHubContentRequest$HubName' => 'The name of the hub to import content into.
', 'ListHubContentVersionsRequest$HubName' => 'The name of the hub to list the content versions of.
', 'ListHubContentsRequest$HubName' => 'The name of the hub to list the contents of.
', 'UpdateHubRequest$HubName' => 'The name of the hub to update.
', ], ], 'HubS3StorageConfig' => [ 'base' => 'The Amazon S3 storage configuration of a hub.
', 'refs' => [ 'CreateHubRequest$S3StorageConfig' => 'The Amazon S3 storage configuration for the hub.
', 'DescribeHubResponse$S3StorageConfig' => 'The Amazon S3 storage configuration for the hub.
', ], ], 'HubSearchKeyword' => [ 'base' => NULL, 'refs' => [ 'HubContentSearchKeywordList$member' => NULL, 'HubSearchKeywordList$member' => NULL, ], ], 'HubSearchKeywordList' => [ 'base' => NULL, 'refs' => [ 'CreateHubRequest$HubSearchKeywords' => 'The searchable keywords for the hub.
', 'DescribeHubResponse$HubSearchKeywords' => 'The searchable keywords for the hub.
', 'HubInfo$HubSearchKeywords' => 'The searchable keywords for the hub.
', 'UpdateHubRequest$HubSearchKeywords' => 'The searchable keywords for the hub.
', ], ], 'HubSortBy' => [ 'base' => NULL, 'refs' => [ 'ListHubsRequest$SortBy' => 'Sort hubs by either name or creation time.
', ], ], 'HubStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeHubResponse$HubStatus' => 'The status of the hub.
', 'HubInfo$HubStatus' => 'The status of the hub.
', ], ], 'HumanLoopActivationConditions' => [ 'base' => NULL, 'refs' => [ 'HumanLoopActivationConditionsConfig$HumanLoopActivationConditions' => 'JSON expressing use-case specific conditions declaratively. If any condition is matched, atomic tasks are created against the configured work team. The set of conditions is different for Rekognition and Textract. For more information about how to structure the JSON, see JSON Schema for Human Loop Activation Conditions in Amazon Augmented AI in the Amazon SageMaker Developer Guide.
', ], ], 'HumanLoopActivationConditionsConfig' => [ 'base' => 'Defines under what conditions SageMaker creates a human loop. Used within CreateFlowDefinition. See HumanLoopActivationConditionsConfig for the required format of activation conditions.
', 'refs' => [ 'HumanLoopActivationConfig$HumanLoopActivationConditionsConfig' => 'Container structure for defining under what conditions SageMaker creates a human loop.
', ], ], 'HumanLoopActivationConfig' => [ 'base' => 'Provides information about how and under what conditions SageMaker creates a human loop. If HumanLoopActivationConfig is not given, then all requests go to humans.
An object containing information about the events that trigger a human workflow.
', 'DescribeFlowDefinitionResponse$HumanLoopActivationConfig' => 'An object containing information about what triggers a human review workflow.
', ], ], 'HumanLoopConfig' => [ 'base' => 'Describes the work to be performed by human workers.
', 'refs' => [ 'CreateFlowDefinitionRequest$HumanLoopConfig' => 'An object containing information about the tasks the human reviewers will perform.
', 'DescribeFlowDefinitionResponse$HumanLoopConfig' => 'An object containing information about who works on the task, the workforce task price, and other task details.
', ], ], 'HumanLoopRequestSource' => [ 'base' => 'Container for configuring the source of human task requests.
', 'refs' => [ 'CreateFlowDefinitionRequest$HumanLoopRequestSource' => 'Container for configuring the source of human task requests. Use to specify if Amazon Rekognition or Amazon Textract is used as an integration source.
', 'DescribeFlowDefinitionResponse$HumanLoopRequestSource' => 'Container for configuring the source of human task requests. Used to specify if Amazon Rekognition or Amazon Textract is used as an integration source.
', ], ], 'HumanTaskConfig' => [ 'base' => 'Information required for human workers to complete a labeling task.
', 'refs' => [ 'CreateLabelingJobRequest$HumanTaskConfig' => 'Configures the labeling task and how it is presented to workers; including, but not limited to price, keywords, and batch size (task count).
', 'DescribeLabelingJobResponse$HumanTaskConfig' => 'Configuration information required for human workers to complete a labeling task.
', ], ], 'HumanTaskUiArn' => [ 'base' => NULL, 'refs' => [ 'CreateHumanTaskUiResponse$HumanTaskUiArn' => 'The Amazon Resource Name (ARN) of the human review workflow user interface you create.
', 'DescribeHumanTaskUiResponse$HumanTaskUiArn' => 'The Amazon Resource Name (ARN) of the human task user interface (worker task template).
', 'HumanLoopConfig$HumanTaskUiArn' => 'The Amazon Resource Name (ARN) of the human task user interface.
You can use standard HTML and Crowd HTML Elements to create a custom worker task template. You use this template to create a human task UI.
To learn how to create a custom HTML template, see Create Custom Worker Task Template.
To learn how to create a human task UI, which is a worker task template that can be used in a flow definition, see Create and Delete a Worker Task Templates.
', 'HumanTaskUiSummary$HumanTaskUiArn' => 'The Amazon Resource Name (ARN) of the human task user interface.
', 'RenderUiTemplateRequest$HumanTaskUiArn' => 'The HumanTaskUiArn of the worker UI that you want to render. Do not provide a HumanTaskUiArn if you use the UiTemplate parameter.
See a list of available Human Ui Amazon Resource Names (ARNs) in UiConfig.
', 'UiConfig$HumanTaskUiArn' => 'The ARN of the worker task template used to render the worker UI and tools for labeling job tasks.
Use this parameter when you are creating a labeling job for named entity recognition, 3D point cloud and video frame labeling jobs. Use your labeling job task type to select one of the following ARNs and use it with this parameter when you create a labeling job. Replace aws-region with the Amazon Web Services Region you are creating your labeling job in. For example, replace aws-region with us-west-1 if you create a labeling job in US West (N. California).
Named Entity Recognition
Use the following HumanTaskUiArn for named entity recognition labeling jobs:
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/NamedEntityRecognition
3D Point Cloud HumanTaskUiArns
Use this HumanTaskUiArn for 3D point cloud object detection and 3D point cloud object detection adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectDetection
Use this HumanTaskUiArn for 3D point cloud object tracking and 3D point cloud object tracking adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectTracking
Use this HumanTaskUiArn for 3D point cloud semantic segmentation and 3D point cloud semantic segmentation adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudSemanticSegmentation
Video Frame HumanTaskUiArns
Use this HumanTaskUiArn for video frame object detection and video frame object detection adjustment labeling jobs.
arn:aws:sagemaker:region:394669845002:human-task-ui/VideoObjectDetection
Use this HumanTaskUiArn for video frame object tracking and video frame object tracking adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/VideoObjectTracking
The name of the user interface you are creating.
', 'DeleteHumanTaskUiRequest$HumanTaskUiName' => 'The name of the human task user interface (work task template) you want to delete.
', 'DescribeHumanTaskUiRequest$HumanTaskUiName' => 'The name of the human task user interface (worker task template) you want information about.
', 'DescribeHumanTaskUiResponse$HumanTaskUiName' => 'The name of the human task user interface (worker task template).
', 'HumanTaskUiSummary$HumanTaskUiName' => 'The name of the human task user interface.
', ], ], 'HumanTaskUiStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeHumanTaskUiResponse$HumanTaskUiStatus' => 'The status of the human task user interface (worker task template). Valid values are listed below.
', ], ], 'HumanTaskUiSummaries' => [ 'base' => NULL, 'refs' => [ 'ListHumanTaskUisResponse$HumanTaskUiSummaries' => 'An array of objects describing the human task user interfaces.
', ], ], 'HumanTaskUiSummary' => [ 'base' => 'Container for human task user interface information.
', 'refs' => [ 'HumanTaskUiSummaries$member' => NULL, ], ], 'HyperParameterAlgorithmSpecification' => [ 'base' => 'Specifies which training algorithm to use for training jobs that a hyperparameter tuning job launches and the metrics to monitor.
', 'refs' => [ 'HyperParameterTrainingJobDefinition$AlgorithmSpecification' => 'The HyperParameterAlgorithmSpecification object that specifies the resource algorithm to use for the training jobs that the tuning job launches.
', ], ], 'HyperParameterKey' => [ 'base' => NULL, 'refs' => [ 'HyperParameters$key' => NULL, ], ], 'HyperParameterScalingType' => [ 'base' => NULL, 'refs' => [ 'ContinuousParameterRange$ScalingType' => 'The scale that hyperparameter tuning uses to search the hyperparameter range. For information about choosing a hyperparameter scale, see Hyperparameter Scaling. One of the following values:
SageMaker hyperparameter tuning chooses the best scale for the hyperparameter.
Hyperparameter tuning searches the values in the hyperparameter range by using a linear scale.
Hyperparameter tuning searches the values in the hyperparameter range by using a logarithmic scale.
Logarithmic scaling works only for ranges that have only values greater than 0.
Hyperparameter tuning searches the values in the hyperparameter range by using a reverse logarithmic scale.
Reverse logarithmic scaling works only for ranges that are entirely within the range 0<=x<1.0.
The scale that hyperparameter tuning uses to search the hyperparameter range. For information about choosing a hyperparameter scale, see Hyperparameter Scaling. One of the following values:
SageMaker hyperparameter tuning chooses the best scale for the hyperparameter.
Hyperparameter tuning searches the values in the hyperparameter range by using a linear scale.
Hyperparameter tuning searches the values in the hyperparameter range by using a logarithmic scale.
Logarithmic scaling works only for ranges that have only values greater than 0.
Defines a hyperparameter to be used by an algorithm.
', 'refs' => [ 'HyperParameterSpecifications$member' => NULL, ], ], 'HyperParameterSpecifications' => [ 'base' => NULL, 'refs' => [ 'TrainingSpecification$SupportedHyperParameters' => 'A list of the HyperParameterSpecification objects, that define the supported hyperparameters. This is required if the algorithm supports automatic model tuning.>
Defines the training jobs launched by a hyperparameter tuning job.
', 'refs' => [ 'CreateHyperParameterTuningJobRequest$TrainingJobDefinition' => 'The HyperParameterTrainingJobDefinition object that describes the training jobs that this tuning job launches, including static hyperparameters, input data configuration, output data configuration, resource configuration, and stopping condition.
', 'DescribeHyperParameterTuningJobResponse$TrainingJobDefinition' => 'The HyperParameterTrainingJobDefinition object that specifies the definition of the training jobs that this tuning job launches.
', 'HyperParameterTrainingJobDefinitions$member' => NULL, 'HyperParameterTuningJobSearchEntity$TrainingJobDefinition' => NULL, ], ], 'HyperParameterTrainingJobDefinitionName' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTrainingJobDefinition$DefinitionName' => 'The job definition name.
', 'HyperParameterTrainingJobSummary$TrainingJobDefinitionName' => 'The training job definition name.
', ], ], 'HyperParameterTrainingJobDefinitions' => [ 'base' => NULL, 'refs' => [ 'CreateHyperParameterTuningJobRequest$TrainingJobDefinitions' => 'A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.
', 'DescribeHyperParameterTuningJobResponse$TrainingJobDefinitions' => 'A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.
', 'HyperParameterTuningJobSearchEntity$TrainingJobDefinitions' => 'The job definitions included in a hyperparameter tuning job.
', ], ], 'HyperParameterTrainingJobEnvironmentKey' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTrainingJobEnvironmentMap$key' => NULL, ], ], 'HyperParameterTrainingJobEnvironmentMap' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTrainingJobDefinition$Environment' => 'An environment variable that you can pass into the SageMaker CreateTrainingJob API. You can use an existing environment variable from the training container or use your own. See Define metrics and variables for more information.
The maximum number of items specified for Map Entries refers to the maximum number of environment variables for each TrainingJobDefinition and also the maximum for the hyperparameter tuning job itself. That is, the sum of the number of environment variables for all the training job definitions can\'t exceed the maximum number specified.
A list of TrainingJobSummary objects that describe the training jobs that the ListTrainingJobsForHyperParameterTuningJob request returned.
The container for the summary information about a training job.
', 'refs' => [ 'DescribeHyperParameterTuningJobResponse$BestTrainingJob' => 'A TrainingJobSummary object that describes the training job that completed with the best current HyperParameterTuningJobObjective.
', 'DescribeHyperParameterTuningJobResponse$OverallBestTrainingJob' => 'If the hyperparameter tuning job is an warm start tuning job with a WarmStartType of IDENTICAL_DATA_AND_ALGORITHM, this is the TrainingJobSummary for the training job with the best objective metric value of all training jobs launched by this tuning job and all parent jobs specified for the warm start tuning job.
The strategy that determines the order of preference for resources specified in InstanceConfigs used in hyperparameter optimization.
The configuration for hyperparameter tuning resources for use in training jobs launched by the tuning job. These resources include compute instances and storage volumes. Specify one or more compute instance configurations and allocation strategies to select resources (optional).
', 'refs' => [ 'HyperParameterTuningInstanceConfigs$member' => NULL, ], ], 'HyperParameterTuningInstanceConfigs' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTuningResourceConfig$InstanceConfigs' => 'A list containing the configuration(s) for one or more resources for processing hyperparameter jobs. These resources include compute instances and storage volumes to use in model training jobs launched by hyperparameter tuning jobs. The AllocationStrategy controls the order in which multiple configurations provided in InstanceConfigs are used.
If you only want to use a single instance configuration inside the HyperParameterTuningResourceConfig API, do not provide a value for InstanceConfigs. Instead, use InstanceType, VolumeSizeInGB and InstanceCount. If you use InstanceConfigs, do not provide values for InstanceType, VolumeSizeInGB or InstanceCount.
The Amazon Resource Name (ARN) of the tuning job. SageMaker assigns an ARN to a hyperparameter tuning job when you create it.
', 'DescribeHyperParameterTuningJobResponse$HyperParameterTuningJobArn' => 'The Amazon Resource Name (ARN) of the tuning job.
', 'DescribeTrainingJobResponse$TuningJobArn' => 'The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.
', 'HyperParameterTuningJobSearchEntity$HyperParameterTuningJobArn' => 'The Amazon Resource Name (ARN) of a hyperparameter tuning job.
', 'HyperParameterTuningJobSummary$HyperParameterTuningJobArn' => 'The Amazon Resource Name (ARN) of the tuning job.
', 'TrainingJob$TuningJobArn' => 'The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.
', 'TuningJobStepMetaData$Arn' => 'The Amazon Resource Name (ARN) of the tuning job that was run by this step execution.
', ], ], 'HyperParameterTuningJobCompletionDetails' => [ 'base' => 'A structure that contains runtime information about both current and completed hyperparameter tuning jobs.
', 'refs' => [ 'DescribeHyperParameterTuningJobResponse$TuningJobCompletionDetails' => 'Tuning job completion information returned as the response from a hyperparameter tuning job. This information tells if your tuning job has or has not converged. It also includes the number of training jobs that have not improved model performance as evaluated against the objective function.
', 'HyperParameterTuningJobSearchEntity$TuningJobCompletionDetails' => 'Information about either a current or completed hyperparameter tuning job.
', ], ], 'HyperParameterTuningJobConfig' => [ 'base' => 'Configures a hyperparameter tuning job.
', 'refs' => [ 'CreateHyperParameterTuningJobRequest$HyperParameterTuningJobConfig' => 'The HyperParameterTuningJobConfig object that describes the tuning job, including the search strategy, the objective metric used to evaluate training jobs, ranges of parameters to search, and resource limits for the tuning job. For more information, see How Hyperparameter Tuning Works.
', 'DescribeHyperParameterTuningJobResponse$HyperParameterTuningJobConfig' => 'The HyperParameterTuningJobConfig object that specifies the configuration of the tuning job.
', 'HyperParameterTuningJobSearchEntity$HyperParameterTuningJobConfig' => NULL, ], ], 'HyperParameterTuningJobConsumedResources' => [ 'base' => 'The total resources consumed by your hyperparameter tuning job.
', 'refs' => [ 'DescribeHyperParameterTuningJobResponse$ConsumedResources' => NULL, 'HyperParameterTuningJobSearchEntity$ConsumedResources' => 'The total amount of resources consumed by a hyperparameter tuning job.
', ], ], 'HyperParameterTuningJobName' => [ 'base' => NULL, 'refs' => [ 'CreateHyperParameterTuningJobRequest$HyperParameterTuningJobName' => 'The name of the tuning job. This name is the prefix for the names of all training jobs that this tuning job launches. The name must be unique within the same Amazon Web Services account and Amazon Web Services Region. The name must have 1 to 32 characters. Valid characters are a-z, A-Z, 0-9, and : + = @ _ % - (hyphen). The name is not case sensitive.
', 'DescribeHyperParameterTuningJobRequest$HyperParameterTuningJobName' => 'The name of the tuning job.
', 'DescribeHyperParameterTuningJobResponse$HyperParameterTuningJobName' => 'The name of the hyperparameter tuning job.
', 'HyperParameterTrainingJobSummary$TuningJobName' => 'The HyperParameter tuning job that launched the training job.
', 'HyperParameterTuningJobSearchEntity$HyperParameterTuningJobName' => 'The name of a hyperparameter tuning job.
', 'HyperParameterTuningJobSummary$HyperParameterTuningJobName' => 'The name of the tuning job.
', 'ListTrainingJobsForHyperParameterTuningJobRequest$HyperParameterTuningJobName' => 'The name of the tuning job whose training jobs you want to list.
', 'ParentHyperParameterTuningJob$HyperParameterTuningJobName' => 'The name of the hyperparameter tuning job to be used as a starting point for a new hyperparameter tuning job.
', 'StopHyperParameterTuningJobRequest$HyperParameterTuningJobName' => 'The name of the tuning job to stop.
', ], ], 'HyperParameterTuningJobObjective' => [ 'base' => 'Defines the objective metric for a hyperparameter tuning job. Hyperparameter tuning uses the value of this metric to evaluate the training jobs it launches, and returns the training job that results in either the highest or lowest value for this metric, depending on the value you specify for the Type parameter. If you want to define a custom objective metric, see Define metrics and environment variables.
The HyperParameterTuningJobObjective specifies the objective metric used to evaluate the performance of training jobs launched by this tuning job.
', 'HyperParameterTuningJobObjectives$member' => NULL, ], ], 'HyperParameterTuningJobObjectiveType' => [ 'base' => NULL, 'refs' => [ 'FinalHyperParameterTuningJobObjectiveMetric$Type' => 'Select if you want to minimize or maximize the objective metric during hyperparameter tuning.
', 'HyperParameterTuningJobObjective$Type' => 'Whether to minimize or maximize the objective metric.
', ], ], 'HyperParameterTuningJobObjectives' => [ 'base' => NULL, 'refs' => [ 'TrainingSpecification$SupportedTuningJobObjectiveMetrics' => 'A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.
', ], ], 'HyperParameterTuningJobSearchEntity' => [ 'base' => 'An entity returned by the SearchRecord API containing the properties of a hyperparameter tuning job.
', 'refs' => [ 'SearchRecord$HyperParameterTuningJob' => 'The properties of a hyperparameter tuning job.
', ], ], 'HyperParameterTuningJobSortByOptions' => [ 'base' => NULL, 'refs' => [ 'ListHyperParameterTuningJobsRequest$SortBy' => 'The field to sort results by. The default is Name.
The status of the tuning job: InProgress, Completed, Failed, Stopping, or Stopped.
', 'HyperParameterTuningJobSearchEntity$HyperParameterTuningJobStatus' => 'The status of a hyperparameter tuning job.
', 'HyperParameterTuningJobSummary$HyperParameterTuningJobStatus' => 'The status of the tuning job.
', 'ListHyperParameterTuningJobsRequest$StatusEquals' => 'A filter that returns only tuning jobs with the specified status.
', ], ], 'HyperParameterTuningJobStrategyConfig' => [ 'base' => 'The configuration for a training job launched by a hyperparameter tuning job. Choose Bayesian for Bayesian optimization, and Random for random search optimization. For more advanced use cases, use Hyperband, which evaluates objective metrics for training jobs after every epoch. For more information about strategies, see How Hyperparameter Tuning Works.
The configuration for the Hyperband optimization strategy. This parameter should be provided only if Hyperband is selected as the strategy for HyperParameterTuningJobConfig.
The strategy hyperparameter tuning uses to find the best combination of hyperparameters for your model.
', 'refs' => [ 'HyperParameterTuningJobConfig$Strategy' => 'Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training job it launches. For information about search strategies, see How Hyperparameter Tuning Works.
', 'HyperParameterTuningJobSummary$Strategy' => 'Specifies the search strategy hyperparameter tuning uses to choose which hyperparameters to evaluate at each iteration.
', ], ], 'HyperParameterTuningJobSummaries' => [ 'base' => NULL, 'refs' => [ 'ListHyperParameterTuningJobsResponse$HyperParameterTuningJobSummaries' => 'A list of HyperParameterTuningJobSummary objects that describe the tuning jobs that the ListHyperParameterTuningJobs request returned.
Provides summary information about a hyperparameter tuning job.
', 'refs' => [ 'HyperParameterTuningJobSummaries$member' => NULL, ], ], 'HyperParameterTuningJobWarmStartConfig' => [ 'base' => 'Specifies the configuration for a hyperparameter tuning job that uses one or more previous hyperparameter tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.
All training jobs launched by the new hyperparameter tuning job are evaluated by using the objective metric, and the training job that performs the best is compared to the best training jobs from the parent tuning jobs. From these, the training job that performs the best as measured by the objective metric is returned as the overall best training job.
All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.
Specifies the configuration for starting the hyperparameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.
All training jobs launched by the new hyperparameter tuning job are evaluated by using the objective metric. If you specify IDENTICAL_DATA_AND_ALGORITHM as the WarmStartType value for the warm start configuration, the training job that performs the best in the new tuning job is compared to the best training jobs from the parent tuning jobs. From these, the training job that performs the best as measured by the objective metric is returned as the overall best training job.
All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.
The configuration for starting the hyperparameter parameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.
', 'HyperParameterTuningJobSearchEntity$WarmStartConfig' => NULL, ], ], 'HyperParameterTuningJobWarmStartType' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTuningJobWarmStartConfig$WarmStartType' => 'Specifies one of the following:
The new hyperparameter tuning job uses the same input data and training image as the parent tuning jobs. You can change the hyperparameter ranges to search and the maximum number of training jobs that the hyperparameter tuning job launches. You cannot use a new version of the training algorithm, unless the changes in the new version do not affect the algorithm itself. For example, changes that improve logging or adding support for a different data format are allowed. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.
The new hyperparameter tuning job can include input data, hyperparameter ranges, maximum number of concurrent training jobs, and maximum number of training jobs that are different than those of its parent hyperparameter tuning jobs. The training image can also be a different version from the version used in the parent hyperparameter tuning job. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.
The maximum time in seconds that a hyperparameter tuning job can run.
', ], ], 'HyperParameterTuningResourceConfig' => [ 'base' => 'The configuration of resources, including compute instances and storage volumes for use in training jobs launched by hyperparameter tuning jobs. HyperParameterTuningResourceConfig is similar to ResourceConfig, but has the additional InstanceConfigs and AllocationStrategy fields to allow for flexible instance management. Specify one or more instance types, count, and the allocation strategy for instance selection.
HyperParameterTuningResourceConfig supports the capabilities of ResourceConfig with the exception of KeepAlivePeriodInSeconds. Hyperparameter tuning jobs use warm pools by default, which reuse clusters between training jobs.
The configuration for the hyperparameter tuning resources, including the compute instances and storage volumes, used for training jobs launched by the tuning job. By default, storage volumes hold model artifacts and incremental states. Choose File for TrainingInputMode in the AlgorithmSpecification parameter to additionally store training data in the storage volume (optional).
The default value for this hyperparameter. If a default value is specified, a hyperparameter cannot be required.
', 'HyperParameters$value' => NULL, ], ], 'HyperParameters' => [ 'base' => NULL, 'refs' => [ 'CreateTrainingJobRequest$HyperParameters' => 'Algorithm-specific parameters that influence the quality of the model. You set hyperparameters before you start the learning process. For a list of hyperparameters for each training algorithm provided by SageMaker, see Algorithms.
You can specify a maximum of 100 hyperparameters. Each hyperparameter is a key-value pair. Each key and value is limited to 256 characters, as specified by the Length Constraint.
Do not include any security-sensitive information including account access IDs, secrets or tokens in any hyperparameter field. If the use of security-sensitive credentials are detected, SageMaker will reject your training job request and return an exception error.
Algorithm-specific parameters.
', 'HyperParameterTrainingJobDefinition$StaticHyperParameters' => 'Specifies the values of hyperparameters that do not change for the tuning job.
', 'HyperParameterTrainingJobSummary$TunedHyperParameters' => 'A list of the hyperparameters for which you specified ranges to search.
', 'TrainingJob$HyperParameters' => 'Algorithm-specific parameters.
', 'TrainingJobDefinition$HyperParameters' => 'The hyperparameters used for the training job.
', ], ], 'HyperbandStrategyConfig' => [ 'base' => 'The configuration for Hyperband, a multi-fidelity based hyperparameter tuning strategy. Hyperband uses the final and intermediate results of a training job to dynamically allocate resources to utilized hyperparameter configurations while automatically stopping under-performing configurations. This parameter should be provided only if Hyperband is selected as the StrategyConfig under the HyperParameterTuningJobConfig API.
The configuration for the object that specifies the Hyperband strategy. This parameter is only supported for the Hyperband selection for Strategy within the HyperParameterTuningJobConfig API.
The maximum number of resources (such as epochs) that can be used by a training job launched by a hyperparameter tuning job. Once a job reaches the MaxResource value, it is stopped. If a value for MaxResource is not provided, and Hyperband is selected as the hyperparameter tuning strategy, HyperbandTrainingJ attempts to infer MaxResource from the following keys (if present) in StaticsHyperParameters:
epochs
numepochs
n-epochs
n_epochs
num_epochs
If HyperbandStrategyConfig is unable to infer a value for MaxResource, it generates a validation error. The maximum value is 20,000 epochs. All metrics that correspond to an objective metric are used to derive early stopping decisions. For distributive training jobs, ensure that duplicate metrics are not printed in the logs across the individual nodes in a training job. If multiple nodes are publishing duplicate or incorrect metrics, training jobs may make an incorrect stopping decision and stop the job prematurely.
The minimum number of resources (such as epochs) that can be used by a training job launched by a hyperparameter tuning job. If the value for MinResource has not been reached, the training job is not stopped by Hyperband.
The IAM Identity details associated with the user. These details are associated with model package groups, model packages and project entities only.
', 'refs' => [ 'UserContext$IamIdentity' => 'The IAM Identity details associated with the user. These details are associated with model package groups, model packages, and project entities only.
', ], ], 'IdempotencyToken' => [ 'base' => NULL, 'refs' => [ 'CreatePipelineRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
', 'DeletePipelineRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
', 'RetryPipelineExecutionRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.
', 'SendPipelineExecutionStepFailureRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
', 'SendPipelineExecutionStepSuccessRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
', 'StartPipelineExecutionRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.
', 'StopPipelineExecutionRequest$ClientRequestToken' => 'A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.
', ], ], 'IdentityProviderOAuthSetting' => [ 'base' => 'The Amazon SageMaker Canvas application setting where you configure OAuth for connecting to an external data source, such as Snowflake.
', 'refs' => [ 'IdentityProviderOAuthSettings$member' => NULL, ], ], 'IdentityProviderOAuthSettings' => [ 'base' => NULL, 'refs' => [ 'CanvasAppSettings$IdentityProviderOAuthSettings' => 'The settings for connecting to an external data source with OAuth.
', ], ], 'Image' => [ 'base' => 'A SageMaker image. A SageMaker image represents a set of container images that are derived from a common base container image. Each of these container images is represented by a SageMaker ImageVersion.
The ARN of the image.
', 'DescribeImageResponse$ImageArn' => 'The ARN of the image.
', 'DescribeImageVersionResponse$ImageArn' => 'The ARN of the image the version is based on.
', 'Image$ImageArn' => 'The ARN of the image.
', 'ImageVersion$ImageArn' => 'The ARN of the image the version is based on.
', 'ResourceSpec$SageMakerImageArn' => 'The ARN of the SageMaker image that the image version belongs to.
', 'UpdateImageResponse$ImageArn' => 'The ARN of the image.
', ], ], 'ImageBaseImage' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$BaseImage' => 'The registry path of the container image to use as the starting point for this version. The path is an Amazon Elastic Container Registry (ECR) URI in the following format:
<acct-id>.dkr.ecr.<region>.amazonaws.com/<repo-name[:tag] or [@digest]>
The registry path of the container image on which this image version is based.
', ], ], 'ImageClassificationJobConfig' => [ 'base' => 'The collection of settings used by an AutoML job V2 for the image classification problem type.
', 'refs' => [ 'AutoMLProblemTypeConfig$ImageClassificationJobConfig' => 'Settings used to configure an AutoML job V2 for the image classification problem type.
', ], ], 'ImageConfig' => [ 'base' => 'Specifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon Virtual Private Cloud (VPC).
', 'refs' => [ 'ContainerDefinition$ImageConfig' => 'Specifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon Virtual Private Cloud (VPC). For information about storing containers in a private Docker registry, see Use a Private Docker Registry for Real-Time Inference Containers.
The model artifacts in an Amazon S3 bucket and the Docker image for inference container in Amazon EC2 Container Registry must be in the same region as the model or endpoint you are creating.
The registry path of the container image that contains this image version.
', ], ], 'ImageDeleteProperty' => [ 'base' => NULL, 'refs' => [ 'ImageDeletePropertyList$member' => NULL, ], ], 'ImageDeletePropertyList' => [ 'base' => NULL, 'refs' => [ 'UpdateImageRequest$DeleteProperties' => 'A list of properties to delete. Only the Description and DisplayName properties can be deleted.
The description of the image.
', 'DescribeImageResponse$Description' => 'The description of the image.
', 'Image$Description' => 'The description of the image.
', 'UpdateImageRequest$Description' => 'The new description for the image.
', ], ], 'ImageDigest' => [ 'base' => NULL, 'refs' => [ 'ModelPackageContainerDefinition$ImageDigest' => 'An MD5 hash of the training algorithm that identifies the Docker image used for training.
', 'TrainingSpecification$TrainingImageDigest' => 'An MD5 hash of the training algorithm that identifies the Docker image used for training.
', ], ], 'ImageDisplayName' => [ 'base' => NULL, 'refs' => [ 'CreateImageRequest$DisplayName' => 'The display name of the image. If not provided, ImageName is displayed.
The name of the image as displayed.
', 'Image$DisplayName' => 'The name of the image as displayed.
', 'UpdateImageRequest$DisplayName' => 'The new display name for the image.
', ], ], 'ImageName' => [ 'base' => NULL, 'refs' => [ 'CreateImageRequest$ImageName' => 'The name of the image. Must be unique to your account.
', 'CreateImageVersionRequest$ImageName' => 'The ImageName of the Image to create a version of.
The name of the CustomImage. Must be unique to your account.
', 'DeleteImageRequest$ImageName' => 'The name of the image to delete.
', 'DeleteImageVersionRequest$ImageName' => 'The name of the image to delete.
', 'DescribeImageRequest$ImageName' => 'The name of the image to describe.
', 'DescribeImageResponse$ImageName' => 'The name of the image.
', 'DescribeImageVersionRequest$ImageName' => 'The name of the image.
', 'Image$ImageName' => 'The name of the image.
', 'ListAliasesRequest$ImageName' => 'The name of the image.
', 'ListImageVersionsRequest$ImageName' => 'The name of the image to list the versions of.
', 'UpdateImageRequest$ImageName' => 'The name of the image to update.
', 'UpdateImageVersionRequest$ImageName' => 'The name of the image.
', ], ], 'ImageNameContains' => [ 'base' => NULL, 'refs' => [ 'ListImagesRequest$NameContains' => 'A filter that returns only images whose name contains the specified string.
', ], ], 'ImageSortBy' => [ 'base' => NULL, 'refs' => [ 'ListImagesRequest$SortBy' => 'The property used to sort results. The default value is CREATION_TIME.
The sort order. The default value is DESCENDING.
The status of the image.
', 'Image$ImageStatus' => 'The status of the image.
', ], ], 'ImageUri' => [ 'base' => NULL, 'refs' => [ 'AppSpecification$ImageUri' => 'The container image to be run by the processing job.
', 'DataQualityAppSpecification$ImageUri' => 'The container image that the data quality monitoring job runs.
', 'ModelBiasAppSpecification$ImageUri' => 'The container image to be run by the model bias job.
', 'ModelExplainabilityAppSpecification$ImageUri' => 'The container image to be run by the model explainability job.
', 'ModelQualityAppSpecification$ImageUri' => 'The address of the container image that the monitoring job runs.
', 'MonitoringAppSpecification$ImageUri' => 'The container image to be run by the monitoring job.
', ], ], 'ImageVersion' => [ 'base' => 'A version of a SageMaker Image. A version represents an existing container image.
The ARN of the image version.
', 'DescribeImageVersionResponse$ImageVersionArn' => 'The ARN of the version.
', 'ImageVersion$ImageVersionArn' => 'The ARN of the version.
', 'ResourceSpec$SageMakerImageVersionArn' => 'The ARN of the image version created on the instance.
', 'UpdateImageVersionResponse$ImageVersionArn' => 'The ARN of the image version.
', ], ], 'ImageVersionNumber' => [ 'base' => NULL, 'refs' => [ 'CustomImage$ImageVersionNumber' => 'The version number of the CustomImage.
', 'DeleteImageVersionRequest$Version' => 'The version to delete.
', 'DescribeImageVersionRequest$Version' => 'The version of the image. If not specified, the latest version is described.
', 'DescribeImageVersionResponse$Version' => 'The version number.
', 'ImageVersion$Version' => 'The version number.
', 'ListAliasesRequest$Version' => 'The version of the image. If image version is not specified, the aliases of all versions of the image are listed.
', 'UpdateImageVersionRequest$Version' => 'The version of the image.
', ], ], 'ImageVersionSortBy' => [ 'base' => NULL, 'refs' => [ 'ListImageVersionsRequest$SortBy' => 'The property used to sort results. The default value is CREATION_TIME.
The sort order. The default value is DESCENDING.
The status of the version.
', 'ImageVersion$ImageVersionStatus' => 'The status of the version.
', ], ], 'ImageVersions' => [ 'base' => NULL, 'refs' => [ 'ListImageVersionsResponse$ImageVersions' => 'A list of versions and their properties.
', ], ], 'Images' => [ 'base' => NULL, 'refs' => [ 'ListImagesResponse$Images' => 'A list of images and their properties.
', ], ], 'ImportHubContentRequest' => [ 'base' => NULL, 'refs' => [], ], 'ImportHubContentResponse' => [ 'base' => NULL, 'refs' => [], ], 'InferenceExecutionConfig' => [ 'base' => 'Specifies details about how containers in a multi-container endpoint are run.
', 'refs' => [ 'CreateModelInput$InferenceExecutionConfig' => 'Specifies details of how containers in a multi-container endpoint are called.
', 'DescribeModelOutput$InferenceExecutionConfig' => 'Specifies details of how containers in a multi-container endpoint are called.
', 'Model$InferenceExecutionConfig' => NULL, ], ], 'InferenceExecutionMode' => [ 'base' => NULL, 'refs' => [ 'InferenceExecutionConfig$Mode' => 'How containers in a multi-container are run. The following values are valid.
SERIAL - Containers run as a serial pipeline.
DIRECT - Only the individual container that you specify is run.
The ARN for your inference experiment.
', 'DeleteInferenceExperimentResponse$InferenceExperimentArn' => 'The ARN of the deleted inference experiment.
', 'DescribeInferenceExperimentResponse$Arn' => 'The ARN of the inference experiment being described.
', 'StartInferenceExperimentResponse$InferenceExperimentArn' => 'The ARN of the started inference experiment to start.
', 'StopInferenceExperimentResponse$InferenceExperimentArn' => 'The ARN of the stopped inference experiment.
', 'UpdateInferenceExperimentResponse$InferenceExperimentArn' => 'The ARN of the updated inference experiment.
', ], ], 'InferenceExperimentDataStorageConfig' => [ 'base' => 'The Amazon S3 location and configuration for storing inference request and response data.
', 'refs' => [ 'CreateInferenceExperimentRequest$DataStorageConfig' => 'The Amazon S3 location and configuration for storing inference request and response data.
This is an optional parameter that you can use for data capture. For more information, see Capture data.
', 'DescribeInferenceExperimentResponse$DataStorageConfig' => 'The Amazon S3 location and configuration for storing inference request and response data.
', 'UpdateInferenceExperimentRequest$DataStorageConfig' => 'The Amazon S3 location and configuration for storing inference request and response data.
', ], ], 'InferenceExperimentDescription' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceExperimentRequest$Description' => 'A description for the inference experiment.
', 'DescribeInferenceExperimentResponse$Description' => 'The description of the inference experiment.
', 'InferenceExperimentSummary$Description' => 'The description of the inference experiment.
', 'UpdateInferenceExperimentRequest$Description' => 'The description of the inference experiment.
', ], ], 'InferenceExperimentList' => [ 'base' => NULL, 'refs' => [ 'ListInferenceExperimentsResponse$InferenceExperiments' => 'List of inference experiments.
', ], ], 'InferenceExperimentName' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceExperimentRequest$Name' => 'The name for the inference experiment.
', 'DeleteInferenceExperimentRequest$Name' => 'The name of the inference experiment you want to delete.
', 'DescribeInferenceExperimentRequest$Name' => 'The name of the inference experiment to describe.
', 'DescribeInferenceExperimentResponse$Name' => 'The name of the inference experiment.
', 'InferenceExperimentSummary$Name' => 'The name of the inference experiment.
', 'StartInferenceExperimentRequest$Name' => 'The name of the inference experiment to start.
', 'StopInferenceExperimentRequest$Name' => 'The name of the inference experiment to stop.
', 'UpdateInferenceExperimentRequest$Name' => 'The name of the inference experiment to be updated.
', ], ], 'InferenceExperimentSchedule' => [ 'base' => 'The start and end times of an inference experiment.
The maximum duration that you can set for an inference experiment is 30 days.
', 'refs' => [ 'CreateInferenceExperimentRequest$Schedule' => 'The duration for which you want the inference experiment to run. If you don\'t specify this field, the experiment automatically starts immediately upon creation and concludes after 7 days.
', 'DescribeInferenceExperimentResponse$Schedule' => 'The duration for which the inference experiment ran or will run.
', 'InferenceExperimentSummary$Schedule' => 'The duration for which the inference experiment ran or will run.
The maximum duration that you can set for an inference experiment is 30 days.
', 'UpdateInferenceExperimentRequest$Schedule' => ' The duration for which the inference experiment will run. If the status of the inference experiment is Created, then you can update both the start and end dates. If the status of the inference experiment is Running, then you can update only the end date.
The status of the inference experiment. The following are the possible statuses for an inference experiment:
Creating - Amazon SageMaker is creating your experiment.
Created - Amazon SageMaker has finished the creation of your experiment and will begin the experiment at the scheduled time.
Updating - When you make changes to your experiment, your experiment shows as updating.
Starting - Amazon SageMaker is beginning your experiment.
Running - Your experiment is in progress.
Stopping - Amazon SageMaker is stopping your experiment.
Completed - Your experiment has completed.
Cancelled - When you conclude your experiment early using the StopInferenceExperiment API, or if any operation fails with an unexpected error, it shows as cancelled.
The status of the inference experiment.
', 'ListInferenceExperimentsRequest$StatusEquals' => 'Selects inference experiments which are in this status. For the possible statuses, see DescribeInferenceExperiment.
', ], ], 'InferenceExperimentStatusReason' => [ 'base' => NULL, 'refs' => [ 'DescribeInferenceExperimentResponse$StatusReason' => ' The error message or client-specified Reason from the StopInferenceExperiment API, that explains the status of the inference experiment.
The error message for the inference experiment status result.
', 'StopInferenceExperimentRequest$Reason' => 'The reason for stopping the experiment.
', ], ], 'InferenceExperimentStopDesiredState' => [ 'base' => NULL, 'refs' => [ 'StopInferenceExperimentRequest$DesiredState' => 'The desired state of the experiment after stopping. The possible states are the following:
Completed: The experiment completed successfully
Cancelled: The experiment was canceled
Lists a summary of properties of an inference experiment.
', 'refs' => [ 'InferenceExperimentList$member' => NULL, ], ], 'InferenceExperimentType' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceExperimentRequest$Type' => 'The type of the inference experiment that you want to run. The following types of experiments are possible:
ShadowMode: You can use this type to validate a shadow variant. For more information, see Shadow tests.
The type of the inference experiment.
', 'InferenceExperimentSummary$Type' => 'The type of the inference experiment.
', 'ListInferenceExperimentsRequest$Type' => 'Selects inference experiments of this type. For the possible types of inference experiments, see CreateInferenceExperiment.
', ], ], 'InferenceImage' => [ 'base' => NULL, 'refs' => [ 'DescribeCompilationJobResponse$InferenceImage' => 'The inference image to use when compiling a model. Specify an image only if the target device is a cloud instance.
', ], ], 'InferenceMetrics' => [ 'base' => 'The metrics for an existing endpoint compared in an Inference Recommender job.
', 'refs' => [ 'EndpointPerformance$Metrics' => 'The metrics for an existing endpoint.
', 'RecommendationJobInferenceBenchmark$EndpointMetrics' => NULL, ], ], 'InferenceRecommendation' => [ 'base' => 'A list of recommendations made by Amazon SageMaker Inference Recommender.
', 'refs' => [ 'InferenceRecommendations$member' => NULL, ], ], 'InferenceRecommendations' => [ 'base' => NULL, 'refs' => [ 'DescribeInferenceRecommendationsJobResponse$InferenceRecommendations' => 'The recommendations made by Inference Recommender.
', ], ], 'InferenceRecommendationsJob' => [ 'base' => 'A structure that contains a list of recommendation jobs.
', 'refs' => [ 'InferenceRecommendationsJobs$member' => NULL, ], ], 'InferenceRecommendationsJobStep' => [ 'base' => 'A returned array object for the Steps response field in the ListInferenceRecommendationsJobSteps API command.
A list of all subtask details in Inference Recommender.
', ], ], 'InferenceRecommendationsJobs' => [ 'base' => NULL, 'refs' => [ 'ListInferenceRecommendationsJobsResponse$InferenceRecommendationsJobs' => 'The recommendations created from the Amazon SageMaker Inference Recommender job.
', ], ], 'InferenceSpecification' => [ 'base' => 'Defines how to perform inference generation after a training job is run.
', 'refs' => [ 'BatchDescribeModelPackageSummary$InferenceSpecification' => NULL, 'CreateAlgorithmInput$InferenceSpecification' => 'Specifies details about inference jobs that the algorithm runs, including the following:
The Amazon ECR paths of containers that contain the inference code and model artifacts.
The instance types that the algorithm supports for transform jobs and real-time endpoints used for inference.
The input and output content formats that the algorithm supports for inference.
Specifies details about inference jobs that can be run with models based on this model package, including the following:
The Amazon ECR paths of containers that contain the inference code and model artifacts.
The instance types that the model package supports for transform jobs and real-time endpoints used for inference.
The input and output content formats that the model package supports for inference.
Details about inference jobs that the algorithm runs.
', 'DescribeModelPackageOutput$InferenceSpecification' => 'Details about inference jobs that can be run with models based on this model package.
', 'ModelPackage$InferenceSpecification' => 'Defines how to perform inference generation after a training job is run.
', ], ], 'InferenceSpecificationName' => [ 'base' => NULL, 'refs' => [ 'ContainerDefinition$InferenceSpecificationName' => 'The inference specification name in the model package version.
', 'EndpointInputConfiguration$InferenceSpecificationName' => 'The inference specification name in the model package version.
', 'ModelConfiguration$InferenceSpecificationName' => 'The inference specification name in the model package version.
', ], ], 'InitialInstanceCount' => [ 'base' => NULL, 'refs' => [ 'EndpointOutputConfiguration$InitialInstanceCount' => 'The number of instances recommended to launch initially.
', ], ], 'InitialNumberOfUsers' => [ 'base' => NULL, 'refs' => [ 'Phase$InitialNumberOfUsers' => 'Specifies how many concurrent users to start with. The value should be between 1 and 3.
', ], ], 'InitialTaskCount' => [ 'base' => NULL, 'refs' => [ 'ProductionVariant$InitialInstanceCount' => 'Number of instances to launch initially.
', ], ], 'InputConfig' => [ 'base' => 'Contains information about the location of input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.
', 'refs' => [ 'CreateCompilationJobRequest$InputConfig' => 'Provides information about the location of input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.
', 'DescribeCompilationJobResponse$InputConfig' => 'Information about the location in Amazon S3 of the input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.
', ], ], 'InputDataConfig' => [ 'base' => NULL, 'refs' => [ 'CreateTrainingJobRequest$InputDataConfig' => 'An array of Channel objects. Each channel is a named input source. InputDataConfig describes the input data and its location.
Algorithms can accept input data from one or more channels. For example, an algorithm might have two channels of input data, training_data and validation_data. The configuration for each channel provides the S3, EFS, or FSx location where the input data is stored. It also provides information about the stored data: the MIME type, compression method, and whether the data is wrapped in RecordIO format.
Depending on the input mode that the algorithm supports, SageMaker either copies input data files from an S3 bucket to a local directory in the Docker container, or makes it available as input streams. For example, if you specify an EFS location, input data files are available as input streams. They do not need to be downloaded.
Your input must be in the same Amazon Web Services region as your training job.
', 'DescribeTrainingJobResponse$InputDataConfig' => 'An array of Channel objects that describes each data input channel.
An array of Channel objects that specify the input for the training jobs that the tuning job launches.
', 'TrainingJob$InputDataConfig' => 'An array of Channel objects that describes each data input channel.
Your input must be in the same Amazon Web Services region as your training job.
', 'TrainingJobDefinition$InputDataConfig' => 'An array of Channel objects, each of which specifies an input source.
Whether to use File or Pipe input mode. In File (default) mode, Amazon SageMaker copies the data from the input source onto the local Amazon Elastic Block Store (Amazon EBS) volumes before starting your training algorithm. This is the most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your algorithm without using the EBS volume.
The allowed input mode, either FILE or PIPE.
In FILE mode, Amazon SageMaker copies the data from the input source onto the local Amazon Elastic Block Store (Amazon EBS) volumes before starting your training algorithm. This is the most commonly used input mode.
In PIPE mode, Amazon SageMaker streams input data from the source directly to your algorithm without using the EBS volume.
', ], ], 'InstanceGroup' => [ 'base' => 'Defines an instance group for heterogeneous cluster training. When requesting a training job using the CreateTrainingJob API, you can configure multiple instance groups .
', 'refs' => [ 'InstanceGroups$member' => NULL, ], ], 'InstanceGroupName' => [ 'base' => NULL, 'refs' => [ 'InstanceGroup$InstanceGroupName' => 'Specifies the name of the instance group.
', 'InstanceGroupNames$member' => NULL, ], ], 'InstanceGroupNames' => [ 'base' => NULL, 'refs' => [ 'S3DataSource$InstanceGroupNames' => 'A list of names of instance groups that get data from the S3 data source.
', ], ], 'InstanceGroups' => [ 'base' => NULL, 'refs' => [ 'ResourceConfig$InstanceGroups' => 'The configuration of a heterogeneous cluster in JSON format.
', ], ], 'InstanceMetadataServiceConfiguration' => [ 'base' => 'Information on the IMDS configuration of the notebook instance
', 'refs' => [ 'CreateNotebookInstanceInput$InstanceMetadataServiceConfiguration' => 'Information on the IMDS configuration of the notebook instance
', 'DescribeNotebookInstanceOutput$InstanceMetadataServiceConfiguration' => 'Information on the IMDS configuration of the notebook instance
', 'UpdateNotebookInstanceInput$InstanceMetadataServiceConfiguration' => 'Information on the IMDS configuration of the notebook instance
', ], ], 'InstanceType' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$InstanceType' => 'The type of ML compute instance to launch for the notebook instance.
', 'DescribeNotebookInstanceOutput$InstanceType' => 'The type of ML compute instance running on the notebook instance.
', 'NotebookInstanceSummary$InstanceType' => 'The type of ML compute instance that the notebook instance is running on.
', 'RealTimeInferenceConfig$InstanceType' => 'The instance type the model is deployed to.
', 'UpdateNotebookInstanceInput$InstanceType' => 'The Amazon ML compute instance type.
', ], ], 'Integer' => [ 'base' => NULL, 'refs' => [ 'CreateModelCardExportJobRequest$ModelCardVersion' => 'The version of the model card to export. If a version is not provided, then the latest version of the model card is exported.
', 'DescribeDeviceResponse$MaxModels' => 'The maximum number of models.
', 'DescribeEdgeDeploymentPlanResponse$EdgeDeploymentSuccess' => 'The number of edge devices with the successful deployment.
', 'DescribeEdgeDeploymentPlanResponse$EdgeDeploymentPending' => 'The number of edge devices yet to pick up deployment, or in progress.
', 'DescribeEdgeDeploymentPlanResponse$EdgeDeploymentFailed' => 'The number of edge devices that failed the deployment.
', 'DescribeModelCardExportJobResponse$ModelCardVersion' => 'The version of the model card that the model export job exports.
', 'DescribeModelCardRequest$ModelCardVersion' => 'The version of the model card to describe. If a version is not provided, then the latest version of the model card is described.
', 'DescribeModelCardResponse$ModelCardVersion' => 'The version of the model card.
', 'DynamicScalingConfiguration$MinCapacity' => 'The recommended minimum capacity to specify for your autoscaling policy.
', 'DynamicScalingConfiguration$MaxCapacity' => 'The recommended maximum capacity to specify for your autoscaling policy.
', 'DynamicScalingConfiguration$ScaleInCooldown' => 'The recommended scale in cooldown time for your autoscaling policy.
', 'DynamicScalingConfiguration$ScaleOutCooldown' => 'The recommended scale out cooldown time for your autoscaling policy.
', 'EdgeDeploymentPlanSummary$EdgeDeploymentSuccess' => 'The number of edge devices with the successful deployment.
', 'EdgeDeploymentPlanSummary$EdgeDeploymentPending' => 'The number of edge devices yet to pick up the deployment, or in progress.
', 'EdgeDeploymentPlanSummary$EdgeDeploymentFailed' => 'The number of edge devices that failed the deployment.
', 'EdgeDeploymentStatus$EdgeDeploymentSuccessInStage' => 'The number of edge devices with the successful deployment in the current stage.
', 'EdgeDeploymentStatus$EdgeDeploymentPendingInStage' => 'The number of edge devices yet to pick up the deployment in current stage, or in progress.
', 'EdgeDeploymentStatus$EdgeDeploymentFailedInStage' => 'The number of edge devices that failed the deployment in current stage.
', 'HyperParameterTuningJobCompletionDetails$NumberOfTrainingJobsObjectiveNotImproving' => 'The number of training jobs launched by a tuning job that are not improving (1% or less) as measured by model performance evaluated against an objective function.
', 'HyperParameterTuningJobConsumedResources$RuntimeInSeconds' => 'The wall clock runtime in seconds used by your hyperparameter tuning job.
', 'InferenceMetrics$MaxInvocations' => 'The expected maximum number of requests per minute for the instance.
', 'InferenceMetrics$ModelLatency' => 'The expected model latency at maximum invocations per minute for the instance.
', 'ListModelCardExportJobsRequest$ModelCardVersion' => 'List export jobs for the model card with the specified version.
', 'ModelCard$ModelCardVersion' => 'The version of the model card.
', 'ModelCardExportJobSummary$ModelCardVersion' => 'The version of the model card that the export job exports.
', 'ModelCardVersionSummary$ModelCardVersion' => 'A version of the model card.
', 'ModelDashboardModelCard$ModelCardVersion' => 'The model card version.
', 'ModelLatencyThreshold$ValueInMilliseconds' => 'The model latency percentile value in milliseconds.
', 'RecommendationJobStoppingConditions$MaxInvocations' => 'The maximum number of requests per minute expected for the endpoint.
', 'RecommendationMetrics$MaxInvocations' => 'The expected maximum number of requests per minute for the instance.
', 'RecommendationMetrics$ModelLatency' => 'The expected model latency at maximum invocation per minute for the instance.
', 'ScalingPolicyMetric$InvocationsPerInstance' => 'The number of invocations sent to a model, normalized by InstanceCount in each ProductionVariant. 1/numberOfInstances is sent as the value on each request, where numberOfInstances is the number of active instances for the ProductionVariant behind the endpoint at the time of the request.
The interval of time taken by a model to respond as viewed from SageMaker. This interval includes the local communication times taken to send the request and to fetch the response from the container of a model and the time taken to complete the inference in the container.
', 'ScalingPolicyObjective$MinInvocationsPerMinute' => 'The minimum number of expected requests to your endpoint per minute.
', 'ScalingPolicyObjective$MaxInvocationsPerMinute' => 'The maximum number of expected requests to your endpoint per minute.
', ], ], 'IntegerParameterRange' => [ 'base' => 'For a hyperparameter of the integer type, specifies the range that a hyperparameter tuning job searches.
', 'refs' => [ 'IntegerParameterRanges$member' => NULL, ], ], 'IntegerParameterRangeSpecification' => [ 'base' => 'Defines the possible values for an integer hyperparameter.
', 'refs' => [ 'ParameterRange$IntegerParameterRangeSpecification' => 'A IntegerParameterRangeSpecification object that defines the possible values for an integer hyperparameter.
The array of IntegerParameterRange objects that specify ranges of integer hyperparameters that a hyperparameter tuning job searches.
', ], ], 'IntegerValue' => [ 'base' => NULL, 'refs' => [ 'PipelineExecutionStep$AttemptCount' => 'The current attempt of the execution step. For more information, see Retry Policy for SageMaker Pipelines steps.
', ], ], 'InvocationEndTime' => [ 'base' => NULL, 'refs' => [ 'InferenceRecommendation$InvocationEndTime' => 'A timestamp that shows when the benchmark completed.
', 'RecommendationJobInferenceBenchmark$InvocationEndTime' => 'A timestamp that shows when the benchmark completed.
', ], ], 'InvocationStartTime' => [ 'base' => NULL, 'refs' => [ 'InferenceRecommendation$InvocationStartTime' => 'A timestamp that shows when the benchmark started.
', 'RecommendationJobInferenceBenchmark$InvocationStartTime' => 'A timestamp that shows when the benchmark started.
', ], ], 'InvocationsMaxRetries' => [ 'base' => NULL, 'refs' => [ 'ModelClientConfig$InvocationsMaxRetries' => 'The maximum number of retries when invocation requests are failing. The default value is 3.
', ], ], 'InvocationsTimeoutInSeconds' => [ 'base' => NULL, 'refs' => [ 'ModelClientConfig$InvocationsTimeoutInSeconds' => 'The timeout value in seconds for an invocation request. The default value is 600.
', ], ], 'IotRoleAlias' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceFleetResponse$IotRoleAlias' => 'The Amazon Resource Name (ARN) alias created in Amazon Web Services Internet of Things (IoT).
', ], ], 'ItemIdentifierAttributeName' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesConfig$ItemIdentifierAttributeName' => 'The name of the column that represents the set of item identifiers for which you want to predict the target value.
', ], ], 'JobDurationInSeconds' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobInputConfig$JobDurationInSeconds' => 'Specifies the maximum duration of the job, in seconds. The maximum value is 18,000 seconds.
', ], ], 'JobReferenceCode' => [ 'base' => NULL, 'refs' => [ 'DescribeLabelingJobResponse$JobReferenceCode' => 'A unique identifier for work done as part of a labeling job.
', 'LabelingJobForWorkteamSummary$JobReferenceCode' => 'A unique identifier for a labeling job. You can use this to refer to a specific labeling job.
', ], ], 'JobReferenceCodeContains' => [ 'base' => NULL, 'refs' => [ 'ListLabelingJobsForWorkteamRequest$JobReferenceCodeContains' => 'A filter the limits jobs to only the ones whose job reference code contains the specified string.
', ], ], 'JobType' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$JobType' => 'Indicates SageMaker job type compatibility.
TRAINING: The image version is compatible with SageMaker training jobs.
INFERENCE: The image version is compatible with SageMaker inference jobs.
NOTEBOOK_KERNEL: The image version is compatible with SageMaker notebook kernels.
Indicates SageMaker job type compatibility.
TRAINING: The image version is compatible with SageMaker training jobs.
INFERENCE: The image version is compatible with SageMaker inference jobs.
NOTEBOOK_KERNEL: The image version is compatible with SageMaker notebook kernels.
Indicates SageMaker job type compatibility.
TRAINING: The image version is compatible with SageMaker training jobs.
INFERENCE: The image version is compatible with SageMaker inference jobs.
NOTEBOOK_KERNEL: The image version is compatible with SageMaker notebook kernels.
Specifies the source of the data to join with the transformed data. The valid values are None and Input. The default value is None, which specifies not to join the input with the transformed data. If you want the batch transform job to join the original input data with the transformed data, set JoinSource to Input. You can specify OutputFilter as an additional filter to select a portion of the joined dataset and store it in the output file.
For JSON or JSONLines objects, such as a JSON array, SageMaker adds the transformed data to the input JSON object in an attribute called SageMakerOutput. The joined result for JSON must be a key-value pair object. If the input is not a key-value pair object, SageMaker creates a new JSON file. In the new JSON file, and the input data is stored under the SageMakerInput key and the results are stored in SageMakerOutput.
For CSV data, SageMaker takes each row as a JSON array and joins the transformed data with the input by appending each transformed row to the end of the input. The joined data has the original input data followed by the transformed data and the output is a CSV file.
For information on how joining in applied, see Workflow for Associating Inferences with Input Records.
', ], ], 'JsonContentType' => [ 'base' => NULL, 'refs' => [ 'JsonContentTypes$member' => NULL, ], ], 'JsonContentTypes' => [ 'base' => NULL, 'refs' => [ 'CaptureContentTypeHeader$JsonContentTypes' => 'The list of all content type headers that SageMaker will treat as JSON and capture accordingly.
', ], ], 'JsonPath' => [ 'base' => NULL, 'refs' => [ 'DataProcessing$InputFilter' => 'A JSONPath expression used to select a portion of the input data to pass to the algorithm. Use the InputFilter parameter to exclude fields, such as an ID column, from the input. If you want SageMaker to pass the entire input dataset to the algorithm, accept the default value $.
Examples: "$", "$[1:]", "$.features"
A JSONPath expression used to select a portion of the joined dataset to save in the output file for a batch transform job. If you want SageMaker to store the entire input dataset in the output file, leave the default value, $. If you specify indexes that aren\'t within the dimension size of the joined dataset, you get an error.
Examples: "$", "$[0,5:]", "$[\'id\',\'SageMakerOutput\']"
The JupyterServer app settings.
', 'refs' => [ 'DefaultSpaceSettings$JupyterServerAppSettings' => NULL, 'SpaceSettings$JupyterServerAppSettings' => NULL, 'UserSettings$JupyterServerAppSettings' => 'The Jupyter server\'s app settings.
', ], ], 'KeepAlivePeriodInSeconds' => [ 'base' => NULL, 'refs' => [ 'ResourceConfig$KeepAlivePeriodInSeconds' => 'The duration of time in seconds to retain configured resources in a warm pool for subsequent training jobs.
', 'ResourceConfigForUpdate$KeepAlivePeriodInSeconds' => 'The KeepAlivePeriodInSeconds value specified in the ResourceConfig to update.
The Amazon SageMaker Canvas application setting where you configure document querying.
', 'refs' => [ 'CanvasAppSettings$KendraSettings' => 'The settings for document querying.
', ], ], 'KernelDisplayName' => [ 'base' => NULL, 'refs' => [ 'KernelSpec$DisplayName' => 'The display name of the kernel.
', ], ], 'KernelGatewayAppSettings' => [ 'base' => 'The KernelGateway app settings.
', 'refs' => [ 'DefaultSpaceSettings$KernelGatewayAppSettings' => NULL, 'SpaceSettings$KernelGatewayAppSettings' => NULL, 'UserSettings$KernelGatewayAppSettings' => 'The kernel gateway app settings.
', ], ], 'KernelGatewayImageConfig' => [ 'base' => 'The configuration for the file system and kernels in a SageMaker image running as a KernelGateway app.
', 'refs' => [ 'AppImageConfigDetails$KernelGatewayImageConfig' => 'The configuration for the file system and kernels in the SageMaker image.
', 'CreateAppImageConfigRequest$KernelGatewayImageConfig' => 'The KernelGatewayImageConfig. You can only specify one image kernel in the AppImageConfig API. This kernel will be shown to users before the image starts. Once the image runs, all kernels are visible in JupyterLab.
', 'DescribeAppImageConfigResponse$KernelGatewayImageConfig' => 'The configuration of a KernelGateway app.
', 'UpdateAppImageConfigRequest$KernelGatewayImageConfig' => 'The new KernelGateway app to run on the image.
', ], ], 'KernelName' => [ 'base' => NULL, 'refs' => [ 'KernelSpec$Name' => 'The name of the Jupyter kernel in the image. This value is case sensitive.
', ], ], 'KernelSpec' => [ 'base' => 'The specification of a Jupyter kernel.
', 'refs' => [ 'KernelSpecs$member' => NULL, ], ], 'KernelSpecs' => [ 'base' => NULL, 'refs' => [ 'KernelGatewayImageConfig$KernelSpecs' => 'The specification of the Jupyter kernels in the image.
', ], ], 'Key' => [ 'base' => NULL, 'refs' => [ 'PipelineDefinitionS3Location$ObjectKey' => 'The object key (or key name) uniquely identifies the object in an S3 bucket.
', ], ], 'KmsKeyId' => [ 'base' => NULL, 'refs' => [ 'AsyncInferenceOutputConfig$KmsKeyId' => 'The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the asynchronous inference output in Amazon S3.
', 'AthenaDatasetDefinition$KmsKeyId' => 'The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data generated from an Athena query execution.
', 'AutoMLOutputDataConfig$KmsKeyId' => 'The Key Management Service (KMS) encryption key ID.
', 'AutoMLSecurityConfig$VolumeKmsKeyId' => 'The key used to encrypt stored data.
', 'BatchDataCaptureConfig$KmsKeyId' => 'The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the batch transform job.
The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
Use KmsKeyId.
SageMaker uses Amazon Web Services KMS to encrypt the EFS volume attached to the domain with an Amazon Web Services managed key by default. For more control, specify a customer managed key.
', 'CreateEdgePackagingJobRequest$ResourceKey' => 'The Amazon Web Services KMS key to use when encrypting the EBS volume the edge packaging job runs on.
', 'CreateEndpointConfigInput$KmsKeyId' => 'The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.
The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint, UpdateEndpoint requests. For more information, refer to the Amazon Web Services Key Management Service section Using Key Policies in Amazon Web Services KMS
Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can\'t request a KmsKeyId when using an instance type with local storage. If any of the models that you specify in the ProductionVariants parameter use nitro-based instances with local storage, do not specify a value for the KmsKeyId parameter. If you specify a value for KmsKeyId when using any nitro-based instances with local storage, the call to CreateEndpointConfig fails.
For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. The KmsKey can be any of the following formats:
KMS key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
Amazon Resource Name (ARN) of a KMS key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
KMS key Alias
"alias/ExampleAlias"
Amazon Resource Name (ARN) of a KMS key Alias
"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
If you use a KMS key ID or an alias of your KMS key, the Amazon SageMaker execution role must include permissions to call kms:Encrypt. If you don\'t provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role\'s account. Amazon SageMaker uses server-side encryption with KMS managed keys for OutputDataConfig. If you use a bucket policy with an s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to "aws:kms". For more information, see KMS managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint and UpdateEndpoint requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to your notebook instance. The KMS key you provide must be enabled. For information, see Enabling and Disabling Keys in the Amazon Web Services Key Management Service Developer Guide.
', 'DataCaptureConfig$KmsKeyId' => 'The Amazon Resource Name (ARN) of an Key Management Service key that SageMaker uses to encrypt the captured data at rest using Amazon S3 server-side encryption.
The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
The KMS key being used to encrypt the data in Amazon S3.
', 'DescribeDomainResponse$HomeEfsFileSystemKmsKeyId' => 'Use KmsKeyId.
The Amazon Web Services KMS customer managed key used to encrypt the EFS volume attached to the domain.
', 'DescribeEdgePackagingJobResponse$ResourceKey' => 'The Amazon Web Services KMS key to use when encrypting the EBS volume the job run on.
', 'DescribeEndpointConfigOutput$KmsKeyId' => 'Amazon Web Services KMS key ID Amazon SageMaker uses to encrypt data when storing it on the ML storage volume attached to the instance.
', 'DescribeInferenceExperimentResponse$KmsKey' => 'The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. For more information, see CreateInferenceExperiment.
', 'DescribeNotebookInstanceOutput$KmsKeyId' => 'The Amazon Web Services KMS key ID SageMaker uses to encrypt data when storing it on the ML storage volume attached to the instance.
', 'EdgeOutputConfig$KmsKeyId' => 'The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume after compilation job. If you don\'t provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role\'s account.
', 'FlowDefinitionOutputConfig$KmsKeyId' => 'The Amazon Key Management Service (KMS) key ID for server-side encryption.
', 'HyperParameterTuningResourceConfig$VolumeKmsKeyId' => 'A key used by Amazon Web Services Key Management Service to encrypt data on the storage volume attached to the compute instances used to run the training job. You can use either of the following formats to specify a key.
KMS Key ID:
"1234abcd-12ab-34cd-56ef-1234567890ab"
Amazon Resource Name (ARN) of a KMS key:
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
Some instances use local storage, which use a hardware module to encrypt storage volumes. If you choose one of these instance types, you cannot request a VolumeKmsKeyId. For a list of instance types that use local storage, see instance store volumes. For more information about Amazon Web Services Key Management Service, see KMS encryption for more information.
The Amazon Web Services Key Management Service key that Amazon SageMaker uses to encrypt captured data at rest using Amazon S3 server-side encryption.
', 'LabelingJobOutputConfig$KmsKeyId' => 'The Amazon Web Services Key Management Service ID of the key used to encrypt the output data, if any.
If you provide your own KMS key ID, you must add the required permissions to your KMS key described in Encrypt Output Data and Storage Volume with Amazon Web Services KMS.
If you don\'t provide a KMS key ID, Amazon SageMaker uses the default Amazon Web Services KMS key for Amazon S3 for your role\'s account to encrypt your output data.
If you use a bucket policy with an s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to "aws:kms". For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the training and inference jobs used for automated data labeling.
You can only specify a VolumeKmsKeyId when you create a labeling job with automated data labeling enabled using the API operation CreateLabelingJob. You cannot specify an Amazon Web Services KMS key to encrypt the storage volume used for automated data labeling model training and inference when you create a labeling job using the console. To learn more, see Output Data and Storage Volume Encryption.
The VolumeKmsKeyId can be any of the following formats:
KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
A Key Management Service key ID to use for encrypting a model card.
', 'MonitoringClusterConfig$VolumeKmsKeyId' => 'The Key Management Service (KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the model monitoring job.
', 'MonitoringOutputConfig$KmsKeyId' => 'The Key Management Service (KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
', 'OnlineStoreSecurityConfig$KmsKeyId' => 'The Amazon Web Services Key Management Service (KMS) key ARN that SageMaker Feature Store uses to encrypt the Amazon S3 objects at rest using Amazon S3 server-side encryption.
The caller (either user or IAM role) of CreateFeatureGroup must have below permissions to the OnlineStore KmsKeyId:
"kms:Encrypt"
"kms:Decrypt"
"kms:DescribeKey"
"kms:CreateGrant"
"kms:RetireGrant"
"kms:ReEncryptFrom"
"kms:ReEncryptTo"
"kms:GenerateDataKey"
"kms:ListAliases"
"kms:ListGrants"
"kms:RevokeGrant"
The caller (either user or IAM role) to all DataPlane operations (PutRecord, GetRecord, DeleteRecord) must have the following permissions to the KmsKeyId:
"kms:Decrypt"
The Amazon Web Services Key Management Service key (Amazon Web Services KMS) that Amazon SageMaker uses to encrypt your output models with Amazon S3 server-side encryption after compilation job. If you don\'t provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role\'s account. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption. The KmsKeyId can be any of the following formats:
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
// KMS Key Alias
"alias/ExampleAlias"
// Amazon Resource Name (ARN) of a KMS Key Alias
"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must include permissions to call kms:Encrypt. If you don\'t provide a KMS key ID, SageMaker uses the default KMS key for Amazon S3 for your role\'s account. SageMaker uses server-side encryption with KMS-managed keys for OutputDataConfig. If you use a bucket policy with an s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to "aws:kms". For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KMS key policy must grant permission to the IAM role that you specify in your CreateTrainingJob, CreateTransformJob, or CreateHyperParameterTuningJob requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the processing job.
Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can\'t request a VolumeKmsKeyId when using an instance type with local storage.
For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the processing job output. KmsKeyId can be an ID of a KMS key, ARN of a KMS key, alias of a KMS key, or alias of a KMS key. The KmsKeyId is applied to all outputs.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the core dump data at rest using Amazon S3 server-side encryption. The KmsKeyId can be any of the following formats:
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
// KMS Key Alias
"alias/ExampleAlias"
// Amazon Resource Name (ARN) of a KMS Key Alias
"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must include permissions to call kms:Encrypt. If you don\'t provide a KMS key ID, SageMaker uses the default KMS key for Amazon S3 for your role\'s account. SageMaker uses server-side encryption with KMS-managed keys for OutputDataConfig. If you use a bucket policy with an s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to "aws:kms". For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint and UpdateEndpoint requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. This key will be passed to SageMaker Hosting for endpoint creation.
The SageMaker execution role must have kms:CreateGrant permission in order to encrypt data on the storage volume of the endpoints created for inference recommendation. The inference recommendation job will fail asynchronously during endpoint configuration creation if the role passed does not have kms:CreateGrant permission.
The KmsKeyId can be any of the following formats:
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:<region>:<account>:key/<key-id-12ab-34cd-56ef-1234567890ab>"
// KMS Key Alias
"alias/ExampleAlias"
// Amazon Resource Name (ARN) of a KMS Key Alias
"arn:aws:kms:<region>:<account>:alias/<ExampleAlias>"
For more information about key identifiers, see Key identifiers (KeyID) in the Amazon Web Services Key Management Service (Amazon Web Services KMS) documentation.
', 'RecommendationJobOutputConfig$KmsKeyId' => 'The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt your output artifacts with Amazon S3 server-side encryption. The SageMaker execution role must have kms:GenerateDataKey permission.
The KmsKeyId can be any of the following formats:
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:<region>:<account>:key/<key-id-12ab-34cd-56ef-1234567890ab>"
// KMS Key Alias
"alias/ExampleAlias"
// Amazon Resource Name (ARN) of a KMS Key Alias
"arn:aws:kms:<region>:<account>:alias/<ExampleAlias>"
For more information about key identifiers, see Key identifiers (KeyID) in the Amazon Web Services Key Management Service (Amazon Web Services KMS) documentation.
', 'RedshiftDatasetDefinition$KmsKeyId' => 'The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data from a Redshift execution.
', 'ResourceConfig$VolumeKmsKeyId' => 'The Amazon Web Services KMS key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the training job.
Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can\'t request a VolumeKmsKeyId when using an instance type with local storage.
For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
The VolumeKmsKeyId can be in any of the following formats:
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
The Amazon Web Services Key Management Service (KMS) key ARN of the key used to encrypt any objects written into the OfflineStore S3 location.
The IAM roleARN that is passed as a parameter to CreateFeatureGroup must have below permissions to the KmsKeyId:
"kms:GenerateDataKey"
When NotebookOutputOption is Allowed, the Amazon Web Services Key Management Service (KMS) encryption key ID used to encrypt the notebook cell output in the Amazon S3 bucket.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption. The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
If you don\'t provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role\'s account. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KMS key policy must grant permission to the IAM role that you specify in your CreateModel request. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
', 'TransformResources$VolumeKmsKeyId' => 'The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt model data on the storage volume attached to the ML compute instance(s) that run the batch transform job.
Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can\'t request a VolumeKmsKeyId when using an instance type with local storage.
For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
The VolumeKmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
The Amazon Web Services Key Management Service (KMS) encryption key ID that is used to encrypt artifacts generated by Canvas in the Amazon S3 bucket.
', ], ], 'LabelAttributeName' => [ 'base' => NULL, 'refs' => [ 'CreateLabelingJobRequest$LabelAttributeName' => 'The attribute name to use for the label in the output manifest file. This is the key for the key/value pair formed with the label that a worker assigns to the object. The LabelAttributeName must meet the following requirements.
The name can\'t end with "-metadata".
If you are using one of the following built-in task types, the attribute name must end with "-ref". If the task type you are using is not listed below, the attribute name must not end with "-ref".
Image semantic segmentation (SemanticSegmentation), and adjustment (AdjustmentSemanticSegmentation) and verification (VerificationSemanticSegmentation) labeling jobs for this task type.
Video frame object detection (VideoObjectDetection), and adjustment and verification (AdjustmentVideoObjectDetection) labeling jobs for this task type.
Video frame object tracking (VideoObjectTracking), and adjustment and verification (AdjustmentVideoObjectTracking) labeling jobs for this task type.
3D point cloud semantic segmentation (3DPointCloudSemanticSegmentation), and adjustment and verification (Adjustment3DPointCloudSemanticSegmentation) labeling jobs for this task type.
3D point cloud object tracking (3DPointCloudObjectTracking), and adjustment and verification (Adjustment3DPointCloudObjectTracking) labeling jobs for this task type.
If you are creating an adjustment or verification labeling job, you must use a different LabelAttributeName than the one used in the original labeling job. The original labeling job is the Ground Truth labeling job that produced the labels that you want verified or adjusted. To learn more about adjustment and verification labeling jobs, see Verify and Adjust Labels.
The attribute used as the label in the output manifest file.
', ], ], 'LabelCounter' => [ 'base' => NULL, 'refs' => [ 'LabelCounters$TotalLabeled' => 'The total number of objects labeled.
', 'LabelCounters$HumanLabeled' => 'The total number of objects labeled by a human worker.
', 'LabelCounters$MachineLabeled' => 'The total number of objects labeled by automated data labeling.
', 'LabelCounters$FailedNonRetryableError' => 'The total number of objects that could not be labeled due to an error.
', 'LabelCounters$Unlabeled' => 'The total number of objects not yet labeled.
', 'LabelCountersForWorkteam$HumanLabeled' => 'The total number of data objects labeled by a human worker.
', 'LabelCountersForWorkteam$PendingHuman' => 'The total number of data objects that need to be labeled by a human worker.
', 'LabelCountersForWorkteam$Total' => 'The total number of tasks in the labeling job.
', ], ], 'LabelCounters' => [ 'base' => 'Provides a breakdown of the number of objects labeled.
', 'refs' => [ 'DescribeLabelingJobResponse$LabelCounters' => 'Provides a breakdown of the number of data objects labeled by humans, the number of objects labeled by machine, the number of objects than couldn\'t be labeled, and the total number of objects labeled.
', 'LabelingJobSummary$LabelCounters' => 'Counts showing the progress of the labeling job.
', ], ], 'LabelCountersForWorkteam' => [ 'base' => 'Provides counts for human-labeled tasks in the labeling job.
', 'refs' => [ 'LabelingJobForWorkteamSummary$LabelCounters' => 'Provides information about the progress of a labeling job.
', ], ], 'LabelingJobAlgorithmSpecificationArn' => [ 'base' => NULL, 'refs' => [ 'LabelingJobAlgorithmsConfig$LabelingJobAlgorithmSpecificationArn' => 'Specifies the Amazon Resource Name (ARN) of the algorithm used for auto-labeling. You must select one of the following ARNs:
Image classification
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/image-classification
Text classification
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/text-classification
Object detection
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/object-detection
Semantic Segmentation
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/semantic-segmentation
Provides configuration information for auto-labeling of your data objects. A LabelingJobAlgorithmsConfig object must be supplied in order to use auto-labeling.
Configures the information required to perform automated data labeling.
', 'DescribeLabelingJobResponse$LabelingJobAlgorithmsConfig' => 'Configuration information for automated data labeling.
', ], ], 'LabelingJobArn' => [ 'base' => NULL, 'refs' => [ 'CreateLabelingJobResponse$LabelingJobArn' => 'The Amazon Resource Name (ARN) of the labeling job. You use this ARN to identify the labeling job.
', 'DescribeLabelingJobResponse$LabelingJobArn' => 'The Amazon Resource Name (ARN) of the labeling job.
', 'DescribeTrainingJobResponse$LabelingJobArn' => 'The Amazon Resource Name (ARN) of the SageMaker Ground Truth labeling job that created the transform or training job.
', 'DescribeTransformJobResponse$LabelingJobArn' => 'The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling job that created the transform or training job.
', 'LabelingJobSummary$LabelingJobArn' => 'The Amazon Resource Name (ARN) assigned to the labeling job when it was created.
', 'TrainingJob$LabelingJobArn' => 'The Amazon Resource Name (ARN) of the labeling job.
', 'TransformJob$LabelingJobArn' => 'The Amazon Resource Name (ARN) of the labeling job that created the transform job.
', ], ], 'LabelingJobDataAttributes' => [ 'base' => 'Attributes of the data specified by the customer. Use these to describe the data to be labeled.
', 'refs' => [ 'LabelingJobInputConfig$DataAttributes' => 'Attributes of the data specified by the customer.
', ], ], 'LabelingJobDataSource' => [ 'base' => 'Provides information about the location of input data.
You must specify at least one of the following: S3DataSource or SnsDataSource.
Use SnsDataSource to specify an SNS input topic for a streaming labeling job. If you do not specify and SNS input topic ARN, Ground Truth will create a one-time labeling job.
Use S3DataSource to specify an input manifest file for both streaming and one-time labeling jobs. Adding an S3DataSource is optional if you use SnsDataSource to create a streaming labeling job.
The location of the input data.
', ], ], 'LabelingJobForWorkteamSummary' => [ 'base' => 'Provides summary information for a work team.
', 'refs' => [ 'LabelingJobForWorkteamSummaryList$member' => NULL, ], ], 'LabelingJobForWorkteamSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListLabelingJobsForWorkteamResponse$LabelingJobSummaryList' => 'An array of LabelingJobSummary objects, each describing a labeling job.
Input configuration information for a labeling job.
', 'refs' => [ 'CreateLabelingJobRequest$InputConfig' => 'Input data for the labeling job, such as the Amazon S3 location of the data objects and the location of the manifest file that describes the data objects.
You must specify at least one of the following: S3DataSource or SnsDataSource.
Use SnsDataSource to specify an SNS input topic for a streaming labeling job. If you do not specify and SNS input topic ARN, Ground Truth will create a one-time labeling job that stops after all data objects in the input manifest file have been labeled.
Use S3DataSource to specify an input manifest file for both streaming and one-time labeling jobs. Adding an S3DataSource is optional if you use SnsDataSource to create a streaming labeling job.
If you use the Amazon Mechanical Turk workforce, your input data should not include confidential information, personal information or protected health information. Use ContentClassifiers to specify that your data is free of personally identifiable information and adult content.
Input configuration information for the labeling job, such as the Amazon S3 location of the data objects and the location of the manifest file that describes the data objects.
', 'LabelingJobSummary$InputConfig' => 'Input configuration for the labeling job.
', ], ], 'LabelingJobName' => [ 'base' => NULL, 'refs' => [ 'CreateLabelingJobRequest$LabelingJobName' => 'The name of the labeling job. This name is used to identify the job in a list of labeling jobs. Labeling job names must be unique within an Amazon Web Services account and region. LabelingJobName is not case sensitive. For example, Example-job and example-job are considered the same labeling job name by Ground Truth.
The name of the labeling job to return information for.
', 'DescribeLabelingJobResponse$LabelingJobName' => 'The name assigned to the labeling job when it was created.
', 'LabelingJobForWorkteamSummary$LabelingJobName' => 'The name of the labeling job that the work team is assigned to.
', 'LabelingJobSummary$LabelingJobName' => 'The name of the labeling job.
', 'StopLabelingJobRequest$LabelingJobName' => 'The name of the labeling job to stop.
', ], ], 'LabelingJobOutput' => [ 'base' => 'Specifies the location of the output produced by the labeling job.
', 'refs' => [ 'DescribeLabelingJobResponse$LabelingJobOutput' => 'The location of the output produced by the labeling job.
', 'LabelingJobSummary$LabelingJobOutput' => 'The location of the output produced by the labeling job.
', ], ], 'LabelingJobOutputConfig' => [ 'base' => 'Output configuration information for a labeling job.
', 'refs' => [ 'CreateLabelingJobRequest$OutputConfig' => 'The location of the output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt the output data, if any.
', 'DescribeLabelingJobResponse$OutputConfig' => 'The location of the job\'s output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt the output data, if any.
', ], ], 'LabelingJobResourceConfig' => [ 'base' => 'Configure encryption on the storage volume attached to the ML compute instance used to run automated data labeling model training and inference.
', 'refs' => [ 'LabelingJobAlgorithmsConfig$LabelingJobResourceConfig' => 'Provides configuration information for a labeling job.
', ], ], 'LabelingJobS3DataSource' => [ 'base' => 'The Amazon S3 location of the input data objects.
', 'refs' => [ 'LabelingJobDataSource$S3DataSource' => 'The Amazon S3 location of the input data objects.
', ], ], 'LabelingJobSnsDataSource' => [ 'base' => 'An Amazon SNS data source used for streaming labeling jobs.
', 'refs' => [ 'LabelingJobDataSource$SnsDataSource' => 'An Amazon SNS data source used for streaming labeling jobs. To learn more, see Send Data to a Streaming Labeling Job.
', ], ], 'LabelingJobStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeLabelingJobResponse$LabelingJobStatus' => 'The processing status of the labeling job.
', 'LabelingJobSummary$LabelingJobStatus' => 'The current status of the labeling job.
', 'ListLabelingJobsRequest$StatusEquals' => 'A filter that retrieves only labeling jobs with a specific status.
', ], ], 'LabelingJobStoppingConditions' => [ 'base' => 'A set of conditions for stopping a labeling job. If any of the conditions are met, the job is automatically stopped. You can use these conditions to control the cost of data labeling.
Labeling jobs fail after 30 days with an appropriate client error message.
A set of conditions for stopping the labeling job. If any of the conditions are met, the job is automatically stopped. You can use these conditions to control the cost of data labeling.
', 'DescribeLabelingJobResponse$StoppingConditions' => 'A set of conditions for stopping a labeling job. If any of the conditions are met, the job is automatically stopped.
', ], ], 'LabelingJobSummary' => [ 'base' => 'Provides summary information about a labeling job.
', 'refs' => [ 'LabelingJobSummaryList$member' => NULL, ], ], 'LabelingJobSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListLabelingJobsResponse$LabelingJobSummaryList' => 'An array of LabelingJobSummary objects, each describing a labeling job.
The Amazon Resource Name (ARN) of a Lambda function implements the logic for annotation consolidation and to process output data.
This parameter is required for all labeling jobs. For built-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for AnnotationConsolidationLambdaArn. For custom labeling workflows, see Post-annotation Lambda.
Bounding box - Finds the most similar boxes from different workers based on the Jaccard index of the boxes.
arn:aws:lambda:us-east-1:432418664414:function:ACS-BoundingBox
arn:aws:lambda:us-east-2:266458841044:function:ACS-BoundingBox
arn:aws:lambda:us-west-2:081040173940:function:ACS-BoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:ACS-BoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-BoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-BoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:ACS-BoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:ACS-BoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-BoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:ACS-BoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-BoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:ACS-BoundingBox
Image classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClass
arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClass
arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClass
Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClassMultiLabel
Semantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as "votes" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:ACS-SemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-SemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-SemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-SemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-SemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-SemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-SemanticSegmentation
Text classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClass
arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClass
arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClass
Multi-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClassMultiLabel
Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.
arn:aws:lambda:us-east-1:432418664414:function:ACS-NamedEntityRecognition
arn:aws:lambda:us-east-2:266458841044:function:ACS-NamedEntityRecognition
arn:aws:lambda:us-west-2:081040173940:function:ACS-NamedEntityRecognition
arn:aws:lambda:eu-west-1:568282634449:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-south-1:565803892007:function:ACS-NamedEntityRecognition
arn:aws:lambda:eu-central-1:203001061592:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-NamedEntityRecognition
arn:aws:lambda:eu-west-2:487402164563:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-NamedEntityRecognition
arn:aws:lambda:ca-central-1:918755190332:function:ACS-NamedEntityRecognition
Video Classification - Use this task type when you need workers to classify videos using predefined labels that you specify. Workers are shown videos and are asked to choose one label for each video.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoMultiClass
arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoMultiClass
arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoMultiClass
Video Frame Object Detection - Use this task type to have workers identify and locate objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to identify and localize various objects in a series of video frames, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectDetection
Video Frame Object Tracking - Use this task type to have workers track the movement of objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to track the movement of objects, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectTracking
3D Point Cloud Object Detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectDetection
3D Point Cloud Object Tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectTracking
3D Point Cloud Semantic Segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudSemanticSegmentation
Use the following ARNs for Label Verification and Adjustment Jobs
Use label verification and adjustment jobs to review and adjust labels. To learn more, see Verify and Adjust Labels .
Semantic Segmentation Adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as "votes" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentSemanticSegmentation
Semantic Segmentation Verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationSemanticSegmentation
Bounding Box Adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentBoundingBox
Bounding Box Verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationBoundingBox
Video Frame Object Detection Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to classify and localize objects in a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectDetection
Video Frame Object Tracking Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to track object movement across a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectTracking
3D Point Cloud Object Detection Adjustment - Use this task type when you want workers to adjust 3D cuboids around objects in a 3D point cloud.
arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectDetection
3D Point Cloud Object Tracking Adjustment - Use this task type when you want workers to adjust 3D cuboids around objects that appear in a sequence of 3D point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectTracking
3D Point Cloud Semantic Segmentation Adjustment - Use this task type when you want workers to adjust a point-level semantic segmentation masks using a paint tool.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudSemanticSegmentation
The Amazon Resource Name (ARN) of a Lambda function that is run before a data object is sent to a human worker. Use this function to provide input to a custom labeling job.
For built-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for PreHumanTaskLambdaArn. For custom labeling workflows, see Pre-annotation Lambda.
Bounding box - Finds the most similar boxes from different workers based on the Jaccard index of the boxes.
arn:aws:lambda:us-east-1:432418664414:function:PRE-BoundingBox
arn:aws:lambda:us-east-2:266458841044:function:PRE-BoundingBox
arn:aws:lambda:us-west-2:081040173940:function:PRE-BoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:PRE-BoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:PRE-BoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:PRE-BoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:PRE-BoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-BoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-BoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:PRE-BoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-BoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-BoundingBox
Image classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClass
arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClass
arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClass
Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClassMultiLabel
Semantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as "votes" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:PRE-SemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-SemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-SemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-SemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-SemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-SemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-SemanticSegmentation
Text classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClass
arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClass
arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClass
Multi-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClassMultiLabel
Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.
arn:aws:lambda:us-east-1:432418664414:function:PRE-NamedEntityRecognition
arn:aws:lambda:us-east-2:266458841044:function:PRE-NamedEntityRecognition
arn:aws:lambda:us-west-2:081040173940:function:PRE-NamedEntityRecognition
arn:aws:lambda:ca-central-1:918755190332:function:PRE-NamedEntityRecognition
arn:aws:lambda:eu-west-1:568282634449:function:PRE-NamedEntityRecognition
arn:aws:lambda:eu-west-2:487402164563:function:PRE-NamedEntityRecognition
arn:aws:lambda:eu-central-1:203001061592:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-south-1:565803892007:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-NamedEntityRecognition
Video Classification - Use this task type when you need workers to classify videos using predefined labels that you specify. Workers are shown videos and are asked to choose one label for each video.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoMultiClass
arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoMultiClass
arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoMultiClass
Video Frame Object Detection - Use this task type to have workers identify and locate objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to identify and localize various objects in a series of video frames, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectDetection
Video Frame Object Tracking - Use this task type to have workers track the movement of objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to track the movement of objects, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectTracking
3D Point Cloud Modalities
Use the following pre-annotation lambdas for 3D point cloud labeling modality tasks. See 3D Point Cloud Task types to learn more.
3D Point Cloud Object Detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectDetection
3D Point Cloud Object Tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectTracking
3D Point Cloud Semantic Segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify.
arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudSemanticSegmentation
Use the following ARNs for Label Verification and Adjustment Jobs
Use label verification and adjustment jobs to review and adjust labels. To learn more, see Verify and Adjust Labels .
Bounding box verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationBoundingBox
Bounding box adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentBoundingBox
Semantic segmentation verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationSemanticSegmentation
Semantic segmentation adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as "votes" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentSemanticSegmentation
Video Frame Object Detection Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to classify and localize objects in a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectDetection
Video Frame Object Tracking Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to track object movement across a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectTracking
3D point cloud object detection adjustment - Adjust 3D cuboids in a point cloud frame.
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectDetection
3D point cloud object tracking adjustment - Adjust 3D cuboids across a sequence of point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectTracking
3D point cloud semantic segmentation adjustment - Adjust semantic segmentation masks in a 3D point cloud.
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudSemanticSegmentation
The Amazon Resource Name (ARN) of a Lambda function. The function is run before each data object is sent to a worker.
', 'LabelingJobSummary$AnnotationConsolidationLambdaArn' => 'The Amazon Resource Name (ARN) of the Lambda function used to consolidate the annotations from individual workers into a label for a data object. For more information, see Annotation Consolidation.
', ], ], 'LambdaStepMetadata' => [ 'base' => 'Metadata for a Lambda step.
', 'refs' => [ 'PipelineExecutionStepMetadata$Lambda' => 'The Amazon Resource Name (ARN) of the Lambda function that was run by this step execution and a list of output parameters.
', ], ], 'LastModifiedTime' => [ 'base' => NULL, 'refs' => [ 'CodeRepositorySummary$LastModifiedTime' => 'The date and time that the Git repository was last modified.
', 'CompilationJobSummary$LastModifiedTime' => 'The time when the model compilation job was last modified.
', 'DescribeCodeRepositoryOutput$LastModifiedTime' => 'The date and time that the repository was last changed.
', 'DescribeCompilationJobResponse$LastModifiedTime' => 'The time that the status of the model compilation job was last modified.
', 'DescribeDomainResponse$LastModifiedTime' => 'The last modified time.
', 'DescribeFeatureGroupResponse$LastModifiedTime' => 'A timestamp indicating when the feature group was last updated.
', 'DescribeFeatureMetadataResponse$LastModifiedTime' => 'A timestamp indicating when the metadata for the feature group was modified. For example, if you add a parameter describing the feature, the timestamp changes to reflect the last time you
', 'DescribeInferenceRecommendationsJobResponse$LastModifiedTime' => 'A timestamp that shows when the job was last modified.
', 'DescribeNotebookInstanceLifecycleConfigOutput$LastModifiedTime' => 'A timestamp that tells when the lifecycle configuration was last modified.
', 'DescribeNotebookInstanceOutput$LastModifiedTime' => 'A timestamp. Use this parameter to retrieve the time when the notebook instance was last modified.
', 'DescribeSpaceResponse$LastModifiedTime' => 'The last modified time.
', 'DescribeUserProfileResponse$LastModifiedTime' => 'The last modified time.
', 'DomainDetails$LastModifiedTime' => 'The last modified time.
', 'FeatureGroup$LastModifiedTime' => 'A timestamp indicating the last time you updated the feature group.
', 'FeatureMetadata$LastModifiedTime' => 'A timestamp indicating when the feature was last modified.
', 'InferenceRecommendationsJob$LastModifiedTime' => 'A timestamp that shows when the job was last modified.
', 'ListCompilationJobsRequest$LastModifiedTimeAfter' => 'A filter that returns the model compilation jobs that were modified after a specified time.
', 'ListCompilationJobsRequest$LastModifiedTimeBefore' => 'A filter that returns the model compilation jobs that were modified before a specified time.
', 'ListInferenceRecommendationsJobsRequest$LastModifiedTimeAfter' => 'A filter that returns only jobs that were last modified after the specified time (timestamp).
', 'ListInferenceRecommendationsJobsRequest$LastModifiedTimeBefore' => 'A filter that returns only jobs that were last modified before the specified time (timestamp).
', 'ListNotebookInstanceLifecycleConfigsInput$LastModifiedTimeBefore' => 'A filter that returns only lifecycle configurations that were modified before the specified time (timestamp).
', 'ListNotebookInstanceLifecycleConfigsInput$LastModifiedTimeAfter' => 'A filter that returns only lifecycle configurations that were modified after the specified time (timestamp).
', 'ListNotebookInstancesInput$LastModifiedTimeBefore' => 'A filter that returns only notebook instances that were modified before the specified time (timestamp).
', 'ListNotebookInstancesInput$LastModifiedTimeAfter' => 'A filter that returns only notebook instances that were modified after the specified time (timestamp).
', 'NotebookInstanceLifecycleConfigSummary$LastModifiedTime' => 'A timestamp that tells when the lifecycle configuration was last modified.
', 'NotebookInstanceSummary$LastModifiedTime' => 'A timestamp that shows when the notebook instance was last modified.
', 'SpaceDetails$LastModifiedTime' => 'The last modified time.
', 'UserProfileDetails$LastModifiedTime' => 'The last modified time.
', ], ], 'LastUpdateStatus' => [ 'base' => 'A value that indicates whether the update was successful.
', 'refs' => [ 'DescribeFeatureGroupResponse$LastUpdateStatus' => 'A value indicating whether the update made to the feature group was successful.
', 'FeatureGroup$LastUpdateStatus' => 'A value that indicates whether the feature group was updated successfully.
', ], ], 'LastUpdateStatusValue' => [ 'base' => NULL, 'refs' => [ 'LastUpdateStatus$Status' => 'A value that indicates whether the update was made successful.
', ], ], 'LifecycleConfigArns' => [ 'base' => NULL, 'refs' => [ 'JupyterServerAppSettings$LifecycleConfigArns' => ' The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the JupyterServerApp. If you use this parameter, the DefaultResourceSpec parameter is also required.
To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the the user profile or domain.
To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.
A list of properties to add to the action.
', 'CreateArtifactRequest$Properties' => 'A list of properties to add to the artifact.
', 'CreateContextRequest$Properties' => 'A list of properties to add to the context.
', 'DescribeActionResponse$Properties' => 'A list of the action\'s properties.
', 'DescribeArtifactResponse$Properties' => 'A list of the artifact\'s properties.
', 'DescribeContextResponse$Properties' => 'A list of the context\'s properties.
', 'UpdateActionRequest$Properties' => 'The new list of properties. Overwrites the current property list.
', 'UpdateArtifactRequest$Properties' => 'The new list of properties. Overwrites the current property list.
', 'UpdateContextRequest$Properties' => 'The new list of properties. Overwrites the current property list.
', ], ], 'LineageGroupArn' => [ 'base' => NULL, 'refs' => [ 'DescribeActionResponse$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group.
', 'DescribeArtifactResponse$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group.
', 'DescribeContextResponse$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group.
', 'DescribeLineageGroupResponse$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group.
', 'DescribeTrialComponentResponse$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group.
', 'GetLineageGroupPolicyResponse$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group.
', 'LineageGroupSummary$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group resource.
', 'TrialComponent$LineageGroupArn' => 'The Amazon Resource Name (ARN) of the lineage group resource.
', ], ], 'LineageGroupNameOrArn' => [ 'base' => NULL, 'refs' => [ 'GetLineageGroupPolicyRequest$LineageGroupName' => 'The name or Amazon Resource Name (ARN) of the lineage group.
', ], ], 'LineageGroupSummaries' => [ 'base' => NULL, 'refs' => [ 'ListLineageGroupsResponse$LineageGroupSummaries' => 'A list of lineage groups and their properties.
', ], ], 'LineageGroupSummary' => [ 'base' => 'Lists a summary of the properties of a lineage group. A lineage group provides a group of shareable lineage entity resources.
', 'refs' => [ 'LineageGroupSummaries$member' => NULL, ], ], 'LineageType' => [ 'base' => NULL, 'refs' => [ 'QueryLineageTypes$member' => NULL, 'Vertex$LineageType' => 'The type of resource of the lineage entity.
', ], ], 'ListActionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListActionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListAlgorithmsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListAlgorithmsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListAliasesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListAliasesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListAppImageConfigsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListAppImageConfigsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListAppsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListAppsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListArtifactsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListArtifactsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListAssociationsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListAssociationsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListAutoMLJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListAutoMLJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListCandidatesForAutoMLJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListCandidatesForAutoMLJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListCodeRepositoriesInput' => [ 'base' => NULL, 'refs' => [], ], 'ListCodeRepositoriesOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListCompilationJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListCompilationJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListCompilationJobsSortBy' => [ 'base' => NULL, 'refs' => [ 'ListCompilationJobsRequest$SortBy' => 'The field by which to sort results. The default is CreationTime.
The column to sort by.
', ], ], 'ListDevicesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListDevicesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListDomainsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListDomainsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListEdgeDeploymentPlansRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListEdgeDeploymentPlansResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListEdgeDeploymentPlansSortBy' => [ 'base' => NULL, 'refs' => [ 'ListEdgeDeploymentPlansRequest$SortBy' => 'The column by which to sort the edge deployment plans. Can be one of NAME, DEVICEFLEETNAME, CREATIONTIME, LASTMODIFIEDTIME.
Use to specify what column to sort by.
', ], ], 'ListEndpointConfigsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListEndpointConfigsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListEndpointsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListEndpointsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListExperimentsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListExperimentsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListFeatureGroupsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListFeatureGroupsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListFlowDefinitionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListFlowDefinitionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListHubContentVersionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListHubContentVersionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListHubContentsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListHubContentsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListHubsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListHubsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListHumanTaskUisRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListHumanTaskUisResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListHyperParameterTuningJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListHyperParameterTuningJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListImageVersionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListImageVersionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListImagesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListImagesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceExperimentsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceExperimentsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceRecommendationsJobStepsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceRecommendationsJobStepsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceRecommendationsJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceRecommendationsJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListInferenceRecommendationsJobsSortBy' => [ 'base' => NULL, 'refs' => [ 'ListInferenceRecommendationsJobsRequest$SortBy' => 'The parameter by which to sort the results.
', ], ], 'ListLabelingJobsForWorkteamRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListLabelingJobsForWorkteamResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListLabelingJobsForWorkteamSortByOptions' => [ 'base' => NULL, 'refs' => [ 'ListLabelingJobsForWorkteamRequest$SortBy' => 'The field to sort results by. The default is CreationTime.
A list of properties to remove.
', 'UpdateArtifactRequest$PropertiesToRemove' => 'A list of properties to remove.
', 'UpdateContextRequest$PropertiesToRemove' => 'A list of properties to remove.
', ], ], 'ListLineageGroupsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListLineageGroupsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListMaxResults' => [ 'base' => NULL, 'refs' => [ 'ListDeviceFleetsRequest$MaxResults' => 'The maximum number of results to select.
', 'ListDevicesRequest$MaxResults' => 'Maximum number of results to select.
', 'ListEdgeDeploymentPlansRequest$MaxResults' => 'The maximum number of results to select (50 by default).
', 'ListEdgePackagingJobsRequest$MaxResults' => 'Maximum number of results to select.
', 'ListStageDevicesRequest$MaxResults' => 'The maximum number of requests to select.
', ], ], 'ListModelBiasJobDefinitionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelBiasJobDefinitionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelCardExportJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelCardExportJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelCardVersionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelCardVersionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelCardsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelCardsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelExplainabilityJobDefinitionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelExplainabilityJobDefinitionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelMetadataRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelMetadataResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelPackageGroupsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListModelPackageGroupsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListModelPackagesInput' => [ 'base' => NULL, 'refs' => [], ], 'ListModelPackagesOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListModelQualityJobDefinitionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListModelQualityJobDefinitionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListModelsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListModelsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringAlertHistoryRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringAlertHistoryResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringAlertsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringAlertsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringExecutionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringExecutionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringSchedulesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListMonitoringSchedulesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListNotebookInstanceLifecycleConfigsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListNotebookInstanceLifecycleConfigsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListNotebookInstancesInput' => [ 'base' => NULL, 'refs' => [], ], 'ListNotebookInstancesOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelineExecutionStepsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelineExecutionStepsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelineExecutionsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelineExecutionsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelineParametersForExecutionRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelineParametersForExecutionResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelinesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListPipelinesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListProcessingJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListProcessingJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListProjectsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListProjectsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListResourceCatalogsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListResourceCatalogsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListSpacesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListSpacesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListStageDevicesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListStageDevicesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListStudioLifecycleConfigsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListStudioLifecycleConfigsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListSubscribedWorkteamsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListSubscribedWorkteamsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListTagsInput' => [ 'base' => NULL, 'refs' => [], ], 'ListTagsMaxResults' => [ 'base' => NULL, 'refs' => [ 'ListTagsInput$MaxResults' => 'Maximum number of tags to return.
', ], ], 'ListTagsOutput' => [ 'base' => NULL, 'refs' => [], ], 'ListTrainingJobsForHyperParameterTuningJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListTrainingJobsForHyperParameterTuningJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListTrainingJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListTrainingJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListTransformJobsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListTransformJobsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListTrialComponentKey256' => [ 'base' => NULL, 'refs' => [ 'UpdateTrialComponentRequest$ParametersToRemove' => 'The hyperparameters to remove from the component.
', 'UpdateTrialComponentRequest$InputArtifactsToRemove' => 'The input artifacts to remove from the component.
', 'UpdateTrialComponentRequest$OutputArtifactsToRemove' => 'The output artifacts to remove from the component.
', ], ], 'ListTrialComponentsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListTrialComponentsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListTrialsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListTrialsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListUserProfilesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListUserProfilesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListWorkforcesRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListWorkforcesResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListWorkforcesSortByOptions' => [ 'base' => NULL, 'refs' => [ 'ListWorkforcesRequest$SortBy' => 'Sort workforces using the workforce name or creation date.
', ], ], 'ListWorkteamsRequest' => [ 'base' => NULL, 'refs' => [], ], 'ListWorkteamsResponse' => [ 'base' => NULL, 'refs' => [], ], 'ListWorkteamsSortByOptions' => [ 'base' => NULL, 'refs' => [ 'ListWorkteamsRequest$SortBy' => 'The field to sort results by. The default is CreationTime.
The number of Edge Manager agents.
', 'DeviceStats$ConnectedDeviceCount' => 'The number of devices connected with a heartbeat.
', 'DeviceStats$RegisteredDeviceCount' => 'The number of registered devices.
', 'EdgeModelStat$OfflineDeviceCount' => 'The number of devices that have this model version and do not have a heart beat.
', 'EdgeModelStat$ConnectedDeviceCount' => 'The number of devices that have this model version and have a heart beat.
', 'EdgeModelStat$ActiveDeviceCount' => 'The number of devices that have this model version, a heart beat, and are currently running.
', 'EdgeModelStat$SamplingDeviceCount' => 'The number of devices with this model version and are producing sample data.
', ], ], 'MLFramework' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$MLFramework' => 'The machine learning framework vended in the image version.
', 'DescribeImageVersionResponse$MLFramework' => 'The machine learning framework vended in the image version.
', 'UpdateImageVersionRequest$MLFramework' => 'The machine learning framework vended in the image version.
', ], ], 'MaxAutoMLJobRuntimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobCompletionCriteria$MaxAutoMLJobRuntimeInSeconds' => 'The maximum runtime, in seconds, an AutoML job has to complete.
If an AutoML job exceeds the maximum runtime, the job is stopped automatically and its processing is ended gracefully. The AutoML job identifies the best model whose training was completed and marks it as the best-performing model. Any unfinished steps of the job, such as automatic one-click Autopilot model deployment, are not completed.
', ], ], 'MaxCandidates' => [ 'base' => NULL, 'refs' => [ 'AutoMLJobCompletionCriteria$MaxCandidates' => 'The maximum number of times a training job is allowed to run.
For text and image classification, time-series forecasting, as well as text generation (LLMs fine-tuning) problem types, the supported value is 1. For tabular problem types, the maximum value is 750.
', ], ], 'MaxConcurrentInvocationsPerInstance' => [ 'base' => NULL, 'refs' => [ 'AsyncInferenceClientConfig$MaxConcurrentInvocationsPerInstance' => 'The maximum number of concurrent requests sent by the SageMaker client to the model container. If no value is provided, SageMaker chooses an optimal value.
', ], ], 'MaxConcurrentTaskCount' => [ 'base' => NULL, 'refs' => [ 'HumanTaskConfig$MaxConcurrentTaskCount' => 'Defines the maximum number of data objects that can be labeled by human workers at the same time. Also referred to as batch size. Each object may have more than one worker at one time. The default value is 1000 objects. To increase the maximum value to 5000 objects, contact Amazon Web Services Support.
', ], ], 'MaxConcurrentTransforms' => [ 'base' => NULL, 'refs' => [ 'CreateTransformJobRequest$MaxConcurrentTransforms' => 'The maximum number of parallel requests that can be sent to each instance in a transform job. If MaxConcurrentTransforms is set to 0 or left unset, Amazon SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 1. For more information on execution-parameters, see How Containers Serve Requests. For built-in algorithms, you don\'t need to set a value for MaxConcurrentTransforms.
The maximum number of parallel requests on each instance node that can be launched in a transform job. The default value is 1.
', 'TransformJob$MaxConcurrentTransforms' => 'The maximum number of parallel requests that can be sent to each instance in a transform job. If MaxConcurrentTransforms is set to 0 or left unset, SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 1. For built-in algorithms, you don\'t need to set a value for MaxConcurrentTransforms.
The maximum number of parallel requests that can be sent to each instance in a transform job. The default value is 1.
', ], ], 'MaxHumanLabeledObjectCount' => [ 'base' => NULL, 'refs' => [ 'LabelingJobStoppingConditions$MaxHumanLabeledObjectCount' => 'The maximum number of objects that can be labeled by human workers.
', ], ], 'MaxNumberOfTests' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobResourceLimit$MaxNumberOfTests' => 'Defines the maximum number of load tests.
', ], ], 'MaxNumberOfTrainingJobs' => [ 'base' => NULL, 'refs' => [ 'ResourceLimits$MaxNumberOfTrainingJobs' => 'The maximum number of training jobs that a hyperparameter tuning job can launch.
', ], ], 'MaxNumberOfTrainingJobsNotImproving' => [ 'base' => NULL, 'refs' => [ 'BestObjectiveNotImproving$MaxNumberOfTrainingJobsNotImproving' => 'The number of training jobs that have failed to improve model performance by 1% or greater over prior training jobs as evaluated against an objective function.
', ], ], 'MaxParallelExecutionSteps' => [ 'base' => NULL, 'refs' => [ 'ParallelismConfiguration$MaxParallelExecutionSteps' => 'The max number of steps that can be executed in parallel.
', ], ], 'MaxParallelOfTests' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobResourceLimit$MaxParallelOfTests' => 'Defines the maximum number of parallel load tests.
', ], ], 'MaxParallelTrainingJobs' => [ 'base' => NULL, 'refs' => [ 'ResourceLimits$MaxParallelTrainingJobs' => 'The maximum number of concurrent training jobs that a hyperparameter tuning job can launch.
', ], ], 'MaxPayloadInMB' => [ 'base' => NULL, 'refs' => [ 'CreateTransformJobRequest$MaxPayloadInMB' => 'The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6 MB.
The value of MaxPayloadInMB cannot be greater than 100 MB. If you specify the MaxConcurrentTransforms parameter, the value of (MaxConcurrentTransforms * MaxPayloadInMB) also cannot exceed 100 MB.
For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0. This feature works only in supported algorithms. Currently, Amazon SageMaker built-in algorithms do not support HTTP chunked encoding.
The maximum payload size, in MB, used in the transform job.
', 'TransformJob$MaxPayloadInMB' => 'The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6 MB. For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0. This feature works only in supported algorithms. Currently, SageMaker built-in algorithms do not support HTTP chunked encoding.
The maximum payload size allowed, in MB. A payload is the data portion of a record (without metadata).
', ], ], 'MaxPendingTimeInSeconds' => [ 'base' => 'Maximum job scheduler pending time in seconds.', 'refs' => [ 'StoppingCondition$MaxPendingTimeInSeconds' => 'The maximum length of time, in seconds, that a training or compilation job can be pending before it is stopped.
', ], ], 'MaxPercentageOfInputDatasetLabeled' => [ 'base' => NULL, 'refs' => [ 'LabelingJobStoppingConditions$MaxPercentageOfInputDatasetLabeled' => 'The maximum number of input data objects that should be labeled.
', ], ], 'MaxResults' => [ 'base' => NULL, 'refs' => [ 'ListActionsRequest$MaxResults' => 'The maximum number of actions to return in the response. The default value is 10.
', 'ListAlgorithmsInput$MaxResults' => 'The maximum number of algorithms to return in the response.
', 'ListAliasesRequest$MaxResults' => 'The maximum number of aliases to return.
', 'ListAppImageConfigsRequest$MaxResults' => 'The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken is provided in the response. To resume pagination, provide the NextToken value in the as part of a subsequent call. The default value is 10.
The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken is provided in the response. To resume pagination, provide the NextToken value in the as part of a subsequent call. The default value is 10.
The maximum number of artifacts to return in the response. The default value is 10.
', 'ListAssociationsRequest$MaxResults' => 'The maximum number of associations to return in the response. The default value is 10.
', 'ListCodeRepositoriesInput$MaxResults' => 'The maximum number of Git repositories to return in the response.
', 'ListCompilationJobsRequest$MaxResults' => 'The maximum number of model compilation jobs to return in the response.
', 'ListContextsRequest$MaxResults' => 'The maximum number of contexts to return in the response. The default value is 10.
', 'ListDataQualityJobDefinitionsRequest$MaxResults' => 'The maximum number of data quality monitoring job definitions to return in the response.
', 'ListDomainsRequest$MaxResults' => 'The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken is provided in the response. To resume pagination, provide the NextToken value in the as part of a subsequent call. The default value is 10.
The maximum number of training jobs to return in the response.
', 'ListEndpointsInput$MaxResults' => 'The maximum number of endpoints to return in the response. This value defaults to 10.
', 'ListExperimentsRequest$MaxResults' => 'The maximum number of experiments to return in the response. The default value is 10.
', 'ListFlowDefinitionsRequest$MaxResults' => 'The total number of items to return. If the total number of available items is more than the value specified in MaxResults, then a NextToken will be provided in the output that you can use to resume pagination.
The maximum number of hub content versions to list.
', 'ListHubContentsRequest$MaxResults' => 'The maximum amount of hub content to list.
', 'ListHubsRequest$MaxResults' => 'The maximum number of hubs to list.
', 'ListHumanTaskUisRequest$MaxResults' => 'The total number of items to return. If the total number of available items is more than the value specified in MaxResults, then a NextToken will be provided in the output that you can use to resume pagination.
The maximum number of tuning jobs to return. The default value is 10.
', 'ListImageVersionsRequest$MaxResults' => 'The maximum number of versions to return in the response. The default value is 10.
', 'ListImagesRequest$MaxResults' => 'The maximum number of images to return in the response. The default value is 10.
', 'ListInferenceExperimentsRequest$MaxResults' => 'The maximum number of results to select.
', 'ListInferenceRecommendationsJobStepsRequest$MaxResults' => 'The maximum number of results to return.
', 'ListInferenceRecommendationsJobsRequest$MaxResults' => 'The maximum number of recommendations to return in the response.
', 'ListLabelingJobsForWorkteamRequest$MaxResults' => 'The maximum number of labeling jobs to return in each page of the response.
', 'ListLabelingJobsRequest$MaxResults' => 'The maximum number of labeling jobs to return in each page of the response.
', 'ListLineageGroupsRequest$MaxResults' => 'The maximum number of endpoints to return in the response. This value defaults to 10.
', 'ListModelBiasJobDefinitionsRequest$MaxResults' => 'The maximum number of model bias jobs to return in the response. The default value is 10.
', 'ListModelCardExportJobsRequest$MaxResults' => 'The maximum number of model card export jobs to list.
', 'ListModelCardVersionsRequest$MaxResults' => 'The maximum number of model card versions to list.
', 'ListModelCardsRequest$MaxResults' => 'The maximum number of model cards to list.
', 'ListModelExplainabilityJobDefinitionsRequest$MaxResults' => 'The maximum number of jobs to return in the response. The default value is 10.
', 'ListModelMetadataRequest$MaxResults' => 'The maximum number of models to return in the response.
', 'ListModelPackageGroupsInput$MaxResults' => 'The maximum number of results to return in the response.
', 'ListModelPackagesInput$MaxResults' => 'The maximum number of model packages to return in the response.
', 'ListModelQualityJobDefinitionsRequest$MaxResults' => 'The maximum number of results to return in a call to ListModelQualityJobDefinitions.
The maximum number of models to return in the response.
', 'ListMonitoringAlertHistoryRequest$MaxResults' => 'The maximum number of results to display. The default is 100.
', 'ListMonitoringAlertsRequest$MaxResults' => 'The maximum number of results to display. The default is 100.
', 'ListMonitoringExecutionsRequest$MaxResults' => 'The maximum number of jobs to return in the response. The default value is 10.
', 'ListMonitoringSchedulesRequest$MaxResults' => 'The maximum number of jobs to return in the response. The default value is 10.
', 'ListNotebookInstanceLifecycleConfigsInput$MaxResults' => 'The maximum number of lifecycle configurations to return in the response.
', 'ListNotebookInstancesInput$MaxResults' => 'The maximum number of notebook instances to return.
', 'ListPipelineExecutionStepsRequest$MaxResults' => 'The maximum number of pipeline execution steps to return in the response.
', 'ListPipelineExecutionsRequest$MaxResults' => 'The maximum number of pipeline executions to return in the response.
', 'ListPipelineParametersForExecutionRequest$MaxResults' => 'The maximum number of parameters to return in the response.
', 'ListPipelinesRequest$MaxResults' => 'The maximum number of pipelines to return in the response.
', 'ListProcessingJobsRequest$MaxResults' => 'The maximum number of processing jobs to return in the response.
', 'ListProjectsInput$MaxResults' => 'The maximum number of projects to return in the response.
', 'ListResourceCatalogsRequest$MaxResults' => ' The maximum number of results returned by ListResourceCatalogs.
The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken is provided in the response. To resume pagination, provide the NextToken value in the as part of a subsequent call. The default value is 10.
The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken is provided in the response. To resume pagination, provide the NextToken value in the as part of a subsequent call. The default value is 10.
The maximum number of work teams to return in each page of the response.
', 'ListTrainingJobsForHyperParameterTuningJobRequest$MaxResults' => 'The maximum number of training jobs to return. The default value is 10.
', 'ListTrainingJobsRequest$MaxResults' => 'The maximum number of training jobs to return in the response.
', 'ListTransformJobsRequest$MaxResults' => 'The maximum number of transform jobs to return in the response. The default value is 10.
The maximum number of components to return in the response. The default value is 10.
', 'ListTrialsRequest$MaxResults' => 'The maximum number of trials to return in the response. The default value is 10.
', 'ListUserProfilesRequest$MaxResults' => 'The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken is provided in the response. To resume pagination, provide the NextToken value in the as part of a subsequent call. The default value is 10.
The maximum number of workforces returned in the response.
', 'ListWorkteamsRequest$MaxResults' => 'The maximum number of work teams to return in each page of the response.
', 'SearchRequest$MaxResults' => 'The maximum number of results to return.
', ], ], 'MaxRuntimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'StoppingCondition$MaxRuntimeInSeconds' => 'The maximum length of time, in seconds, that a training or compilation job can run before it is stopped.
For compilation jobs, if the job does not complete during this time, a TimeOut error is generated. We recommend starting with 900 seconds and increasing as necessary based on your model.
For all other jobs, if the job does not complete during this time, SageMaker ends the job. When RetryStrategy is specified in the job request, MaxRuntimeInSeconds specifies the maximum time for all of the attempts in total, not each individual attempt. The default value is 1 day. The maximum value is 28 days.
The maximum time that a TrainingJob can run in total, including any time spent publishing metrics or archiving and uploading models after it has been stopped, is 30 days.
The maximum time, in seconds, that each training job executed inside hyperparameter tuning is allowed to run as part of a hyperparameter tuning job. For more information, see the StoppingCondition used by the CreateHyperParameterTuningJob action.
For job V2s (jobs created by calling CreateAutoMLJobV2), this field controls the runtime of the job candidate.
The maximum length of time, in seconds, that a managed Spot training job has to complete. It is the amount of time spent waiting for Spot capacity plus the amount of time the job can run. It must be equal to or greater than MaxRuntimeInSeconds. If the job does not complete during this time, SageMaker ends the job.
When RetryStrategy is specified in the job request, MaxWaitTimeInSeconds specifies the maximum time for all of the attempts in total, not each individual attempt.
Maximum execution timeout for the deployment. Note that the timeout value should be larger than the total waiting time specified in TerminationWaitInSeconds and WaitIntervalInSeconds.
The time limit for the total deployment. Exceeding this limit causes a timeout.
', ], ], 'MaximumRetryAttempts' => [ 'base' => NULL, 'refs' => [ 'RetryStrategy$MaximumRetryAttempts' => 'The number of times to retry the job. When the job is retried, it\'s SecondaryStatus is changed to STARTING.
The media type of the artifact, which indicates the type of data in the artifact file. The media type consists of a type and a subtype concatenated with a slash (/) character, for example, text/csv, image/jpeg, and s3/uri. The type specifies the category of the media. The subtype specifies the kind of data.
', ], ], 'MemberDefinition' => [ 'base' => 'Defines an Amazon Cognito or your own OIDC IdP user group that is part of a work team.
', 'refs' => [ 'MemberDefinitions$member' => NULL, ], ], 'MemberDefinitions' => [ 'base' => NULL, 'refs' => [ 'CreateWorkteamRequest$MemberDefinitions' => 'A list of MemberDefinition objects that contains objects that identify the workers that make up the work team.
Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use CognitoMemberDefinition. For workforces created using your own OIDC identity provider (IdP) use OidcMemberDefinition. Do not provide input for both of these parameters in a single request.
For workforces created using Amazon Cognito, private work teams correspond to Amazon Cognito user groups within the user pool used to create a workforce. All of the CognitoMemberDefinition objects that make up the member definition must have the same ClientId and UserPool values. To add a Amazon Cognito user group to an existing worker pool, see Adding groups to a User Pool. For more information about user pools, see Amazon Cognito User Pools.
For workforces created using your own OIDC IdP, specify the user groups that you want to include in your private work team in OidcMemberDefinition by listing those groups in Groups.
A list of MemberDefinition objects that contains objects that identify the workers that make up the work team.
Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use CognitoMemberDefinition. For workforces created using your own OIDC identity provider (IdP) use OidcMemberDefinition. You should not provide input for both of these parameters in a single request.
For workforces created using Amazon Cognito, private work teams correspond to Amazon Cognito user groups within the user pool used to create a workforce. All of the CognitoMemberDefinition objects that make up the member definition must have the same ClientId and UserPool values. To add a Amazon Cognito user group to an existing worker pool, see Adding groups to a User Pool. For more information about user pools, see Amazon Cognito User Pools.
For workforces created using your own OIDC IdP, specify the user groups that you want to include in your private work team in OidcMemberDefinition by listing those groups in Groups. Be aware that user groups that are already in the work team must also be listed in Groups when you make this request to remain on the work team. If you do not include these user groups, they will no longer be associated with the work team you update.
A list of MemberDefinition objects that contains objects that identify the workers that make up the work team.
Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use CognitoMemberDefinition. For workforces created using your own OIDC identity provider (IdP) use OidcMemberDefinition.
Metadata properties of the tracking entity, trial, or trial component.
', 'refs' => [ 'CreateActionRequest$MetadataProperties' => NULL, 'CreateArtifactRequest$MetadataProperties' => NULL, 'CreateModelPackageInput$MetadataProperties' => NULL, 'CreateTrialComponentRequest$MetadataProperties' => NULL, 'CreateTrialRequest$MetadataProperties' => NULL, 'DescribeActionResponse$MetadataProperties' => NULL, 'DescribeArtifactResponse$MetadataProperties' => NULL, 'DescribeModelPackageOutput$MetadataProperties' => NULL, 'DescribeTrialComponentResponse$MetadataProperties' => NULL, 'DescribeTrialResponse$MetadataProperties' => NULL, 'ModelPackage$MetadataProperties' => 'Metadata properties of the tracking entity, trial, or trial component.
', 'Trial$MetadataProperties' => NULL, 'TrialComponent$MetadataProperties' => NULL, ], ], 'MetadataPropertyValue' => [ 'base' => NULL, 'refs' => [ 'MetadataProperties$CommitId' => 'The commit ID.
', 'MetadataProperties$Repository' => 'The repository.
', 'MetadataProperties$GeneratedBy' => 'The entity this entity was generated by.
', 'MetadataProperties$ProjectId' => 'The project ID.
', ], ], 'MetricData' => [ 'base' => 'The name, value, and date and time of a metric that was emitted to Amazon CloudWatch.
', 'refs' => [ 'FinalMetricDataList$member' => NULL, ], ], 'MetricDataList' => [ 'base' => NULL, 'refs' => [ 'CandidateProperties$CandidateMetrics' => 'Information about the candidate metrics for an AutoML job.
', ], ], 'MetricDatum' => [ 'base' => 'Information about the metric for a candidate produced by an AutoML job.
', 'refs' => [ 'MetricDataList$member' => NULL, ], ], 'MetricDefinition' => [ 'base' => 'Specifies a metric that the training algorithm writes to stderr or stdout. You can view these logs to understand how your training job performs and check for any errors encountered during training. SageMaker hyperparameter tuning captures all defined metrics. Specify one of the defined metrics to use as an objective metric using the TuningObjective parameter in the HyperParameterTrainingJobDefinition API to evaluate job performance during hyperparameter tuning.
A list of metric definition objects. Each object specifies the metric name and regular expressions used to parse algorithm logs. SageMaker publishes each metric to Amazon CloudWatch.
', 'HyperParameterAlgorithmSpecification$MetricDefinitions' => 'An array of MetricDefinition objects that specify the metrics that the algorithm emits.
', 'TrainingSpecification$MetricDefinitions' => 'A list of MetricDefinition objects, which are used for parsing metrics generated by the algorithm.
The name of the objective metric. For SageMaker built-in algorithms, metrics are defined per algorithm. See the metrics for XGBoost as an example. You can also use a custom algorithm for training and define your own metrics. For more information, see Define metrics and environment variables.
', 'HyperParameterTuningJobObjective$MetricName' => 'The name of the metric to use for the objective metric.
', 'MetricData$MetricName' => 'The name of the metric.
', 'MetricDefinition$Name' => 'The name of the metric.
', 'TrialComponentMetricSummary$MetricName' => 'The name of the metric.
', ], ], 'MetricRegex' => [ 'base' => NULL, 'refs' => [ 'MetricDefinition$Regex' => 'A regular expression that searches the output of a training job and gets the value of the metric. For more information about using regular expressions to define metrics, see Defining metrics and environment variables.
', ], ], 'MetricSetSource' => [ 'base' => NULL, 'refs' => [ 'MetricDatum$Set' => 'The dataset split from which the AutoML job produced the metric.
', ], ], 'MetricSpecification' => [ 'base' => 'An object containing information about a metric.
', 'refs' => [ 'TargetTrackingScalingPolicyConfiguration$MetricSpecification' => 'An object containing information about a metric.
', ], ], 'MetricValue' => [ 'base' => NULL, 'refs' => [ 'FinalAutoMLJobObjectiveMetric$Value' => 'The value of the metric with the best result.
', 'FinalHyperParameterTuningJobObjectiveMetric$Value' => 'The value of the objective metric.
', ], ], 'MetricsSource' => [ 'base' => 'Details about the metrics source.
', 'refs' => [ 'Bias$Report' => 'The bias report for a model
', 'Bias$PreTrainingReport' => 'The pre-training bias report for a model.
', 'Bias$PostTrainingReport' => 'The post-training bias report for a model.
', 'DriftCheckBias$PreTrainingConstraints' => 'The pre-training constraints.
', 'DriftCheckBias$PostTrainingConstraints' => 'The post-training constraints.
', 'DriftCheckExplainability$Constraints' => 'The drift check explainability constraints.
', 'DriftCheckModelDataQuality$Statistics' => 'The drift check model data quality statistics.
', 'DriftCheckModelDataQuality$Constraints' => 'The drift check model data quality constraints.
', 'DriftCheckModelQuality$Statistics' => 'The drift check model quality statistics.
', 'DriftCheckModelQuality$Constraints' => 'The drift check model quality constraints.
', 'Explainability$Report' => 'The explainability report for a model.
', 'ModelDataQuality$Statistics' => 'Data quality statistics for a model.
', 'ModelDataQuality$Constraints' => 'Data quality constraints for a model.
', 'ModelQuality$Statistics' => 'Model quality statistics.
', 'ModelQuality$Constraints' => 'Model quality constraints.
', ], ], 'MinimumInstanceMetadataServiceVersion' => [ 'base' => NULL, 'refs' => [ 'InstanceMetadataServiceConfiguration$MinimumInstanceMetadataServiceVersion' => 'Indicates the minimum IMDS version that the notebook instance supports. When passed as part of CreateNotebookInstance, if no value is selected, then it defaults to IMDSv1. This means that both IMDSv1 and IMDSv2 are supported. If passed as part of UpdateNotebookInstance, there is no default.
The properties of a model as returned by the Search API.
', 'refs' => [ 'ModelDashboardModel$Model' => 'A model displayed in the Model Dashboard.
', ], ], 'ModelAccessConfig' => [ 'base' => 'The access configuration file for the ML model. You can explicitly accept the model end-user license agreement (EULA) within the ModelAccessConfig. For more information, see End-user license agreements.
Specifies the access configuration file for the ML model. You can explicitly accept the model end-user license agreement (EULA) within the ModelAccessConfig. You are responsible for reviewing and complying with any applicable license terms and making sure they are acceptable for your use case before downloading or using a model.
The approval status of the model.
', 'CreateModelPackageInput$ModelApprovalStatus' => 'Whether the model is approved for deployment.
This parameter is optional for versioned models, and does not apply to unversioned models.
For versioned models, the value of this parameter must be set to Approved to deploy the model.
The approval status of the model package.
', 'ListModelPackagesInput$ModelApprovalStatus' => 'A filter that returns only the model packages with the specified approval status.
', 'ModelPackage$ModelApprovalStatus' => 'The approval status of the model. This can be one of the following values.
APPROVED - The model is approved
REJECTED - The model is rejected.
PENDING_MANUAL_APPROVAL - The model is waiting for manual approval.
The approval status of the model. This can be one of the following values.
APPROVED - The model is approved
REJECTED - The model is rejected.
PENDING_MANUAL_APPROVAL - The model is waiting for manual approval.
The approval status of the model.
', ], ], 'ModelArn' => [ 'base' => NULL, 'refs' => [ 'CreateModelOutput$ModelArn' => 'The ARN of the model created in SageMaker.
', 'DescribeModelOutput$ModelArn' => 'The Amazon Resource Name (ARN) of the model.
', 'LabelingJobAlgorithmsConfig$InitialActiveLearningModelArn' => 'At the end of an auto-label job Ground Truth sends the Amazon Resource Name (ARN) of the final model used for auto-labeling. You can use this model as the starting point for subsequent similar jobs by providing the ARN of the model here.
', 'LabelingJobOutput$FinalActiveLearningModelArn' => 'The Amazon Resource Name (ARN) for the most recent SageMaker model trained as part of automated data labeling.
', 'Model$ModelArn' => 'The Amazon Resource Name (ARN) of the model.
', 'ModelSummary$ModelArn' => 'The Amazon Resource Name (ARN) of the model.
', ], ], 'ModelArtifacts' => [ 'base' => 'Provides information about the location that is configured for storing model artifacts.
Model artifacts are the output that results from training a model, and typically consist of trained parameters, a model definition that describes how to compute inferences, and other metadata.
', 'refs' => [ 'DescribeCompilationJobResponse$ModelArtifacts' => 'Information about the location in Amazon S3 that has been configured for storing the model artifacts used in the compilation job.
', 'DescribeTrainingJobResponse$ModelArtifacts' => 'Information about the Amazon S3 location that is configured for storing model artifacts.
', 'TrainingJob$ModelArtifacts' => 'Information about the Amazon S3 location that is configured for storing model artifacts.
', ], ], 'ModelBiasAppSpecification' => [ 'base' => 'Docker container image configuration object for the model bias job.
', 'refs' => [ 'CreateModelBiasJobDefinitionRequest$ModelBiasAppSpecification' => 'Configures the model bias job to run a specified Docker container image.
', 'DescribeModelBiasJobDefinitionResponse$ModelBiasAppSpecification' => 'Configures the model bias job to run a specified Docker container image.
', ], ], 'ModelBiasBaselineConfig' => [ 'base' => 'The configuration for a baseline model bias job.
', 'refs' => [ 'CreateModelBiasJobDefinitionRequest$ModelBiasBaselineConfig' => 'The baseline configuration for a model bias job.
', 'DescribeModelBiasJobDefinitionResponse$ModelBiasBaselineConfig' => 'The baseline configuration for a model bias job.
', ], ], 'ModelBiasJobInput' => [ 'base' => 'Inputs for the model bias job.
', 'refs' => [ 'CreateModelBiasJobDefinitionRequest$ModelBiasJobInput' => 'Inputs for the model bias job.
', 'DescribeModelBiasJobDefinitionResponse$ModelBiasJobInput' => 'Inputs for the model bias job.
', ], ], 'ModelCacheSetting' => [ 'base' => NULL, 'refs' => [ 'MultiModelConfig$ModelCacheSetting' => 'Whether to cache models for a multi-model endpoint. By default, multi-model endpoints cache models so that a model does not have to be loaded into memory each time it is invoked. Some use cases do not benefit from model caching. For example, if an endpoint hosts a large number of models that are each invoked infrequently, the endpoint might perform better if you disable model caching. To disable model caching, set the value of this parameter to Disabled.
An Amazon SageMaker Model Card.
', 'refs' => [ 'SearchRecord$ModelCard' => 'An Amazon SageMaker Model Card that documents details about a machine learning model.
', ], ], 'ModelCardArn' => [ 'base' => NULL, 'refs' => [ 'CreateModelCardResponse$ModelCardArn' => 'The Amazon Resource Name (ARN) of the successfully created model card.
', 'DescribeModelCardResponse$ModelCardArn' => 'The Amazon Resource Name (ARN) of the model card.
', 'ModelCard$ModelCardArn' => 'The Amazon Resource Name (ARN) of the model card.
', 'ModelCardSummary$ModelCardArn' => 'The Amazon Resource Name (ARN) of the model card.
', 'ModelCardVersionSummary$ModelCardArn' => 'The Amazon Resource Name (ARN) of the model card.
', 'ModelDashboardModelCard$ModelCardArn' => 'The Amazon Resource Name (ARN) for a model card.
', 'UpdateModelCardResponse$ModelCardArn' => 'The Amazon Resource Name (ARN) of the updated model card.
', ], ], 'ModelCardContent' => [ 'base' => NULL, 'refs' => [ 'CreateModelCardRequest$Content' => 'The content of the model card. Content must be in model card JSON schema and provided as a string.
', 'DescribeModelCardResponse$Content' => 'The content of the model card.
', 'ModelCard$Content' => 'The content of the model card. Content uses the model card JSON schema and provided as a string.
', 'UpdateModelCardRequest$Content' => 'The updated model card content. Content must be in model card JSON schema and provided as a string.
When updating model card content, be sure to include the full content and not just updated content.
', ], ], 'ModelCardExportArtifacts' => [ 'base' => 'The artifacts of the model card export job.
', 'refs' => [ 'DescribeModelCardExportJobResponse$ExportArtifacts' => 'The exported model card artifacts.
', ], ], 'ModelCardExportJobArn' => [ 'base' => NULL, 'refs' => [ 'CreateModelCardExportJobResponse$ModelCardExportJobArn' => 'The Amazon Resource Name (ARN) of the model card export job.
', 'DescribeModelCardExportJobRequest$ModelCardExportJobArn' => 'The Amazon Resource Name (ARN) of the model card export job to describe.
', 'DescribeModelCardExportJobResponse$ModelCardExportJobArn' => 'The Amazon Resource Name (ARN) of the model card export job.
', 'ModelCardExportJobSummary$ModelCardExportJobArn' => 'The Amazon Resource Name (ARN) of the model card export job.
', ], ], 'ModelCardExportJobSortBy' => [ 'base' => 'Attribute by which to sort returned export jobs.', 'refs' => [ 'ListModelCardExportJobsRequest$SortBy' => 'Sort model card export jobs by either name or creation time. Sorts by creation time by default.
', ], ], 'ModelCardExportJobSortOrder' => [ 'base' => NULL, 'refs' => [ 'ListModelCardExportJobsRequest$SortOrder' => 'Sort model card export jobs by ascending or descending order.
', ], ], 'ModelCardExportJobStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeModelCardExportJobResponse$Status' => 'The completion status of the model card export job.
InProgress: The model card export job is in progress.
Completed: The model card export job is complete.
Failed: The model card export job failed. To see the reason for the failure, see the FailureReason field in the response to a DescribeModelCardExportJob call.
Only list model card export jobs with the specified status.
', 'ModelCardExportJobSummary$Status' => 'The completion status of the model card export job.
', ], ], 'ModelCardExportJobSummary' => [ 'base' => 'The summary of the Amazon SageMaker Model Card export job.
', 'refs' => [ 'ModelCardExportJobSummaryList$member' => NULL, ], ], 'ModelCardExportJobSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListModelCardExportJobsResponse$ModelCardExportJobSummaries' => 'The summaries of the listed model card export jobs.
', ], ], 'ModelCardExportOutputConfig' => [ 'base' => 'Configure the export output details for an Amazon SageMaker Model Card.
', 'refs' => [ 'CreateModelCardExportJobRequest$OutputConfig' => 'The model card output configuration that specifies the Amazon S3 path for exporting.
', 'DescribeModelCardExportJobResponse$OutputConfig' => 'The export output details for the model card.
', ], ], 'ModelCardNameOrArn' => [ 'base' => NULL, 'refs' => [ 'CreateModelCardExportJobRequest$ModelCardName' => 'The name or Amazon Resource Name (ARN) of the model card to export.
', 'DescribeModelCardRequest$ModelCardName' => 'The name or Amazon Resource Name (ARN) of the model card to describe.
', 'ListModelCardVersionsRequest$ModelCardName' => 'List model card versions for the model card with the specified name or Amazon Resource Name (ARN).
', 'UpdateModelCardRequest$ModelCardName' => 'The name or Amazon Resource Name (ARN) of the model card to update.
', ], ], 'ModelCardProcessingStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeModelCardResponse$ModelCardProcessingStatus' => 'The processing status of model card deletion. The ModelCardProcessingStatus updates throughout the different deletion steps.
DeletePending: Model card deletion request received.
DeleteInProgress: Model card deletion is in progress.
ContentDeleted: Deleted model card content.
ExportJobsDeleted: Deleted all export jobs associated with the model card.
DeleteCompleted: Successfully deleted the model card.
DeleteFailed: The model card failed to delete.
Configure the security settings to protect model card data.
', 'refs' => [ 'CreateModelCardRequest$SecurityConfig' => 'An optional Key Management Service key to encrypt, decrypt, and re-encrypt model card content for regulated workloads with highly sensitive data.
', 'DescribeModelCardResponse$SecurityConfig' => 'The security configuration used to protect model card content.
', 'ModelCard$SecurityConfig' => 'The security configuration used to protect model card data.
', 'ModelDashboardModelCard$SecurityConfig' => 'The KMS Key ID (KMSKeyId) for encryption of model card information.
Sort model cards by either name or creation time. Sorts by creation time by default.
', ], ], 'ModelCardSortOrder' => [ 'base' => NULL, 'refs' => [ 'ListModelCardVersionsRequest$SortOrder' => 'Sort model card versions by ascending or descending order.
', 'ListModelCardsRequest$SortOrder' => 'Sort model cards by ascending or descending order.
', ], ], 'ModelCardStatus' => [ 'base' => NULL, 'refs' => [ 'CreateModelCardRequest$ModelCardStatus' => 'The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft: The model card is a work in progress.
PendingReview: The model card is pending review.
Approved: The model card is approved.
Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft: The model card is a work in progress.
PendingReview: The model card is pending review.
Approved: The model card is approved.
Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.
Only list model card versions with the specified approval status.
', 'ListModelCardsRequest$ModelCardStatus' => 'Only list model cards with the specified approval status.
', 'ModelCard$ModelCardStatus' => 'The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft: The model card is a work in progress.
PendingReview: The model card is pending review.
Approved: The model card is approved.
Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft: The model card is a work in progress.
PendingReview: The model card is pending review.
Approved: The model card is approved.
Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.
The approval status of the model card version within your organization. Different organizations might have different criteria for model card review and approval.
Draft: The model card is a work in progress.
PendingReview: The model card is pending review.
Approved: The model card is approved.
Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.
The model card status.
', 'UpdateModelCardRequest$ModelCardStatus' => 'The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft: The model card is a work in progress.
PendingReview: The model card is pending review.
Approved: The model card is approved.
Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.
A summary of the model card.
', 'refs' => [ 'ModelCardSummaryList$member' => NULL, ], ], 'ModelCardSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListModelCardsResponse$ModelCardSummaries' => 'The summaries of the listed model cards.
', ], ], 'ModelCardVersionSortBy' => [ 'base' => NULL, 'refs' => [ 'ListModelCardVersionsRequest$SortBy' => 'Sort listed model card versions by version. Sorts by version by default.
', ], ], 'ModelCardVersionSummary' => [ 'base' => 'A summary of a specific version of the model card.
', 'refs' => [ 'ModelCardVersionSummaryList$member' => NULL, ], ], 'ModelCardVersionSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListModelCardVersionsResponse$ModelCardVersionSummaryList' => 'The summaries of the listed versions of the model card.
', ], ], 'ModelClientConfig' => [ 'base' => 'Configures the timeout and maximum number of retries for processing a transform job invocation.
', 'refs' => [ 'CreateTransformJobRequest$ModelClientConfig' => 'Configures the timeout and maximum number of retries for processing a transform job invocation.
', 'DescribeTransformJobResponse$ModelClientConfig' => 'The timeout and maximum number of retries for processing a transform job invocation.
', 'TransformJob$ModelClientConfig' => NULL, ], ], 'ModelCompressionType' => [ 'base' => NULL, 'refs' => [ 'S3ModelDataSource$CompressionType' => 'Specifies how the ML model data is prepared.
If you choose Gzip and choose S3Object as the value of S3DataType, S3Uri identifies an object that is a gzip-compressed TAR archive. SageMaker will attempt to decompress and untar the object during model deployment.
If you choose None and chooose S3Object as the value of S3DataType, S3Uri identifies an object that represents an uncompressed ML model to deploy.
If you choose None and choose S3Prefix as the value of S3DataType, S3Uri identifies a key name prefix, under which all objects represents the uncompressed ML model to deploy.
If you choose None, then SageMaker will follow rules below when creating model data files under /opt/ml/model directory for use by your inference code:
If you choose S3Object as the value of S3DataType, then SageMaker will split the key of the S3 object referenced by S3Uri by slash (/), and use the last part as the filename of the file holding the content of the S3 object.
If you choose S3Prefix as the value of S3DataType, then for each S3 object under the key name pefix referenced by S3Uri, SageMaker will trim its key by the prefix, and use the remainder as the path (relative to /opt/ml/model) of the file holding the content of the S3 object. SageMaker will split the remainder by slash (/), using intermediate parts as directory names and the last part as filename of the file holding the content of the S3 object.
Do not use any of the following as file names or directory names:
An empty or blank string
A string which contains null bytes
A string longer than 255 bytes
A single dot (.)
A double dot (..)
Ambiguous file names will result in model deployment failure. For example, if your uncompressed ML model consists of two S3 objects s3://mybucket/model/weights and s3://mybucket/model/weights/part1 and you specify s3://mybucket/model/ as the value of S3Uri and S3Prefix as the value of S3DataType, then it will result in name clash between /opt/ml/model/weights (a regular file) and /opt/ml/model/weights/ (a directory).
Do not organize the model artifacts in S3 console using folders. When you create a folder in S3 console, S3 creates a 0-byte object with a key set to the folder name you provide. They key of the 0-byte object ends with a slash (/) which violates SageMaker restrictions on model artifact file names, leading to model deployment failure.
Defines the model configuration. Includes the specification name and environment parameters.
', 'refs' => [ 'InferenceRecommendation$ModelConfiguration' => 'Defines the model configuration.
', 'RecommendationJobInferenceBenchmark$ModelConfiguration' => NULL, ], ], 'ModelDashboardEndpoint' => [ 'base' => 'An endpoint that hosts a model displayed in the Amazon SageMaker Model Dashboard.
', 'refs' => [ 'ModelDashboardEndpoints$member' => NULL, ], ], 'ModelDashboardEndpoints' => [ 'base' => NULL, 'refs' => [ 'ModelDashboardModel$Endpoints' => 'The endpoints that host a model.
', ], ], 'ModelDashboardIndicatorAction' => [ 'base' => 'An alert action taken to light up an icon on the Amazon SageMaker Model Dashboard when an alert goes into InAlert status.
An alert action taken to light up an icon on the Model Dashboard when an alert goes into InAlert status.
A model displayed in the Amazon SageMaker Model Dashboard.
', 'refs' => [ 'SearchRecord$Model' => NULL, ], ], 'ModelDashboardModelCard' => [ 'base' => 'The model card for a model displayed in the Amazon SageMaker Model Dashboard.
', 'refs' => [ 'ModelDashboardModel$ModelCard' => 'The model card for a model.
', ], ], 'ModelDashboardMonitoringSchedule' => [ 'base' => 'A monitoring schedule for a model displayed in the Amazon SageMaker Model Dashboard.
', 'refs' => [ 'ModelDashboardMonitoringSchedules$member' => NULL, ], ], 'ModelDashboardMonitoringSchedules' => [ 'base' => NULL, 'refs' => [ 'ModelDashboardModel$MonitoringSchedules' => 'The monitoring schedules for a model.
', ], ], 'ModelDataQuality' => [ 'base' => 'Data quality constraints and statistics for a model.
', 'refs' => [ 'ModelMetrics$ModelDataQuality' => 'Metrics that measure the quality of the input data for a model.
', ], ], 'ModelDataSource' => [ 'base' => 'Specifies the location of ML model data to deploy. If specified, you must specify one and only one of the available data sources.
', 'refs' => [ 'ContainerDefinition$ModelDataSource' => 'Specifies the location of ML model data to deploy.
Currently you cannot use ModelDataSource in conjunction with SageMaker batch transform, SageMaker serverless endpoints, SageMaker multi-model endpoints, and SageMaker Marketplace.
Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
', 'refs' => [ 'CreateAutoMLJobRequest$ModelDeployConfig' => 'Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
', 'CreateAutoMLJobV2Request$ModelDeployConfig' => 'Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
', 'DescribeAutoMLJobResponse$ModelDeployConfig' => 'Indicates whether the model was deployed automatically to an endpoint and the name of that endpoint if deployed automatically.
', 'DescribeAutoMLJobV2Response$ModelDeployConfig' => 'Indicates whether the model was deployed automatically to an endpoint and the name of that endpoint if deployed automatically.
', ], ], 'ModelDeployResult' => [ 'base' => 'Provides information about the endpoint of the model deployment.
', 'refs' => [ 'DescribeAutoMLJobResponse$ModelDeployResult' => 'Provides information about endpoint for the model deployment.
', 'DescribeAutoMLJobV2Response$ModelDeployResult' => 'Provides information about endpoint for the model deployment.
', ], ], 'ModelDigests' => [ 'base' => 'Provides information to verify the integrity of stored model artifacts.
', 'refs' => [ 'DescribeCompilationJobResponse$ModelDigests' => 'Provides a BLAKE2 hash value that identifies the compiled model artifacts in Amazon S3.
', ], ], 'ModelExplainabilityAppSpecification' => [ 'base' => 'Docker container image configuration object for the model explainability job.
', 'refs' => [ 'CreateModelExplainabilityJobDefinitionRequest$ModelExplainabilityAppSpecification' => 'Configures the model explainability job to run a specified Docker container image.
', 'DescribeModelExplainabilityJobDefinitionResponse$ModelExplainabilityAppSpecification' => 'Configures the model explainability job to run a specified Docker container image.
', ], ], 'ModelExplainabilityBaselineConfig' => [ 'base' => 'The configuration for a baseline model explainability job.
', 'refs' => [ 'CreateModelExplainabilityJobDefinitionRequest$ModelExplainabilityBaselineConfig' => 'The baseline configuration for a model explainability job.
', 'DescribeModelExplainabilityJobDefinitionResponse$ModelExplainabilityBaselineConfig' => 'The baseline configuration for a model explainability job.
', ], ], 'ModelExplainabilityJobInput' => [ 'base' => 'Inputs for the model explainability job.
', 'refs' => [ 'CreateModelExplainabilityJobDefinitionRequest$ModelExplainabilityJobInput' => 'Inputs for the model explainability job.
', 'DescribeModelExplainabilityJobDefinitionResponse$ModelExplainabilityJobInput' => 'Inputs for the model explainability job.
', ], ], 'ModelInfrastructureConfig' => [ 'base' => 'The configuration for the infrastructure that the model will be deployed to.
', 'refs' => [ 'ModelVariantConfig$InfrastructureConfig' => 'The configuration for the infrastructure that the model will be deployed to.
', 'ModelVariantConfigSummary$InfrastructureConfig' => 'The configuration of the infrastructure that the model has been deployed to.
', ], ], 'ModelInfrastructureType' => [ 'base' => NULL, 'refs' => [ 'ModelInfrastructureConfig$InfrastructureType' => 'The inference option to which to deploy your model. Possible values are the following:
RealTime: Deploy to real-time inference.
Input object for the model.
', 'refs' => [ 'ModelPackageContainerDefinition$ModelInput' => 'A structure with Model Input details.
', ], ], 'ModelInsightsLocation' => [ 'base' => NULL, 'refs' => [ 'CandidateArtifactLocations$ModelInsights' => 'The Amazon S3 prefix to the model insight artifacts generated for the AutoML candidate.
', ], ], 'ModelLatencyThreshold' => [ 'base' => 'The model latency threshold.
', 'refs' => [ 'ModelLatencyThresholds$member' => NULL, ], ], 'ModelLatencyThresholds' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobStoppingConditions$ModelLatencyThresholds' => 'The interval of time taken by a model to respond as viewed from SageMaker. The interval includes the local communication time taken to send the request and to fetch the response from the container of a model and the time taken to complete the inference in the container.
', ], ], 'ModelMetadataFilter' => [ 'base' => 'Part of the search expression. You can specify the name and value (domain, task, framework, framework version, task, and model).
', 'refs' => [ 'ModelMetadataFilters$member' => NULL, ], ], 'ModelMetadataFilterType' => [ 'base' => NULL, 'refs' => [ 'ModelMetadataFilter$Name' => 'The name of the of the model to filter by.
', ], ], 'ModelMetadataFilters' => [ 'base' => NULL, 'refs' => [ 'ModelMetadataSearchExpression$Filters' => 'A list of filter objects.
', ], ], 'ModelMetadataSearchExpression' => [ 'base' => 'One or more filters that searches for the specified resource or resources in a search. All resource objects that satisfy the expression\'s condition are included in the search results
', 'refs' => [ 'ListModelMetadataRequest$SearchExpression' => 'One or more filters that searches for the specified resource or resources in a search. All resource objects that satisfy the expression\'s condition are included in the search results. Specify the Framework, FrameworkVersion, Domain or Task to filter supported. Filter names and values are case-sensitive.
', ], ], 'ModelMetadataSummaries' => [ 'base' => NULL, 'refs' => [ 'ListModelMetadataResponse$ModelMetadataSummaries' => 'A structure that holds model metadata.
', ], ], 'ModelMetadataSummary' => [ 'base' => 'A summary of the model metadata.
', 'refs' => [ 'ModelMetadataSummaries$member' => NULL, ], ], 'ModelMetrics' => [ 'base' => 'Contains metrics captured from a model.
', 'refs' => [ 'CreateModelPackageInput$ModelMetrics' => 'A structure that contains model metrics reports.
', 'DescribeModelPackageOutput$ModelMetrics' => 'Metrics for the model.
', 'ModelPackage$ModelMetrics' => 'Metrics for the model.
', ], ], 'ModelName' => [ 'base' => NULL, 'refs' => [ 'CreateModelInput$ModelName' => 'The name of the new model.
', 'CreateTransformJobRequest$ModelName' => 'The name of the model that you want to use for the transform job. ModelName must be the name of an existing Amazon SageMaker model within an Amazon Web Services Region in an Amazon Web Services account.
The name of the model to delete.
', 'DescribeModelInput$ModelName' => 'The name of the model.
', 'DescribeModelOutput$ModelName' => 'Name of the SageMaker model.
', 'DescribeTransformJobResponse$ModelName' => 'The name of the model used in the transform job.
', 'InferenceRecommendationsJob$ModelName' => 'The name of the created model.
', 'ListInferenceRecommendationsJobsRequest$ModelNameEquals' => 'A filter that returns only jobs that were created for this model.
', 'Model$ModelName' => 'The name of the model.
', 'ModelSummary$ModelName' => 'The name of the model that you want a summary for.
', 'ModelVariantConfig$ModelName' => 'The name of the Amazon SageMaker Model entity.
', 'ModelVariantConfigSummary$ModelName' => 'The name of the Amazon SageMaker Model entity.
', 'ProductionVariant$ModelName' => 'The name of the model that you want to host. This is the name that you specified when creating the model.
', 'RecommendationJobInputConfig$ModelName' => 'The name of the created model.
', 'TransformJob$ModelName' => 'The name of the model associated with the transform job.
', ], ], 'ModelNameContains' => [ 'base' => NULL, 'refs' => [ 'ListModelsInput$NameContains' => 'A string in the model name. This filter returns only models whose name contains the specified string.
', ], ], 'ModelPackage' => [ 'base' => 'A versioned model that can be deployed for SageMaker inference.
', 'refs' => [ 'SearchRecord$ModelPackage' => NULL, ], ], 'ModelPackageArn' => [ 'base' => NULL, 'refs' => [ 'BatchDescribeModelPackageErrorMap$key' => NULL, 'BatchDescribeModelPackageSummary$ModelPackageArn' => 'The Amazon Resource Name (ARN) of the model package.
', 'CreateCompilationJobRequest$ModelPackageVersionArn' => 'The Amazon Resource Name (ARN) of a versioned model package. Provide either a ModelPackageVersionArn or an InputConfig object in the request syntax. The presence of both objects in the CreateCompilationJob request will return an exception.
The Amazon Resource Name (ARN) of the new model package.
', 'DescribeCompilationJobResponse$ModelPackageVersionArn' => 'The Amazon Resource Name (ARN) of the versioned model package that was provided to SageMaker Neo when you initiated a compilation job.
', 'DescribeModelPackageOutput$ModelPackageArn' => 'The Amazon Resource Name (ARN) of the model package.
', 'InferenceRecommendationsJob$ModelPackageVersionArn' => 'The Amazon Resource Name (ARN) of a versioned model package.
', 'ListInferenceRecommendationsJobsRequest$ModelPackageVersionArnEquals' => 'A filter that returns only jobs that were created for this versioned model package.
', 'ModelPackage$ModelPackageArn' => 'The Amazon Resource Name (ARN) of the model package.
', 'ModelPackageArnList$member' => NULL, 'ModelPackageSummaries$key' => NULL, 'ModelPackageSummary$ModelPackageArn' => 'The Amazon Resource Name (ARN) of the model package.
', 'RecommendationJobInputConfig$ModelPackageVersionArn' => 'The Amazon Resource Name (ARN) of a versioned model package.
', 'UpdateModelPackageInput$ModelPackageArn' => 'The Amazon Resource Name (ARN) of the model package.
', 'UpdateModelPackageOutput$ModelPackageArn' => 'The Amazon Resource Name (ARN) of the model.
', ], ], 'ModelPackageArnList' => [ 'base' => NULL, 'refs' => [ 'BatchDescribeModelPackageInput$ModelPackageArnList' => 'The list of Amazon Resource Name (ARN) of the model package groups.
', ], ], 'ModelPackageContainerDefinition' => [ 'base' => 'Describes the Docker container for the model package.
', 'refs' => [ 'ModelPackageContainerDefinitionList$member' => NULL, ], ], 'ModelPackageContainerDefinitionList' => [ 'base' => NULL, 'refs' => [ 'AdditionalInferenceSpecificationDefinition$Containers' => 'The Amazon ECR registry path of the Docker image that contains the inference code.
', 'InferenceSpecification$Containers' => 'The Amazon ECR registry path of the Docker image that contains the inference code.
', ], ], 'ModelPackageFrameworkVersion' => [ 'base' => NULL, 'refs' => [ 'ModelPackageContainerDefinition$FrameworkVersion' => 'The framework version of the Model Package Container Image.
', ], ], 'ModelPackageGroup' => [ 'base' => 'A group of versioned models in the model registry.
', 'refs' => [ 'SearchRecord$ModelPackageGroup' => NULL, ], ], 'ModelPackageGroupArn' => [ 'base' => NULL, 'refs' => [ 'CreateModelPackageGroupOutput$ModelPackageGroupArn' => 'The Amazon Resource Name (ARN) of the model group.
', 'DescribeModelPackageGroupOutput$ModelPackageGroupArn' => 'The Amazon Resource Name (ARN) of the model group.
', 'ModelPackageGroup$ModelPackageGroupArn' => 'The Amazon Resource Name (ARN) of the model group.
', 'ModelPackageGroupSummary$ModelPackageGroupArn' => 'The Amazon Resource Name (ARN) of the model group.
', 'PutModelPackageGroupPolicyOutput$ModelPackageGroupArn' => 'The Amazon Resource Name (ARN) of the model package group.
', ], ], 'ModelPackageGroupSortBy' => [ 'base' => NULL, 'refs' => [ 'ListModelPackageGroupsInput$SortBy' => 'The field to sort results by. The default is CreationTime.
The status of the model group.
', 'ModelPackageGroup$ModelPackageGroupStatus' => 'The status of the model group. This can be one of the following values.
PENDING - The model group is pending being created.
IN_PROGRESS - The model group is in the process of being created.
COMPLETED - The model group was successfully created.
FAILED - The model group failed.
DELETING - The model group is in the process of being deleted.
DELETE_FAILED - SageMaker failed to delete the model group.
The status of the model group.
', ], ], 'ModelPackageGroupSummary' => [ 'base' => 'Summary information about a model group.
', 'refs' => [ 'ModelPackageGroupSummaryList$member' => NULL, ], ], 'ModelPackageGroupSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListModelPackageGroupsOutput$ModelPackageGroupSummaryList' => 'A list of summaries of the model groups in your Amazon Web Services account.
', ], ], 'ModelPackageSortBy' => [ 'base' => NULL, 'refs' => [ 'ListModelPackagesInput$SortBy' => 'The parameter by which to sort the results. The default is CreationTime.
The status of the mortgage package.
', 'DescribeModelPackageOutput$ModelPackageStatus' => 'The current status of the model package.
', 'ModelPackage$ModelPackageStatus' => 'The status of the model package. This can be one of the following values.
PENDING - The model package is pending being created.
IN_PROGRESS - The model package is in the process of being created.
COMPLETED - The model package was successfully created.
FAILED - The model package failed.
DELETING - The model package is in the process of being deleted.
The overall status of the model package.
', ], ], 'ModelPackageStatusDetails' => [ 'base' => 'Specifies the validation and image scan statuses of the model package.
', 'refs' => [ 'DescribeModelPackageOutput$ModelPackageStatusDetails' => 'Details about the current status of the model package.
', 'ModelPackage$ModelPackageStatusDetails' => 'Specifies the validation and image scan statuses of the model package.
', ], ], 'ModelPackageStatusItem' => [ 'base' => 'Represents the overall status of a model package.
', 'refs' => [ 'ModelPackageStatusItemList$member' => NULL, ], ], 'ModelPackageStatusItemList' => [ 'base' => NULL, 'refs' => [ 'ModelPackageStatusDetails$ValidationStatuses' => 'The validation status of the model package.
', 'ModelPackageStatusDetails$ImageScanStatuses' => 'The status of the scan of the Docker image container for the model package.
', ], ], 'ModelPackageSummaries' => [ 'base' => NULL, 'refs' => [ 'BatchDescribeModelPackageOutput$ModelPackageSummaries' => 'The summaries for the model package versions
', ], ], 'ModelPackageSummary' => [ 'base' => 'Provides summary information about a model package.
', 'refs' => [ 'ModelPackageSummaryList$member' => NULL, ], ], 'ModelPackageSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListModelPackagesOutput$ModelPackageSummaryList' => 'An array of ModelPackageSummary objects, each of which lists a model package.
A filter that returns only the model packages of the specified type. This can be one of the following values.
UNVERSIONED - List only unversioined models. This is the default value if no ModelPackageType is specified.
VERSIONED - List only versioned models.
BOTH - List both versioned and unversioned models.
Contains data, such as the inputs and targeted instance types that are used in the process of validating the model package.
The data provided in the validation profile is made available to your buyers on Amazon Web Services Marketplace.
', 'refs' => [ 'ModelPackageValidationProfiles$member' => NULL, ], ], 'ModelPackageValidationProfiles' => [ 'base' => NULL, 'refs' => [ 'ModelPackageValidationSpecification$ValidationProfiles' => 'An array of ModelPackageValidationProfile objects, each of which specifies a batch transform job that SageMaker runs to validate your model package.
Specifies batch transform jobs that SageMaker runs to validate your model package.
', 'refs' => [ 'CreateModelPackageInput$ValidationSpecification' => 'Specifies configurations for one or more transform jobs that SageMaker runs to test the model package.
', 'DescribeModelPackageOutput$ValidationSpecification' => 'Configurations for one or more transform jobs that SageMaker runs to test the model package.
', 'ModelPackage$ValidationSpecification' => 'Specifies batch transform jobs that SageMaker runs to validate your model package.
', ], ], 'ModelPackageVersion' => [ 'base' => NULL, 'refs' => [ 'BatchDescribeModelPackageSummary$ModelPackageVersion' => 'The version number of a versioned model.
', 'DescribeModelPackageOutput$ModelPackageVersion' => 'The version of the model package.
', 'ModelPackage$ModelPackageVersion' => 'The version number of a versioned model.
', 'ModelPackageSummary$ModelPackageVersion' => 'If the model package is a versioned model, the version of the model.
', ], ], 'ModelQuality' => [ 'base' => 'Model quality statistics and constraints.
', 'refs' => [ 'ModelMetrics$ModelQuality' => 'Metrics that measure the quality of a model.
', ], ], 'ModelQualityAppSpecification' => [ 'base' => 'Container image configuration object for the monitoring job.
', 'refs' => [ 'CreateModelQualityJobDefinitionRequest$ModelQualityAppSpecification' => 'The container that runs the monitoring job.
', 'DescribeModelQualityJobDefinitionResponse$ModelQualityAppSpecification' => 'Configures the model quality job to run a specified Docker container image.
', ], ], 'ModelQualityBaselineConfig' => [ 'base' => 'Configuration for monitoring constraints and monitoring statistics. These baseline resources are compared against the results of the current job from the series of jobs scheduled to collect data periodically.
', 'refs' => [ 'CreateModelQualityJobDefinitionRequest$ModelQualityBaselineConfig' => 'Specifies the constraints and baselines for the monitoring job.
', 'DescribeModelQualityJobDefinitionResponse$ModelQualityBaselineConfig' => 'The baseline configuration for a model quality job.
', ], ], 'ModelQualityJobInput' => [ 'base' => 'The input for the model quality monitoring job. Currently endpoints are supported for input for model quality monitoring jobs.
', 'refs' => [ 'CreateModelQualityJobDefinitionRequest$ModelQualityJobInput' => 'A list of the inputs that are monitored. Currently endpoints are supported.
', 'DescribeModelQualityJobDefinitionResponse$ModelQualityJobInput' => 'Inputs for the model quality job.
', ], ], 'ModelRegisterSettings' => [ 'base' => 'The model registry settings for the SageMaker Canvas application.
', 'refs' => [ 'CanvasAppSettings$ModelRegisterSettings' => 'The model registry settings for the SageMaker Canvas application.
', ], ], 'ModelSetupTime' => [ 'base' => NULL, 'refs' => [ 'RecommendationMetrics$ModelSetupTime' => 'The time it takes to launch new compute resources for a serverless endpoint. The time can vary depending on the model size, how long it takes to download the model, and the start-up time of the container.
NaN indicates that the value is not available.
Sorts the list of results. The default is CreationTime.
Metadata for Model steps.
', 'refs' => [ 'PipelineExecutionStepMetadata$Model' => 'The Amazon Resource Name (ARN) of the model that was created by this step execution.
', ], ], 'ModelSummary' => [ 'base' => 'Provides summary information about a model.
', 'refs' => [ 'ModelSummaryList$member' => NULL, ], ], 'ModelSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListModelsOutput$Models' => 'An array of ModelSummary objects, each of which lists a model.
Array of key-value pairs, with names of variants mapped to actions. The possible actions are the following:
Promote - Promote the shadow variant to a production variant
Remove - Delete the variant
Retain - Keep the variant as it is
Contains information about the deployment options of a model.
', 'refs' => [ 'ModelVariantConfigList$member' => NULL, ], ], 'ModelVariantConfigList' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceExperimentRequest$ModelVariants' => ' An array of ModelVariantConfig objects. There is one for each variant in the inference experiment. Each ModelVariantConfig object in the array describes the infrastructure configuration for the corresponding variant.
An array of ModelVariantConfig objects. There is one for each variant that you want to deploy after the inference experiment stops. Each ModelVariantConfig describes the infrastructure configuration for deploying the corresponding variant.
An array of ModelVariantConfig objects. There is one for each variant, whose infrastructure configuration you want to update.
Summary of the deployment configuration of a model.
', 'refs' => [ 'ModelVariantConfigSummaryList$member' => NULL, ], ], 'ModelVariantConfigSummaryList' => [ 'base' => NULL, 'refs' => [ 'DescribeInferenceExperimentResponse$ModelVariants' => ' An array of ModelVariantConfigSummary objects. There is one for each variant in the inference experiment. Each ModelVariantConfigSummary object in the array describes the infrastructure configuration for deploying the corresponding variant.
The name of the variant.
', 'ModelVariantConfigSummary$VariantName' => 'The name of the variant.
', 'ShadowModeConfig$SourceModelVariantName' => 'The name of the production variant, which takes all the inference requests.
', 'ShadowModelVariantConfig$ShadowModelVariantName' => 'The name of the shadow variant.
', ], ], 'ModelVariantStatus' => [ 'base' => NULL, 'refs' => [ 'ModelVariantConfigSummary$Status' => 'The status of deployment for the model variant on the hosted inference endpoint.
Creating - Amazon SageMaker is preparing the model variant on the hosted inference endpoint.
InService - The model variant is running on the hosted inference endpoint.
Updating - Amazon SageMaker is updating the model variant on the hosted inference endpoint.
Deleting - Amazon SageMaker is deleting the model variant on the hosted inference endpoint.
Deleted - The model variant has been deleted on the hosted inference endpoint. This can only happen after stopping the experiment.
A list of alert actions taken in response to an alert going into InAlert status.
A list of alert actions taken in response to an alert going into InAlert status.
An alert history for a model monitoring schedule.
', ], ], 'MonitoringAlertHistorySortKey' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringAlertHistoryRequest$SortBy' => 'The field used to sort results. The default is CreationTime.
Provides summary information of an alert\'s history.
', 'refs' => [ 'MonitoringAlertHistoryList$member' => NULL, ], ], 'MonitoringAlertName' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringAlertHistoryRequest$MonitoringAlertName' => 'The name of a monitoring alert.
', 'MonitoringAlertHistorySummary$MonitoringAlertName' => 'The name of a monitoring alert.
', 'MonitoringAlertSummary$MonitoringAlertName' => 'The name of a monitoring alert.
', 'UpdateMonitoringAlertRequest$MonitoringAlertName' => 'The name of a monitoring alert.
', 'UpdateMonitoringAlertResponse$MonitoringAlertName' => 'The name of a monitoring alert.
', ], ], 'MonitoringAlertStatus' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringAlertHistoryRequest$StatusEquals' => 'A filter that retrieves only alerts with a specific status.
', 'MonitoringAlertHistorySummary$AlertStatus' => 'The current alert status of an alert.
', 'MonitoringAlertSummary$AlertStatus' => 'The current status of an alert.
', ], ], 'MonitoringAlertSummary' => [ 'base' => 'Provides summary information about a monitor alert.
', 'refs' => [ 'MonitoringAlertSummaryList$member' => NULL, ], ], 'MonitoringAlertSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringAlertsResponse$MonitoringAlertSummaries' => 'A JSON array where each element is a summary for a monitoring alert.
', 'ModelDashboardMonitoringSchedule$MonitoringAlertSummaries' => 'A JSON array where each element is a summary for a monitoring alert.
', ], ], 'MonitoringAppSpecification' => [ 'base' => 'Container image configuration object for the monitoring job.
', 'refs' => [ 'MonitoringJobDefinition$MonitoringAppSpecification' => 'Configures the monitoring job to run a specified Docker container image.
', ], ], 'MonitoringBaselineConfig' => [ 'base' => 'Configuration for monitoring constraints and monitoring statistics. These baseline resources are compared against the results of the current job from the series of jobs scheduled to collect data periodically.
', 'refs' => [ 'MonitoringJobDefinition$BaselineConfig' => 'Baseline configuration used to validate that the data conforms to the specified constraints and statistics
', ], ], 'MonitoringClusterConfig' => [ 'base' => 'Configuration for the cluster used to run model monitoring jobs.
', 'refs' => [ 'MonitoringResources$ClusterConfig' => 'The configuration for the cluster resources used to run the processing job.
', ], ], 'MonitoringConstraintsResource' => [ 'base' => 'The constraints resource for a monitoring job.
', 'refs' => [ 'DataQualityBaselineConfig$ConstraintsResource' => NULL, 'ModelBiasBaselineConfig$ConstraintsResource' => NULL, 'ModelExplainabilityBaselineConfig$ConstraintsResource' => NULL, 'ModelQualityBaselineConfig$ConstraintsResource' => NULL, 'MonitoringBaselineConfig$ConstraintsResource' => 'The baseline constraint file in Amazon S3 that the current monitoring job should validated against.
', ], ], 'MonitoringContainerArguments' => [ 'base' => NULL, 'refs' => [ 'DataQualityAppSpecification$ContainerArguments' => 'The arguments to send to the container that the monitoring job runs.
', 'ModelQualityAppSpecification$ContainerArguments' => 'An array of arguments for the container used to run the monitoring job.
', 'MonitoringAppSpecification$ContainerArguments' => 'An array of arguments for the container used to run the monitoring job.
', ], ], 'MonitoringCsvDatasetFormat' => [ 'base' => 'Represents the CSV dataset format used when running a monitoring job.
', 'refs' => [ 'MonitoringDatasetFormat$Csv' => 'The CSV dataset used in the monitoring job.
', ], ], 'MonitoringDatapointsToAlert' => [ 'base' => NULL, 'refs' => [ 'MonitoringAlertSummary$DatapointsToAlert' => 'Within EvaluationPeriod, how many execution failures will raise an alert.
Within EvaluationPeriod, how many execution failures will raise an alert.
Represents the dataset format used when running a monitoring job.
', 'refs' => [ 'BatchTransformInput$DatasetFormat' => 'The dataset format for your batch transform job.
', ], ], 'MonitoringEnvironmentMap' => [ 'base' => NULL, 'refs' => [ 'DataQualityAppSpecification$Environment' => 'Sets the environment variables in the container that the monitoring job runs.
', 'ModelBiasAppSpecification$Environment' => 'Sets the environment variables in the Docker container.
', 'ModelExplainabilityAppSpecification$Environment' => 'Sets the environment variables in the Docker container.
', 'ModelQualityAppSpecification$Environment' => 'Sets the environment variables in the container that the monitoring job runs.
', 'MonitoringJobDefinition$Environment' => 'Sets the environment variables in the Docker container.
', ], ], 'MonitoringEvaluationPeriod' => [ 'base' => NULL, 'refs' => [ 'MonitoringAlertSummary$EvaluationPeriod' => 'The number of most recent monitoring executions to consider when evaluating alert status.
', 'UpdateMonitoringAlertRequest$EvaluationPeriod' => 'The number of most recent monitoring executions to consider when evaluating alert status.
', ], ], 'MonitoringExecutionSortKey' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringExecutionsRequest$SortBy' => 'Whether to sort the results by the Status, CreationTime, or ScheduledTime field. The default is CreationTime.
Summary of information about the last monitoring job to run.
', 'refs' => [ 'DescribeMonitoringScheduleResponse$LastMonitoringExecutionSummary' => 'Describes metadata on the last execution to run, if there was one.
', 'ModelDashboardMonitoringSchedule$LastMonitoringExecutionSummary' => NULL, 'MonitoringExecutionSummaryList$member' => NULL, 'MonitoringSchedule$LastMonitoringExecutionSummary' => NULL, ], ], 'MonitoringExecutionSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringExecutionsResponse$MonitoringExecutionSummaries' => 'A JSON array in which each element is a summary for a monitoring execution.
', ], ], 'MonitoringGroundTruthS3Input' => [ 'base' => 'The ground truth labels for the dataset used for the monitoring job.
', 'refs' => [ 'ModelBiasJobInput$GroundTruthS3Input' => 'Location of ground truth labels to use in model bias job.
', 'ModelQualityJobInput$GroundTruthS3Input' => 'The ground truth label provided for the model.
', ], ], 'MonitoringInput' => [ 'base' => 'The inputs for a monitoring job.
', 'refs' => [ 'MonitoringInputs$member' => NULL, ], ], 'MonitoringInputs' => [ 'base' => NULL, 'refs' => [ 'MonitoringJobDefinition$MonitoringInputs' => 'The array of inputs for the monitoring job. Currently we support monitoring an Amazon SageMaker Endpoint.
', ], ], 'MonitoringJobDefinition' => [ 'base' => 'Defines the monitoring job.
', 'refs' => [ 'MonitoringScheduleConfig$MonitoringJobDefinition' => 'Defines the monitoring job.
', ], ], 'MonitoringJobDefinitionArn' => [ 'base' => NULL, 'refs' => [ 'CreateDataQualityJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the job definition.
', 'CreateModelBiasJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the model bias job.
', 'CreateModelExplainabilityJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the model explainability job.
', 'CreateModelQualityJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the model quality monitoring job.
', 'DescribeDataQualityJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the data quality monitoring job definition.
', 'DescribeModelBiasJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the model bias job.
', 'DescribeModelExplainabilityJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the model explainability job.
', 'DescribeModelQualityJobDefinitionResponse$JobDefinitionArn' => 'The Amazon Resource Name (ARN) of the model quality job.
', 'MonitoringJobDefinitionSummary$MonitoringJobDefinitionArn' => 'The Amazon Resource Name (ARN) of the monitoring job.
', ], ], 'MonitoringJobDefinitionName' => [ 'base' => NULL, 'refs' => [ 'CreateDataQualityJobDefinitionRequest$JobDefinitionName' => 'The name for the monitoring job definition.
', 'CreateModelBiasJobDefinitionRequest$JobDefinitionName' => 'The name of the bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'CreateModelExplainabilityJobDefinitionRequest$JobDefinitionName' => 'The name of the model explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'CreateModelQualityJobDefinitionRequest$JobDefinitionName' => 'The name of the monitoring job definition.
', 'DeleteDataQualityJobDefinitionRequest$JobDefinitionName' => 'The name of the data quality monitoring job definition to delete.
', 'DeleteModelBiasJobDefinitionRequest$JobDefinitionName' => 'The name of the model bias job definition to delete.
', 'DeleteModelExplainabilityJobDefinitionRequest$JobDefinitionName' => 'The name of the model explainability job definition to delete.
', 'DeleteModelQualityJobDefinitionRequest$JobDefinitionName' => 'The name of the model quality monitoring job definition to delete.
', 'DescribeDataQualityJobDefinitionRequest$JobDefinitionName' => 'The name of the data quality monitoring job definition to describe.
', 'DescribeDataQualityJobDefinitionResponse$JobDefinitionName' => 'The name of the data quality monitoring job definition.
', 'DescribeModelBiasJobDefinitionRequest$JobDefinitionName' => 'The name of the model bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeModelBiasJobDefinitionResponse$JobDefinitionName' => 'The name of the bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeModelExplainabilityJobDefinitionRequest$JobDefinitionName' => 'The name of the model explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeModelExplainabilityJobDefinitionResponse$JobDefinitionName' => 'The name of the explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeModelQualityJobDefinitionRequest$JobDefinitionName' => 'The name of the model quality job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeModelQualityJobDefinitionResponse$JobDefinitionName' => 'The name of the quality job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'ListMonitoringExecutionsRequest$MonitoringJobDefinitionName' => 'Gets a list of the monitoring job runs of the specified monitoring job definitions.
', 'ListMonitoringSchedulesRequest$MonitoringJobDefinitionName' => 'Gets a list of the monitoring schedules for the specified monitoring job definition.
', 'MonitoringExecutionSummary$MonitoringJobDefinitionName' => 'The name of the monitoring job.
', 'MonitoringJobDefinitionSummary$MonitoringJobDefinitionName' => 'The name of the monitoring job.
', 'MonitoringScheduleConfig$MonitoringJobDefinitionName' => 'The name of the monitoring job definition to schedule.
', 'MonitoringScheduleSummary$MonitoringJobDefinitionName' => 'The name of the monitoring job definition that the schedule is for.
', ], ], 'MonitoringJobDefinitionSortKey' => [ 'base' => NULL, 'refs' => [ 'ListDataQualityJobDefinitionsRequest$SortBy' => 'The field to sort results by. The default is CreationTime.
Whether to sort results by the Name or CreationTime field. The default is CreationTime.
Whether to sort results by the Name or CreationTime field. The default is CreationTime.
The field to sort results by. The default is CreationTime.
Summary information about a monitoring job.
', 'refs' => [ 'MonitoringJobDefinitionSummaryList$member' => NULL, ], ], 'MonitoringJobDefinitionSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListDataQualityJobDefinitionsResponse$JobDefinitionSummaries' => 'A list of data quality monitoring job definitions.
', 'ListModelBiasJobDefinitionsResponse$JobDefinitionSummaries' => 'A JSON array in which each element is a summary for a model bias jobs.
', 'ListModelExplainabilityJobDefinitionsResponse$JobDefinitionSummaries' => 'A JSON array in which each element is a summary for a explainability bias jobs.
', 'ListModelQualityJobDefinitionsResponse$JobDefinitionSummaries' => 'A list of summaries of model quality monitoring job definitions.
', ], ], 'MonitoringJsonDatasetFormat' => [ 'base' => 'Represents the JSON dataset format used when running a monitoring job.
', 'refs' => [ 'MonitoringDatasetFormat$Json' => 'The JSON dataset used in the monitoring job
', ], ], 'MonitoringMaxRuntimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'MonitoringStoppingCondition$MaxRuntimeInSeconds' => 'The maximum runtime allowed in seconds.
The MaxRuntimeInSeconds cannot exceed the frequency of the job. For data quality and model explainability, this can be up to 3600 seconds for an hourly schedule. For model bias and model quality hourly schedules, this can be up to 1800 seconds.
The networking configuration for the monitoring job.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$NetworkConfig' => 'Specifies networking configuration for the monitoring job.
', 'CreateModelBiasJobDefinitionRequest$NetworkConfig' => 'Networking options for a model bias job.
', 'CreateModelExplainabilityJobDefinitionRequest$NetworkConfig' => 'Networking options for a model explainability job.
', 'CreateModelQualityJobDefinitionRequest$NetworkConfig' => 'Specifies the network configuration for the monitoring job.
', 'DescribeDataQualityJobDefinitionResponse$NetworkConfig' => 'The networking configuration for the data quality monitoring job.
', 'DescribeModelBiasJobDefinitionResponse$NetworkConfig' => 'Networking options for a model bias job.
', 'DescribeModelExplainabilityJobDefinitionResponse$NetworkConfig' => 'Networking options for a model explainability job.
', 'DescribeModelQualityJobDefinitionResponse$NetworkConfig' => 'Networking options for a model quality job.
', ], ], 'MonitoringOutput' => [ 'base' => 'The output object for a monitoring job.
', 'refs' => [ 'MonitoringOutputs$member' => NULL, ], ], 'MonitoringOutputConfig' => [ 'base' => 'The output configuration for monitoring jobs.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$DataQualityJobOutputConfig' => NULL, 'CreateModelBiasJobDefinitionRequest$ModelBiasJobOutputConfig' => NULL, 'CreateModelExplainabilityJobDefinitionRequest$ModelExplainabilityJobOutputConfig' => NULL, 'CreateModelQualityJobDefinitionRequest$ModelQualityJobOutputConfig' => NULL, 'DescribeDataQualityJobDefinitionResponse$DataQualityJobOutputConfig' => NULL, 'DescribeModelBiasJobDefinitionResponse$ModelBiasJobOutputConfig' => NULL, 'DescribeModelExplainabilityJobDefinitionResponse$ModelExplainabilityJobOutputConfig' => NULL, 'DescribeModelQualityJobDefinitionResponse$ModelQualityJobOutputConfig' => NULL, 'MonitoringJobDefinition$MonitoringOutputConfig' => 'The array of outputs from the monitoring job to be uploaded to Amazon S3.
', ], ], 'MonitoringOutputs' => [ 'base' => NULL, 'refs' => [ 'MonitoringOutputConfig$MonitoringOutputs' => 'Monitoring outputs for monitoring jobs. This is where the output of the periodic monitoring jobs is uploaded.
', ], ], 'MonitoringParquetDatasetFormat' => [ 'base' => 'Represents the Parquet dataset format used when running a monitoring job.
', 'refs' => [ 'MonitoringDatasetFormat$Parquet' => 'The Parquet dataset used in the monitoring job
', ], ], 'MonitoringProblemType' => [ 'base' => NULL, 'refs' => [ 'ModelQualityAppSpecification$ProblemType' => 'The machine learning problem type of the model that the monitoring job monitors.
', ], ], 'MonitoringResources' => [ 'base' => 'Identifies the resources to deploy for a monitoring job.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$JobResources' => NULL, 'CreateModelBiasJobDefinitionRequest$JobResources' => NULL, 'CreateModelExplainabilityJobDefinitionRequest$JobResources' => NULL, 'CreateModelQualityJobDefinitionRequest$JobResources' => NULL, 'DescribeDataQualityJobDefinitionResponse$JobResources' => NULL, 'DescribeModelBiasJobDefinitionResponse$JobResources' => NULL, 'DescribeModelExplainabilityJobDefinitionResponse$JobResources' => NULL, 'DescribeModelQualityJobDefinitionResponse$JobResources' => NULL, 'MonitoringJobDefinition$MonitoringResources' => 'Identifies the resources, ML compute instances, and ML storage volumes to deploy for a monitoring job. In distributed processing, you specify more than one instance.
', ], ], 'MonitoringS3Output' => [ 'base' => 'Information about where and how you want to store the results of a monitoring job.
', 'refs' => [ 'MonitoringOutput$S3Output' => 'The Amazon S3 storage location where the results of a monitoring job are saved.
', ], ], 'MonitoringS3Uri' => [ 'base' => NULL, 'refs' => [ 'MonitoringGroundTruthS3Input$S3Uri' => 'The address of the Amazon S3 location of the ground truth labels.
', 'MonitoringS3Output$S3Uri' => 'A URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job.
', ], ], 'MonitoringSchedule' => [ 'base' => 'A schedule for a model monitoring job. For information about model monitor, see Amazon SageMaker Model Monitor.
', 'refs' => [ 'MonitoringScheduleList$member' => NULL, ], ], 'MonitoringScheduleArn' => [ 'base' => NULL, 'refs' => [ 'CreateMonitoringScheduleResponse$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of the monitoring schedule.
', 'DescribeMonitoringScheduleResponse$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of the monitoring schedule.
', 'DescribeProcessingJobResponse$MonitoringScheduleArn' => 'The ARN of a monitoring schedule for an endpoint associated with this processing job.
', 'ModelDashboardMonitoringSchedule$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of a monitoring schedule.
', 'MonitoringSchedule$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of the monitoring schedule.
', 'MonitoringScheduleSummary$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of the monitoring schedule.
', 'ProcessingJob$MonitoringScheduleArn' => 'The ARN of a monitoring schedule for an endpoint associated with this processing job.
', 'UpdateMonitoringAlertResponse$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of the monitoring schedule.
', 'UpdateMonitoringScheduleResponse$MonitoringScheduleArn' => 'The Amazon Resource Name (ARN) of the monitoring schedule.
', ], ], 'MonitoringScheduleConfig' => [ 'base' => 'Configures the monitoring schedule and defines the monitoring job.
', 'refs' => [ 'CreateMonitoringScheduleRequest$MonitoringScheduleConfig' => 'The configuration object that specifies the monitoring schedule and defines the monitoring job.
', 'DescribeMonitoringScheduleResponse$MonitoringScheduleConfig' => 'The configuration object that specifies the monitoring schedule and defines the monitoring job.
', 'ModelDashboardMonitoringSchedule$MonitoringScheduleConfig' => NULL, 'MonitoringSchedule$MonitoringScheduleConfig' => NULL, 'UpdateMonitoringScheduleRequest$MonitoringScheduleConfig' => 'The configuration object that specifies the monitoring schedule and defines the monitoring job.
', ], ], 'MonitoringScheduleList' => [ 'base' => NULL, 'refs' => [ 'Endpoint$MonitoringSchedules' => 'A list of monitoring schedules for the endpoint. For information about model monitoring, see Amazon SageMaker Model Monitor.
', ], ], 'MonitoringScheduleName' => [ 'base' => NULL, 'refs' => [ 'CreateMonitoringScheduleRequest$MonitoringScheduleName' => 'The name of the monitoring schedule. The name must be unique within an Amazon Web Services Region within an Amazon Web Services account.
', 'DeleteMonitoringScheduleRequest$MonitoringScheduleName' => 'The name of the monitoring schedule to delete.
', 'DescribeMonitoringScheduleRequest$MonitoringScheduleName' => 'Name of a previously created monitoring schedule.
', 'DescribeMonitoringScheduleResponse$MonitoringScheduleName' => 'Name of the monitoring schedule.
', 'ListMonitoringAlertHistoryRequest$MonitoringScheduleName' => 'The name of a monitoring schedule.
', 'ListMonitoringAlertsRequest$MonitoringScheduleName' => 'The name of a monitoring schedule.
', 'ListMonitoringExecutionsRequest$MonitoringScheduleName' => 'Name of a specific schedule to fetch jobs for.
', 'ModelDashboardMonitoringSchedule$MonitoringScheduleName' => 'The name of a monitoring schedule.
', 'MonitoringAlertHistorySummary$MonitoringScheduleName' => 'The name of a monitoring schedule.
', 'MonitoringExecutionSummary$MonitoringScheduleName' => 'The name of the monitoring schedule.
', 'MonitoringSchedule$MonitoringScheduleName' => 'The name of the monitoring schedule.
', 'MonitoringScheduleSummary$MonitoringScheduleName' => 'The name of the monitoring schedule.
', 'StartMonitoringScheduleRequest$MonitoringScheduleName' => 'The name of the schedule to start.
', 'StopMonitoringScheduleRequest$MonitoringScheduleName' => 'The name of the schedule to stop.
', 'UpdateMonitoringAlertRequest$MonitoringScheduleName' => 'The name of a monitoring schedule.
', 'UpdateMonitoringScheduleRequest$MonitoringScheduleName' => 'The name of the monitoring schedule. The name must be unique within an Amazon Web Services Region within an Amazon Web Services account.
', ], ], 'MonitoringScheduleSortKey' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringSchedulesRequest$SortBy' => 'Whether to sort the results by the Status, CreationTime, or ScheduledTime field. The default is CreationTime.
Summarizes the monitoring schedule.
', 'refs' => [ 'MonitoringScheduleSummaryList$member' => NULL, ], ], 'MonitoringScheduleSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListMonitoringSchedulesResponse$MonitoringScheduleSummaries' => 'A JSON array in which each element is a summary for a monitoring schedule.
', ], ], 'MonitoringStatisticsResource' => [ 'base' => 'The statistics resource for a monitoring job.
', 'refs' => [ 'DataQualityBaselineConfig$StatisticsResource' => NULL, 'MonitoringBaselineConfig$StatisticsResource' => 'The baseline statistics file in Amazon S3 that the current monitoring job should be validated against.
', ], ], 'MonitoringStoppingCondition' => [ 'base' => 'A time limit for how long the monitoring job is allowed to run before stopping.
', 'refs' => [ 'CreateDataQualityJobDefinitionRequest$StoppingCondition' => NULL, 'CreateModelBiasJobDefinitionRequest$StoppingCondition' => NULL, 'CreateModelExplainabilityJobDefinitionRequest$StoppingCondition' => NULL, 'CreateModelQualityJobDefinitionRequest$StoppingCondition' => NULL, 'DescribeDataQualityJobDefinitionResponse$StoppingCondition' => NULL, 'DescribeModelBiasJobDefinitionResponse$StoppingCondition' => NULL, 'DescribeModelExplainabilityJobDefinitionResponse$StoppingCondition' => NULL, 'DescribeModelQualityJobDefinitionResponse$StoppingCondition' => NULL, 'MonitoringJobDefinition$StoppingCondition' => 'Specifies a time limit for how long the monitoring job is allowed to run.
', ], ], 'MonitoringTimeOffsetString' => [ 'base' => NULL, 'refs' => [ 'BatchTransformInput$StartTimeOffset' => 'If specified, monitoring jobs substract this time from the start time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
', 'BatchTransformInput$EndTimeOffset' => 'If specified, monitoring jobs subtract this time from the end time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
', 'EndpointInput$StartTimeOffset' => 'If specified, monitoring jobs substract this time from the start time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
', 'EndpointInput$EndTimeOffset' => 'If specified, monitoring jobs substract this time from the end time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
', ], ], 'MonitoringType' => [ 'base' => NULL, 'refs' => [ 'DescribeMonitoringScheduleResponse$MonitoringType' => 'The type of the monitoring job that this schedule runs. This is one of the following values.
DATA_QUALITY - The schedule is for a data quality monitoring job.
MODEL_QUALITY - The schedule is for a model quality monitoring job.
MODEL_BIAS - The schedule is for a bias monitoring job.
MODEL_EXPLAINABILITY - The schedule is for an explainability monitoring job.
A filter that returns only the monitoring job runs of the specified monitoring type.
', 'ListMonitoringSchedulesRequest$MonitoringTypeEquals' => 'A filter that returns only the monitoring schedules for the specified monitoring type.
', 'ModelDashboardMonitoringSchedule$MonitoringType' => 'The monitor type of a model monitor.
', 'MonitoringExecutionSummary$MonitoringType' => 'The type of the monitoring job.
', 'MonitoringSchedule$MonitoringType' => 'The type of the monitoring job definition to schedule.
', 'MonitoringScheduleConfig$MonitoringType' => 'The type of the monitoring job definition to schedule.
', 'MonitoringScheduleSummary$MonitoringType' => 'The type of the monitoring job definition that the schedule is for.
', ], ], 'MountPath' => [ 'base' => NULL, 'refs' => [ 'FileSystemConfig$MountPath' => 'The path within the image to mount the user\'s EFS home directory. The directory should be empty. If not specified, defaults to /home/sagemaker-user.
', ], ], 'MultiModelConfig' => [ 'base' => 'Specifies additional configuration for hosting multi-model endpoints.
', 'refs' => [ 'ContainerDefinition$MultiModelConfig' => 'Specifies additional configuration for multi-model endpoints.
', ], ], 'NameContains' => [ 'base' => NULL, 'refs' => [ 'ListAlgorithmsInput$NameContains' => 'A string in the algorithm name. This filter returns only algorithms whose name contains the specified string.
', 'ListCompilationJobsRequest$NameContains' => 'A filter that returns the model compilation jobs whose name contains a specified string.
', 'ListDataQualityJobDefinitionsRequest$NameContains' => 'A string in the data quality monitoring job definition name. This filter returns only data quality monitoring job definitions whose name contains the specified string.
', 'ListDeviceFleetsRequest$NameContains' => 'Filter for fleets containing this name in their fleet device name.
', 'ListEdgeDeploymentPlansRequest$NameContains' => 'Selects edge deployment plans with names containing this name.
', 'ListEdgeDeploymentPlansRequest$DeviceFleetNameContains' => 'Selects edge deployment plans with a device fleet name containing this name.
', 'ListEdgePackagingJobsRequest$NameContains' => 'Filter for jobs containing this name in their packaging job name.
', 'ListEdgePackagingJobsRequest$ModelNameContains' => 'Filter for jobs where the model name contains this string.
', 'ListHubContentsRequest$NameContains' => 'Only list hub content if the name contains the specified string.
', 'ListHubsRequest$NameContains' => 'Only list hubs with names that contain the specified string.
', 'ListHyperParameterTuningJobsRequest$NameContains' => 'A string in the tuning job name. This filter returns only tuning jobs whose name contains the specified string.
', 'ListInferenceExperimentsRequest$NameContains' => 'Selects inference experiments whose names contain this name.
', 'ListInferenceRecommendationsJobsRequest$NameContains' => 'A string in the job name. This filter returns only recommendations whose name contains the specified string.
', 'ListLabelingJobsRequest$NameContains' => 'A string in the labeling job name. This filter returns only labeling jobs whose name contains the specified string.
', 'ListModelBiasJobDefinitionsRequest$NameContains' => 'Filter for model bias jobs whose name contains a specified string.
', 'ListModelExplainabilityJobDefinitionsRequest$NameContains' => 'Filter for model explainability jobs whose name contains a specified string.
', 'ListModelPackageGroupsInput$NameContains' => 'A string in the model group name. This filter returns only model groups whose name contains the specified string.
', 'ListModelPackagesInput$NameContains' => 'A string in the model package name. This filter returns only model packages whose name contains the specified string.
', 'ListModelQualityJobDefinitionsRequest$NameContains' => 'A string in the transform job name. This filter returns only model quality monitoring job definitions whose name contains the specified string.
', 'ListMonitoringSchedulesRequest$NameContains' => 'Filter for monitoring schedules whose name contains a specified string.
', 'ListTrainingJobsRequest$NameContains' => 'A string in the training job name. This filter returns only training jobs whose name contains the specified string.
', 'ListTransformJobsRequest$NameContains' => 'A string in the transform job name. This filter returns only transform jobs whose name contains the specified string.
', ], ], 'NeoVpcConfig' => [ 'base' => 'The VpcConfig configuration object that specifies the VPC that you want the compilation jobs to connect to. For more information on controlling access to your Amazon S3 buckets used for compilation job, see Give Amazon SageMaker Compilation Jobs Access to Resources in Your Amazon VPC.
', 'refs' => [ 'CreateCompilationJobRequest$VpcConfig' => 'A VpcConfig object that specifies the VPC that you want your compilation job to connect to. Control access to your models by configuring the VPC. For more information, see Protect Compilation Jobs by Using an Amazon Virtual Private Cloud.
', 'DescribeCompilationJobResponse$VpcConfig' => 'A VpcConfig object that specifies the VPC that you want your compilation job to connect to. Control access to your models by configuring the VPC. For more information, see Protect Compilation Jobs by Using an Amazon Virtual Private Cloud.
', ], ], 'NeoVpcSecurityGroupId' => [ 'base' => NULL, 'refs' => [ 'NeoVpcSecurityGroupIds$member' => NULL, ], ], 'NeoVpcSecurityGroupIds' => [ 'base' => NULL, 'refs' => [ 'NeoVpcConfig$SecurityGroupIds' => 'The VPC security group IDs. IDs have the form of sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
The ID of the subnets in the VPC that you want to connect the compilation job to for accessing the model in Amazon S3.
', ], ], 'NestedFilters' => [ 'base' => 'A list of nested Filter objects. A resource must satisfy the conditions of all filters to be included in the results returned from the Search API.
For example, to filter on a training job\'s InputDataConfig property with a specific channel name and S3Uri prefix, define the following filters:
\'{Name:"InputDataConfig.ChannelName", "Operator":"Equals", "Value":"train"}\',
\'{Name:"InputDataConfig.DataSource.S3DataSource.S3Uri", "Operator":"Contains", "Value":"mybucket/catdata"}\'
A list of nested filter objects.
', ], ], 'NetworkConfig' => [ 'base' => 'Networking options for a job, such as network traffic encryption between containers, whether to allow inbound and outbound network calls to and from containers, and the VPC subnets and security groups to use for VPC-enabled jobs.
', 'refs' => [ 'CreateProcessingJobRequest$NetworkConfig' => 'Networking options for a processing job, such as whether to allow inbound and outbound network calls to and from processing containers, and the VPC subnets and security groups to use for VPC-enabled processing jobs.
', 'DescribeProcessingJobResponse$NetworkConfig' => 'Networking options for a processing job.
', 'MonitoringJobDefinition$NetworkConfig' => 'Specifies networking options for an monitoring job.
', 'ProcessingJob$NetworkConfig' => NULL, ], ], 'NetworkInterfaceId' => [ 'base' => NULL, 'refs' => [ 'DescribeNotebookInstanceOutput$NetworkInterfaceId' => 'The network interface IDs that SageMaker created at the time of creating the instance.
', ], ], 'NextToken' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceRequest$NextToken' => 'Next token of device description.
', 'DescribeDeviceResponse$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'DescribeEdgeDeploymentPlanRequest$NextToken' => 'If the edge deployment plan has enough stages to require tokening, then this is the response from the last list of stages returned.
', 'DescribeEdgeDeploymentPlanResponse$NextToken' => 'Token to use when calling the next set of stages in the edge deployment plan.
', 'DescribeFeatureGroupRequest$NextToken' => 'A token to resume pagination of the list of Features (FeatureDefinitions). 2,500 Features are returned by default.
A token to resume pagination of the list of Features (FeatureDefinitions).
If the previous call to ListActions didn\'t return the full set of actions, the call returns a token for getting the next set of actions.
A token for getting the next set of actions, if there are any.
', 'ListAlgorithmsInput$NextToken' => 'If the response to a previous ListAlgorithms request was truncated, the response includes a NextToken. To retrieve the next set of algorithms, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of algorithms, use it in the subsequent request.
', 'ListAliasesRequest$NextToken' => 'If the previous call to ListAliases didn\'t return the full set of aliases, the call returns a token for retrieving the next set of aliases.
A token for getting the next set of aliases, if more aliases exist.
', 'ListAppImageConfigsRequest$NextToken' => 'If the previous call to ListImages didn\'t return the full set of AppImageConfigs, the call returns a token for getting the next set of AppImageConfigs.
A token for getting the next set of AppImageConfigs, if there are any.
', 'ListAppsRequest$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListAppsResponse$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListArtifactsRequest$NextToken' => 'If the previous call to ListArtifacts didn\'t return the full set of artifacts, the call returns a token for getting the next set of artifacts.
A token for getting the next set of artifacts, if there are any.
', 'ListAssociationsRequest$NextToken' => 'If the previous call to ListAssociations didn\'t return the full set of associations, the call returns a token for getting the next set of associations.
A token for getting the next set of associations, if there are any.
', 'ListAutoMLJobsRequest$NextToken' => 'If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
', 'ListAutoMLJobsResponse$NextToken' => 'If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
', 'ListCandidatesForAutoMLJobRequest$NextToken' => 'If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
', 'ListCandidatesForAutoMLJobResponse$NextToken' => 'If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
', 'ListCodeRepositoriesInput$NextToken' => 'If the result of a ListCodeRepositoriesOutput request was truncated, the response includes a NextToken. To get the next set of Git repositories, use the token in the next request.
If the result of a ListCodeRepositoriesOutput request was truncated, the response includes a NextToken. To get the next set of Git repositories, use the token in the next request.
If the result of the previous ListCompilationJobs request was truncated, the response includes a NextToken. To retrieve the next set of model compilation jobs, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this NextToken. To retrieve the next set of model compilation jobs, use this token in the next request.
If the previous call to ListContexts didn\'t return the full set of contexts, the call returns a token for getting the next set of contexts.
A token for getting the next set of contexts, if there are any.
', 'ListDataQualityJobDefinitionsRequest$NextToken' => 'If the result of the previous ListDataQualityJobDefinitions request was truncated, the response includes a NextToken. To retrieve the next set of transform jobs, use the token in the next request.>
If the result of the previous ListDataQualityJobDefinitions request was truncated, the response includes a NextToken. To retrieve the next set of data quality monitoring job definitions, use the token in the next request.
The response from the last list when returning a list large enough to need tokening.
', 'ListDeviceFleetsResponse$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'ListDevicesRequest$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'ListDevicesResponse$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'ListDomainsRequest$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListDomainsResponse$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListEdgeDeploymentPlansRequest$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'ListEdgeDeploymentPlansResponse$NextToken' => 'The token to use when calling the next page of results.
', 'ListEdgePackagingJobsRequest$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'ListEdgePackagingJobsResponse$NextToken' => 'Token to use when calling the next page of results.
', 'ListExperimentsRequest$NextToken' => 'If the previous call to ListExperiments didn\'t return the full set of experiments, the call returns a token for getting the next set of experiments.
A token for getting the next set of experiments, if there are any.
', 'ListFeatureGroupsRequest$NextToken' => 'A token to resume pagination of ListFeatureGroups results.
A token to resume pagination of ListFeatureGroups results.
A token to resume pagination.
', 'ListFlowDefinitionsResponse$NextToken' => 'A token to resume pagination.
', 'ListHubContentVersionsRequest$NextToken' => 'If the response to a previous ListHubContentVersions request was truncated, the response includes a NextToken. To retrieve the next set of hub content versions, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of hub content versions, use it in the subsequent request.
', 'ListHubContentsRequest$NextToken' => 'If the response to a previous ListHubContents request was truncated, the response includes a NextToken. To retrieve the next set of hub content, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of hub content, use it in the subsequent request.
', 'ListHubsRequest$NextToken' => 'If the response to a previous ListHubs request was truncated, the response includes a NextToken. To retrieve the next set of hubs, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of hubs, use it in the subsequent request.
', 'ListHumanTaskUisRequest$NextToken' => 'A token to resume pagination.
', 'ListHumanTaskUisResponse$NextToken' => 'A token to resume pagination.
', 'ListHyperParameterTuningJobsRequest$NextToken' => 'If the result of the previous ListHyperParameterTuningJobs request was truncated, the response includes a NextToken. To retrieve the next set of tuning jobs, use the token in the next request.
If the result of this ListHyperParameterTuningJobs request was truncated, the response includes a NextToken. To retrieve the next set of tuning jobs, use the token in the next request.
If the previous call to ListImageVersions didn\'t return the full set of versions, the call returns a token for getting the next set of versions.
A token for getting the next set of versions, if there are any.
', 'ListImagesRequest$NextToken' => 'If the previous call to ListImages didn\'t return the full set of images, the call returns a token for getting the next set of images.
A token for getting the next set of images, if there are any.
', 'ListInferenceExperimentsRequest$NextToken' => 'The response from the last list when returning a list large enough to need tokening.
', 'ListInferenceExperimentsResponse$NextToken' => 'The token to use when calling the next page of results.
', 'ListInferenceRecommendationsJobStepsRequest$NextToken' => 'A token that you can specify to return more results from the list. Specify this field if you have a token that was returned from a previous request.
', 'ListInferenceRecommendationsJobStepsResponse$NextToken' => 'A token that you can specify in your next request to return more results from the list.
', 'ListInferenceRecommendationsJobsRequest$NextToken' => 'If the response to a previous ListInferenceRecommendationsJobsRequest request was truncated, the response includes a NextToken. To retrieve the next set of recommendations, use the token in the next request.
A token for getting the next set of recommendations, if there are any.
', 'ListLabelingJobsForWorkteamRequest$NextToken' => 'If the result of the previous ListLabelingJobsForWorkteam request was truncated, the response includes a NextToken. To retrieve the next set of labeling jobs, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of labeling jobs, use it in the subsequent request.
', 'ListLabelingJobsRequest$NextToken' => 'If the result of the previous ListLabelingJobs request was truncated, the response includes a NextToken. To retrieve the next set of labeling jobs, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of labeling jobs, use it in the subsequent request.
', 'ListLineageGroupsRequest$NextToken' => 'If the response is truncated, SageMaker returns this token. To retrieve the next set of algorithms, use it in the subsequent request.
', 'ListLineageGroupsResponse$NextToken' => 'If the response is truncated, SageMaker returns this token. To retrieve the next set of algorithms, use it in the subsequent request.
', 'ListModelBiasJobDefinitionsRequest$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListModelBiasJobDefinitionsResponse$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListModelCardExportJobsRequest$NextToken' => 'If the response to a previous ListModelCardExportJobs request was truncated, the response includes a NextToken. To retrieve the next set of model card export jobs, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of model card export jobs, use it in the subsequent request.
', 'ListModelCardVersionsRequest$NextToken' => 'If the response to a previous ListModelCardVersions request was truncated, the response includes a NextToken. To retrieve the next set of model card versions, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of model card versions, use it in the subsequent request.
', 'ListModelCardsRequest$NextToken' => 'If the response to a previous ListModelCards request was truncated, the response includes a NextToken. To retrieve the next set of model cards, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of model cards, use it in the subsequent request.
', 'ListModelExplainabilityJobDefinitionsRequest$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListModelExplainabilityJobDefinitionsResponse$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListModelMetadataRequest$NextToken' => 'If the response to a previous ListModelMetadataResponse request was truncated, the response includes a NextToken. To retrieve the next set of model metadata, use the token in the next request.
A token for getting the next set of recommendations, if there are any.
', 'ListModelPackageGroupsInput$NextToken' => 'If the result of the previous ListModelPackageGroups request was truncated, the response includes a NextToken. To retrieve the next set of model groups, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of model groups, use it in the subsequent request.
', 'ListModelPackagesInput$NextToken' => 'If the response to a previous ListModelPackages request was truncated, the response includes a NextToken. To retrieve the next set of model packages, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of model packages, use it in the subsequent request.
', 'ListModelQualityJobDefinitionsRequest$NextToken' => 'If the result of the previous ListModelQualityJobDefinitions request was truncated, the response includes a NextToken. To retrieve the next set of model quality monitoring job definitions, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of model quality monitoring job definitions, use it in the next request.
', 'ListMonitoringAlertHistoryRequest$NextToken' => 'If the result of the previous ListMonitoringAlertHistory request was truncated, the response includes a NextToken. To retrieve the next set of alerts in the history, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of alerts, use it in the subsequent request.
', 'ListMonitoringAlertsRequest$NextToken' => 'If the result of the previous ListMonitoringAlerts request was truncated, the response includes a NextToken. To retrieve the next set of alerts in the history, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of alerts, use it in the subsequent request.
', 'ListMonitoringExecutionsRequest$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListMonitoringExecutionsResponse$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListMonitoringSchedulesRequest$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListMonitoringSchedulesResponse$NextToken' => 'The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
', 'ListNotebookInstanceLifecycleConfigsInput$NextToken' => 'If the result of a ListNotebookInstanceLifecycleConfigs request was truncated, the response includes a NextToken. To get the next set of lifecycle configurations, use the token in the next request.
If the response is truncated, SageMaker returns this token. To get the next set of lifecycle configurations, use it in the next request.
', 'ListNotebookInstancesInput$NextToken' => ' If the previous call to the ListNotebookInstances is truncated, the response includes a NextToken. You can use this token in your subsequent ListNotebookInstances request to fetch the next set of notebook instances.
You might specify a filter or a sort order in your request. When response is truncated, you must use the same values for the filer and sort order in the next request.
If the response to the previous ListNotebookInstances request was truncated, SageMaker returns this token. To retrieve the next set of notebook instances, use the token in the next request.
If the result of the previous ListPipelineExecutionSteps request was truncated, the response includes a NextToken. To retrieve the next set of pipeline execution steps, use the token in the next request.
If the result of the previous ListPipelineExecutionSteps request was truncated, the response includes a NextToken. To retrieve the next set of pipeline execution steps, use the token in the next request.
If the result of the previous ListPipelineExecutions request was truncated, the response includes a NextToken. To retrieve the next set of pipeline executions, use the token in the next request.
If the result of the previous ListPipelineExecutions request was truncated, the response includes a NextToken. To retrieve the next set of pipeline executions, use the token in the next request.
If the result of the previous ListPipelineParametersForExecution request was truncated, the response includes a NextToken. To retrieve the next set of parameters, use the token in the next request.
If the result of the previous ListPipelineParametersForExecution request was truncated, the response includes a NextToken. To retrieve the next set of parameters, use the token in the next request.
If the result of the previous ListPipelines request was truncated, the response includes a NextToken. To retrieve the next set of pipelines, use the token in the next request.
If the result of the previous ListPipelines request was truncated, the response includes a NextToken. To retrieve the next set of pipelines, use the token in the next request.
If the result of the previous ListProcessingJobs request was truncated, the response includes a NextToken. To retrieve the next set of processing jobs, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of processing jobs, use it in the subsequent request.
', 'ListProjectsInput$NextToken' => 'If the result of the previous ListProjects request was truncated, the response includes a NextToken. To retrieve the next set of projects, use the token in the next request.
If the result of the previous ListCompilationJobs request was truncated, the response includes a NextToken. To retrieve the next set of model compilation jobs, use the token in the next request.
A token to resume pagination of ListResourceCatalogs results.
A token to resume pagination of ListResourceCatalogs results.
If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListSpacesResponse$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListStageDevicesRequest$NextToken' => 'The response from the last list when returning a list large enough to neeed tokening.
', 'ListStageDevicesResponse$NextToken' => 'The token to use when calling the next page of results.
', 'ListStudioLifecycleConfigsRequest$NextToken' => 'If the previous call to ListStudioLifecycleConfigs didn\'t return the full set of Lifecycle Configurations, the call returns a token for getting the next set of Lifecycle Configurations.
', 'ListStudioLifecycleConfigsResponse$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListSubscribedWorkteamsRequest$NextToken' => 'If the result of the previous ListSubscribedWorkteams request was truncated, the response includes a NextToken. To retrieve the next set of labeling jobs, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of work teams, use it in the subsequent request.
', 'ListTagsInput$NextToken' => ' If the response to the previous ListTags request is truncated, SageMaker returns this token. To retrieve the next set of tags, use it in the subsequent request.
If response is truncated, SageMaker includes a token in the response. You can use this token in your subsequent request to fetch next set of tokens.
', 'ListTrainingJobsForHyperParameterTuningJobRequest$NextToken' => 'If the result of the previous ListTrainingJobsForHyperParameterTuningJob request was truncated, the response includes a NextToken. To retrieve the next set of training jobs, use the token in the next request.
If the result of this ListTrainingJobsForHyperParameterTuningJob request was truncated, the response includes a NextToken. To retrieve the next set of training jobs, use the token in the next request.
If the result of the previous ListTrainingJobs request was truncated, the response includes a NextToken. To retrieve the next set of training jobs, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of training jobs, use it in the subsequent request.
', 'ListTransformJobsRequest$NextToken' => 'If the result of the previous ListTransformJobs request was truncated, the response includes a NextToken. To retrieve the next set of transform jobs, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of transform jobs, use it in the next request.
', 'ListTrialComponentsRequest$NextToken' => 'If the previous call to ListTrialComponents didn\'t return the full set of components, the call returns a token for getting the next set of components.
A token for getting the next set of components, if there are any.
', 'ListTrialsRequest$NextToken' => 'If the previous call to ListTrials didn\'t return the full set of trials, the call returns a token for getting the next set of trials.
A token for getting the next set of trials, if there are any.
', 'ListUserProfilesRequest$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListUserProfilesResponse$NextToken' => 'If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
', 'ListWorkforcesRequest$NextToken' => 'A token to resume pagination.
', 'ListWorkforcesResponse$NextToken' => 'A token to resume pagination.
', 'ListWorkteamsRequest$NextToken' => 'If the result of the previous ListWorkteams request was truncated, the response includes a NextToken. To retrieve the next set of labeling jobs, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of work teams, use it in the subsequent request.
', 'SearchRequest$NextToken' => 'If more than MaxResults resources match the specified SearchExpression, the response includes a NextToken. The NextToken can be passed to the next SearchRequest to continue retrieving results.
If the result of the previous Search request was truncated, the response includes a NextToken. To retrieve the next set of results, use the token in the next request.
A list of Elastic Inference (EI) instance types to associate with this notebook instance. Currently, only one instance type can be associated with a notebook instance. For more information, see Using Elastic Inference in Amazon SageMaker.
', 'DescribeNotebookInstanceOutput$AcceleratorTypes' => 'A list of the Elastic Inference (EI) instance types associated with this notebook instance. Currently only one EI instance type can be associated with a notebook instance. For more information, see Using Elastic Inference in Amazon SageMaker.
', 'UpdateNotebookInstanceInput$AcceleratorTypes' => 'A list of the Elastic Inference (EI) instance types to associate with this notebook instance. Currently only one EI instance type can be associated with a notebook instance. For more information, see Using Elastic Inference in Amazon SageMaker.
', ], ], 'NotebookInstanceArn' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceOutput$NotebookInstanceArn' => 'The Amazon Resource Name (ARN) of the notebook instance.
', 'DescribeNotebookInstanceOutput$NotebookInstanceArn' => 'The Amazon Resource Name (ARN) of the notebook instance.
', 'NotebookInstanceSummary$NotebookInstanceArn' => 'The Amazon Resource Name (ARN) of the notebook instance.
', ], ], 'NotebookInstanceLifecycleConfigArn' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceLifecycleConfigOutput$NotebookInstanceLifecycleConfigArn' => 'The Amazon Resource Name (ARN) of the lifecycle configuration.
', 'DescribeNotebookInstanceLifecycleConfigOutput$NotebookInstanceLifecycleConfigArn' => 'The Amazon Resource Name (ARN) of the lifecycle configuration.
', 'NotebookInstanceLifecycleConfigSummary$NotebookInstanceLifecycleConfigArn' => 'The Amazon Resource Name (ARN) of the lifecycle configuration.
', ], ], 'NotebookInstanceLifecycleConfigContent' => [ 'base' => NULL, 'refs' => [ 'NotebookInstanceLifecycleHook$Content' => 'A base64-encoded string that contains a shell script for a notebook instance lifecycle configuration.
', ], ], 'NotebookInstanceLifecycleConfigList' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceLifecycleConfigInput$OnCreate' => 'A shell script that runs only once, when you create a notebook instance. The shell script must be a base64-encoded string.
', 'CreateNotebookInstanceLifecycleConfigInput$OnStart' => 'A shell script that runs every time you start a notebook instance, including when you create the notebook instance. The shell script must be a base64-encoded string.
', 'DescribeNotebookInstanceLifecycleConfigOutput$OnCreate' => 'The shell script that runs only once, when you create a notebook instance.
', 'DescribeNotebookInstanceLifecycleConfigOutput$OnStart' => 'The shell script that runs every time you start a notebook instance, including when you create the notebook instance.
', 'UpdateNotebookInstanceLifecycleConfigInput$OnCreate' => 'The shell script that runs only once, when you create a notebook instance. The shell script must be a base64-encoded string.
', 'UpdateNotebookInstanceLifecycleConfigInput$OnStart' => 'The shell script that runs every time you start a notebook instance, including when you create the notebook instance. The shell script must be a base64-encoded string.
', ], ], 'NotebookInstanceLifecycleConfigName' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$LifecycleConfigName' => 'The name of a lifecycle configuration to associate with the notebook instance. For information about lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
', 'CreateNotebookInstanceLifecycleConfigInput$NotebookInstanceLifecycleConfigName' => 'The name of the lifecycle configuration.
', 'DeleteNotebookInstanceLifecycleConfigInput$NotebookInstanceLifecycleConfigName' => 'The name of the lifecycle configuration to delete.
', 'DescribeNotebookInstanceLifecycleConfigInput$NotebookInstanceLifecycleConfigName' => 'The name of the lifecycle configuration to describe.
', 'DescribeNotebookInstanceLifecycleConfigOutput$NotebookInstanceLifecycleConfigName' => 'The name of the lifecycle configuration.
', 'DescribeNotebookInstanceOutput$NotebookInstanceLifecycleConfigName' => 'Returns the name of a notebook instance lifecycle configuration.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance
', 'ListNotebookInstancesInput$NotebookInstanceLifecycleConfigNameContains' => 'A string in the name of a notebook instances lifecycle configuration associated with this notebook instance. This filter returns only notebook instances associated with a lifecycle configuration with a name that contains the specified string.
', 'NotebookInstanceLifecycleConfigSummary$NotebookInstanceLifecycleConfigName' => 'The name of the lifecycle configuration.
', 'NotebookInstanceSummary$NotebookInstanceLifecycleConfigName' => 'The name of a notebook instance lifecycle configuration associated with this notebook instance.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
', 'UpdateNotebookInstanceInput$LifecycleConfigName' => 'The name of a lifecycle configuration to associate with the notebook instance. For information about lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
', 'UpdateNotebookInstanceLifecycleConfigInput$NotebookInstanceLifecycleConfigName' => 'The name of the lifecycle configuration.
', ], ], 'NotebookInstanceLifecycleConfigNameContains' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstanceLifecycleConfigsInput$NameContains' => 'A string in the lifecycle configuration name. This filter returns only lifecycle configurations whose name contains the specified string.
', ], ], 'NotebookInstanceLifecycleConfigSortKey' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstanceLifecycleConfigsInput$SortBy' => 'Sorts the list of results. The default is CreationTime.
The sort order for results.
', ], ], 'NotebookInstanceLifecycleConfigSummary' => [ 'base' => 'Provides a summary of a notebook instance lifecycle configuration.
', 'refs' => [ 'NotebookInstanceLifecycleConfigSummaryList$member' => NULL, ], ], 'NotebookInstanceLifecycleConfigSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstanceLifecycleConfigsOutput$NotebookInstanceLifecycleConfigs' => 'An array of NotebookInstanceLifecycleConfiguration objects, each listing a lifecycle configuration.
Contains the notebook instance lifecycle configuration script.
Each lifecycle configuration script has a limit of 16384 characters.
The value of the $PATH environment variable that is available to both scripts is /sbin:bin:/usr/sbin:/usr/bin.
View CloudWatch Logs for notebook instance lifecycle configurations in log group /aws/sagemaker/NotebookInstances in log stream [notebook-instance-name]/[LifecycleConfigHook].
Lifecycle configuration scripts cannot run for longer than 5 minutes. If a script runs for longer than 5 minutes, it fails and the notebook instance is not created or started.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
', 'refs' => [ 'NotebookInstanceLifecycleConfigList$member' => NULL, ], ], 'NotebookInstanceName' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$NotebookInstanceName' => 'The name of the new notebook instance.
', 'CreatePresignedNotebookInstanceUrlInput$NotebookInstanceName' => 'The name of the notebook instance.
', 'DeleteNotebookInstanceInput$NotebookInstanceName' => 'The name of the SageMaker notebook instance to delete.
', 'DescribeNotebookInstanceInput$NotebookInstanceName' => 'The name of the notebook instance that you want information about.
', 'DescribeNotebookInstanceOutput$NotebookInstanceName' => 'The name of the SageMaker notebook instance.
', 'NotebookInstanceSummary$NotebookInstanceName' => 'The name of the notebook instance that you want a summary for.
', 'StartNotebookInstanceInput$NotebookInstanceName' => 'The name of the notebook instance to start.
', 'StopNotebookInstanceInput$NotebookInstanceName' => 'The name of the notebook instance to terminate.
', 'UpdateNotebookInstanceInput$NotebookInstanceName' => 'The name of the notebook instance to update.
', ], ], 'NotebookInstanceNameContains' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstancesInput$NameContains' => 'A string in the notebook instances\' name. This filter returns only notebook instances whose name contains the specified string.
', ], ], 'NotebookInstanceSortKey' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstancesInput$SortBy' => 'The field to sort results by. The default is Name.
The sort order for results.
', ], ], 'NotebookInstanceStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeNotebookInstanceOutput$NotebookInstanceStatus' => 'The status of the notebook instance.
', 'ListNotebookInstancesInput$StatusEquals' => 'A filter that returns only notebook instances with the specified status.
', 'NotebookInstanceSummary$NotebookInstanceStatus' => 'The status of the notebook instance.
', ], ], 'NotebookInstanceSummary' => [ 'base' => 'Provides summary information for an SageMaker notebook instance.
', 'refs' => [ 'NotebookInstanceSummaryList$member' => NULL, ], ], 'NotebookInstanceSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListNotebookInstancesOutput$NotebookInstances' => 'An array of NotebookInstanceSummary objects, one for each notebook instance.
A JSON object that contains the URL string.
', 'DescribeNotebookInstanceOutput$Url' => 'The URL that you use to connect to the Jupyter notebook that is running in your notebook instance.
', 'NotebookInstanceSummary$Url' => 'The URL that you use to connect to the Jupyter notebook running in your notebook instance.
', ], ], 'NotebookInstanceVolumeSizeInGB' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$VolumeSizeInGB' => 'The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB.
', 'DescribeNotebookInstanceOutput$VolumeSizeInGB' => 'The size, in GB, of the ML storage volume attached to the notebook instance.
', 'UpdateNotebookInstanceInput$VolumeSizeInGB' => 'The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB. ML storage volumes are encrypted, so SageMaker can\'t determine the amount of available free space on the volume. Because of this, you can increase the volume size when you update a notebook instance, but you can\'t decrease the volume size. If you want to decrease the size of the ML storage volume in use, create a new notebook instance with the desired size.
', ], ], 'NotebookOutputOption' => [ 'base' => NULL, 'refs' => [ 'SharingSettings$NotebookOutputOption' => 'Whether to include the notebook cell output when sharing the notebook. The default is Disabled.
Configures Amazon SNS notifications of available or expiring work items for work teams.
', 'refs' => [ 'CreateWorkteamRequest$NotificationConfiguration' => 'Configures notification of workers regarding available or expiring work items.
', 'UpdateWorkteamRequest$NotificationConfiguration' => 'Configures SNS topic notifications for available or expiring work items
', 'Workteam$NotificationConfiguration' => 'Configures SNS notifications of available or expiring work items for work teams.
', ], ], 'NotificationTopicArn' => [ 'base' => NULL, 'refs' => [ 'NotificationConfiguration$NotificationTopicArn' => 'The ARN for the Amazon SNS topic to which notifications should be published.
', ], ], 'NumberOfHumanWorkersPerDataObject' => [ 'base' => NULL, 'refs' => [ 'HumanTaskConfig$NumberOfHumanWorkersPerDataObject' => 'The number of human workers that will label an object.
', 'LabelingJobForWorkteamSummary$NumberOfHumanWorkersPerDataObject' => 'The configured number of workers per data object.
', ], ], 'NumberOfSteps' => [ 'base' => NULL, 'refs' => [ 'Stairs$NumberOfSteps' => 'Specifies how many steps to perform during traffic.
', ], ], 'ObjectiveStatus' => [ 'base' => NULL, 'refs' => [ 'AutoMLCandidate$ObjectiveStatus' => 'The objective\'s status.
', 'HyperParameterTrainingJobSummary$ObjectiveStatus' => 'The status of the objective metric for the training job:
Succeeded: The final objective metric for the training job was evaluated by the hyperparameter tuning job and used in the hyperparameter tuning process.
Pending: The training job is in progress and evaluation of its final objective metric is pending.
Failed: The final objective metric for the training job was not evaluated, and was not used in the hyperparameter tuning process. This typically occurs when the training job failed or did not emit an objective metric.
The number of training jobs whose final objective metric was evaluated by the hyperparameter tuning job and used in the hyperparameter tuning process.
', 'ObjectiveStatusCounters$Pending' => 'The number of training jobs that are in progress and pending evaluation of their final objective metric.
', 'ObjectiveStatusCounters$Failed' => 'The number of training jobs whose final objective metric was not evaluated and used in the hyperparameter tuning process. This typically occurs when the training job failed or did not emit an objective metric.
', ], ], 'ObjectiveStatusCounters' => [ 'base' => 'Specifies the number of training jobs that this hyperparameter tuning job launched, categorized by the status of their objective metric. The objective metric status shows whether the final objective metric for the training job has been evaluated by the tuning job and used in the hyperparameter tuning process.
', 'refs' => [ 'DescribeHyperParameterTuningJobResponse$ObjectiveStatusCounters' => 'The ObjectiveStatusCounters object that specifies the number of training jobs, categorized by the status of their final objective metric, that this tuning job launched.
', 'HyperParameterTuningJobSearchEntity$ObjectiveStatusCounters' => NULL, 'HyperParameterTuningJobSummary$ObjectiveStatusCounters' => 'The ObjectiveStatusCounters object that specifies the numbers of training jobs, categorized by objective metric status, that this tuning job launched.
', ], ], 'OfflineStoreConfig' => [ 'base' => 'The configuration of an OfflineStore.
Provide an OfflineStoreConfig in a request to CreateFeatureGroup to create an OfflineStore.
To encrypt an OfflineStore using at rest data encryption, specify Amazon Web Services Key Management Service (KMS) key ID, or KMSKeyId, in S3StorageConfig.
Use this to configure an OfflineFeatureStore. This parameter allows you to specify:
The Amazon Simple Storage Service (Amazon S3) location of an OfflineStore.
A configuration for an Amazon Web Services Glue or Amazon Web Services Hive data catalog.
An KMS encryption key to encrypt the Amazon S3 location used for OfflineStore. If KMS encryption key is not specified, by default we encrypt all data at rest using Amazon Web Services KMS key. By defining your bucket-level key for SSE, you can reduce Amazon Web Services KMS requests costs by up to 99 percent.
Format for the offline store table. Supported formats are Glue (Default) and Apache Iceberg.
To learn more about this parameter, see OfflineStoreConfig.
', 'DescribeFeatureGroupResponse$OfflineStoreConfig' => 'The configuration of the offline store. It includes the following configurations:
Amazon S3 location of the offline store.
Configuration of the Glue data catalog.
Table format of the offline store.
Option to disable the automatic creation of a Glue table for the offline store.
Encryption configuration.
The status of OfflineStore.
The status of the OfflineStore. Notifies you if replicating data into the OfflineStore has failed. Returns either: Active or Blocked
Notifies you if replicating data into the OfflineStore has failed. Returns either: Active or Blocked.
An OfflineStore status. Filters by OfflineStore status.
An OfflineStore status.
Use this parameter to configure your OIDC Identity Provider (IdP).
', 'refs' => [ 'CreateWorkforceRequest$OidcConfig' => 'Use this parameter to configure a private workforce using your own OIDC Identity Provider.
Do not use CognitoConfig if you specify values for OidcConfig.
Use this parameter to update your OIDC Identity Provider (IdP) configuration for a workforce made using your own IdP.
', ], ], 'OidcConfigForResponse' => [ 'base' => 'Your OIDC IdP workforce configuration.
', 'refs' => [ 'Workforce$OidcConfig' => 'The configuration of an OIDC Identity Provider (IdP) private workforce.
', ], ], 'OidcEndpoint' => [ 'base' => NULL, 'refs' => [ 'OidcConfig$Issuer' => 'The OIDC IdP issuer used to configure your private workforce.
', 'OidcConfig$AuthorizationEndpoint' => 'The OIDC IdP authorization endpoint used to configure your private workforce.
', 'OidcConfig$TokenEndpoint' => 'The OIDC IdP token endpoint used to configure your private workforce.
', 'OidcConfig$UserInfoEndpoint' => 'The OIDC IdP user information endpoint used to configure your private workforce.
', 'OidcConfig$LogoutEndpoint' => 'The OIDC IdP logout endpoint used to configure your private workforce.
', 'OidcConfig$JwksUri' => 'The OIDC IdP JSON Web Key Set (Jwks) URI used to configure your private workforce.
', 'OidcConfigForResponse$Issuer' => 'The OIDC IdP issuer used to configure your private workforce.
', 'OidcConfigForResponse$AuthorizationEndpoint' => 'The OIDC IdP authorization endpoint used to configure your private workforce.
', 'OidcConfigForResponse$TokenEndpoint' => 'The OIDC IdP token endpoint used to configure your private workforce.
', 'OidcConfigForResponse$UserInfoEndpoint' => 'The OIDC IdP user information endpoint used to configure your private workforce.
', 'OidcConfigForResponse$LogoutEndpoint' => 'The OIDC IdP logout endpoint used to configure your private workforce.
', 'OidcConfigForResponse$JwksUri' => 'The OIDC IdP JSON Web Key Set (Jwks) URI used to configure your private workforce.
', ], ], 'OidcMemberDefinition' => [ 'base' => 'A list of user groups that exist in your OIDC Identity Provider (IdP). One to ten groups can be used to create a single private work team. When you add a user group to the list of Groups, you can add that user group to one or more private work teams. If you add a user group to a private work team, all workers in that user group are added to the work team.
A list user groups that exist in your OIDC Identity Provider (IdP). One to ten groups can be used to create a single private work team. When you add a user group to the list of Groups, you can add that user group to one or more private work teams. If you add a user group to a private work team, all workers in that user group are added to the work team.
Use this to specify the Amazon Web Services Key Management Service (KMS) Key ID, or KMSKeyId, for at rest data encryption. You can turn OnlineStore on or off by specifying the EnableOnlineStore flag at General Assembly.
The default value is False.
You can turn the OnlineStore on or off by specifying True for the EnableOnlineStore flag in OnlineStoreConfig.
You can also include an Amazon Web Services KMS key ID (KMSKeyId) for at-rest encryption of the OnlineStore.
The default value is False.
The configuration for the OnlineStore.
Updates the feature group online store configuration.
', 'refs' => [ 'UpdateFeatureGroupRequest$OnlineStoreConfig' => 'Updates the feature group online store configuration.
', ], ], 'OnlineStoreSecurityConfig' => [ 'base' => 'The security configuration for OnlineStore.
Use to specify KMS Key ID (KMSKeyId) for at-rest encryption of your OnlineStore.
The size of the OnlineStore in bytes.
A Boolean binary operator that is used to evaluate the filter. The operator field contains one of the following values:
The value of Name equals Value.
The value of Name doesn\'t equal Value.
The Name property exists.
The Name property does not exist.
The value of Name is greater than Value. Not supported for text properties.
The value of Name is greater than or equal to Value. Not supported for text properties.
The value of Name is less than Value. Not supported for text properties.
The value of Name is less than or equal to Value. Not supported for text properties.
The value of Name is one of the comma delimited strings in Value. Only supported for text properties.
The value of Name contains the string Value. Only supported for text properties.
A SearchExpression can include the Contains operator multiple times when the value of Name is one of the following:
Experiment.DisplayName
Experiment.ExperimentName
Experiment.Tags
Trial.DisplayName
Trial.TrialName
Trial.Tags
TrialComponent.DisplayName
TrialComponent.TrialComponentName
TrialComponent.Tags
TrialComponent.InputArtifacts
TrialComponent.OutputArtifacts
A SearchExpression can include only one Contains operator for all other values of Name. In these cases, if you include multiple Contains operators in the SearchExpression, the result is the following error message: "\'CONTAINS\' operator usage limit of 1 exceeded."
The maximum value of the metric.
', 'TrialComponentMetricSummary$Min' => 'The minimum value of the metric.
', 'TrialComponentMetricSummary$Last' => 'The most recent value of the metric.
', 'TrialComponentMetricSummary$Avg' => 'The average value of the metric.
', 'TrialComponentMetricSummary$StdDev' => 'The standard deviation of the metric.
', ], ], 'OptionalInteger' => [ 'base' => NULL, 'refs' => [ 'TrialComponentMetricSummary$Count' => 'The number of samples used to generate the metric.
', ], ], 'OptionalVolumeSizeInGB' => [ 'base' => NULL, 'refs' => [ 'DebugRuleConfiguration$VolumeSizeInGB' => 'The size, in GB, of the ML storage volume attached to the processing instance.
', 'HyperParameterTuningResourceConfig$VolumeSizeInGB' => 'The volume size in GB for the storage volume to be used in processing hyperparameter optimization jobs (optional). These volumes store model artifacts, incremental states and optionally, scratch space for training algorithms. Do not provide a value for this parameter if a value for InstanceConfigs is also specified.
Some instance types have a fixed total local storage size. If you select one of these instances for training, VolumeSizeInGB cannot be greater than this total size. For a list of instance types with local instance storage and their sizes, see instance store volumes.
SageMaker supports only the General Purpose SSD (gp2) storage volume type.
The size, in GB, of the ML storage volume attached to the processing instance.
', ], ], 'OrderKey' => [ 'base' => NULL, 'refs' => [ 'ListEndpointConfigsInput$SortOrder' => 'The sort order for results. The default is Descending.
The sort order for results. The default is Descending.
The sort order for results. The default is Descending.
The model output compression type. Select None to output an uncompressed model, recommended for large model outputs. Defaults to gzip.
Contains information about the output location for the compiled model and the target device that the model runs on. TargetDevice and TargetPlatform are mutually exclusive, so you need to choose one between the two to specify your target device or platform. If you cannot find your device you want to use from the TargetDevice list, use TargetPlatform to describe the platform of your edge device and CompilerOptions if there are specific settings that are required or recommended to use for particular TargetPlatform.
Provides information about the output location for the compiled model and the target device the model runs on.
', 'DescribeCompilationJobResponse$OutputConfig' => 'Information about the output location for the compiled model and the target device that the model runs on.
', ], ], 'OutputDataConfig' => [ 'base' => 'Provides information about how to store model training results (model artifacts).
', 'refs' => [ 'CreateTrainingJobRequest$OutputDataConfig' => 'Specifies the path to the S3 location where you want to store model artifacts. SageMaker creates subfolders for the artifacts.
', 'DescribeTrainingJobResponse$OutputDataConfig' => 'The S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.
', 'HyperParameterTrainingJobDefinition$OutputDataConfig' => 'Specifies the path to the Amazon S3 bucket where you store model artifacts from the training jobs that the tuning job launches.
', 'TrainingJob$OutputDataConfig' => 'The S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.
', 'TrainingJobDefinition$OutputDataConfig' => 'the path to the S3 bucket where you want to store model artifacts. SageMaker creates subfolders for the artifacts.
', ], ], 'OutputParameter' => [ 'base' => 'An output parameter of a pipeline step.
', 'refs' => [ 'OutputParameterList$member' => NULL, ], ], 'OutputParameterList' => [ 'base' => NULL, 'refs' => [ 'CallbackStepMetadata$OutputParameters' => 'A list of the output parameters of the callback step.
', 'LambdaStepMetadata$OutputParameters' => 'A list of the output parameters of the Lambda step.
', 'SendPipelineExecutionStepSuccessRequest$OutputParameters' => 'A list of the output parameters of the callback step.
', ], ], 'PaginationToken' => [ 'base' => NULL, 'refs' => [ 'ListEndpointConfigsInput$NextToken' => 'If the result of the previous ListEndpointConfig request was truncated, the response includes a NextToken. To retrieve the next set of endpoint configurations, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of endpoint configurations, use it in the subsequent request
', 'ListEndpointsInput$NextToken' => 'If the result of a ListEndpoints request was truncated, the response includes a NextToken. To retrieve the next set of endpoints, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of training jobs, use it in the subsequent request.
', 'ListModelsInput$NextToken' => 'If the response to a previous ListModels request was truncated, the response includes a NextToken. To retrieve the next set of models, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of models, use it in the subsequent request.
', ], ], 'ParallelismConfiguration' => [ 'base' => 'Configuration that controls the parallelism of the pipeline. By default, the parallelism configuration specified applies to all executions of the pipeline unless overridden.
', 'refs' => [ 'CreatePipelineRequest$ParallelismConfiguration' => 'This is the configuration that controls the parallelism of the pipeline. If specified, it applies to all runs of this pipeline by default.
', 'DescribePipelineExecutionResponse$ParallelismConfiguration' => 'The parallelism configuration applied to the pipeline.
', 'DescribePipelineResponse$ParallelismConfiguration' => 'Lists the parallelism configuration applied to the pipeline.
', 'Pipeline$ParallelismConfiguration' => 'The parallelism configuration applied to the pipeline.
', 'PipelineExecution$ParallelismConfiguration' => 'The parallelism configuration applied to the pipeline execution.
', 'RetryPipelineExecutionRequest$ParallelismConfiguration' => 'This configuration, if specified, overrides the parallelism configuration of the parent pipeline.
', 'StartPipelineExecutionRequest$ParallelismConfiguration' => 'This configuration, if specified, overrides the parallelism configuration of the parent pipeline for this specific run.
', 'UpdatePipelineExecutionRequest$ParallelismConfiguration' => 'This configuration, if specified, overrides the parallelism configuration of the parent pipeline for this specific run.
', 'UpdatePipelineRequest$ParallelismConfiguration' => 'If specified, it applies to all executions of this pipeline by default.
', ], ], 'Parameter' => [ 'base' => 'Assigns a value to a named Pipeline parameter.
', 'refs' => [ 'ParameterList$member' => NULL, ], ], 'ParameterKey' => [ 'base' => NULL, 'refs' => [ 'AutoParameter$Name' => 'The name of the hyperparameter to optimize using Autotune.
', 'CategoricalParameterRange$Name' => 'The name of the categorical hyperparameter to tune.
', 'ContinuousParameterRange$Name' => 'The name of the continuous hyperparameter to tune.
', 'IntegerParameterRange$Name' => 'The name of the hyperparameter to search.
', ], ], 'ParameterList' => [ 'base' => NULL, 'refs' => [ 'ListPipelineParametersForExecutionResponse$PipelineParameters' => 'Contains a list of pipeline parameters. This list can be empty.
', 'PipelineExecution$PipelineParameters' => 'Contains a list of pipeline parameters. This list can be empty.
', 'StartPipelineExecutionRequest$PipelineParameters' => 'Contains a list of pipeline parameters. This list can be empty.
', ], ], 'ParameterName' => [ 'base' => NULL, 'refs' => [ 'HyperParameterSpecification$Name' => 'The name of this hyperparameter. The name must be unique.
', ], ], 'ParameterRange' => [ 'base' => 'Defines the possible values for categorical, continuous, and integer hyperparameters to be used by an algorithm.
', 'refs' => [ 'HyperParameterSpecification$Range' => 'The allowed range for this hyperparameter.
', ], ], 'ParameterRanges' => [ 'base' => 'Specifies ranges of integer, continuous, and categorical hyperparameters that a hyperparameter tuning job searches. The hyperparameter tuning job launches training jobs with hyperparameter values within these ranges to find the combination of values that result in the training job with the best performance as measured by the objective metric of the hyperparameter tuning job.
The maximum number of items specified for Array Members refers to the maximum number of hyperparameters for each range and also the maximum for the hyperparameter tuning job itself. That is, the sum of the number of hyperparameters for all the ranges can\'t exceed the maximum number specified.
The ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches over to find the optimal configuration for the highest model performance against your chosen objective metric.
', ], ], 'ParameterType' => [ 'base' => NULL, 'refs' => [ 'HyperParameterSpecification$Type' => 'The type of this hyperparameter. The valid types are Integer, Continuous, Categorical, and FreeText.
An example value of the hyperparameter to optimize using Autotune.
', 'ContinuousParameterRange$MinValue' => 'The minimum value for the hyperparameter. The tuning job uses floating-point values between this value and MaxValuefor tuning.
The maximum value for the hyperparameter. The tuning job uses floating-point values between MinValue value and this value for tuning.
The minimum floating-point value allowed.
', 'ContinuousParameterRangeSpecification$MaxValue' => 'The maximum floating-point value allowed.
', 'IntegerParameterRange$MinValue' => 'The minimum value of the hyperparameter to search.
', 'IntegerParameterRange$MaxValue' => 'The maximum value of the hyperparameter to search.
', 'IntegerParameterRangeSpecification$MinValue' => 'The minimum integer value allowed.
', 'IntegerParameterRangeSpecification$MaxValue' => 'The maximum integer value allowed.
', 'ParameterValues$member' => NULL, ], ], 'ParameterValues' => [ 'base' => NULL, 'refs' => [ 'CategoricalParameterRange$Values' => 'A list of the categories for the hyperparameter.
', 'CategoricalParameterRangeSpecification$Values' => 'The allowed categories for the hyperparameter.
', ], ], 'Parent' => [ 'base' => 'The trial that a trial component is associated with and the experiment the trial is part of. A component might not be associated with a trial. A component can be associated with multiple trials.
', 'refs' => [ 'Parents$member' => NULL, ], ], 'ParentHyperParameterTuningJob' => [ 'base' => 'A previously completed or stopped hyperparameter tuning job to be used as a starting point for a new hyperparameter tuning job.
', 'refs' => [ 'ParentHyperParameterTuningJobs$member' => NULL, ], ], 'ParentHyperParameterTuningJobs' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTuningJobWarmStartConfig$ParentHyperParameterTuningJobs' => 'An array of hyperparameter tuning jobs that are used as the starting point for the new hyperparameter tuning job. For more information about warm starting a hyperparameter tuning job, see Using a Previous Hyperparameter Tuning Job as a Starting Point.
Hyperparameter tuning jobs created before October 1, 2018 cannot be used as parent jobs for warm start tuning jobs.
', ], ], 'Parents' => [ 'base' => NULL, 'refs' => [ 'TrialComponent$Parents' => 'An array of the parents of the component. A parent is a trial the component is associated with and the experiment the trial is part of. A component might not have any parents.
', ], ], 'PendingDeploymentSummary' => [ 'base' => 'The summary of an in-progress deployment when an endpoint is creating or updating with a new endpoint configuration.
', 'refs' => [ 'DescribeEndpointOutput$PendingDeploymentSummary' => 'Returns the summary of an in-progress deployment. This field is only returned when the endpoint is creating or updating with a new endpoint configuration.
', ], ], 'PendingProductionVariantSummary' => [ 'base' => 'The production variant summary for a deployment when an endpoint is creating or updating with the CreateEndpoint or UpdateEndpoint operations. Describes the VariantStatus , weight and capacity for a production variant associated with an endpoint.
An array of PendingProductionVariantSummary objects, one for each model hosted behind this endpoint for the in-progress deployment.
', 'PendingDeploymentSummary$ShadowProductionVariants' => 'An array of PendingProductionVariantSummary objects, one for each model hosted behind this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants for the in-progress deployment.
Percentage of devices in the fleet to deploy to the current stage.
', 'ShadowModelVariantConfig$SamplingPercentage' => 'The percentage of inference requests that Amazon SageMaker replicates from the production variant to the shadow variant.
', ], ], 'Phase' => [ 'base' => 'Defines the traffic pattern.
', 'refs' => [ 'Phases$member' => NULL, ], ], 'Phases' => [ 'base' => NULL, 'refs' => [ 'TrafficPattern$Phases' => 'Defines the phases traffic specification.
', ], ], 'Pipeline' => [ 'base' => 'A SageMaker Model Building Pipeline instance.
', 'refs' => [ 'SearchRecord$Pipeline' => NULL, ], ], 'PipelineArn' => [ 'base' => NULL, 'refs' => [ 'CreatePipelineResponse$PipelineArn' => 'The Amazon Resource Name (ARN) of the created pipeline.
', 'DeletePipelineResponse$PipelineArn' => 'The Amazon Resource Name (ARN) of the pipeline to delete.
', 'DescribePipelineExecutionResponse$PipelineArn' => 'The Amazon Resource Name (ARN) of the pipeline.
', 'DescribePipelineResponse$PipelineArn' => 'The Amazon Resource Name (ARN) of the pipeline.
', 'Pipeline$PipelineArn' => 'The Amazon Resource Name (ARN) of the pipeline.
', 'PipelineExecution$PipelineArn' => 'The Amazon Resource Name (ARN) of the pipeline that was executed.
', 'PipelineSummary$PipelineArn' => 'The Amazon Resource Name (ARN) of the pipeline.
', 'UpdatePipelineResponse$PipelineArn' => 'The Amazon Resource Name (ARN) of the updated pipeline.
', ], ], 'PipelineDefinition' => [ 'base' => NULL, 'refs' => [ 'CreatePipelineRequest$PipelineDefinition' => 'The JSON pipeline definition of the pipeline.
', 'DescribePipelineDefinitionForExecutionResponse$PipelineDefinition' => 'The JSON pipeline definition.
', 'DescribePipelineResponse$PipelineDefinition' => 'The JSON pipeline definition.
', 'UpdatePipelineRequest$PipelineDefinition' => 'The JSON pipeline definition.
', ], ], 'PipelineDefinitionS3Location' => [ 'base' => 'The location of the pipeline definition stored in Amazon S3.
', 'refs' => [ 'CreatePipelineRequest$PipelineDefinitionS3Location' => 'The location of the pipeline definition stored in Amazon S3. If specified, SageMaker will retrieve the pipeline definition from this location.
', 'UpdatePipelineRequest$PipelineDefinitionS3Location' => 'The location of the pipeline definition stored in Amazon S3. If specified, SageMaker will retrieve the pipeline definition from this location.
', ], ], 'PipelineDescription' => [ 'base' => NULL, 'refs' => [ 'CreatePipelineRequest$PipelineDescription' => 'A description of the pipeline.
', 'DescribePipelineResponse$PipelineDescription' => 'The description of the pipeline.
', 'Pipeline$PipelineDescription' => 'The description of the pipeline.
', 'PipelineSummary$PipelineDescription' => 'The description of the pipeline.
', 'UpdatePipelineRequest$PipelineDescription' => 'The description of the pipeline.
', ], ], 'PipelineExecution' => [ 'base' => 'An execution of a pipeline.
', 'refs' => [ 'SearchRecord$PipelineExecution' => NULL, ], ], 'PipelineExecutionArn' => [ 'base' => NULL, 'refs' => [ 'CacheHitResult$SourcePipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'DescribePipelineDefinitionForExecutionRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'DescribePipelineExecutionRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'DescribePipelineExecutionResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'ListPipelineExecutionStepsRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'ListPipelineParametersForExecutionRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'PipelineExecution$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'PipelineExecutionSummary$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'RetryPipelineExecutionRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'RetryPipelineExecutionResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'SelectiveExecutionConfig$SourcePipelineExecutionArn' => 'The ARN from a reference execution of the current pipeline. Used to copy input collaterals needed for the selected steps to run. The execution status of the pipeline can be either Failed or Success.
This field is required if the steps you specify for SelectedSteps depend on output collaterals from any non-specified pipeline steps. For more information, see Selective Execution for Pipeline Steps.
The ARN from an execution of the current pipeline.
', 'SendPipelineExecutionStepFailureResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'SendPipelineExecutionStepSuccessResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'StartPipelineExecutionResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'StopPipelineExecutionRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'StopPipelineExecutionResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'UpdatePipelineExecutionRequest$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the pipeline execution.
', 'UpdatePipelineExecutionResponse$PipelineExecutionArn' => 'The Amazon Resource Name (ARN) of the updated pipeline execution.
', ], ], 'PipelineExecutionDescription' => [ 'base' => NULL, 'refs' => [ 'DescribePipelineExecutionResponse$PipelineExecutionDescription' => 'The description of the pipeline execution.
', 'PipelineExecution$PipelineExecutionDescription' => 'The description of the pipeline execution.
', 'PipelineExecutionSummary$PipelineExecutionDescription' => 'The description of the pipeline execution.
', 'StartPipelineExecutionRequest$PipelineExecutionDescription' => 'The description of the pipeline execution.
', 'UpdatePipelineExecutionRequest$PipelineExecutionDescription' => 'The description of the pipeline execution.
', ], ], 'PipelineExecutionFailureReason' => [ 'base' => NULL, 'refs' => [ 'DescribePipelineExecutionResponse$FailureReason' => 'If the execution failed, a message describing why.
', 'PipelineExecution$FailureReason' => 'If the execution failed, a message describing why.
', ], ], 'PipelineExecutionName' => [ 'base' => NULL, 'refs' => [ 'DescribePipelineExecutionResponse$PipelineExecutionDisplayName' => 'The display name of the pipeline execution.
', 'PipelineExecution$PipelineExecutionDisplayName' => 'The display name of the pipeline execution.
', 'PipelineExecutionSummary$PipelineExecutionDisplayName' => 'The display name of the pipeline execution.
', 'StartPipelineExecutionRequest$PipelineExecutionDisplayName' => 'The display name of the pipeline execution.
', 'UpdatePipelineExecutionRequest$PipelineExecutionDisplayName' => 'The display name of the pipeline execution.
', ], ], 'PipelineExecutionStatus' => [ 'base' => NULL, 'refs' => [ 'DescribePipelineExecutionResponse$PipelineExecutionStatus' => 'The status of the pipeline execution.
', 'PipelineExecution$PipelineExecutionStatus' => 'The status of the pipeline status.
', 'PipelineExecutionSummary$PipelineExecutionStatus' => 'The status of the pipeline execution.
', ], ], 'PipelineExecutionStep' => [ 'base' => 'An execution of a step in a pipeline.
', 'refs' => [ 'PipelineExecutionStepList$member' => NULL, ], ], 'PipelineExecutionStepList' => [ 'base' => NULL, 'refs' => [ 'ListPipelineExecutionStepsResponse$PipelineExecutionSteps' => 'A list of PipeLineExecutionStep objects. Each PipeLineExecutionStep consists of StepName, StartTime, EndTime, StepStatus, and Metadata. Metadata is an object with properties for each job that contains relevant information about the job created by the step.
Metadata for a step execution.
', 'refs' => [ 'PipelineExecutionStep$Metadata' => 'Metadata to run the pipeline step.
', ], ], 'PipelineExecutionSummary' => [ 'base' => 'A pipeline execution summary.
', 'refs' => [ 'PipelineExecutionSummaryList$member' => NULL, ], ], 'PipelineExecutionSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListPipelineExecutionsResponse$PipelineExecutionSummaries' => 'Contains a sorted list of pipeline execution summary objects matching the specified filters. Each run summary includes the Amazon Resource Name (ARN) of the pipeline execution, the run date, and the status. This list can be empty.
', ], ], 'PipelineExperimentConfig' => [ 'base' => 'Specifies the names of the experiment and trial created by a pipeline.
', 'refs' => [ 'DescribePipelineExecutionResponse$PipelineExperimentConfig' => NULL, 'PipelineExecution$PipelineExperimentConfig' => NULL, ], ], 'PipelineName' => [ 'base' => NULL, 'refs' => [ 'CreatePipelineRequest$PipelineName' => 'The name of the pipeline.
', 'CreatePipelineRequest$PipelineDisplayName' => 'The display name of the pipeline.
', 'DeletePipelineRequest$PipelineName' => 'The name of the pipeline to delete.
', 'DescribePipelineResponse$PipelineName' => 'The name of the pipeline.
', 'DescribePipelineResponse$PipelineDisplayName' => 'The display name of the pipeline.
', 'ListPipelinesRequest$PipelineNamePrefix' => 'The prefix of the pipeline name.
', 'Pipeline$PipelineName' => 'The name of the pipeline.
', 'Pipeline$PipelineDisplayName' => 'The display name of the pipeline.
', 'PipelineSummary$PipelineName' => 'The name of the pipeline.
', 'PipelineSummary$PipelineDisplayName' => 'The display name of the pipeline.
', 'UpdatePipelineRequest$PipelineName' => 'The name of the pipeline to update.
', 'UpdatePipelineRequest$PipelineDisplayName' => 'The display name of the pipeline.
', ], ], 'PipelineNameOrArn' => [ 'base' => NULL, 'refs' => [ 'DescribePipelineRequest$PipelineName' => 'The name or Amazon Resource Name (ARN) of the pipeline to describe.
', 'ListPipelineExecutionsRequest$PipelineName' => 'The name or Amazon Resource Name (ARN) of the pipeline.
', 'StartPipelineExecutionRequest$PipelineName' => 'The name or Amazon Resource Name (ARN) of the pipeline.
', ], ], 'PipelineParameterName' => [ 'base' => NULL, 'refs' => [ 'Parameter$Name' => 'The name of the parameter to assign a value to. This parameter name must match a named parameter in the pipeline definition.
', ], ], 'PipelineStatus' => [ 'base' => NULL, 'refs' => [ 'DescribePipelineResponse$PipelineStatus' => 'The status of the pipeline execution.
', 'Pipeline$PipelineStatus' => 'The status of the pipeline.
', ], ], 'PipelineSummary' => [ 'base' => 'A summary of a pipeline.
', 'refs' => [ 'PipelineSummaryList$member' => NULL, ], ], 'PipelineSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListPipelinesResponse$PipelineSummaries' => 'Contains a sorted list of PipelineSummary objects matching the specified filters. Each PipelineSummary consists of PipelineArn, PipelineName, ExperimentName, PipelineDescription, CreationTime, LastModifiedTime, LastRunTime, and RoleArn. This list can be empty.
The platform identifier of the notebook instance runtime environment.
', 'DescribeNotebookInstanceOutput$PlatformIdentifier' => 'The platform identifier of the notebook instance runtime environment.
', ], ], 'PolicyString' => [ 'base' => NULL, 'refs' => [ 'GetModelPackageGroupPolicyOutput$ResourcePolicy' => 'The resource policy for the model group.
', 'PutModelPackageGroupPolicyInput$ResourcePolicy' => 'The resource policy for the model group.
', ], ], 'PredefinedMetricSpecification' => [ 'base' => 'A specification for a predefined metric.
', 'refs' => [ 'MetricSpecification$Predefined' => 'Information about a predefined metric.
', ], ], 'PresignedDomainUrl' => [ 'base' => NULL, 'refs' => [ 'CreatePresignedDomainUrlResponse$AuthorizedUrl' => 'The presigned URL.
', ], ], 'ProbabilityThresholdAttribute' => [ 'base' => NULL, 'refs' => [ 'BatchTransformInput$ProbabilityThresholdAttribute' => 'The threshold for the class probability to be evaluated as a positive result.
', 'EndpointInput$ProbabilityThresholdAttribute' => 'The threshold for the class probability to be evaluated as a positive result.
', ], ], 'ProblemType' => [ 'base' => NULL, 'refs' => [ 'CreateAutoMLJobRequest$ProblemType' => 'Defines the type of supervised learning problem available for the candidates. For more information, see Amazon SageMaker Autopilot problem types.
', 'DescribeAutoMLJobResponse$ProblemType' => 'Returns the job\'s problem type.
', 'ResolvedAttributes$ProblemType' => 'The problem type.
', 'TabularJobConfig$ProblemType' => 'The type of supervised learning problem available for the model candidates of the AutoML job V2. For more information, see Amazon SageMaker Autopilot problem types.
You must either specify the type of supervised learning problem in ProblemType and provide the AutoMLJobObjective metric, or none at all.
The type of supervised learning problem available for the model candidates of the AutoML job V2 (Binary Classification, Multiclass Classification, Regression). For more information, see Amazon SageMaker Autopilot problem types.
', ], ], 'ProcessingClusterConfig' => [ 'base' => 'Configuration for the cluster used to run a processing job.
', 'refs' => [ 'ProcessingResources$ClusterConfig' => 'The configuration for the resources in a cluster used to run the processing job.
', ], ], 'ProcessingEnvironmentKey' => [ 'base' => NULL, 'refs' => [ 'MonitoringEnvironmentMap$key' => NULL, 'ProcessingEnvironmentMap$key' => NULL, ], ], 'ProcessingEnvironmentMap' => [ 'base' => NULL, 'refs' => [ 'CreateProcessingJobRequest$Environment' => 'The environment variables to set in the Docker container. Up to 100 key and values entries in the map are supported.
', 'DescribeProcessingJobResponse$Environment' => 'The environment variables set in the Docker container.
', 'ProcessingJob$Environment' => 'Sets the environment variables in the Docker container.
', ], ], 'ProcessingEnvironmentValue' => [ 'base' => NULL, 'refs' => [ 'MonitoringEnvironmentMap$value' => NULL, 'ProcessingEnvironmentMap$value' => NULL, ], ], 'ProcessingFeatureStoreOutput' => [ 'base' => 'Configuration for processing job outputs in Amazon SageMaker Feature Store.
', 'refs' => [ 'ProcessingOutput$FeatureStoreOutput' => 'Configuration for processing job outputs in Amazon SageMaker Feature Store. This processing output type is only supported when AppManaged is specified.
The inputs for a processing job. The processing input must specify exactly one of either S3Input or DatasetDefinition types.
An array of inputs configuring the data to download into the processing container.
', 'DescribeProcessingJobResponse$ProcessingInputs' => 'The inputs for a processing job.
', 'ProcessingJob$ProcessingInputs' => 'List of input configurations for the processing job.
', ], ], 'ProcessingInstanceCount' => [ 'base' => NULL, 'refs' => [ 'MonitoringClusterConfig$InstanceCount' => 'The number of ML compute instances to use in the model monitoring job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
', 'ProcessingClusterConfig$InstanceCount' => 'The number of ML compute instances to use in the processing job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
', ], ], 'ProcessingInstanceType' => [ 'base' => NULL, 'refs' => [ 'DebugRuleConfiguration$InstanceType' => 'The instance type to deploy a custom rule for debugging a training job.
', 'MonitoringClusterConfig$InstanceType' => 'The ML compute instance type for the processing job.
', 'ProcessingClusterConfig$InstanceType' => 'The ML compute instance type for the processing job.
', 'ProfilerRuleConfiguration$InstanceType' => 'The instance type to deploy a custom rule for profiling a training job.
', ], ], 'ProcessingJob' => [ 'base' => 'An Amazon SageMaker processing job that is used to analyze data and evaluate models. For more information, see Process Data and Evaluate Models.
', 'refs' => [ 'TrialComponentSourceDetail$ProcessingJob' => 'Information about a processing job that\'s the source of a trial component.
', ], ], 'ProcessingJobArn' => [ 'base' => NULL, 'refs' => [ 'CreateProcessingJobResponse$ProcessingJobArn' => 'The Amazon Resource Name (ARN) of the processing job.
', 'DebugRuleEvaluationStatus$RuleEvaluationJobArn' => 'The Amazon Resource Name (ARN) of the rule evaluation job.
', 'DescribeProcessingJobResponse$ProcessingJobArn' => 'The Amazon Resource Name (ARN) of the processing job.
', 'MonitoringExecutionSummary$ProcessingJobArn' => 'The Amazon Resource Name (ARN) of the monitoring job.
', 'ProcessingJob$ProcessingJobArn' => 'The ARN of the processing job.
', 'ProcessingJobStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the processing job.
', 'ProcessingJobSummary$ProcessingJobArn' => 'The Amazon Resource Name (ARN) of the processing job..
', 'ProfilerRuleEvaluationStatus$RuleEvaluationJobArn' => 'The Amazon Resource Name (ARN) of the rule evaluation job.
', ], ], 'ProcessingJobName' => [ 'base' => NULL, 'refs' => [ 'CreateProcessingJobRequest$ProcessingJobName' => 'The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DataQualityBaselineConfig$BaseliningJobName' => 'The name of the job that performs baselining for the data quality monitoring job.
', 'DescribeProcessingJobRequest$ProcessingJobName' => 'The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeProcessingJobResponse$ProcessingJobName' => 'The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'ModelBiasBaselineConfig$BaseliningJobName' => 'The name of the baseline model bias job.
', 'ModelExplainabilityBaselineConfig$BaseliningJobName' => 'The name of the baseline model explainability job.
', 'ModelQualityBaselineConfig$BaseliningJobName' => 'The name of the job that performs baselining for the monitoring job.
', 'MonitoringBaselineConfig$BaseliningJobName' => 'The name of the job that performs baselining for the monitoring job.
', 'ProcessingJob$ProcessingJobName' => 'The name of the processing job.
', 'ProcessingJobSummary$ProcessingJobName' => 'The name of the processing job.
', 'StopProcessingJobRequest$ProcessingJobName' => 'The name of the processing job to stop.
', ], ], 'ProcessingJobStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeProcessingJobResponse$ProcessingJobStatus' => 'Provides the status of a processing job.
', 'ListProcessingJobsRequest$StatusEquals' => 'A filter that retrieves only processing jobs with a specific status.
', 'ProcessingJob$ProcessingJobStatus' => 'The status of the processing job.
', 'ProcessingJobSummary$ProcessingJobStatus' => 'The status of the processing job.
', ], ], 'ProcessingJobStepMetadata' => [ 'base' => 'Metadata for a processing job step.
', 'refs' => [ 'PipelineExecutionStepMetadata$ProcessingJob' => 'The Amazon Resource Name (ARN) of the processing job that was run by this step execution.
', ], ], 'ProcessingJobSummaries' => [ 'base' => NULL, 'refs' => [ 'ListProcessingJobsResponse$ProcessingJobSummaries' => 'An array of ProcessingJobSummary objects, each listing a processing job.
Summary of information about a processing job.
', 'refs' => [ 'ProcessingJobSummaries$member' => NULL, ], ], 'ProcessingLocalPath' => [ 'base' => NULL, 'refs' => [ 'BatchTransformInput$LocalPath' => 'Path to the filesystem where the batch transform data is available to the container.
', 'DatasetDefinition$LocalPath' => 'The local path where you want Amazon SageMaker to download the Dataset Definition inputs to run a processing job. LocalPath is an absolute path to the input data. This is a required parameter when AppManaged is False (default).
Path to the filesystem where the endpoint data is available to the container.
', 'MonitoringS3Output$LocalPath' => 'The local path to the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job. LocalPath is an absolute path for the output data.
', 'ProcessingS3Input$LocalPath' => 'The local path in your container where you want Amazon SageMaker to write input data to. LocalPath is an absolute path to the input data and must begin with /opt/ml/processing/. LocalPath is a required parameter when AppManaged is False (default).
The local path of a directory where you want Amazon SageMaker to upload its contents to Amazon S3. LocalPath is an absolute path to a directory containing output files. This directory will be created by the platform and exist when your container\'s entrypoint is invoked.
Specifies the maximum runtime in seconds.
', ], ], 'ProcessingOutput' => [ 'base' => 'Describes the results of a processing job. The processing output must specify exactly one of either S3Output or FeatureStoreOutput types.
Configuration for uploading output from the processing container.
', 'refs' => [ 'CreateProcessingJobRequest$ProcessingOutputConfig' => 'Output configuration for the processing job.
', 'DescribeProcessingJobResponse$ProcessingOutputConfig' => 'Output configuration for the processing job.
', 'ProcessingJob$ProcessingOutputConfig' => NULL, ], ], 'ProcessingOutputs' => [ 'base' => NULL, 'refs' => [ 'ProcessingOutputConfig$Outputs' => 'An array of outputs configuring the data to upload from the processing container.
', ], ], 'ProcessingResources' => [ 'base' => 'Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.
', 'refs' => [ 'CreateProcessingJobRequest$ProcessingResources' => 'Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.
', 'DescribeProcessingJobResponse$ProcessingResources' => 'Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.
', 'ProcessingJob$ProcessingResources' => NULL, ], ], 'ProcessingS3CompressionType' => [ 'base' => NULL, 'refs' => [ 'ProcessingS3Input$S3CompressionType' => 'Whether to GZIP-decompress the data in Amazon S3 as it is streamed into the processing container. Gzip can only be used when Pipe mode is specified as the S3InputMode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your container without using the EBS volume.
Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defaults to FullyReplicated
Whether input data distributed in Amazon S3 is fully replicated or sharded by an Amazon S3 key. Defaults to FullyReplicated
Whether to distribute the data from Amazon S3 to all processing instances with FullyReplicated, or whether the data from Amazon S3 is shared by Amazon S3 key, downloading one shard of data to each processing instance.
Whether you use an S3Prefix or a ManifestFile for the data type. If you choose S3Prefix, S3Uri identifies a key name prefix. Amazon SageMaker uses all objects with the specified key name prefix for the processing job. If you choose ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want Amazon SageMaker to use for the processing job.
Configuration for downloading input data from Amazon S3 into the processing container.
', 'refs' => [ 'ProcessingInput$S3Input' => 'Configuration for downloading input data from Amazon S3 into the processing container.
', ], ], 'ProcessingS3InputMode' => [ 'base' => NULL, 'refs' => [ 'BatchTransformInput$S3InputMode' => 'Whether the Pipe or File is used as the input mode for transferring data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
Whether the Pipe or File is used as the input mode for transferring data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
Whether to use File or Pipe input mode. In File mode, Amazon SageMaker copies the data from the input source onto the local ML storage volume before starting your processing container. This is the most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your processing container into named pipes without using the ML storage volume.
Configuration for uploading output data to Amazon S3 from the processing container.
', 'refs' => [ 'ProcessingOutput$S3Output' => 'Configuration for processing job outputs in Amazon S3.
', ], ], 'ProcessingS3UploadMode' => [ 'base' => NULL, 'refs' => [ 'MonitoringS3Output$S3UploadMode' => 'Whether to upload the results of the monitoring job continuously or after the job completes.
', 'ProcessingS3Output$S3UploadMode' => 'Whether to upload the results of the processing job continuously or after the job completes.
', ], ], 'ProcessingStoppingCondition' => [ 'base' => 'Configures conditions under which the processing job should be stopped, such as how long the processing job has been running. After the condition is met, the processing job is stopped.
', 'refs' => [ 'CreateProcessingJobRequest$StoppingCondition' => 'The time limit for how long the processing job is allowed to run.
', 'DescribeProcessingJobResponse$StoppingCondition' => 'The time limit for how long the processing job is allowed to run.
', 'ProcessingJob$StoppingCondition' => NULL, ], ], 'ProcessingVolumeSizeInGB' => [ 'base' => NULL, 'refs' => [ 'MonitoringClusterConfig$VolumeSizeInGB' => 'The size of the ML storage volume, in gigabytes, that you want to provision. You must specify sufficient ML storage for your scenario.
', 'ProcessingClusterConfig$VolumeSizeInGB' => 'The size of the ML storage volume in gigabytes that you want to provision. You must specify sufficient ML storage for your scenario.
Certain Nitro-based instances include local storage with a fixed total size, dependent on the instance type. When using these instances for processing, Amazon SageMaker mounts the local instance storage instead of Amazon EBS gp2 storage. You can\'t request a VolumeSizeInGB greater than the total size of the local instance storage.
For a list of instance types that support local instance storage, including the total size per instance type, see Instance Store Volumes.
Indicates CPU or GPU compatibility.
CPU: The image version is compatible with CPU.
GPU: The image version is compatible with GPU.
Indicates CPU or GPU compatibility.
CPU: The image version is compatible with CPU.
GPU: The image version is compatible with GPU.
Indicates CPU or GPU compatibility.
CPU: The image version is compatible with CPU.
GPU: The image version is compatible with GPU.
The product identifier of the algorithm.
', 'ModelPackageContainerDefinition$ProductId' => 'The Amazon Web Services Marketplace product ID of the model package.
', ], ], 'ProductListings' => [ 'base' => NULL, 'refs' => [ 'Workteam$ProductListingIds' => 'The Amazon Marketplace identifier for a vendor\'s work team.
', ], ], 'ProductionVariant' => [ 'base' => 'Identifies a model that you want to host and the resources chosen to deploy for hosting it. If you are deploying multiple models, tell SageMaker how to distribute traffic among the models by specifying variant weights. For more information on production variants, check Production variants.
', 'refs' => [ 'ProductionVariantList$member' => NULL, ], ], 'ProductionVariantAcceleratorType' => [ 'base' => NULL, 'refs' => [ 'PendingProductionVariantSummary$AcceleratorType' => 'The size of the Elastic Inference (EI) instance to use for the production variant. EI instances provide on-demand GPU computing for inference. For more information, see Using Elastic Inference in Amazon SageMaker.
', 'ProductionVariant$AcceleratorType' => 'The size of the Elastic Inference (EI) instance to use for the production variant. EI instances provide on-demand GPU computing for inference. For more information, see Using Elastic Inference in Amazon SageMaker.
', ], ], 'ProductionVariantContainerStartupHealthCheckTimeoutInSeconds' => [ 'base' => NULL, 'refs' => [ 'ProductionVariant$ContainerStartupHealthCheckTimeoutInSeconds' => 'The timeout value, in seconds, for your inference container to pass health check by SageMaker Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests.
', ], ], 'ProductionVariantCoreDumpConfig' => [ 'base' => 'Specifies configuration for a core dump from the model container when the process crashes.
', 'refs' => [ 'ProductionVariant$CoreDumpConfig' => 'Specifies configuration for a core dump from the model container when the process crashes.
', ], ], 'ProductionVariantInstanceType' => [ 'base' => NULL, 'refs' => [ 'EndpointInputConfiguration$InstanceType' => 'The instance types to use for the load test.
', 'EndpointOutputConfiguration$InstanceType' => 'The instance type recommended by Amazon SageMaker Inference Recommender.
', 'PendingProductionVariantSummary$InstanceType' => 'The type of instances associated with the variant.
', 'ProductionVariant$InstanceType' => 'The ML compute instance type.
', 'RealTimeInferenceRecommendation$InstanceType' => 'The recommended instance type for Real-Time Inference.
', 'RealtimeInferenceInstanceTypes$member' => NULL, ], ], 'ProductionVariantList' => [ 'base' => NULL, 'refs' => [ 'CreateEndpointConfigInput$ProductionVariants' => 'An array of ProductionVariant objects, one for each model that you want to host at this endpoint.
An array of ProductionVariant objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants. If you use this field, you can only specify one variant for ProductionVariants and one variant for ShadowProductionVariants.
An array of ProductionVariant objects, one for each model that you want to host at this endpoint.
An array of ProductionVariant objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants.
The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this production variant.
', ], ], 'ProductionVariantSSMAccess' => [ 'base' => NULL, 'refs' => [ 'ProductionVariant$EnableSSMAccess' => ' You can use this parameter to turn on native Amazon Web Services Systems Manager (SSM) access for a production variant behind an endpoint. By default, SSM access is disabled for all production variants behind an endpoint. You can turn on or turn off SSM access for a production variant behind an existing endpoint by creating a new endpoint configuration and calling UpdateEndpoint.
Specifies the serverless configuration for an endpoint variant.
', 'refs' => [ 'EndpointInputConfiguration$ServerlessConfig' => NULL, 'EndpointOutputConfiguration$ServerlessConfig' => NULL, 'PendingProductionVariantSummary$CurrentServerlessConfig' => 'The serverless configuration for the endpoint.
', 'PendingProductionVariantSummary$DesiredServerlessConfig' => 'The serverless configuration requested for this deployment, as specified in the endpoint configuration for the endpoint.
', 'ProductionVariant$ServerlessConfig' => 'The serverless configuration for an endpoint. Specifies a serverless endpoint configuration instead of an instance-based endpoint configuration.
', 'ProductionVariantSummary$CurrentServerlessConfig' => 'The serverless configuration for the endpoint.
', 'ProductionVariantSummary$DesiredServerlessConfig' => 'The serverless configuration requested for the endpoint update.
', ], ], 'ProductionVariantServerlessUpdateConfig' => [ 'base' => 'Specifies the serverless update concurrency configuration for an endpoint variant.
', 'refs' => [ 'DesiredWeightAndCapacity$ServerlessUpdateConfig' => 'Specifies the serverless update concurrency configuration for an endpoint variant.
', ], ], 'ProductionVariantStatus' => [ 'base' => 'Describes the status of the production variant.
', 'refs' => [ 'ProductionVariantStatusList$member' => NULL, ], ], 'ProductionVariantStatusList' => [ 'base' => NULL, 'refs' => [ 'PendingProductionVariantSummary$VariantStatus' => 'The endpoint variant status which describes the current deployment stage status or operational status.
', 'ProductionVariantSummary$VariantStatus' => 'The endpoint variant status which describes the current deployment stage status or operational status.
', ], ], 'ProductionVariantSummary' => [ 'base' => 'Describes weight and capacities for a production variant associated with an endpoint. If you sent a request to the UpdateEndpointWeightsAndCapacities API and the endpoint status is Updating, you get different desired and current values.
An array of ProductionVariantSummary objects, one for each model hosted behind this endpoint.
', 'DescribeEndpointOutput$ShadowProductionVariants' => 'An array of ProductionVariantSummary objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants.
A list of the production variants hosted on the endpoint. Each production variant is a model.
', 'Endpoint$ShadowProductionVariants' => 'A list of the shadow variants hosted on the endpoint. Each shadow variant is a model in shadow mode with production traffic replicated from the production variant.
', ], ], 'ProductionVariantVolumeSizeInGB' => [ 'base' => NULL, 'refs' => [ 'ProductionVariant$VolumeSizeInGB' => 'The size, in GB, of the ML storage volume attached to individual inference instance associated with the production variant. Currently only Amazon EBS gp2 storage volumes are supported.
', ], ], 'ProfilerConfig' => [ 'base' => 'Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.
', 'refs' => [ 'CreateTrainingJobRequest$ProfilerConfig' => NULL, 'DescribeTrainingJobResponse$ProfilerConfig' => NULL, 'TrainingJob$ProfilerConfig' => NULL, ], ], 'ProfilerConfigForUpdate' => [ 'base' => 'Configuration information for updating the Amazon SageMaker Debugger profile parameters, system and framework metrics configurations, and storage paths.
', 'refs' => [ 'UpdateTrainingJobRequest$ProfilerConfig' => 'Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.
', ], ], 'ProfilerRuleConfiguration' => [ 'base' => 'Configuration information for profiling rules.
', 'refs' => [ 'ProfilerRuleConfigurations$member' => NULL, ], ], 'ProfilerRuleConfigurations' => [ 'base' => NULL, 'refs' => [ 'CreateTrainingJobRequest$ProfilerRuleConfigurations' => 'Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
', 'DescribeTrainingJobResponse$ProfilerRuleConfigurations' => 'Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
', 'UpdateTrainingJobRequest$ProfilerRuleConfigurations' => 'Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
', ], ], 'ProfilerRuleEvaluationStatus' => [ 'base' => 'Information about the status of the rule evaluation.
', 'refs' => [ 'ProfilerRuleEvaluationStatuses$member' => NULL, ], ], 'ProfilerRuleEvaluationStatuses' => [ 'base' => NULL, 'refs' => [ 'DescribeTrainingJobResponse$ProfilerRuleEvaluationStatuses' => 'Evaluation status of Amazon SageMaker Debugger rules for profiling on a training job.
', ], ], 'ProfilingIntervalInMilliseconds' => [ 'base' => NULL, 'refs' => [ 'ProfilerConfig$ProfilingIntervalInMilliseconds' => 'A time interval for capturing system metrics in milliseconds. Available values are 100, 200, 500, 1000 (1 second), 5000 (5 seconds), and 60000 (1 minute) milliseconds. The default value is 500 milliseconds.
', 'ProfilerConfigForUpdate$ProfilingIntervalInMilliseconds' => 'A time interval for capturing system metrics in milliseconds. Available values are 100, 200, 500, 1000 (1 second), 5000 (5 seconds), and 60000 (1 minute) milliseconds. The default value is 500 milliseconds.
', ], ], 'ProfilingParameters' => [ 'base' => NULL, 'refs' => [ 'ProfilerConfig$ProfilingParameters' => 'Configuration information for capturing framework metrics. Available key strings for different profiling options are DetailedProfilingConfig, PythonProfilingConfig, and DataLoaderProfilingConfig. The following codes are configuration structures for the ProfilingParameters parameter. To learn more about how to configure the ProfilingParameters parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Configuration information for capturing framework metrics. Available key strings for different profiling options are DetailedProfilingConfig, PythonProfilingConfig, and DataLoaderProfilingConfig. The following codes are configuration structures for the ProfilingParameters parameter. To learn more about how to configure the ProfilingParameters parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Profiling status of a training job.
', ], ], 'ProgrammingLang' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$ProgrammingLang' => 'The supported programming language and its version.
', 'DescribeImageVersionResponse$ProgrammingLang' => 'The supported programming language and its version.
', 'UpdateImageVersionRequest$ProgrammingLang' => 'The supported programming language and its version.
', ], ], 'Project' => [ 'base' => 'The properties of a project as returned by the Search API.
', 'refs' => [ 'SearchRecord$Project' => 'The properties of a project.
', ], ], 'ProjectArn' => [ 'base' => NULL, 'refs' => [ 'CreateProjectOutput$ProjectArn' => 'The Amazon Resource Name (ARN) of the project.
', 'DescribeProjectOutput$ProjectArn' => 'The Amazon Resource Name (ARN) of the project.
', 'Project$ProjectArn' => 'The Amazon Resource Name (ARN) of the project.
', 'ProjectSummary$ProjectArn' => 'The Amazon Resource Name (ARN) of the project.
', 'UpdateProjectOutput$ProjectArn' => 'The Amazon Resource Name (ARN) of the project.
', ], ], 'ProjectEntityName' => [ 'base' => NULL, 'refs' => [ 'CreateProjectInput$ProjectName' => 'The name of the project.
', 'DeleteProjectInput$ProjectName' => 'The name of the project to delete.
', 'DescribeProjectInput$ProjectName' => 'The name of the project to describe.
', 'DescribeProjectOutput$ProjectName' => 'The name of the project.
', 'ListProjectsInput$NameContains' => 'A filter that returns the projects whose name contains a specified string.
', 'Project$ProjectName' => 'The name of the project.
', 'ProjectSummary$ProjectName' => 'The name of the project.
', 'UpdateProjectInput$ProjectName' => 'The name of the project.
', ], ], 'ProjectId' => [ 'base' => NULL, 'refs' => [ 'CreateProjectOutput$ProjectId' => 'The ID of the new project.
', 'DescribeProjectOutput$ProjectId' => 'The ID of the project.
', 'Project$ProjectId' => 'The ID of the project.
', 'ProjectSummary$ProjectId' => 'The ID of the project.
', ], ], 'ProjectSortBy' => [ 'base' => NULL, 'refs' => [ 'ListProjectsInput$SortBy' => 'The field by which to sort results. The default is CreationTime.
The sort order for results. The default is Ascending.
The status of the project.
', 'Project$ProjectStatus' => 'The status of the project.
', 'ProjectSummary$ProjectStatus' => 'The status of the project.
', ], ], 'ProjectSummary' => [ 'base' => 'Information about a project.
', 'refs' => [ 'ProjectSummaryList$member' => NULL, ], ], 'ProjectSummaryList' => [ 'base' => NULL, 'refs' => [ 'ListProjectsOutput$ProjectSummaryList' => 'A list of summaries of projects.
', ], ], 'PropertyNameHint' => [ 'base' => NULL, 'refs' => [ 'PropertyNameQuery$PropertyNameHint' => 'Text that begins a property\'s name.
', ], ], 'PropertyNameQuery' => [ 'base' => 'Part of the SuggestionQuery type. Specifies a hint for retrieving property names that begin with the specified text.
Defines a property name hint. Only property names that begin with the specified hint are included in the response.
', ], ], 'PropertyNameSuggestion' => [ 'base' => 'A property name returned from a GetSearchSuggestions call that specifies a value in the PropertyNameQuery field.
A list of property names for a Resource that match a SuggestionQuery.
The current status of the product.
AVAILABLE - Stable state, ready to perform any operation. The most recent operation succeeded and completed.
UNDER_CHANGE - Transitive state. Operations performed might not have valid results. Wait for an AVAILABLE status before performing operations.
TAINTED - Stable state, ready to perform any operation. The stack has completed the requested operation but is not exactly what was requested. For example, a request to update to a new version failed and the stack rolled back to the current version.
ERROR - An unexpected error occurred. The provisioned product exists but the stack is not running. For example, CloudFormation received a parameter value that was not valid and could not launch the stack.
PLAN_IN_PROGRESS - Transitive state. The plan operations were performed to provision a new product, but resources have not yet been created. After reviewing the list of resources to be created, execute the plan. Wait for an AVAILABLE status before performing operations.
A key value pair used when you provision a project as a service catalog product. For information, see What is Amazon Web Services Service Catalog.
', 'refs' => [ 'ProvisioningParameters$member' => NULL, ], ], 'ProvisioningParameterKey' => [ 'base' => NULL, 'refs' => [ 'ProvisioningParameter$Key' => 'The key that identifies a provisioning parameter.
', ], ], 'ProvisioningParameterValue' => [ 'base' => NULL, 'refs' => [ 'ProvisioningParameter$Value' => 'The value of the provisioning parameter.
', ], ], 'ProvisioningParameters' => [ 'base' => NULL, 'refs' => [ 'ServiceCatalogProvisioningDetails$ProvisioningParameters' => 'A list of key value pairs that you specify when you provision a product.
', 'ServiceCatalogProvisioningUpdateDetails$ProvisioningParameters' => 'A list of key value pairs that you specify when you provision a product.
', ], ], 'PublicWorkforceTaskPrice' => [ 'base' => 'Defines the amount of money paid to an Amazon Mechanical Turk worker for each task performed.
Use one of the following prices for bounding box tasks. Prices are in US dollars and should be based on the complexity of the task; the longer it takes in your initial testing, the more you should offer.
0.036
0.048
0.060
0.072
0.120
0.240
0.360
0.480
0.600
0.720
0.840
0.960
1.080
1.200
Use one of the following prices for image classification, text classification, and custom tasks. Prices are in US dollars.
0.012
0.024
0.036
0.048
0.060
0.072
0.120
0.240
0.360
0.480
0.600
0.720
0.840
0.960
1.080
1.200
Use one of the following prices for semantic segmentation tasks. Prices are in US dollars.
0.840
0.960
1.080
1.200
Use one of the following prices for Textract AnalyzeDocument Important Form Key Amazon Augmented AI review tasks. Prices are in US dollars.
2.400
2.280
2.160
2.040
1.920
1.800
1.680
1.560
1.440
1.320
1.200
1.080
0.960
0.840
0.720
0.600
0.480
0.360
0.240
0.120
0.072
0.060
0.048
0.036
0.024
0.012
Use one of the following prices for Rekognition DetectModerationLabels Amazon Augmented AI review tasks. Prices are in US dollars.
1.200
1.080
0.960
0.840
0.720
0.600
0.480
0.360
0.240
0.120
0.072
0.060
0.048
0.036
0.024
0.012
Use one of the following prices for Amazon Augmented AI custom human review tasks. Prices are in US dollars.
1.200
1.080
0.960
0.840
0.720
0.600
0.480
0.360
0.240
0.120
0.072
0.060
0.048
0.036
0.024
0.012
The price that you pay for each task performed by an Amazon Mechanical Turk worker.
', ], ], 'PutModelPackageGroupPolicyInput' => [ 'base' => NULL, 'refs' => [], ], 'PutModelPackageGroupPolicyOutput' => [ 'base' => NULL, 'refs' => [], ], 'QualityCheckStepMetadata' => [ 'base' => 'Container for the metadata for a Quality check step. For more information, see the topic on QualityCheck step in the Amazon SageMaker Developer Guide.
', 'refs' => [ 'PipelineExecutionStepMetadata$QualityCheck' => 'The configurations and outcomes of the check step execution. This includes:
The type of the check conducted.
The Amazon S3 URIs of baseline constraints and statistics files to be used for the drift check.
The Amazon S3 URIs of newly calculated baseline constraints and statistics.
The model package group name provided.
The Amazon S3 URI of the violation report if violations detected.
The Amazon Resource Name (ARN) of check processing job initiated by the step execution.
The Boolean flags indicating if the drift check is skipped.
If step property BaselineUsedForDriftCheck is set the same as CalculatedBaseline.
A set of filters to narrow the set of lineage entities connected to the StartArn(s) returned by the QueryLineage API action.
A set of filtering parameters that allow you to specify which entities should be returned.
Properties - Key-value pairs to match on the lineage entities\' properties.
LineageTypes - A set of lineage entity types to match on. For example: TrialComponent, Artifact, or Context.
CreatedBefore - Filter entities created before this date.
ModifiedBefore - Filter entities modified before this date.
ModifiedAfter - Filter entities modified after this date.
The maximum depth in lineage relationships from the StartArns that are traversed. Depth is a measure of the number of Associations from the StartArn entity to the matched results.
Limits the number of vertices in the results. Use the NextToken in a response to to retrieve the next page of results.
A list of resource Amazon Resource Name (ARN) that represent the starting point for your lineage query.
', ], ], 'QueryLineageTypes' => [ 'base' => NULL, 'refs' => [ 'QueryFilters$LineageTypes' => 'Filter the lineage entities connected to the StartArn(s) by the type of the lineage entity.
Filter the lineage entities connected to the StartArn(s) by a set if property key value pairs. If multiple pairs are provided, an entity is included in the results if it matches any of the provided pairs.
Filter the lineage entities connected to the StartArn by type. For example: DataSet, Model, Endpoint, or ModelDeployment.
A collection of settings that apply to an RSessionGateway app.
A collection of settings that configure the RSessionGateway app.
Indicates whether the current user has access to the RStudioServerPro app.
A collection of settings that configure user interaction with the RStudioServerPro app.
A collection of settings that configure user interaction with the RStudioServerPro app.
A collection of settings that configure the RStudioServerPro Domain-level app.
A collection of settings that configure the RStudioServerPro Domain-level app.
A collection of settings that update the current configuration for the RStudioServerPro Domain-level app.
A collection of RStudioServerPro Domain-level app settings to update. A single RStudioServerPro application is created for a domain.
The level of permissions that the user has within the RStudioServerPro app. This value defaults to `User`. The `Admin` value allows the user access to the RStudio Administrative Dashboard.
A value used to initialize a pseudo-random number generator. Setting a random seed and using the same seed later for the same tuning job will allow hyperparameter optimization to find more a consistent hyperparameter configuration between the two runs.
', ], ], 'RealTimeInferenceConfig' => [ 'base' => 'The infrastructure configuration for deploying the model to a real-time inference endpoint.
', 'refs' => [ 'ModelInfrastructureConfig$RealTimeInferenceConfig' => 'The infrastructure configuration for deploying the model to real-time inference.
', ], ], 'RealTimeInferenceRecommendation' => [ 'base' => 'The recommended configuration to use for Real-Time Inference.
', 'refs' => [ 'RealTimeInferenceRecommendations$member' => NULL, ], ], 'RealTimeInferenceRecommendations' => [ 'base' => NULL, 'refs' => [ 'DeploymentRecommendation$RealTimeInferenceRecommendations' => 'A list of RealTimeInferenceRecommendation items.
', ], ], 'RealtimeInferenceInstanceTypes' => [ 'base' => NULL, 'refs' => [ 'AdditionalInferenceSpecificationDefinition$SupportedRealtimeInferenceInstanceTypes' => 'A list of the instance types that are used to generate inferences in real-time.
', 'InferenceSpecification$SupportedRealtimeInferenceInstanceTypes' => 'A list of the instance types that are used to generate inferences in real-time.
This parameter is required for unversioned models, and optional for versioned models.
', ], ], 'RecommendationFailureReason' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobInferenceBenchmark$FailureReason' => 'The reason why a benchmark failed.
', ], ], 'RecommendationJobArn' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceRecommendationsJobResponse$JobArn' => 'The Amazon Resource Name (ARN) of the recommendation job.
', 'DescribeInferenceRecommendationsJobResponse$JobArn' => 'The Amazon Resource Name (ARN) of the job.
', 'InferenceRecommendationsJob$JobArn' => 'The Amazon Resource Name (ARN) of the recommendation job.
', ], ], 'RecommendationJobCompilationJobName' => [ 'base' => NULL, 'refs' => [ 'ModelConfiguration$CompilationJobName' => 'The name of the compilation job used to create the recommended model artifacts.
', ], ], 'RecommendationJobCompiledOutputConfig' => [ 'base' => 'Provides information about the output configuration for the compiled model.
', 'refs' => [ 'RecommendationJobOutputConfig$CompiledOutputConfig' => 'Provides information about the output configuration for the compiled model.
', ], ], 'RecommendationJobContainerConfig' => [ 'base' => 'Specifies mandatory fields for running an Inference Recommender job directly in the CreateInferenceRecommendationsJob API. The fields specified in ContainerConfig override the corresponding fields in the model package. Use ContainerConfig if you want to specify these fields for the recommendation job but don\'t want to edit them in your model package.
Specifies mandatory fields for running an Inference Recommender job. The fields specified in ContainerConfig override the corresponding fields in the model package.
Specifies the name and shape of the expected data inputs for your trained model with a JSON dictionary form. This field is used for optimizing your model using SageMaker Neo. For more information, see DataInputConfig.
', ], ], 'RecommendationJobDescription' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceRecommendationsJobRequest$JobDescription' => 'Description of the recommendation job.
', 'DescribeInferenceRecommendationsJobResponse$JobDescription' => 'The job description that you provided when you initiated the job.
', 'InferenceRecommendationsJob$JobDescription' => 'The job description.
', ], ], 'RecommendationJobInferenceBenchmark' => [ 'base' => 'The details for a specific benchmark from an Inference Recommender job.
', 'refs' => [ 'InferenceRecommendationsJobStep$InferenceBenchmark' => 'The details for a specific benchmark.
', ], ], 'RecommendationJobInputConfig' => [ 'base' => 'The input configuration of the recommendation job.
', 'refs' => [ 'CreateInferenceRecommendationsJobRequest$InputConfig' => 'Provides information about the versioned model package Amazon Resource Name (ARN), the traffic pattern, and endpoint configurations.
', 'DescribeInferenceRecommendationsJobResponse$InputConfig' => 'Returns information about the versioned model package Amazon Resource Name (ARN), the traffic pattern, and endpoint configurations you provided when you initiated the job.
', ], ], 'RecommendationJobName' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceRecommendationsJobRequest$JobName' => 'A name for the recommendation job. The name must be unique within the Amazon Web Services Region and within your Amazon Web Services account. The job name is passed down to the resources created by the recommendation job. The names of resources (such as the model, endpoint configuration, endpoint, and compilation) that are prefixed with the job name are truncated at 40 characters.
', 'DescribeInferenceRecommendationsJobRequest$JobName' => 'The name of the job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'DescribeInferenceRecommendationsJobResponse$JobName' => 'The name of the job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
', 'GetScalingConfigurationRecommendationRequest$InferenceRecommendationsJobName' => 'The name of a previously completed Inference Recommender job.
', 'GetScalingConfigurationRecommendationResponse$InferenceRecommendationsJobName' => 'The name of a previously completed Inference Recommender job.
', 'InferenceRecommendationsJob$JobName' => 'The name of the job.
', 'InferenceRecommendationsJobStep$JobName' => 'The name of the Inference Recommender job.
', 'ListInferenceRecommendationsJobStepsRequest$JobName' => 'The name for the Inference Recommender job.
', 'StopInferenceRecommendationsJobRequest$JobName' => 'The name of the job you want to stop.
', ], ], 'RecommendationJobOutputConfig' => [ 'base' => 'Provides information about the output configuration for the compiled model.
', 'refs' => [ 'CreateInferenceRecommendationsJobRequest$OutputConfig' => 'Provides information about the output artifacts and the KMS key to use for Amazon S3 server-side encryption.
', ], ], 'RecommendationJobPayloadConfig' => [ 'base' => 'The configuration for the payload for a recommendation job.
', 'refs' => [ 'RecommendationJobContainerConfig$PayloadConfig' => 'Specifies the SamplePayloadUrl and all other sample payload-related fields.
Specifies the maximum number of jobs that can run in parallel and the maximum number of jobs that can run.
', 'refs' => [ 'RecommendationJobInputConfig$ResourceLimit' => 'Defines the resource limit of the job.
', ], ], 'RecommendationJobStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeInferenceRecommendationsJobResponse$Status' => 'The status of the job.
', 'InferenceRecommendationsJob$Status' => 'The status of the job.
', 'InferenceRecommendationsJobStep$Status' => 'The current status of the benchmark.
', 'ListInferenceRecommendationsJobStepsRequest$Status' => 'A filter to return benchmarks of a specified status. If this field is left empty, then all benchmarks are returned.
', 'ListInferenceRecommendationsJobsRequest$StatusEquals' => 'A filter that retrieves only inference recommendations jobs with a specific status.
', ], ], 'RecommendationJobStoppingConditions' => [ 'base' => 'Specifies conditions for stopping a job. When a job reaches a stopping condition limit, SageMaker ends the job.
', 'refs' => [ 'CreateInferenceRecommendationsJobRequest$StoppingConditions' => 'A set of conditions for stopping a recommendation job. If any of the conditions are met, the job is automatically stopped.
', 'DescribeInferenceRecommendationsJobResponse$StoppingConditions' => 'The stopping conditions that you provided when you initiated the job.
', ], ], 'RecommendationJobSupportedContentTypes' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobPayloadConfig$SupportedContentTypes' => 'The supported MIME types for the input data.
', ], ], 'RecommendationJobSupportedEndpointType' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobContainerConfig$SupportedEndpointType' => 'The endpoint type to receive recommendations for. By default this is null, and the results of the inference recommendation job return a combined list of both real-time and serverless benchmarks. By specifying a value for this field, you can receive a longer list of benchmarks for the desired endpoint type.
', ], ], 'RecommendationJobSupportedInstanceTypes' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobContainerConfig$SupportedInstanceTypes' => 'A list of the instance types that are used to generate inferences in real-time.
', ], ], 'RecommendationJobSupportedResponseMIMEType' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobSupportedResponseMIMETypes$member' => NULL, ], ], 'RecommendationJobSupportedResponseMIMETypes' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobContainerConfig$SupportedResponseMIMETypes' => 'The supported MIME types for the output data.
', ], ], 'RecommendationJobType' => [ 'base' => NULL, 'refs' => [ 'CreateInferenceRecommendationsJobRequest$JobType' => 'Defines the type of recommendation job. Specify Default to initiate an instance recommendation and Advanced to initiate a load test. If left unspecified, Amazon SageMaker Inference Recommender will run an instance recommendation (DEFAULT) job.
The job type that you provided when you initiated the job.
', 'InferenceRecommendationsJob$JobType' => 'The recommendation job type.
', ], ], 'RecommendationJobVpcConfig' => [ 'base' => 'Inference Recommender provisions SageMaker endpoints with access to VPC in the inference recommendation job.
', 'refs' => [ 'RecommendationJobInputConfig$VpcConfig' => 'Inference Recommender provisions SageMaker endpoints with access to VPC in the inference recommendation job.
', ], ], 'RecommendationJobVpcSecurityGroupId' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobVpcSecurityGroupIds$member' => NULL, ], ], 'RecommendationJobVpcSecurityGroupIds' => [ 'base' => NULL, 'refs' => [ 'RecommendationJobVpcConfig$SecurityGroupIds' => 'The VPC security group IDs. IDs have the form of sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
The ID of the subnets in the VPC to which you want to connect your model.
', ], ], 'RecommendationMetrics' => [ 'base' => 'The metrics of recommendations.
', 'refs' => [ 'InferenceRecommendation$Metrics' => 'The metrics used to decide what recommendation to make.
', 'RecommendationJobInferenceBenchmark$Metrics' => NULL, ], ], 'RecommendationStatus' => [ 'base' => NULL, 'refs' => [ 'DeploymentRecommendation$RecommendationStatus' => 'Status of the deployment recommendation. The status NOT_APPLICABLE means that SageMaker is unable to provide a default recommendation for the model using the information provided. If the deployment status is IN_PROGRESS, retry your API call after a few seconds to get a COMPLETED deployment recommendation.
The type of the subtask.
BENCHMARK: Evaluate the performance of your model on different instance types.
A filter to return details about the specified type of subtask.
BENCHMARK: Evaluate the performance of your model on different instance types.
Specify RecordIO as the value when input data is in raw format but the training algorithm requires the RecordIO format. In this case, SageMaker wraps each individual S3 object in a RecordIO record. If the input data is already in RecordIO format, you don\'t need to set this attribute. For more information, see Create a Dataset Using RecordIO.
In File mode, leave this field unset or set it to None.
', ], ], 'RedshiftClusterId' => [ 'base' => 'The Redshift cluster Identifier.
', 'refs' => [ 'RedshiftDatasetDefinition$ClusterId' => NULL, ], ], 'RedshiftDatabase' => [ 'base' => 'The name of the Redshift database used in Redshift query execution.
', 'refs' => [ 'RedshiftDatasetDefinition$Database' => NULL, ], ], 'RedshiftDatasetDefinition' => [ 'base' => 'Configuration for Redshift Dataset Definition input.
', 'refs' => [ 'DatasetDefinition$RedshiftDatasetDefinition' => NULL, ], ], 'RedshiftQueryString' => [ 'base' => 'The SQL query statements to be executed.
', 'refs' => [ 'RedshiftDatasetDefinition$QueryString' => NULL, ], ], 'RedshiftResultCompressionType' => [ 'base' => 'The compression used for Redshift query results.
', 'refs' => [ 'RedshiftDatasetDefinition$OutputCompression' => NULL, ], ], 'RedshiftResultFormat' => [ 'base' => 'The data storage format for Redshift query results.
', 'refs' => [ 'RedshiftDatasetDefinition$OutputFormat' => NULL, ], ], 'RedshiftUserName' => [ 'base' => 'The database user name used in Redshift query execution.
', 'refs' => [ 'RedshiftDatasetDefinition$DbUser' => NULL, ], ], 'RegisterDevicesRequest' => [ 'base' => NULL, 'refs' => [], ], 'RegisterModelStepMetadata' => [ 'base' => 'Metadata for a register model job step.
', 'refs' => [ 'PipelineExecutionStepMetadata$RegisterModel' => 'The Amazon Resource Name (ARN) of the model package that the model was registered to by this step execution.
', ], ], 'ReleaseNotes' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$ReleaseNotes' => 'The maintainer description of the image version.
', 'DescribeImageVersionResponse$ReleaseNotes' => 'The maintainer description of the image version.
', 'UpdateImageVersionRequest$ReleaseNotes' => 'The maintainer description of the image version.
', ], ], 'RenderUiTemplateRequest' => [ 'base' => NULL, 'refs' => [], ], 'RenderUiTemplateResponse' => [ 'base' => NULL, 'refs' => [], ], 'RenderableTask' => [ 'base' => 'Contains input values for a task.
', 'refs' => [ 'RenderUiTemplateRequest$Task' => 'A RenderableTask object containing a representative task to render.
A description of an error that occurred while rendering the template.
', 'refs' => [ 'RenderingErrorList$member' => NULL, ], ], 'RenderingErrorList' => [ 'base' => NULL, 'refs' => [ 'RenderUiTemplateResponse$Errors' => 'A list of one or more RenderingError objects if any were encountered while rendering the template. If there were no errors, the list is empty.
Set this to one of the following values:
Platform - The model image is hosted in Amazon ECR.
Vpc - The model image is hosted in a private Docker registry in your VPC.
Specifies an authentication configuration for the private docker registry where your model image is hosted. Specify a value for this property only if you specified Vpc as the value for the RepositoryAccessMode field of the ImageConfig object that you passed to a call to CreateModel and the private Docker registry where the model image is hosted requires authentication.
(Optional) Specifies an authentication configuration for the private docker registry where your model image is hosted. Specify a value for this property only if you specified Vpc as the value for the RepositoryAccessMode field, and the private Docker registry where the model image is hosted requires authentication.
The Amazon Resource Name (ARN) of an Amazon Web Services Lambda function that provides credentials to authenticate to the private Docker registry where your model image is hosted. For information about how to create an Amazon Web Services Lambda function, see Create a Lambda function with the console in the Amazon Web Services Lambda Developer Guide.
', ], ], 'RepositoryUrl' => [ 'base' => NULL, 'refs' => [ 'CodeRepository$RepositoryUrl' => 'The URL of the Git repository.
', ], ], 'ResolvedAttributes' => [ 'base' => 'The resolved attributes.
', 'refs' => [ 'DescribeAutoMLJobResponse$ResolvedAttributes' => 'Contains ProblemType, AutoMLJobObjective, and CompletionCriteria. If you do not provide these values, they are inferred.
The Amazon Resource Name (ARN) of the resource that you want to tag.
', 'DeleteTagsInput$ResourceArn' => 'The Amazon Resource Name (ARN) of the resource whose tags you want to delete.
', 'ListTagsInput$ResourceArn' => 'The Amazon Resource Name (ARN) of the resource whose tags you want to retrieve.
', ], ], 'ResourceCatalog' => [ 'base' => ' A resource catalog containing all of the resources of a specific resource type within a resource owner account. For an example on sharing the Amazon SageMaker Feature Store DefaultFeatureGroupCatalog, see Share Amazon SageMaker Catalog resource type in the Amazon SageMaker Developer Guide.
The Amazon Resource Name (ARN) of the ResourceCatalog.
A free form description of the ResourceCatalog.
A list of the requested ResourceCatalogs.
A string that partially matches one or more ResourceCatalogs names. Filters ResourceCatalog by name.
The name of the ResourceCatalog.
The value on which the resource catalog list is sorted.
', ], ], 'ResourceCatalogSortOrder' => [ 'base' => NULL, 'refs' => [ 'ListResourceCatalogsRequest$SortOrder' => 'The order in which the resource catalogs are listed.
', ], ], 'ResourceConfig' => [ 'base' => 'Describes the resources, including machine learning (ML) compute instances and ML storage volumes, to use for model training.
', 'refs' => [ 'CreateTrainingJobRequest$ResourceConfig' => 'The resources, including the ML compute instances and ML storage volumes, to use for model training.
ML storage volumes store model artifacts and incremental states. Training algorithms might also use ML storage volumes for scratch space. If you want SageMaker to use the ML storage volume to store the training data, choose File as the TrainingInputMode in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.
Resources, including ML compute instances and ML storage volumes, that are configured for model training.
', 'HyperParameterTrainingJobDefinition$ResourceConfig' => 'The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.
Storage volumes store model artifacts and incremental states. Training algorithms might also use storage volumes for scratch space. If you want SageMaker to use the storage volume to store the training data, choose File as the TrainingInputMode in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.
If you want to use hyperparameter optimization with instance type flexibility, use HyperParameterTuningResourceConfig instead.
Resources, including ML compute instances and ML storage volumes, that are configured for model training.
', 'TrainingJobDefinition$ResourceConfig' => 'The resources, including the ML compute instances and ML storage volumes, to use for model training.
', ], ], 'ResourceConfigForUpdate' => [ 'base' => 'The ResourceConfig to update KeepAlivePeriodInSeconds. Other fields in the ResourceConfig cannot be updated.
The training job ResourceConfig to update warm pool retention length.
The ID of the Amazon Elastic File System (EFS) managed by this Domain.
', ], ], 'ResourceInUse' => [ 'base' => 'Resource being accessed is in use.
', 'refs' => [], ], 'ResourceLimitExceeded' => [ 'base' => 'You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
', 'refs' => [], ], 'ResourceLimits' => [ 'base' => 'Specifies the maximum number of training jobs and parallel training jobs that a hyperparameter tuning job can launch.
', 'refs' => [ 'HyperParameterTuningJobConfig$ResourceLimits' => 'The ResourceLimits object that specifies the maximum number of training and parallel training jobs that can be used for this hyperparameter tuning job.
', 'HyperParameterTuningJobSummary$ResourceLimits' => 'The ResourceLimits object that specifies the maximum number of training jobs and parallel training jobs allowed for this tuning job.
', ], ], 'ResourceNotFound' => [ 'base' => 'Resource being access is not found.
', 'refs' => [], ], 'ResourcePolicyString' => [ 'base' => NULL, 'refs' => [ 'GetLineageGroupPolicyResponse$ResourcePolicy' => 'The resource policy that gives access to the lineage group in another account.
', ], ], 'ResourcePropertyName' => [ 'base' => NULL, 'refs' => [ 'Filter$Name' => 'A resource property name. For example, TrainingJobName. For valid property names, see SearchRecord. You must specify a valid property for the resource.
The name of the property to use in the nested filters. The value must match a listed property name, such as InputDataConfig.
A suggested property name based on what you entered in the search textbox in the SageMaker console.
', 'SearchRequest$SortBy' => 'The name of the resource property used to sort the SearchResults. The default is LastModifiedTime.
The billable time in seconds used by the warm pool. Billable time refers to the absolute wall-clock time.
Multiply ResourceRetainedBillableTimeInSeconds by the number of instances (InstanceCount) in your training cluster to get the total compute time SageMaker bills you if you run warm pool training. The formula is as follows: ResourceRetainedBillableTimeInSeconds * InstanceCount.
Specifies the ARN\'s of a SageMaker image and SageMaker image version, and the instance type that the version runs on.
', 'refs' => [ 'CreateAppRequest$ResourceSpec' => 'The instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.
The value of InstanceType passed as part of the ResourceSpec in the CreateApp call overrides the value passed as part of the ResourceSpec configured for the user profile or the domain. If InstanceType is not specified in any of those three ResourceSpec values for a KernelGateway app, the CreateApp call fails with a request validation error.
The instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.
', 'JupyterServerAppSettings$DefaultResourceSpec' => 'The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the JupyterServer app. If you use the LifecycleConfigArns parameter, then this parameter is also required.
The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the KernelGateway app.
The Amazon SageMaker Studio UI does not use the default instance type value set here. The default instance type set here is used when Apps are created using the Amazon Web Services Command Line Interface or Amazon Web Services CloudFormation and the instance type parameter value is not passed.
The default instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.
', ], ], 'ResourceType' => [ 'base' => NULL, 'refs' => [ 'GetSearchSuggestionsRequest$Resource' => 'The name of the SageMaker resource to search for.
', 'SearchRequest$Resource' => 'The name of the SageMaker resource to search for.
', ], ], 'ResponseMIMEType' => [ 'base' => NULL, 'refs' => [ 'ResponseMIMETypes$member' => NULL, ], ], 'ResponseMIMETypes' => [ 'base' => NULL, 'refs' => [ 'AdditionalInferenceSpecificationDefinition$SupportedResponseMIMETypes' => 'The supported MIME types for the output data.
', 'InferenceSpecification$SupportedResponseMIMETypes' => 'The supported MIME types for the output data.
', ], ], 'RetentionPolicy' => [ 'base' => 'The retention policy for data stored on an Amazon Elastic File System (EFS) volume.
', 'refs' => [ 'DeleteDomainRequest$RetentionPolicy' => 'The retention policy for this domain, which specifies whether resources will be retained after the Domain is deleted. By default, all resources are retained (not automatically deleted).
', ], ], 'RetentionType' => [ 'base' => NULL, 'refs' => [ 'RetentionPolicy$HomeEfsFileSystem' => 'The default is Retain, which specifies to keep the data stored on the EFS volume.
Specify Delete to delete the data stored on the EFS volume.
The retry strategy to use when a training job fails due to an InternalServerError. RetryStrategy is specified as part of the CreateTrainingJob and CreateHyperParameterTuningJob requests. You can add the StoppingCondition parameter to the request to limit the training time for the complete job.
The number of times to retry the job when the job fails due to an InternalServerError.
The number of times to retry the job when the job fails due to an InternalServerError.
The number of times to retry the job when the job fails due to an InternalServerError.
The number of times to retry the job when the job fails due to an InternalServerError.
The IAM roles that SageMaker uses to run the training jobs.
', 'CreateAutoMLJobRequest$RoleArn' => 'The ARN of the role that is used to access the data.
', 'CreateAutoMLJobV2Request$RoleArn' => 'The ARN of the role that is used to access the data.
', 'CreateCompilationJobRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.
During model compilation, Amazon SageMaker needs your permission to:
Read input data from an S3 bucket
Write model artifacts to an S3 bucket
Write logs to Amazon CloudWatch Logs
Publish metrics to Amazon CloudWatch
You grant permissions for all of these tasks to an IAM role. To pass this role to Amazon SageMaker, the caller of this API must have the iam:PassRole permission. For more information, see Amazon SageMaker Roles.
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'CreateDeviceFleetRequest$RoleArn' => 'The Amazon Resource Name (ARN) that has access to Amazon Web Services Internet of Things (IoT).
', 'CreateEdgePackagingJobRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to download and upload the model, and to contact SageMaker Neo.
', 'CreateFeatureGroupRequest$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM execution role used to persist data into the OfflineStore if an OfflineStoreConfig is provided.
The Amazon Resource Name (ARN) of the role needed to call other services on your behalf. For example, arn:aws:iam::1234567890:role/service-role/AmazonSageMaker-ExecutionRole-20180111T151298.
The ARN of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.
', 'CreateInferenceExperimentRequest$RoleArn' => 'The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.
', 'CreateInferenceRecommendationsJobRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.
', 'CreateLabelingJobRequest$RoleArn' => 'The Amazon Resource Number (ARN) that Amazon SageMaker assumes to perform tasks on your behalf during data labeling. You must grant this role the necessary permissions so that Amazon SageMaker can successfully complete data labeling.
', 'CreateModelBiasJobDefinitionRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'CreateModelExplainabilityJobDefinitionRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'CreateModelInput$ExecutionRoleArn' => 'The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access model artifacts and docker image for deployment on ML compute instances or for batch transform jobs. Deploying on ML compute instances is part of model hosting. For more information, see SageMaker Roles.
To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole permission.
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'CreateNotebookInstanceInput$RoleArn' => 'When you send any requests to Amazon Web Services resources from the notebook instance, SageMaker assumes this role to perform tasks on your behalf. You must grant this role necessary permissions so SageMaker can perform these tasks. The policy must allow the SageMaker service principal (sagemaker.amazonaws.com) permissions to assume this role. For more information, see SageMaker Roles.
To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole permission.
The Amazon Resource Name (ARN) of the role used by the pipeline to access and create resources.
', 'CreateProcessingJobRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'CreateTrainingJobRequest$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that SageMaker can assume to perform tasks on your behalf.
During model training, SageMaker needs your permission to read input data from an S3 bucket, download a Docker image that contains training code, write model artifacts to an S3 bucket, write logs to Amazon CloudWatch Logs, and publish metrics to Amazon CloudWatch. You grant permissions for all of these tasks to an IAM role. For more information, see SageMaker Roles.
To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole permission.
The ARN of the execution role for the space.
', 'DescribeAutoMLJobResponse$RoleArn' => 'The Amazon Resource Name (ARN) of the Identity and Access Management (IAM) role that has read permission to the input data location and write permission to the output data location in Amazon S3.
', 'DescribeAutoMLJobV2Response$RoleArn' => 'The ARN of the Identity and Access Management role that has read permission to the input data location and write permission to the output data location in Amazon S3.
', 'DescribeCompilationJobResponse$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker assumes to perform the model compilation job.
', 'DescribeDataQualityJobDefinitionResponse$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'DescribeDeviceFleetResponse$RoleArn' => 'The Amazon Resource Name (ARN) that has access to Amazon Web Services Internet of Things (IoT).
', 'DescribeEdgePackagingJobResponse$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to download and upload the model, and to contact Neo.
', 'DescribeFeatureGroupResponse$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM execution role used to persist data into the OfflineStore if an OfflineStoreConfig is provided.
', 'DescribeFlowDefinitionResponse$RoleArn' => 'The Amazon Resource Name (ARN) of the Amazon Web Services Identity and Access Management (IAM) execution role for the flow definition.
', 'DescribeImageResponse$RoleArn' => 'The ARN of the IAM role that enables Amazon SageMaker to perform tasks on your behalf.
', 'DescribeInferenceExperimentResponse$RoleArn' => 'The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.
', 'DescribeInferenceRecommendationsJobResponse$RoleArn' => 'The Amazon Resource Name (ARN) of the Amazon Web Services Identity and Access Management (IAM) role you provided when you initiated the job.
', 'DescribeLabelingJobResponse$RoleArn' => 'The Amazon Resource Name (ARN) that SageMaker assumes to perform tasks on your behalf during data labeling.
', 'DescribeModelBiasJobDefinitionResponse$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM role that has read permission to the input data location and write permission to the output data location in Amazon S3.
', 'DescribeModelExplainabilityJobDefinitionResponse$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM role that has read permission to the input data location and write permission to the output data location in Amazon S3.
', 'DescribeModelOutput$ExecutionRoleArn' => 'The Amazon Resource Name (ARN) of the IAM role that you specified for the model.
', 'DescribeModelQualityJobDefinitionResponse$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'DescribeNotebookInstanceOutput$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM role associated with the instance.
', 'DescribePipelineResponse$RoleArn' => 'The Amazon Resource Name (ARN) that the pipeline uses to execute.
', 'DescribeProcessingJobResponse$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'DescribeTrainingJobResponse$RoleArn' => 'The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.
', 'FeatureGroup$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM execution role used to create the feature group.
', 'HyperParameterTrainingJobDefinition$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM role associated with the training jobs that the tuning job launches.
', 'InferenceExperimentSummary$RoleArn' => 'The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.
', 'InferenceRecommendationsJob$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.
', 'Model$ExecutionRoleArn' => 'The Amazon Resource Name (ARN) of the IAM role that you specified for the model.
', 'ModelPackageValidationSpecification$ValidationRole' => 'The IAM roles to be used for the validation of the model package.
', 'ModelRegisterSettings$CrossAccountModelRegisterRoleArn' => 'The Amazon Resource Name (ARN) of the SageMaker model registry account. Required only to register model versions created by a different SageMaker Canvas Amazon Web Services account than the Amazon Web Services account in which SageMaker model registry is set up.
', 'MonitoringJobDefinition$RoleArn' => 'The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
', 'Pipeline$RoleArn' => 'The Amazon Resource Name (ARN) of the role that created the pipeline.
', 'PipelineSummary$RoleArn' => 'The Amazon Resource Name (ARN) that the pipeline used to execute.
', 'ProcessingJob$RoleArn' => 'The ARN of the role used to create the processing job.
', 'RStudioServerProDomainSettings$DomainExecutionRoleArn' => 'The ARN of the execution role for the RStudioServerPro Domain-level app.
The execution role for the RStudioServerPro Domain-level app.
The IAM role attached to your Redshift cluster that Amazon SageMaker uses to generate datasets.
', 'RenderUiTemplateRequest$RoleArn' => 'The Amazon Resource Name (ARN) that has access to the S3 objects that are used by the template.
', 'TimeSeriesForecastingSettings$AmazonForecastRoleArn' => 'The IAM role that Canvas passes to Amazon Forecast for time series forecasting. By default, Canvas uses the execution role specified in the UserProfile that launches the Canvas application. If an execution role is not specified in the UserProfile, Canvas uses the execution role specified in the Domain that owns the UserProfile. To allow time series forecasting, this IAM role should have the AmazonSageMakerCanvasForecastAccess policy attached and forecast.amazonaws.com added in the trust relationship as a service principal.
The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.
', 'UpdateDeviceFleetRequest$RoleArn' => 'The Amazon Resource Name (ARN) of the device.
', 'UpdateImageRequest$RoleArn' => 'The new ARN for the IAM role that enables Amazon SageMaker to perform tasks on your behalf.
', 'UpdateNotebookInstanceInput$RoleArn' => 'The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access the notebook instance. For more information, see SageMaker Roles.
To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole permission.
The Amazon Resource Name (ARN) that the pipeline uses to execute.
', 'UserSettings$ExecutionRole' => 'The execution role for the user.
', ], ], 'RollingUpdatePolicy' => [ 'base' => 'Specifies a rolling deployment strategy for updating a SageMaker endpoint.
', 'refs' => [ 'DeploymentConfig$RollingUpdatePolicy' => 'Specifies a rolling deployment strategy for updating a SageMaker endpoint.
', ], ], 'RootAccess' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$RootAccess' => 'Whether root access is enabled or disabled for users of the notebook instance. The default value is Enabled.
Lifecycle configurations need root access to be able to set up a notebook instance. Because of this, lifecycle configurations associated with a notebook instance always run with root access even if you disable root access for users.
Whether root access is enabled or disabled for users of the notebook instance.
Lifecycle configurations need root access to be able to set up a notebook instance. Because of this, lifecycle configurations associated with a notebook instance always run with root access even if you disable root access for users.
Whether root access is enabled or disabled for users of the notebook instance. The default value is Enabled.
If you set this to Disabled, users don\'t have root access on the notebook instance, but lifecycle configuration scripts still run with root permissions.
The name of the rule configuration. It must be unique relative to other rule configuration names.
', 'DebugRuleEvaluationStatus$RuleConfigurationName' => 'The name of the rule configuration.
', 'ProfilerRuleConfiguration$RuleConfigurationName' => 'The name of the rule configuration. It must be unique relative to other rule configuration names.
', 'ProfilerRuleEvaluationStatus$RuleConfigurationName' => 'The name of the rule configuration.
', ], ], 'RuleEvaluationStatus' => [ 'base' => NULL, 'refs' => [ 'DebugRuleEvaluationStatus$RuleEvaluationStatus' => 'Status of the rule evaluation.
', 'ProfilerRuleEvaluationStatus$RuleEvaluationStatus' => 'Status of the rule evaluation.
', ], ], 'RuleParameters' => [ 'base' => NULL, 'refs' => [ 'DebugRuleConfiguration$RuleParameters' => 'Runtime configuration for rule container.
', 'ProfilerRuleConfiguration$RuleParameters' => 'Runtime configuration for rule container.
', ], ], 'S3DataDistribution' => [ 'base' => NULL, 'refs' => [ 'S3DataSource$S3DataDistributionType' => 'If you want SageMaker to replicate the entire dataset on each ML compute instance that is launched for model training, specify FullyReplicated.
If you want SageMaker to replicate a subset of data on each ML compute instance that is launched for model training, specify ShardedByS3Key. If there are n ML compute instances launched for a training job, each instance gets approximately 1/n of the number of S3 objects. In this case, model training on each machine uses only the subset of training data.
Don\'t choose more ML compute instances for training than available S3 objects. If you do, some nodes won\'t get any data and you will pay for nodes that aren\'t getting any training data. This applies in both File and Pipe modes. Keep this in mind when developing algorithms.
In distributed training, where you use multiple ML compute EC2 instances, you might choose ShardedByS3Key. If the algorithm requires copying training data to the ML storage volume (when TrainingInputMode is set to File), this copies 1/n of the number of objects.
Describes the S3 data source.
Your input bucket must be in the same Amazon Web Services region as your training job.
', 'refs' => [ 'DataSource$S3DataSource' => 'The S3 location of the data source that is associated with a channel.
', ], ], 'S3DataType' => [ 'base' => NULL, 'refs' => [ 'S3DataSource$S3DataType' => 'If you choose S3Prefix, S3Uri identifies a key name prefix. SageMaker uses all objects that match the specified key name prefix for model training.
If you choose ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want SageMaker to use for model training.
If you choose AugmentedManifestFile, S3Uri identifies an object that is an augmented manifest file in JSON lines format. This file contains the data you want to use for model training. AugmentedManifestFile can only be used if the Channel\'s input mode is Pipe.
If you choose S3Prefix, S3Uri identifies a key name prefix. Amazon SageMaker uses all objects with the specified key name prefix for batch transform.
If you choose ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want Amazon SageMaker to use for batch transform.
The following values are compatible: ManifestFile, S3Prefix
The following value is not compatible: AugmentedManifestFile
Specifies the S3 location of ML model data to deploy.
', 'refs' => [ 'ModelDataSource$S3DataSource' => 'Specifies the S3 location of ML model data to deploy.
', ], ], 'S3ModelDataType' => [ 'base' => NULL, 'refs' => [ 'S3ModelDataSource$S3DataType' => 'Specifies the type of ML model data to deploy.
If you choose S3Prefix, S3Uri identifies a key name prefix. SageMaker uses all objects that match the specified key name prefix as part of the ML model data to deploy. A valid key name prefix identified by S3Uri always ends with a forward slash (/).
If you choose S3Object, S3Uri identifies an object that is the ML model data to deploy.
Specifies the S3 path of ML model data to deploy.
', ], ], 'S3OutputPath' => [ 'base' => NULL, 'refs' => [ 'HubS3StorageConfig$S3OutputPath' => 'The Amazon S3 bucket prefix for hosting hub content.
', ], ], 'S3StorageConfig' => [ 'base' => 'The Amazon Simple Storage (Amazon S3) location and and security configuration for OfflineStore.
The Amazon Simple Storage (Amazon S3) location of OfflineStore.
The uniform resource identifier (URI) used to identify an additional data source used in inference or training.
', 'AthenaDatasetDefinition$OutputS3Uri' => 'The location in Amazon S3 where Athena query results are stored.
', 'AutoMLCandidateGenerationConfig$FeatureSpecificationS3Uri' => 'A URL to the Amazon S3 data source containing selected features from the input data source to run an Autopilot job. You can input FeatureAttributeNames (optional) in JSON format as shown below:
{ "FeatureAttributeNames":["col1", "col2", ...] }.
You can also specify the data type of the feature (optional) in the format shown below:
{ "FeatureDataTypes":{"col1":"numeric", "col2":"categorical" ... } }
These column keys may not include the target column.
In ensembling mode, Autopilot only supports the following data types: numeric, categorical, text, and datetime. In HPO mode, Autopilot can support numeric, categorical, text, datetime, and sequence.
If only FeatureDataTypes is provided, the column keys (col1, col2,..) should be a subset of the column names in the input data.
If both FeatureDataTypes and FeatureAttributeNames are provided, then the column keys should be a subset of the column names provided in FeatureAttributeNames.
The key name FeatureAttributeNames is fixed. The values listed in ["col1", "col2", ...] are case sensitive and should be a list of strings containing unique values that are a subset of the column names in the input data. The list of columns provided must not include the target column.
The Amazon S3 output path. Must be 128 characters or less.
', 'AutoMLS3DataSource$S3Uri' => 'The URL to the Amazon S3 data source. The Uri refers to the Amazon S3 prefix or ManifestFile depending on the data type.
', 'BatchDataCaptureConfig$DestinationS3Uri' => 'The Amazon S3 location being used to capture the data.
', 'CheckpointConfig$S3Uri' => 'Identifies the S3 path where you want SageMaker to store checkpoints. For example, s3://bucket-name/key-name-prefix.
The S3 URI of the file, referred to as a label category configuration file, that defines the categories used to label the data objects.
For 3D point cloud and video frame task types, you can add label category attributes and frame attributes to your label category configuration file. To learn how, see Create a Labeling Category Configuration File for 3D Point Cloud Labeling Jobs.
For named entity recognition jobs, in addition to "labels", you must provide worker instructions in the label category configuration file using the "instructions" parameter: "instructions": {"shortInstruction":"<h1>Add header</h1><p>Add Instructions</p>", "fullInstruction":"<p>Add additional instructions.</p>"}. For details and an example, see Create a Named Entity Recognition Labeling Job (API) .
For all other built-in task types and custom tasks, your label category configuration file must be a JSON file in the following format. Identify the labels you want to use by replacing label_1, label_2,...,label_n with your label categories.
{
"document-version": "2018-11-28",
"labels": [{"label": "label_1"},{"label": "label_2"},...{"label": "label_n"}]
}
Note the following about the label category configuration file:
For image classification and text classification (single and multi-label) you must specify at least two label categories. For all other task types, the minimum number of label categories required is one.
Each label category must be unique, you cannot specify duplicate label categories.
If you create a 3D point cloud or video frame adjustment or verification labeling job, you must include auditLabelAttributeName in the label category configuration. Use this parameter to enter the LabelAttributeName of the labeling job you want to adjust or verify annotations of.
The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix). This archive can hold multiple files that are all equally used in the load test. Each file in the archive must satisfy the size constraints of the InvokeEndpoint call.
', 'DataQualityAppSpecification$RecordPreprocessorSourceUri' => 'An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flattened JSON so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers.
', 'DataQualityAppSpecification$PostAnalyticsProcessorSourceUri' => 'An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
', 'DebugHookConfig$S3OutputPath' => 'Path to Amazon S3 storage location for metrics and tensors.
', 'DebugRuleConfiguration$S3OutputPath' => 'Path to Amazon S3 storage location for rules.
', 'DescribeEdgePackagingJobResponse$ModelArtifact' => 'The Amazon Simple Storage (S3) URI where model artifacts ares stored.
', 'DescribeLabelingJobResponse$LabelCategoryConfigS3Uri' => 'The S3 location of the JSON file that defines the categories used to label data objects. Please note the following label-category limits:
Semantic segmentation labeling jobs using automated labeling: 20 labels
Box bounding labeling jobs (all): 10 labels
The file is a JSON structure in the following format:
{
"document-version": "2018-11-28"
"labels": [
{
"label": "label 1"
},
{
"label": "label 2"
},
...
{
"label": "label n"
}
]
}
The Amazon Simple Storage (S3) bucker URI.
', 'FileSource$S3Uri' => 'The Amazon S3 URI for the file source.
', 'FlowDefinitionOutputConfig$S3OutputPath' => 'The Amazon S3 path where the object containing human output will be made available.
To learn more about the format of Amazon A2I output data, see Amazon A2I Output Data.
', 'InferenceRecommendationsJob$SamplePayloadUrl' => 'The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
', 'InputConfig$S3Uri' => 'The S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
', 'LabelingJobOutput$OutputDatasetS3Uri' => 'The Amazon S3 bucket location of the manifest file for labeled data.
', 'LabelingJobOutputConfig$S3OutputPath' => 'The Amazon S3 location to write output data.
', 'LabelingJobS3DataSource$ManifestS3Uri' => 'The Amazon S3 location of the manifest file that describes the input data objects.
The input manifest file referenced in ManifestS3Uri must contain one of the following keys: source-ref or source. The value of the keys are interpreted as follows:
source-ref: The source of the object is the Amazon S3 object specified in the value. Use this value when the object is a binary object, such as an image.
source: The source of the object is the value. Use this value when the object is a text value.
If you are a new user of Ground Truth, it is recommended you review Use an Input Manifest File in the Amazon SageMaker Developer Guide to learn how to create an input manifest file.
', 'MetricsSource$S3Uri' => 'The S3 URI for the metrics source.
', 'ModelArtifacts$S3ModelArtifacts' => 'The path of the S3 object that contains the model artifacts. For example, s3://bucket-name/keynameprefix/model.tar.gz.
JSON formatted S3 file that defines bias parameters. For more information on this JSON configuration file, see Configure bias parameters.
', 'ModelCardExportArtifacts$S3ExportArtifacts' => 'The Amazon S3 URI of the exported model artifacts.
', 'ModelCardExportOutputConfig$S3OutputPath' => 'The Amazon S3 output path to export your model card PDF.
', 'ModelExplainabilityAppSpecification$ConfigUri' => 'JSON formatted Amazon S3 file that defines explainability parameters. For more information on this JSON configuration file, see Configure model explainability parameters.
', 'ModelQualityAppSpecification$RecordPreprocessorSourceUri' => 'An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flattened JSON so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers.
', 'ModelQualityAppSpecification$PostAnalyticsProcessorSourceUri' => 'An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
', 'MonitoringAppSpecification$RecordPreprocessorSourceUri' => 'An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flattened JSON so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers.
', 'MonitoringAppSpecification$PostAnalyticsProcessorSourceUri' => 'An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
', 'MonitoringConstraintsResource$S3Uri' => 'The Amazon S3 URI for the constraints resource.
', 'MonitoringStatisticsResource$S3Uri' => 'The Amazon S3 URI for the statistics resource.
', 'OutputConfig$S3OutputLocation' => 'Identifies the S3 bucket where you want Amazon SageMaker to store the model artifacts. For example, s3://bucket-name/key-name-prefix.
Identifies the S3 path where you want SageMaker to store the model artifacts. For example, s3://bucket-name/key-name-prefix.
The URI of the Amazon S3 prefix Amazon SageMaker downloads data required to run a processing job.
', 'ProcessingS3Output$S3Uri' => 'A URI that identifies the Amazon S3 bucket where you want Amazon SageMaker to save the results of a processing job.
', 'ProfilerConfig$S3OutputPath' => 'Path to Amazon S3 storage location for system and framework metrics.
', 'ProfilerConfigForUpdate$S3OutputPath' => 'Path to Amazon S3 storage location for system and framework metrics.
', 'ProfilerRuleConfiguration$S3OutputPath' => 'Path to Amazon S3 storage location for rules.
', 'RecommendationJobCompiledOutputConfig$S3OutputUri' => 'Identifies the Amazon S3 bucket where you want SageMaker to store the compiled model artifacts.
', 'RedshiftDatasetDefinition$OutputS3Uri' => 'The location in Amazon S3 where the Redshift query results are stored.
', 'S3DataSource$S3Uri' => 'Depending on the value specified for the S3DataType, identifies either a key name prefix or a manifest. For example:
A key name prefix might look like this: s3://bucketname/exampleprefix
A manifest might look like this: s3://bucketname/example.manifest
A manifest is an S3 object which is a JSON file consisting of an array of elements. The first element is a prefix which is followed by one or more suffixes. SageMaker appends the suffix elements to the prefix to get a full set of S3Uri. Note that the prefix must be a valid non-empty S3Uri that precludes users from specifying a manifest whose individual S3Uri is sourced from different S3 buckets.
The following code example shows a valid manifest format:
[ {"prefix": "s3://customer_bucket/some/prefix/"},
"relative/path/to/custdata-1",
"relative/path/custdata-2",
...
"relative/path/custdata-N"
]
This JSON is equivalent to the following S3Uri list:
s3://customer_bucket/some/prefix/relative/path/to/custdata-1
s3://customer_bucket/some/prefix/relative/path/custdata-2
...
s3://customer_bucket/some/prefix/relative/path/custdata-N
The complete set of S3Uri in this manifest is the input data for the channel for this data source. The object that each S3Uri points to must be readable by the IAM role that SageMaker uses to perform tasks on your behalf.
Your input bucket must be located in same Amazon Web Services region as your training job.
', 'S3StorageConfig$S3Uri' => 'The S3 URI, or location in Amazon S3, of OfflineStore.
S3 URIs have a format similar to the following: s3://example-bucket/prefix/.
The S3 path where offline records are written.
', 'SharingSettings$S3OutputPath' => 'When NotebookOutputOption is Allowed, the Amazon S3 bucket used to store the shared notebook snapshots.
A URL to the Amazon S3 data source containing selected features from the input data source to run an Autopilot job V2. You can input FeatureAttributeNames (optional) in JSON format as shown below:
{ "FeatureAttributeNames":["col1", "col2", ...] }.
You can also specify the data type of the feature (optional) in the format shown below:
{ "FeatureDataTypes":{"col1":"numeric", "col2":"categorical" ... } }
These column keys may not include the target column.
In ensembling mode, Autopilot only supports the following data types: numeric, categorical, text, and datetime. In HPO mode, Autopilot can support numeric, categorical, text, datetime, and sequence.
If only FeatureDataTypes is provided, the column keys (col1, col2,..) should be a subset of the column names in the input data.
If both FeatureDataTypes and FeatureAttributeNames are provided, then the column keys should be a subset of the column names provided in FeatureAttributeNames.
The key name FeatureAttributeNames is fixed. The values listed in ["col1", "col2", ...] are case sensitive and should be a list of strings containing unique values that are a subset of the column names in the input data. The list of columns provided must not include the target column.
Path to Amazon S3 storage location for TensorBoard output.
', 'TimeSeriesForecastingJobConfig$FeatureSpecificationS3Uri' => 'A URL to the Amazon S3 data source containing additional selected features that complement the target, itemID, timestamp, and grouped columns set in TimeSeriesConfig. When not provided, the AutoML job V2 includes all the columns from the original dataset that are not already declared in TimeSeriesConfig. If provided, the AutoML job V2 only considers these additional columns as a complement to the ones declared in TimeSeriesConfig.
You can input FeatureAttributeNames (optional) in JSON format as shown below:
{ "FeatureAttributeNames":["col1", "col2", ...] }.
You can also specify the data type of the feature (optional) in the format shown below:
{ "FeatureDataTypes":{"col1":"numeric", "col2":"categorical" ... } }
Autopilot supports the following data types: numeric, categorical, text, and datetime.
These column keys must not include any column set in TimeSeriesConfig.
The Amazon S3 path where you want Amazon SageMaker to store the results of the transform job. For example, s3://bucket-name/key-name-prefix.
For every S3 object used as input for the transform job, batch transform stores the transformed data with an .out suffix in a corresponding subfolder in the location in the output prefix. For example, for the input data stored at s3://bucket-name/input-name-prefix/dataset01/data.csv, batch transform stores the transformed data at s3://bucket-name/output-name-prefix/input-name-prefix/data.csv.out. Batch transform doesn\'t upload partially processed objects. For an input S3 object that contains multiple records, it creates an .out file only if the transform job succeeds on the entire file. When the input contains multiple S3 objects, the batch transform job processes the listed S3 objects and uploads only the output for successfully processed objects. If any object fails in the transform job batch transform marks the job as failed to prompt investigation.
Depending on the value specified for the S3DataType, identifies either a key name prefix or a manifest. For example:
A key name prefix might look like this: s3://bucketname/exampleprefix.
A manifest might look like this: s3://bucketname/example.manifest
The manifest is an S3 object which is a JSON file with the following format:
[ {"prefix": "s3://customer_bucket/some/prefix/"},
"relative/path/to/custdata-1",
"relative/path/custdata-2",
...
"relative/path/custdata-N"
]
The preceding JSON matches the following S3Uris:
s3://customer_bucket/some/prefix/relative/path/to/custdata-1
s3://customer_bucket/some/prefix/relative/path/custdata-2
...
s3://customer_bucket/some/prefix/relative/path/custdata-N
The complete set of S3Uris in this manifest constitutes the input data for the channel for this datasource. The object that each S3Uris points to must be readable by the IAM role that Amazon SageMaker uses to perform tasks on your behalf.
The Amazon S3 bucket location of the UI template, or worker task template. This is the template used to render the worker UI and tools for labeling job tasks. For more information about the contents of a UI template, see Creating Your Custom Labeling Task Template.
', 'WorkspaceSettings$S3ArtifactPath' => 'The Amazon S3 bucket used to store artifacts generated by Canvas. Updating the Amazon S3 location impacts existing configuration settings, and Canvas users no longer have access to their artifacts. Canvas users must log out and log back in to apply the new location.
', ], ], 'SageMakerImageVersionAlias' => [ 'base' => NULL, 'refs' => [ 'DeleteImageVersionRequest$Alias' => 'The alias of the image to delete.
', 'DescribeImageVersionRequest$Alias' => 'The alias of the image version.
', 'ListAliasesRequest$Alias' => 'The alias of the image version.
', 'SageMakerImageVersionAliases$member' => NULL, 'UpdateImageVersionRequest$Alias' => 'The alias of the image version.
', ], ], 'SageMakerImageVersionAliases' => [ 'base' => NULL, 'refs' => [ 'CreateImageVersionRequest$Aliases' => 'A list of aliases created with the image version.
', 'ListAliasesResponse$SageMakerImageVersionAliases' => 'A list of SageMaker image version aliases.
', 'UpdateImageVersionRequest$AliasesToAdd' => 'A list of aliases to add.
', 'UpdateImageVersionRequest$AliasesToDelete' => 'A list of aliases to delete.
', ], ], 'SagemakerServicecatalogStatus' => [ 'base' => NULL, 'refs' => [ 'GetSagemakerServicecatalogPortfolioStatusOutput$Status' => 'Whether Service Catalog is enabled or disabled in SageMaker.
', ], ], 'SampleWeightAttributeName' => [ 'base' => NULL, 'refs' => [ 'AutoMLChannel$SampleWeightAttributeName' => 'If specified, this column name indicates which column of the dataset should be treated as sample weights for use by the objective metric during the training, evaluation, and the selection of the best model. This column is not considered as a predictive feature. For more information on Autopilot metrics, see Metrics and validation.
Sample weights should be numeric, non-negative, with larger values indicating which rows are more important than others. Data points that have invalid or no weight value are excluded.
Support for sample weights is available in Ensembling mode only.
', 'TabularJobConfig$SampleWeightAttributeName' => 'If specified, this column name indicates which column of the dataset should be treated as sample weights for use by the objective metric during the training, evaluation, and the selection of the best model. This column is not considered as a predictive feature. For more information on Autopilot metrics, see Metrics and validation.
Sample weights should be numeric, non-negative, with larger values indicating which rows are more important than others. Data points that have invalid or no weight value are excluded.
Support for sample weights is available in Ensembling mode only.
', ], ], 'SamplingPercentage' => [ 'base' => NULL, 'refs' => [ 'DataCaptureConfig$InitialSamplingPercentage' => 'The percentage of requests SageMaker will capture. A lower value is recommended for Endpoints with high traffic.
', 'DataCaptureConfigSummary$CurrentSamplingPercentage' => 'The percentage of requests being captured by your Endpoint.
', ], ], 'ScalingPolicies' => [ 'base' => NULL, 'refs' => [ 'DynamicScalingConfiguration$ScalingPolicies' => 'An object of the scaling policies for each metric.
', ], ], 'ScalingPolicy' => [ 'base' => 'An object containing a recommended scaling policy.
', 'refs' => [ 'ScalingPolicies$member' => NULL, ], ], 'ScalingPolicyMetric' => [ 'base' => 'The metric for a scaling policy.
', 'refs' => [ 'GetScalingConfigurationRecommendationResponse$Metric' => 'An object with a list of metrics that were benchmarked during the previously completed Inference Recommender job.
', ], ], 'ScalingPolicyObjective' => [ 'base' => 'An object where you specify the anticipated traffic pattern for an endpoint.
', 'refs' => [ 'GetScalingConfigurationRecommendationRequest$ScalingPolicyObjective' => 'An object where you specify the anticipated traffic pattern for an endpoint.
', 'GetScalingConfigurationRecommendationResponse$ScalingPolicyObjective' => 'An object representing the anticipated traffic pattern for an endpoint that you specified in the request.
', ], ], 'ScheduleConfig' => [ 'base' => 'Configuration details about the monitoring schedule.
', 'refs' => [ 'MonitoringScheduleConfig$ScheduleConfig' => 'Configures the monitoring schedule.
', ], ], 'ScheduleExpression' => [ 'base' => NULL, 'refs' => [ 'ScheduleConfig$ScheduleExpression' => 'A cron expression that describes details about the monitoring schedule.
The supported cron expressions are:
If you want to set the job to start every hour, use the following:
Hourly: cron(0 * ? * * *)
If you want to start the job daily:
cron(0 [00-23] ? * * *)
If you want to run the job one time, immediately, use the following keyword:
NOW
For example, the following are valid cron expressions:
Daily at noon UTC: cron(0 12 ? * * *)
Daily at midnight UTC: cron(0 0 ? * * *)
To support running every 6, 12 hours, the following are also supported:
cron(0 [00-23]/[01-24] ? * * *)
For example, the following are valid cron expressions:
Every 12 hours, starting at 5pm UTC: cron(0 17/12 ? * * *)
Every two hours starting at midnight: cron(0 0/2 ? * * *)
Even though the cron expression is set to start at 5PM UTC, note that there could be a delay of 0-20 minutes from the actual requested time to run the execution.
We recommend that if you would like a daily schedule, you do not provide this parameter. Amazon SageMaker will pick a time for running every day.
You can also specify the keyword NOW to run the monitoring job immediately, one time, without recurring.
The status of an monitoring job.
', 'ListMonitoringSchedulesRequest$StatusEquals' => 'A filter that returns only monitoring schedules modified before a specified time.
', 'ModelDashboardMonitoringSchedule$MonitoringScheduleStatus' => 'The status of the monitoring schedule.
', 'MonitoringSchedule$MonitoringScheduleStatus' => 'The status of the monitoring schedule. This can be one of the following values.
PENDING - The schedule is pending being created.
FAILED - The schedule failed.
SCHEDULED - The schedule was successfully created.
STOPPED - The schedule was stopped.
The status of the monitoring schedule.
', ], ], 'SearchExpression' => [ 'base' => 'A multi-expression that searches for the specified resource or resources in a search. All resource objects that satisfy the expression\'s condition are included in the search results. You must specify at least one subexpression, filter, or nested filter. A SearchExpression can contain up to twenty elements.
A SearchExpression contains the following components:
A list of Filter objects. Each filter defines a simple Boolean expression comprised of a resource property name, Boolean operator, and value.
A list of NestedFilter objects. Each nested filter defines a list of Boolean expressions using a list of resource properties. A nested filter is satisfied if a single object in the list satisfies all Boolean expressions.
A list of SearchExpression objects. A search expression object can be nested in a list of search expression objects.
A Boolean operator: And or Or.
A Boolean conditional statement. Resources must satisfy this condition to be included in search results. You must provide at least one subexpression, filter, or nested filter. The maximum number of recursive SubExpressions, NestedFilters, and Filters that can be included in a SearchExpression object is 50.
A list of search expression objects.
', ], ], 'SearchRecord' => [ 'base' => 'A single resource returned as part of the Search API response.
', 'refs' => [ 'SearchResultsList$member' => NULL, ], ], 'SearchRequest' => [ 'base' => NULL, 'refs' => [], ], 'SearchResponse' => [ 'base' => NULL, 'refs' => [], ], 'SearchResultsList' => [ 'base' => NULL, 'refs' => [ 'SearchResponse$Results' => 'A list of SearchRecord objects.
How SearchResults are ordered. Valid values are Ascending or Descending. The default is Descending.
Provides detailed information about the state of the training job. For detailed information on the secondary status of the training job, see StatusMessage under SecondaryStatusTransition.
SageMaker provides primary statuses and secondary statuses that apply to each of them:
Starting - Starting the training job.
Downloading - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.
Training - Training is in progress.
Interrupted - The job stopped because the managed spot training instances were interrupted.
Uploading - Training is complete and the model artifacts are being uploaded to the S3 location.
Completed - The training job has completed.
Failed - The training job has failed. The reason for the failure is returned in the FailureReason field of DescribeTrainingJobResponse.
MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.
MaxWaitTimeExceeded - The job stopped because it exceeded the maximum allowed wait time.
Stopped - The training job has stopped.
Stopping - Stopping the training job.
Valid values for SecondaryStatus are subject to change.
We no longer support the following secondary statuses:
LaunchingMLInstances
PreparingTraining
DownloadingTrainingImage
Contains a secondary status information from a training job.
Status might be one of the following secondary statuses:
Starting - Starting the training job.
Downloading - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.
Training - Training is in progress.
Uploading - Training is complete and the model artifacts are being uploaded to the S3 location.
Completed - The training job has completed.
Failed - The training job has failed. The reason for the failure is returned in the FailureReason field of DescribeTrainingJobResponse.
MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.
Stopped - The training job has stopped.
Stopping - Stopping the training job.
We no longer support the following secondary statuses:
LaunchingMLInstances
PreparingTrainingStack
DownloadingTrainingImage
Provides detailed information about the state of the training job. For detailed information about the secondary status of the training job, see StatusMessage under SecondaryStatusTransition.
SageMaker provides primary statuses and secondary statuses that apply to each of them:
Starting - Starting the training job.
Downloading - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.
Training - Training is in progress.
Uploading - Training is complete and the model artifacts are being uploaded to the S3 location.
Completed - The training job has completed.
Failed - The training job has failed. The reason for the failure is returned in the FailureReason field of DescribeTrainingJobResponse.
MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.
Stopped - The training job has stopped.
Stopping - Stopping the training job.
Valid values for SecondaryStatus are subject to change.
We no longer support the following secondary statuses:
LaunchingMLInstances
PreparingTrainingStack
DownloadingTrainingImage
An array element of SecondaryStatusTransitions for DescribeTrainingJob. It provides additional details about a status that the training job has transitioned through. A training job can be in one of several states, for example, starting, downloading, training, or uploading. Within each state, there are a number of intermediate states. For example, within the starting state, SageMaker could be starting the training job or launching the ML instances. These transitional states are referred to as the job\'s secondary status.
A history of all of the secondary statuses that the training job has transitioned through.
', 'TrainingJob$SecondaryStatusTransitions' => 'A history of all of the secondary statuses that the training job has transitioned through.
', ], ], 'SecretArn' => [ 'base' => NULL, 'refs' => [ 'GitConfig$SecretArn' => 'The Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the git repository. The secret must have a staging label of AWSCURRENT and must be in the following format:
{"username": UserName, "password": Password}
The Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the git repository. The secret must have a staging label of AWSCURRENT and must be in the following format:
{"username": UserName, "password": Password}
The ARN of an Amazon Web Services Secrets Manager secret that stores the credentials from your identity provider, such as the client ID and secret, authorization URL, and token URL.
', ], ], 'SecurityGroupId' => [ 'base' => NULL, 'refs' => [ 'DescribeDomainResponse$SecurityGroupIdForDomainBoundary' => 'The ID of the security group that authorizes traffic between the RSessionGateway apps and the RStudioServerPro app.
The VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be for the same VPC as specified in the subnet.
', 'DefaultSpaceSettings$SecurityGroups' => 'The security group IDs for the Amazon Virtual Private Cloud that the space uses for communication.
', 'DescribeNotebookInstanceOutput$SecurityGroups' => 'The IDs of the VPC security groups.
', 'UserSettings$SecurityGroups' => 'The security groups for the Amazon Virtual Private Cloud (VPC) that Studio uses for communication.
Optional when the CreateDomain.AppNetworkAccessType parameter is set to PublicInternetOnly.
Required when the CreateDomain.AppNetworkAccessType parameter is set to VpcOnly, unless specified as part of the DefaultUserSettings for the domain.
Amazon SageMaker adds a security group to allow NFS traffic from SageMaker Studio. Therefore, the number of security groups that you can specify is one less than the maximum number shown.
', ], ], 'Seed' => [ 'base' => NULL, 'refs' => [ 'ShuffleConfig$Seed' => 'Determines the shuffling order in ShuffleConfig value.
A step selected to run in selective execution mode.
', 'refs' => [ 'SelectedStepList$member' => NULL, ], ], 'SelectedStepList' => [ 'base' => NULL, 'refs' => [ 'SelectiveExecutionConfig$SelectedSteps' => 'A list of pipeline steps to run. All step(s) in all path(s) between two selected steps should be included.
', ], ], 'SelectiveExecutionConfig' => [ 'base' => 'The selective execution configuration applied to the pipeline run.
', 'refs' => [ 'DescribePipelineExecutionResponse$SelectiveExecutionConfig' => 'The selective execution configuration applied to the pipeline run.
', 'PipelineExecution$SelectiveExecutionConfig' => 'The selective execution configuration applied to the pipeline run.
', 'StartPipelineExecutionRequest$SelectiveExecutionConfig' => 'The selective execution configuration applied to the pipeline run.
', ], ], 'SelectiveExecutionResult' => [ 'base' => 'The ARN from an execution of the current pipeline.
', 'refs' => [ 'PipelineExecutionStep$SelectiveExecutionResult' => 'The ARN from an execution of the current pipeline from which results are reused for this step.
', ], ], 'SendPipelineExecutionStepFailureRequest' => [ 'base' => NULL, 'refs' => [], ], 'SendPipelineExecutionStepFailureResponse' => [ 'base' => NULL, 'refs' => [], ], 'SendPipelineExecutionStepSuccessRequest' => [ 'base' => NULL, 'refs' => [], ], 'SendPipelineExecutionStepSuccessResponse' => [ 'base' => NULL, 'refs' => [], ], 'ServerlessMaxConcurrency' => [ 'base' => NULL, 'refs' => [ 'ProductionVariantServerlessConfig$MaxConcurrency' => 'The maximum number of concurrent invocations your serverless endpoint can process.
', 'ProductionVariantServerlessUpdateConfig$MaxConcurrency' => 'The updated maximum number of concurrent invocations your serverless endpoint can process.
', ], ], 'ServerlessMemorySizeInMB' => [ 'base' => NULL, 'refs' => [ 'ProductionVariantServerlessConfig$MemorySizeInMB' => 'The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.
', ], ], 'ServerlessProvisionedConcurrency' => [ 'base' => NULL, 'refs' => [ 'ProductionVariantServerlessConfig$ProvisionedConcurrency' => 'The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency.
This field is not supported for serverless endpoint recommendations for Inference Recommender jobs. For more information about creating an Inference Recommender job, see CreateInferenceRecommendationsJobs.
The updated amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency.
The ID of the provisioned product.
', 'ServiceCatalogProvisioningDetails$ProductId' => 'The ID of the product to provision.
', 'ServiceCatalogProvisioningDetails$ProvisioningArtifactId' => 'The ID of the provisioning artifact.
', 'ServiceCatalogProvisioningDetails$PathId' => 'The path identifier of the product. This value is optional if the product has a default path, and required if the product has more than one path.
', 'ServiceCatalogProvisioningUpdateDetails$ProvisioningArtifactId' => 'The ID of the provisioning artifact.
', ], ], 'ServiceCatalogProvisionedProductDetails' => [ 'base' => 'Details of a provisioned service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog.
', 'refs' => [ 'DescribeProjectOutput$ServiceCatalogProvisionedProductDetails' => 'Information about a provisioned service catalog product.
', 'Project$ServiceCatalogProvisionedProductDetails' => NULL, ], ], 'ServiceCatalogProvisioningDetails' => [ 'base' => 'Details that you specify to provision a service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog.
', 'refs' => [ 'CreateProjectInput$ServiceCatalogProvisioningDetails' => 'The product ID and provisioning artifact ID to provision a service catalog. The provisioning artifact ID will default to the latest provisioning artifact ID of the product, if you don\'t provide the provisioning artifact ID. For more information, see What is Amazon Web Services Service Catalog.
', 'DescribeProjectOutput$ServiceCatalogProvisioningDetails' => 'Information used to provision a service catalog product. For information, see What is Amazon Web Services Service Catalog.
', 'Project$ServiceCatalogProvisioningDetails' => NULL, ], ], 'ServiceCatalogProvisioningUpdateDetails' => [ 'base' => 'Details that you specify to provision a service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog.
', 'refs' => [ 'UpdateProjectInput$ServiceCatalogProvisioningUpdateDetails' => 'The product ID and provisioning artifact ID to provision a service catalog. The provisioning artifact ID will default to the latest provisioning artifact ID of the product, if you don\'t provide the provisioning artifact ID. For more information, see What is Amazon Web Services Service Catalog.
', ], ], 'SessionExpirationDurationInSeconds' => [ 'base' => NULL, 'refs' => [ 'CreatePresignedDomainUrlRequest$SessionExpirationDurationInSeconds' => 'The session expiration duration in seconds. This value defaults to 43200.
', 'CreatePresignedNotebookInstanceUrlInput$SessionExpirationDurationInSeconds' => 'The duration of the session, in seconds. The default is 12 hours.
', ], ], 'ShadowModeConfig' => [ 'base' => ' The configuration of ShadowMode inference experiment type, which specifies a production variant to take all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant it also specifies the percentage of requests that Amazon SageMaker replicates.
The configuration of ShadowMode inference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates.
The configuration of ShadowMode inference experiment type, which shows the production variant that takes all the inference requests, and the shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant it also shows the percentage of requests that Amazon SageMaker replicates.
The configuration of ShadowMode inference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates.
The name and sampling percentage of a shadow variant.
', 'refs' => [ 'ShadowModelVariantConfigList$member' => NULL, ], ], 'ShadowModelVariantConfigList' => [ 'base' => NULL, 'refs' => [ 'ShadowModeConfig$ShadowModelVariants' => 'List of shadow variant configurations.
', ], ], 'SharingSettings' => [ 'base' => 'Specifies options for sharing SageMaker Studio notebooks. These settings are specified as part of DefaultUserSettings when the CreateDomain API is called, and as part of UserSettings when the CreateUserProfile API is called. When SharingSettings is not specified, notebook sharing isn\'t allowed.
Specifies options for sharing SageMaker Studio notebooks.
', ], ], 'ShuffleConfig' => [ 'base' => 'A configuration for a shuffle option for input data in a channel. If you use S3Prefix for S3DataType, the results of the S3 key prefix matches are shuffled. If you use ManifestFile, the order of the S3 object references in the ManifestFile is shuffled. If you use AugmentedManifestFile, the order of the JSON lines in the AugmentedManifestFile is shuffled. The shuffling order is determined using the Seed value.
For Pipe input mode, when ShuffleConfig is specified shuffling is done at the start of every epoch. With large datasets, this ensures that the order of the training data is different for each epoch, and it helps reduce bias and possible overfitting. In a multi-node training job when ShuffleConfig is combined with S3DataDistributionType of ShardedByS3Key, the data is shuffled across nodes so that the content sent to a particular node on the first epoch might be sent to a different node on the second epoch.
A configuration for a shuffle option for input data in a channel. If you use S3Prefix for S3DataType, this shuffles the results of the S3 key prefix matches. If you use ManifestFile, the order of the S3 object references in the ManifestFile is shuffled. If you use AugmentedManifestFile, the order of the JSON lines in the AugmentedManifestFile is shuffled. The shuffling order is determined using the Seed value.
For Pipe input mode, shuffling is done at the start of every epoch. With large datasets this ensures that the order of the training data is different for each epoch, it helps reduce bias and possible overfitting. In a multi-node training job when ShuffleConfig is combined with S3DataDistributionType of ShardedByS3Key, the data is shuffled across nodes so that the content sent to a particular node on the first epoch might be sent to a different node on the second epoch.
The ARN of the application managed by SageMaker in IAM Identity Center. This value is only returned for domains created after September 19, 2023.
', ], ], 'SingleSignOnUserIdentifier' => [ 'base' => NULL, 'refs' => [ 'CreateUserProfileRequest$SingleSignOnUserIdentifier' => 'A specifier for the type of value specified in SingleSignOnUserValue. Currently, the only supported value is "UserName". If the Domain\'s AuthMode is IAM Identity Center, this field is required. If the Domain\'s AuthMode is not IAM Identity Center, this field cannot be specified.
', 'DescribeUserProfileResponse$SingleSignOnUserIdentifier' => 'The IAM Identity Center user identifier.
', ], ], 'SkipModelValidation' => [ 'base' => NULL, 'refs' => [ 'CreateModelPackageInput$SkipModelValidation' => 'Indicates if you want to skip model validation.
', 'DescribeModelPackageOutput$SkipModelValidation' => 'Indicates if you want to skip model validation.
', 'ModelPackage$SkipModelValidation' => 'Indicates if you want to skip model validation.
', ], ], 'SnsTopicArn' => [ 'base' => NULL, 'refs' => [ 'AsyncInferenceNotificationConfig$SuccessTopic' => 'Amazon SNS topic to post a notification to when inference completes successfully. If no topic is provided, no notification is sent on success.
', 'AsyncInferenceNotificationConfig$ErrorTopic' => 'Amazon SNS topic to post a notification to when inference fails. If no topic is provided, no notification is sent on failure.
', 'LabelingJobOutputConfig$SnsTopicArn' => 'An Amazon Simple Notification Service (Amazon SNS) output topic ARN. Provide a SnsTopicArn if you want to do real time chaining to another streaming job and receive an Amazon SNS notifications each time a data object is submitted by a worker.
If you provide an SnsTopicArn in OutputConfig, when workers complete labeling tasks, Ground Truth will send labeling task output data to the SNS output topic you specify here.
To learn more, see Receive Output Data from a Streaming Labeling Job.
', 'LabelingJobSnsDataSource$SnsTopicArn' => 'The Amazon SNS input topic Amazon Resource Name (ARN). Specify the ARN of the input topic you will use to send new data objects to a streaming labeling job.
', ], ], 'SortActionsBy' => [ 'base' => NULL, 'refs' => [ 'ListActionsRequest$SortBy' => 'The property used to sort results. The default value is CreationTime.
The property used to sort results. The default value is CreationTime.
The property used to sort results. The default value is CreationTime.
The field to sort results by. The default is CreationTime.
The field to sort results by. The default is CreationTime.
The field to sort results by. The default is CreationTime.
The field to sort results by. The default is CreationTime.
The property used to sort results. The default value is CreationTime.
The property used to sort results. The default value is CreationTime.
The column by which to sort the listed inference experiments.
', ], ], 'SortLineageGroupsBy' => [ 'base' => NULL, 'refs' => [ 'ListLineageGroupsRequest$SortBy' => 'The parameter by which to sort the results. The default is CreationTime.
The sort order. The default value is Descending.
The sort order for the results. The default is Ascending.
The sort order. The default value is Descending.
The sort order for the results. The default is Ascending.
', 'ListArtifactsRequest$SortOrder' => 'The sort order. The default value is Descending.
The sort order. The default value is Descending.
The sort order for results. The default is Ascending.
The sort order. The default value is Descending.
Whether to sort the results in Ascending or Descending order. The default is Descending.
What direction to sort in.
', 'ListEdgeDeploymentPlansRequest$SortOrder' => 'The direction of the sorting (ascending or descending).
', 'ListEdgePackagingJobsRequest$SortOrder' => 'What direction to sort by.
', 'ListExperimentsRequest$SortOrder' => 'The sort order. The default value is Descending.
An optional value that specifies whether you want the results sorted in Ascending or Descending order.
Sort hub content versions by ascending or descending order.
', 'ListHubContentsRequest$SortOrder' => 'Sort hubs by ascending or descending order.
', 'ListHubsRequest$SortOrder' => 'Sort hubs by ascending or descending order.
', 'ListHumanTaskUisRequest$SortOrder' => 'An optional value that specifies whether you want the results sorted in Ascending or Descending order.
The sort order for results. The default is Ascending.
The direction of sorting (ascending or descending).
', 'ListInferenceRecommendationsJobsRequest$SortOrder' => 'The sort order for the results.
', 'ListLabelingJobsForWorkteamRequest$SortOrder' => 'The sort order for results. The default is Ascending.
The sort order for results. The default is Ascending.
The sort order for the results. The default is Ascending.
Whether to sort the results in Ascending or Descending order. The default is Descending.
Whether to sort the results in Ascending or Descending order. The default is Descending.
The sort order for results. The default is Ascending.
The sort order for the results. The default is Ascending.
Whether to sort the results in Ascending or Descending order. The default is Descending.
The sort order, whether Ascending or Descending, of the alert history. The default is Descending.
Whether to sort the results in Ascending or Descending order. The default is Descending.
Whether to sort the results in Ascending or Descending order. The default is Descending.
The field by which to sort results. The default is CreatedTime.
The sort order for results.
', 'ListPipelinesRequest$SortOrder' => 'The sort order for results.
', 'ListProcessingJobsRequest$SortOrder' => 'The sort order for results. The default is Ascending.
The sort order for the results. The default is Ascending.
The sort order. The default value is Descending.
', 'ListTrainingJobsForHyperParameterTuningJobRequest$SortOrder' => 'The sort order for results. The default is Ascending.
The sort order for results. The default is Ascending.
The sort order for results. The default is Descending.
The sort order. The default value is Descending.
The sort order. The default value is Descending.
The sort order for the results. The default is Ascending.
', 'ListWorkforcesRequest$SortOrder' => 'Sort workforces in ascending or descending order.
', 'ListWorkteamsRequest$SortOrder' => 'The sort order for results. The default is Ascending.
The field by which to sort results. The default is CreatedTime.
The field by which to sort results. The default is CreatedTime.
The property used to sort results. The default value is CreationTime.
The property used to sort results. The default value is CreationTime.
Specifies an algorithm that was used to create the model package. The algorithm must be either an algorithm resource in your SageMaker account or an algorithm in Amazon Web Services Marketplace that you are subscribed to.
', 'refs' => [ 'SourceAlgorithmList$member' => NULL, ], ], 'SourceAlgorithmList' => [ 'base' => NULL, 'refs' => [ 'SourceAlgorithmSpecification$SourceAlgorithms' => 'A list of the algorithms that were used to create a model package.
', ], ], 'SourceAlgorithmSpecification' => [ 'base' => 'A list of algorithms that were used to create a model package.
', 'refs' => [ 'CreateModelPackageInput$SourceAlgorithmSpecification' => 'Details about the algorithm that was used to create the model package.
', 'DescribeModelPackageOutput$SourceAlgorithmSpecification' => 'Details about the algorithm that was used to create the model package.
', 'ModelPackage$SourceAlgorithmSpecification' => 'A list of algorithms that were used to create a model package.
', ], ], 'SourceIpConfig' => [ 'base' => 'A list of IP address ranges (CIDRs). Used to create an allow list of IP addresses for a private workforce. Workers will only be able to login to their worker portal from an IP address within this range. By default, a workforce isn\'t restricted to specific IP addresses.
', 'refs' => [ 'CreateWorkforceRequest$SourceIpConfig' => NULL, 'UpdateWorkforceRequest$SourceIpConfig' => 'A list of one to ten worker IP address ranges (CIDRs) that can be used to access tasks assigned to this workforce.
Maximum: Ten CIDR values
', 'Workforce$SourceIpConfig' => 'A list of one to ten IP address ranges (CIDRs) to be added to the workforce allow list. By default, a workforce isn\'t restricted to specific IP addresses.
', ], ], 'SourceType' => [ 'base' => NULL, 'refs' => [ 'ExperimentSource$SourceType' => 'The source type.
', 'TrialComponentSource$SourceType' => 'The source job type.
', 'TrialSource$SourceType' => 'The source job type.
', ], ], 'SourceUri' => [ 'base' => NULL, 'refs' => [ 'ListActionsRequest$SourceUri' => 'A filter that returns only actions with the specified source URI.
', 'ListArtifactsRequest$SourceUri' => 'A filter that returns only artifacts with the specified source URI.
', 'ListContextsRequest$SourceUri' => 'A filter that returns only contexts with the specified source URI.
', ], ], 'SpaceArn' => [ 'base' => NULL, 'refs' => [ 'CreateSpaceResponse$SpaceArn' => 'The space\'s Amazon Resource Name (ARN).
', 'DescribeSpaceResponse$SpaceArn' => 'The space\'s Amazon Resource Name (ARN).
', 'UpdateSpaceResponse$SpaceArn' => 'The space\'s Amazon Resource Name (ARN).
', ], ], 'SpaceDetails' => [ 'base' => 'The space\'s details.
', 'refs' => [ 'SpaceList$member' => NULL, ], ], 'SpaceList' => [ 'base' => NULL, 'refs' => [ 'ListSpacesResponse$Spaces' => 'The list of spaces.
', ], ], 'SpaceName' => [ 'base' => NULL, 'refs' => [ 'AppDetails$SpaceName' => 'The name of the space.
', 'CreateAppRequest$SpaceName' => 'The name of the space. If this value is not set, then UserProfileName must be set.
The name of the space.
', 'CreateSpaceRequest$SpaceName' => 'The name of the space.
', 'DeleteAppRequest$SpaceName' => 'The name of the space. If this value is not set, then UserProfileName must be set.
The name of the space.
', 'DescribeAppRequest$SpaceName' => 'The name of the space.
', 'DescribeAppResponse$SpaceName' => 'The name of the space. If this value is not set, then UserProfileName must be set.
The name of the space.
', 'DescribeSpaceResponse$SpaceName' => 'The name of the space.
', 'ListAppsRequest$SpaceNameEquals' => 'A parameter to search by space name. If UserProfileNameEquals is set, then this value cannot be set.
A parameter by which to filter the results.
', 'SpaceDetails$SpaceName' => 'The name of the space.
', 'UpdateSpaceRequest$SpaceName' => 'The name of the space.
', ], ], 'SpaceSettings' => [ 'base' => 'A collection of space settings.
', 'refs' => [ 'CreateSpaceRequest$SpaceSettings' => 'A collection of space settings.
', 'DescribeSpaceResponse$SpaceSettings' => 'A collection of space settings.
', 'UpdateSpaceRequest$SpaceSettings' => 'A collection of space settings.
', ], ], 'SpaceSortKey' => [ 'base' => NULL, 'refs' => [ 'ListSpacesRequest$SortBy' => 'The parameter by which to sort the results. The default is CreationTime.
The status.
', 'SpaceDetails$Status' => 'The status.
', ], ], 'SpawnRate' => [ 'base' => NULL, 'refs' => [ 'Phase$SpawnRate' => 'Specified how many new users to spawn in a minute.
', ], ], 'SplitType' => [ 'base' => NULL, 'refs' => [ 'TransformInput$SplitType' => 'The method to use to split the transform job\'s data files into smaller batches. Splitting is necessary when the total size of each object is too large to fit in a single request. You can also use data splitting to improve performance by processing multiple concurrent mini-batches. The default value for SplitType is None, which indicates that input data files are not split, and request payloads contain the entire contents of an input object. Set the value of this parameter to Line to split records on a newline character boundary. SplitType also supports a number of record-oriented binary data formats. Currently, the supported record formats are:
RecordIO
TFRecord
When splitting is enabled, the size of a mini-batch depends on the values of the BatchStrategy and MaxPayloadInMB parameters. When the value of BatchStrategy is MultiRecord, Amazon SageMaker sends the maximum number of records in each request, up to the MaxPayloadInMB limit. If the value of BatchStrategy is SingleRecord, Amazon SageMaker sends individual records in each request.
Some data formats represent a record as a binary payload wrapped with extra padding bytes. When splitting is applied to a binary data format, padding is removed if the value of BatchStrategy is set to SingleRecord. Padding is not removed if the value of BatchStrategy is set to MultiRecord.
For more information about RecordIO, see Create a Dataset Using RecordIO in the MXNet documentation. For more information about TFRecord, see Consuming TFRecord data in the TensorFlow documentation.
The general status of the current stage.
', ], ], 'Stairs' => [ 'base' => 'Defines the stairs traffic pattern for an Inference Recommender load test. This pattern type consists of multiple steps where the number of users increases at each step.
Specify either the stairs or phases traffic pattern.
', 'refs' => [ 'TrafficPattern$Stairs' => 'Defines the stairs traffic pattern.
', ], ], 'StartEdgeDeploymentStageRequest' => [ 'base' => NULL, 'refs' => [], ], 'StartInferenceExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'StartInferenceExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'StartMonitoringScheduleRequest' => [ 'base' => NULL, 'refs' => [], ], 'StartNotebookInstanceInput' => [ 'base' => NULL, 'refs' => [], ], 'StartPipelineExecutionRequest' => [ 'base' => NULL, 'refs' => [], ], 'StartPipelineExecutionResponse' => [ 'base' => NULL, 'refs' => [], ], 'Statistic' => [ 'base' => NULL, 'refs' => [ 'CustomizedMetricSpecification$Statistic' => 'The statistic of the customized metric.
', ], ], 'StatusDetails' => [ 'base' => NULL, 'refs' => [ 'DebugRuleEvaluationStatus$StatusDetails' => 'Details from the rule evaluation.
', 'ProfilerRuleEvaluationStatus$StatusDetails' => 'Details from the rule evaluation.
', ], ], 'StatusMessage' => [ 'base' => NULL, 'refs' => [ 'SecondaryStatusTransition$StatusMessage' => 'A detailed description of the progress within a secondary status.
SageMaker provides secondary statuses and status messages that apply to each of them:
Starting the training job.
Launching requested ML instances.
Insufficient capacity error from EC2 while launching instances, retrying!
Launched instance was unhealthy, replacing it!
Preparing the instances for training.
Downloading the training image.
Training image download completed. Training in progress.
Status messages are subject to change. Therefore, we recommend not including them in code that programmatically initiates actions. For examples, don\'t use status messages in if statements.
To have an overview of your training job\'s progress, view TrainingJobStatus and SecondaryStatus in DescribeTrainingJob, and StatusMessage together. For example, at the start of a training job, you might see the following:
TrainingJobStatus - InProgress
SecondaryStatus - Training
StatusMessage - Downloading the training image
The description of the step.
', ], ], 'StepDisplayName' => [ 'base' => NULL, 'refs' => [ 'PipelineExecutionStep$StepDisplayName' => 'The display name of the step.
', ], ], 'StepName' => [ 'base' => NULL, 'refs' => [ 'PipelineExecutionStep$StepName' => 'The name of the step that is executed.
', ], ], 'StepStatus' => [ 'base' => NULL, 'refs' => [ 'PipelineExecutionStep$StepStatus' => 'The status of the step execution.
', ], ], 'StopAutoMLJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopCompilationJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopEdgeDeploymentStageRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopEdgePackagingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopHyperParameterTuningJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopInferenceExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopInferenceExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'StopInferenceRecommendationsJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopLabelingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopMonitoringScheduleRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopNotebookInstanceInput' => [ 'base' => NULL, 'refs' => [], ], 'StopPipelineExecutionRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopPipelineExecutionResponse' => [ 'base' => NULL, 'refs' => [], ], 'StopProcessingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopTrainingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StopTransformJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'StoppingCondition' => [ 'base' => 'Specifies a limit to how long a model training job or model compilation job can run. It also specifies how long a managed spot training job has to complete. When the job reaches the time limit, SageMaker ends the training or compilation job. Use this API to cap model training costs.
To stop a training job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
The training algorithms provided by SageMaker automatically save the intermediate results of a model training job when possible. This attempt to save artifacts is only a best effort case as model might not be in a state from which it can be saved. For example, if training has just started, the model might not be ready to save. When saved, this intermediate data is a valid model artifact. You can use it to create a model with CreateModel.
The Neural Topic Model (NTM) currently does not support saving intermediate model artifacts. When training NTMs, make sure that the maximum runtime is sufficient for the training job to complete.
Specifies a limit to how long a model compilation job can run. When the job reaches the time limit, Amazon SageMaker ends the compilation job. Use this API to cap model training costs.
', 'CreateTrainingJobRequest$StoppingCondition' => 'Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
Specifies a limit to how long a model compilation job can run. When the job reaches the time limit, Amazon SageMaker ends the compilation job. Use this API to cap model training costs.
', 'DescribeTrainingJobResponse$StoppingCondition' => 'Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
Specifies a limit to how long a model hyperparameter training job can run. It also specifies how long a managed spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
', 'TrainingJob$StoppingCondition' => 'Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts.
', ], ], 'StorageType' => [ 'base' => NULL, 'refs' => [ 'OnlineStoreConfig$StorageType' => 'Option for different tiers of low latency storage for real-time data retrieval.
Standard: A managed low latency data store for feature groups.
InMemory: A managed data store for feature groups that supports very low latency retrieval.
if the overall status is Failed, the reason for the failure.
The attributes of the input data that are the input features.
', 'BatchTransformInput$InferenceAttribute' => 'The attribute of the input data that represents the ground truth label.
', 'BatchTransformInput$ProbabilityAttribute' => 'In a classification problem, the attribute that represents the class probability.
', 'CreateModelPackageInput$Domain' => 'The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.
', 'CreateModelPackageInput$Task' => 'The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification. The following tasks are supported by Inference Recommender: "IMAGE_CLASSIFICATION" | "OBJECT_DETECTION" | "TEXT_GENERATION" |"IMAGE_SEGMENTATION" | "FILL_MASK" | "CLASSIFICATION" | "REGRESSION" | "OTHER".
Specify "OTHER" if none of the tasks listed fit your use case.
', 'CustomizedMetricSpecification$MetricName' => 'The name of the customized metric.
', 'CustomizedMetricSpecification$Namespace' => 'The namespace of the customized metric.
', 'DescribeEdgePackagingJobResponse$EdgePackagingJobStatusMessage' => 'Returns a message describing the job status and error messages.
', 'DescribeEdgePackagingJobResponse$ModelSignature' => 'The signature document of files in the model artifact.
', 'DescribeModelPackageOutput$Domain' => 'The machine learning domain of the model package you specified. Common machine learning domains include computer vision and natural language processing.
', 'DescribeModelPackageOutput$Task' => 'The machine learning task you specified that your model package accomplishes. Common machine learning tasks include object detection and image classification.
', 'DescribeModelPackageOutput$SamplePayloadUrl' => 'The Amazon Simple Storage Service (Amazon S3) path where the sample payload are stored. This path points to a single gzip compressed tar archive (.tar.gz suffix).
', 'DeviceDeploymentSummary$DeviceDeploymentStatusMessage' => 'The detailed error message for the deployoment status result.
', 'EdgeDeploymentStatus$EdgeDeploymentStatusMessage' => 'A detailed message about deployment status in current stage.
', 'EdgeOutputConfig$PresetDeploymentConfig' => 'The configuration used to create deployment artifacts. Specify configuration options with a JSON string. The available configuration options for each type are:
ComponentName (optional) - Name of the GreenGrass V2 component. If not specified, the default name generated consists of "SagemakerEdgeManager" and the name of your SageMaker Edge Manager packaging job.
ComponentDescription (optional) - Description of the component.
ComponentVersion (optional) - The version of the component.
Amazon Web Services IoT Greengrass uses semantic versions for components. Semantic versions follow a major.minor.patch number system. For example, version 1.0.0 represents the first major release for a component. For more information, see the semantic version specification.
PlatformOS (optional) - The name of the operating system for the platform. Supported platforms include Windows and Linux.
PlatformArchitecture (optional) - The processor architecture for the platform.
Supported architectures Windows include: Windows32_x86, Windows64_x64.
Supported architectures for Linux include: Linux x86_64, Linux ARMV8.
Returns a message describing the status of the deployed resource.
', 'EndpointInput$FeaturesAttribute' => 'The attributes of the input data that are the input features.
', 'EndpointInput$InferenceAttribute' => 'The attribute of the input data that represents the ground truth label.
', 'EndpointInput$ProbabilityAttribute' => 'In a classification problem, the attribute that represents the class probability.
', 'EndpointOutputConfiguration$EndpointName' => 'The name of the endpoint made during a recommendation job.
', 'EndpointOutputConfiguration$VariantName' => 'The name of the production variant (deployed model) made during a recommendation job.
', 'EnvironmentParameter$Key' => 'The environment key suggested by the Amazon SageMaker Inference Recommender.
', 'EnvironmentParameter$ValueType' => 'The value type suggested by the Amazon SageMaker Inference Recommender.
', 'EnvironmentParameter$Value' => 'The value suggested by the Amazon SageMaker Inference Recommender.
', 'GetScalingConfigurationRecommendationRequest$RecommendationId' => 'The recommendation ID of a previously completed inference recommendation. This ID should come from one of the recommendations returned by the job specified in the InferenceRecommendationsJobName field.
Specify either this field or the EndpointName field.
The recommendation ID of a previously completed inference recommendation.
', 'IamIdentity$Arn' => 'The Amazon Resource Name (ARN) of the IAM identity.
', 'IamIdentity$PrincipalId' => 'The ID of the principal that assumes the IAM identity.
', 'IamIdentity$SourceIdentity' => 'The person or application which assumes the IAM identity.
', 'InferenceRecommendation$RecommendationId' => 'The recommendation ID which uniquely identifies each recommendation.
', 'ListProcessingJobsRequest$NameContains' => 'A string in the processing job name. This filter returns only processing jobs whose name contains the specified string.
', 'ModelCard$ModelId' => 'The unique name (ID) of the model.
', 'ModelCard$RiskRating' => 'The risk rating of the model. Different organizations might have different criteria for model card risk ratings. For more information, see Risk ratings.
', 'ModelCard$ModelPackageGroupName' => 'The model package group that contains the model package. Only relevant for model cards created for model packages in the Amazon SageMaker Model Registry.
', 'ModelDashboardModelCard$ModelId' => 'For models created in SageMaker, this is the model ARN. For models created outside of SageMaker, this is a user-customized string.
', 'ModelDashboardModelCard$RiskRating' => 'A model card\'s risk rating. Can be low, medium, or high.
', 'ModelMetadataSummary$Domain' => 'The machine learning domain of the model.
', 'ModelMetadataSummary$Framework' => 'The machine learning framework of the model.
', 'ModelMetadataSummary$Task' => 'The machine learning task of the model.
', 'ModelMetadataSummary$Model' => 'The name of the model.
', 'ModelMetadataSummary$FrameworkVersion' => 'The framework version of the model.
', 'ModelPackage$Domain' => 'The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.
', 'ModelPackage$Task' => 'The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification.
', 'ModelPackage$SamplePayloadUrl' => 'The Amazon Simple Storage Service path where the sample payload are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
', 'ModelPackageContainerDefinition$Framework' => 'The machine learning framework of the model package container image.
', 'ModelPackageContainerDefinition$NearestModelName' => 'The name of a pre-trained machine learning benchmarked by Amazon SageMaker Inference Recommender model that matches your model. You can find a list of benchmarked models by calling ListModelMetadata.
if the overall status is Failed, the reason for the failure.
The metric type. You can only apply SageMaker metric types to SageMaker endpoints.
', 'ProcessingInput$InputName' => 'The name for the processing job input.
', 'ProcessingOutput$OutputName' => 'The name for the processing job output.
', 'ProductListings$member' => NULL, 'RStudioServerProDomainSettings$RStudioConnectUrl' => 'A URL pointing to an RStudio Connect server.
', 'RStudioServerProDomainSettings$RStudioPackageManagerUrl' => 'A URL pointing to an RStudio Package Manager server.
', 'RStudioServerProDomainSettingsForUpdate$RStudioConnectUrl' => 'A URL pointing to an RStudio Connect server.
', 'RStudioServerProDomainSettingsForUpdate$RStudioPackageManagerUrl' => 'A URL pointing to an RStudio Package Manager server.
', 'RealTimeInferenceRecommendation$RecommendationId' => 'The recommendation ID which uniquely identifies each recommendation.
', 'RecommendationJobContainerConfig$Domain' => 'The machine learning domain of the model and its components.
Valid Values: COMPUTER_VISION | NATURAL_LANGUAGE_PROCESSING | MACHINE_LEARNING
The machine learning task that the model accomplishes.
Valid Values: IMAGE_CLASSIFICATION | OBJECT_DETECTION | TEXT_GENERATION | IMAGE_SEGMENTATION | FILL_MASK | CLASSIFICATION | REGRESSION | OTHER
The machine learning framework of the container image.
Valid Values: TENSORFLOW | PYTORCH | XGBOOST | SAGEMAKER-SCIKIT-LEARN
The framework version of the container image.
', 'RecommendationJobContainerConfig$NearestModelName' => 'The name of a pre-trained machine learning model benchmarked by Amazon SageMaker Inference Recommender that matches your model.
Valid Values: efficientnetb7 | unet | xgboost | faster-rcnn-resnet101 | nasnetlarge | vgg16 | inception-v3 | mask-rcnn | sagemaker-scikit-learn | densenet201-gluon | resnet18v2-gluon | xception | densenet201 | yolov4 | resnet152 | bert-base-cased | xceptionV1-keras | resnet50 | retinanet
The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
', 'RecommendationJobSupportedContentTypes$member' => NULL, 'RecommendationJobSupportedInstanceTypes$member' => NULL, 'RenderUiTemplateResponse$RenderedContent' => 'A Liquid template that renders the HTML for the worker UI.
', 'RenderingError$Code' => 'A unique identifier for a specific class of errors.
', 'RenderingError$Message' => 'A human-readable message describing the error.
', 'ScheduleConfig$DataAnalysisStartTime' => 'Sets the start time for a monitoring job window. Express this time as an offset to the times that you schedule your monitoring jobs to run. You schedule monitoring jobs with the ScheduleExpression parameter. Specify this offset in ISO 8601 duration format. For example, if you want to monitor the five hours of data in your dataset that precede the start of each monitoring job, you would specify: "-PT5H".
The start time that you specify must not precede the end time that you specify by more than 24 hours. You specify the end time with the DataAnalysisEndTime parameter.
If you set ScheduleExpression to NOW, this parameter is required.
Sets the end time for a monitoring job window. Express this time as an offset to the times that you schedule your monitoring jobs to run. You schedule monitoring jobs with the ScheduleExpression parameter. Specify this offset in ISO 8601 duration format. For example, if you want to end the window one hour before the start of each monitoring job, you would specify: "-PT1H".
The end time that you specify must not follow the start time that you specify by more than 24 hours. You specify the start time with the DataAnalysisStartTime parameter.
If you set ScheduleExpression to NOW, this parameter is required.
The name of the vendor in the Amazon Marketplace.
', 'SubscribedWorkteam$ListingId' => 'Marketplace product listing ID.
', 'UserContext$UserProfileArn' => 'The Amazon Resource Name (ARN) of the user\'s profile.
', 'UserContext$UserProfileName' => 'The name of the user\'s profile.
', 'UserContext$DomainId' => 'The domain associated with the user.
', 'Workforce$SubDomain' => 'The subdomain for your OIDC Identity Provider.
', 'Workteam$SubDomain' => 'The URI of the labeling job\'s user interface. Workers open this URI to start labeling your data objects.
', ], ], 'String1024' => [ 'base' => NULL, 'refs' => [ 'ClarifyCheckStepMetadata$BaselineUsedForDriftCheckConstraints' => 'The Amazon S3 URI of baseline constraints file to be used for the drift check.
', 'ClarifyCheckStepMetadata$CalculatedBaselineConstraints' => 'The Amazon S3 URI of the newly calculated baseline constraints file.
', 'ClarifyCheckStepMetadata$ViolationReport' => 'The Amazon S3 URI of the violation report if violations are detected.
', 'CreateDomainResponse$Url' => 'The URL to the created domain.
', 'DescribeDomainResponse$Url' => 'The domain\'s URL.
', 'DomainDetails$Url' => 'The domain\'s URL.
', 'EMRStepMetadata$LogFilePath' => 'The path to the log file where the cluster step\'s failure root cause is recorded.
', 'OutputParameter$Value' => 'The value of the output parameter.
', 'Parameter$Value' => 'The literal value for the parameter.
', 'QualityCheckStepMetadata$BaselineUsedForDriftCheckStatistics' => 'The Amazon S3 URI of the baseline statistics file used for the drift check.
', 'QualityCheckStepMetadata$BaselineUsedForDriftCheckConstraints' => 'The Amazon S3 URI of the baseline constraints file used for the drift check.
', 'QualityCheckStepMetadata$CalculatedBaselineStatistics' => 'The Amazon S3 URI of the newly calculated baseline statistics file.
', 'QualityCheckStepMetadata$CalculatedBaselineConstraints' => 'The Amazon S3 URI of the newly calculated baseline constraints file.
', 'QualityCheckStepMetadata$ViolationReport' => 'The Amazon S3 URI of violation report if violations are detected.
', ], ], 'String128' => [ 'base' => NULL, 'refs' => [ 'CategoricalParameterRangeValues$member' => NULL, ], ], 'String200' => [ 'base' => NULL, 'refs' => [ 'CreateWorkteamRequest$Description' => 'A description of the work team.
', 'SubscribedWorkteam$MarketplaceTitle' => 'The title of the service provided by the vendor in the Amazon Marketplace.
', 'SubscribedWorkteam$MarketplaceDescription' => 'The description of the vendor from the Amazon Marketplace.
', 'UpdateWorkteamRequest$Description' => 'An updated description for the work team.
', 'Workteam$Description' => 'A description of the work team.
', ], ], 'String2048' => [ 'base' => NULL, 'refs' => [ 'ActionSource$SourceUri' => 'The URI of the source.
', 'ArtifactSource$SourceUri' => 'The URI of the source.
', 'ContextSource$SourceUri' => 'The URI of the source.
', ], ], 'String256' => [ 'base' => NULL, 'refs' => [ 'ActionSource$SourceType' => 'The type of the source.
', 'ActionSource$SourceId' => 'The ID of the source.
', 'ArtifactSourceType$Value' => 'The ID.
', 'ArtifactSummary$ArtifactType' => 'The type of the artifact.
', 'AssociationSummary$SourceType' => 'The source type.
', 'AssociationSummary$DestinationType' => 'The destination type.
', 'CallbackStepMetadata$SqsQueueUrl' => 'The URL of the Amazon Simple Queue Service (Amazon SQS) queue used by the callback step.
', 'ClarifyCheckStepMetadata$CheckType' => 'The type of the Clarify Check step
', 'ClarifyCheckStepMetadata$ModelPackageGroupName' => 'The model package group name.
', 'ClarifyCheckStepMetadata$CheckJobArn' => 'The Amazon Resource Name (ARN) of the check processing job that was run by this step\'s execution.
', 'ContextSource$SourceType' => 'The type of the source.
', 'ContextSource$SourceId' => 'The ID of the source.
', 'ContextSummary$ContextType' => 'The type of the context.
', 'CreateActionRequest$ActionType' => 'The action type.
', 'CreateArtifactRequest$ArtifactType' => 'The artifact type.
', 'CreateContextRequest$ContextType' => 'The context type.
', 'CreateUserProfileRequest$SingleSignOnUserValue' => 'The username of the associated Amazon Web Services Single Sign-On User for this UserProfile. If the Domain\'s AuthMode is IAM Identity Center, this field is required, and must match a valid username of a user in your directory. If the Domain\'s AuthMode is not IAM Identity Center, this field cannot be specified.
', 'DescribeActionResponse$ActionType' => 'The type of the action.
', 'DescribeArtifactResponse$ArtifactType' => 'The type of the artifact.
', 'DescribeContextResponse$ContextType' => 'The type of the context.
', 'DescribeDomainResponse$SingleSignOnManagedApplicationInstanceId' => 'The IAM Identity Center managed application instance ID.
', 'DescribeUserProfileResponse$SingleSignOnUserValue' => 'The IAM Identity Center user value.
', 'EMRStepMetadata$ClusterId' => 'The identifier of the EMR cluster.
', 'EMRStepMetadata$StepId' => 'The identifier of the EMR cluster step.
', 'EMRStepMetadata$StepName' => 'The name of the EMR cluster step.
', 'LambdaStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the Lambda function that was run by this step execution.
', 'ListActionsRequest$ActionType' => 'A filter that returns only actions of the specified type.
', 'ListArtifactsRequest$ArtifactType' => 'A filter that returns only artifacts of the specified type.
', 'ListAssociationsRequest$SourceType' => 'A filter that returns only associations with the specified source type.
', 'ListAssociationsRequest$DestinationType' => 'A filter that returns only associations with the specified destination type.
', 'ListContextsRequest$ContextType' => 'A filter that returns only contexts of the specified type.
', 'ListTrialComponentsRequest$SourceArn' => 'A filter that returns only components that have the specified source Amazon Resource Name (ARN). If you specify SourceArn, you can\'t filter by ExperimentName or TrialName.
The value to filter the model metadata.
', 'ModelStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the created model.
', 'OutputParameter$Name' => 'The name of the output parameter.
', 'QualityCheckStepMetadata$CheckType' => 'The type of the Quality check step.
', 'QualityCheckStepMetadata$ModelPackageGroupName' => 'The model package group name.
', 'QualityCheckStepMetadata$CheckJobArn' => 'The Amazon Resource Name (ARN) of the Quality check processing job that was run by this step execution.
', 'QueryProperties$key' => NULL, 'QueryProperties$value' => NULL, 'RegisterModelStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the model package.
', 'SelectedStep$StepName' => 'The name of the pipeline step.
', 'SendPipelineExecutionStepFailureRequest$FailureReason' => 'A message describing why the step failed.
', ], ], 'String3072' => [ 'base' => NULL, 'refs' => [ 'FailStepMetadata$ErrorMessage' => 'A message that you define and then is processed and rendered by the Fail step when the error occurs.
', 'PipelineExecutionSummary$PipelineExecutionFailureReason' => 'A message generated by SageMaker Pipelines describing why the pipeline execution failed.
', ], ], 'String40' => [ 'base' => NULL, 'refs' => [ 'QueryTypes$member' => NULL, 'Vertex$Type' => 'The type of the lineage entity resource. For example: DataSet, Model, Endpoint, etc...
The type of the action.
', 'CategoricalParameter$Name' => 'The Name of the environment variable.
', 'ModelLatencyThreshold$Percentile' => 'The model latency percentile threshold. Acceptable values are P95 and P99. For custom load tests, specify the value as P95.
Limits the number of vertices in the request. Use the NextToken in a response to to retrieve the next page of results.
Limits the number of vertices in the response. Use the NextToken in a response to to retrieve the next page of results.
The string value of a categorical hyperparameter. If you specify a value for this parameter, you can\'t specify the NumberValue parameter.
The App type that the Lifecycle Configuration is attached to.
', 'DescribeStudioLifecycleConfigResponse$StudioLifecycleConfigAppType' => 'The App type that the Lifecycle Configuration is attached to.
', 'ListStudioLifecycleConfigsRequest$AppTypeEquals' => 'A parameter to search for the App Type to which the Lifecycle Configuration is attached.
', 'StudioLifecycleConfigDetails$StudioLifecycleConfigAppType' => 'The App type to which the Lifecycle Configuration is attached.
', ], ], 'StudioLifecycleConfigArn' => [ 'base' => NULL, 'refs' => [ 'CreateStudioLifecycleConfigResponse$StudioLifecycleConfigArn' => 'The ARN of your created Lifecycle Configuration.
', 'DescribeStudioLifecycleConfigResponse$StudioLifecycleConfigArn' => 'The ARN of the Lifecycle Configuration to describe.
', 'LifecycleConfigArns$member' => NULL, 'ResourceSpec$LifecycleConfigArn' => 'The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
', 'StudioLifecycleConfigDetails$StudioLifecycleConfigArn' => 'The Amazon Resource Name (ARN) of the Lifecycle Configuration.
', ], ], 'StudioLifecycleConfigContent' => [ 'base' => NULL, 'refs' => [ 'CreateStudioLifecycleConfigRequest$StudioLifecycleConfigContent' => 'The content of your Studio Lifecycle Configuration script. This content must be base64 encoded.
', 'DescribeStudioLifecycleConfigResponse$StudioLifecycleConfigContent' => 'The content of your Studio Lifecycle Configuration script.
', ], ], 'StudioLifecycleConfigDetails' => [ 'base' => 'Details of the Studio Lifecycle Configuration.
', 'refs' => [ 'StudioLifecycleConfigsList$member' => NULL, ], ], 'StudioLifecycleConfigName' => [ 'base' => NULL, 'refs' => [ 'CreateStudioLifecycleConfigRequest$StudioLifecycleConfigName' => 'The name of the Studio Lifecycle Configuration to create.
', 'DeleteStudioLifecycleConfigRequest$StudioLifecycleConfigName' => 'The name of the Studio Lifecycle Configuration to delete.
', 'DescribeStudioLifecycleConfigRequest$StudioLifecycleConfigName' => 'The name of the Studio Lifecycle Configuration to describe.
', 'DescribeStudioLifecycleConfigResponse$StudioLifecycleConfigName' => 'The name of the Studio Lifecycle Configuration that is described.
', 'ListStudioLifecycleConfigsRequest$NameContains' => 'A string in the Lifecycle Configuration name. This filter returns only Lifecycle Configurations whose name contains the specified string.
', 'StudioLifecycleConfigDetails$StudioLifecycleConfigName' => 'The name of the Studio Lifecycle Configuration.
', ], ], 'StudioLifecycleConfigSortKey' => [ 'base' => NULL, 'refs' => [ 'ListStudioLifecycleConfigsRequest$SortBy' => 'The property used to sort results. The default value is CreationTime.
', ], ], 'StudioLifecycleConfigsList' => [ 'base' => NULL, 'refs' => [ 'ListStudioLifecycleConfigsResponse$StudioLifecycleConfigs' => 'A list of Lifecycle Configurations and their properties.
', ], ], 'SubnetId' => [ 'base' => NULL, 'refs' => [ 'CreateNotebookInstanceInput$SubnetId' => 'The ID of the subnet in a VPC to which you would like to have a connectivity from your ML compute instance.
', 'DescribeNotebookInstanceOutput$SubnetId' => 'The ID of the VPC subnet.
', 'Subnets$member' => NULL, ], ], 'Subnets' => [ 'base' => NULL, 'refs' => [ 'CreateDomainRequest$SubnetIds' => 'The VPC subnets that Studio uses for communication.
', 'DescribeDomainResponse$SubnetIds' => 'The VPC subnets that Studio uses for communication.
', 'VpcConfig$Subnets' => 'The ID of the subnets in the VPC to which you want to connect your training job or model. For information about the availability of specific instance types, see Supported Instance Types and Availability Zones.
', ], ], 'SubscribedWorkteam' => [ 'base' => 'Describes a work team of a vendor that does the a labelling job.
', 'refs' => [ 'DescribeSubscribedWorkteamResponse$SubscribedWorkteam' => 'A Workteam instance that contains information about the work team.
An array of Workteam objects, each describing a work team.
Returns true if the work team was successfully deleted; otherwise, returns false.
Specified in the GetSearchSuggestions request. Limits the property names that are included in the response.
', 'refs' => [ 'GetSearchSuggestionsRequest$SuggestionQuery' => 'Limits the property names that are included in the response.
', ], ], 'TableFormat' => [ 'base' => NULL, 'refs' => [ 'OfflineStoreConfig$TableFormat' => 'Format for the offline store table. Supported formats are Glue (Default) and Apache Iceberg.
', ], ], 'TableName' => [ 'base' => NULL, 'refs' => [ 'DataCatalogConfig$TableName' => 'The name of the Glue table.
', ], ], 'TabularJobConfig' => [ 'base' => 'The collection of settings used by an AutoML job V2 for the tabular problem type.
', 'refs' => [ 'AutoMLProblemTypeConfig$TabularJobConfig' => 'Settings used to configure an AutoML job V2 for the tabular problem type (regression, classification).
', ], ], 'TabularResolvedAttributes' => [ 'base' => 'The resolved attributes specific to the tabular problem type.
', 'refs' => [ 'AutoMLProblemTypeResolvedAttributes$TabularResolvedAttributes' => 'The resolved attributes for the tabular problem type.
', ], ], 'Tag' => [ 'base' => 'A tag object that consists of a key and an optional value, used to manage metadata for SageMaker Amazon Web Services resources.
You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints. For more information on adding tags to SageMaker resources, see AddTags.
For more information on adding metadata to your Amazon Web Services resources with tagging, see Tagging Amazon Web Services resources. For advice on best practices for managing Amazon Web Services resources with tagging, see Tagging Best Practices: Implement an Effective Amazon Web Services Resource Tagging Strategy.
', 'refs' => [ 'TagList$member' => NULL, ], ], 'TagKey' => [ 'base' => NULL, 'refs' => [ 'Tag$Key' => 'The tag key. Tag keys must be unique per resource.
', 'TagKeyList$member' => NULL, ], ], 'TagKeyList' => [ 'base' => NULL, 'refs' => [ 'DeleteTagsInput$TagKeys' => 'An array or one or more tag keys to delete.
', ], ], 'TagList' => [ 'base' => NULL, 'refs' => [ 'AddTagsInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'AddTagsOutput$Tags' => 'A list of tags associated with the SageMaker resource.
', 'CreateActionRequest$Tags' => 'A list of tags to apply to the action.
', 'CreateAlgorithmInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateAppImageConfigRequest$Tags' => 'A list of tags to apply to the AppImageConfig.
', 'CreateAppRequest$Tags' => 'Each tag consists of a key and an optional value. Tag keys must be unique per resource.
', 'CreateArtifactRequest$Tags' => 'A list of tags to apply to the artifact.
', 'CreateAutoMLJobRequest$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web ServicesResources. Tag keys must be unique per resource.
', 'CreateAutoMLJobV2Request$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, such as by purpose, owner, or environment. For more information, see Tagging Amazon Web ServicesResources. Tag keys must be unique per resource.
', 'CreateCodeRepositoryInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateCompilationJobRequest$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateContextRequest$Tags' => 'A list of tags to apply to the context.
', 'CreateDataQualityJobDefinitionRequest$Tags' => '(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateDeviceFleetRequest$Tags' => 'Creates tags for the specified fleet.
', 'CreateDomainRequest$Tags' => 'Tags to associated with the Domain. Each tag consists of a key and an optional value. Tag keys must be unique per resource. Tags are searchable using the Search API.
Tags that you specify for the Domain are also added to all Apps that the Domain launches.
', 'CreateEdgeDeploymentPlanRequest$Tags' => 'List of tags with which to tag the edge deployment plan.
', 'CreateEdgePackagingJobRequest$Tags' => 'Creates tags for the packaging job.
', 'CreateEndpointConfigInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateEndpointInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateExperimentRequest$Tags' => 'A list of tags to associate with the experiment. You can use Search API to search on the tags.
', 'CreateFeatureGroupRequest$Tags' => 'Tags used to identify Features in each FeatureGroup.
An array of key-value pairs that contain metadata to help you categorize and organize a flow definition. Each tag consists of a key and a value, both of which you define.
', 'CreateHubRequest$Tags' => 'Any tags to associate with the hub.
', 'CreateHumanTaskUiRequest$Tags' => 'An array of key-value pairs that contain metadata to help you categorize and organize a human review workflow user interface. Each tag consists of a key and a value, both of which you define.
', 'CreateHyperParameterTuningJobRequest$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
Tags that you specify for the tuning job are also added to all training jobs that the tuning job launches.
', 'CreateImageRequest$Tags' => 'A list of tags to apply to the image.
', 'CreateInferenceExperimentRequest$Tags' => 'Array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging your Amazon Web Services Resources.
', 'CreateInferenceRecommendationsJobRequest$Tags' => 'The metadata that you apply to Amazon Web Services resources to help you categorize and organize them. Each tag consists of a key and a value, both of which you define. For more information, see Tagging Amazon Web Services Resources in the Amazon Web Services General Reference.
', 'CreateLabelingJobRequest$Tags' => 'An array of key/value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateModelBiasJobDefinitionRequest$Tags' => '(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateModelCardRequest$Tags' => 'Key-value pairs used to manage metadata for model cards.
', 'CreateModelExplainabilityJobDefinitionRequest$Tags' => '(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateModelInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateModelPackageGroupInput$Tags' => 'A list of key value pairs associated with the model group. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'CreateModelPackageInput$Tags' => 'A list of key value pairs associated with the model. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
If you supply ModelPackageGroupName, your model package belongs to the model group you specify and uses the tags associated with the model group. In this case, you cannot supply a tag argument.
(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateMonitoringScheduleRequest$Tags' => '(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateNotebookInstanceInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreatePipelineRequest$Tags' => 'A list of tags to apply to the created pipeline.
', 'CreateProcessingJobRequest$Tags' => '(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateProjectInput$Tags' => 'An array of key-value pairs that you want to use to organize and track your Amazon Web Services resource costs. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'CreateSpaceRequest$Tags' => 'Tags to associated with the space. Each tag consists of a key and an optional value. Tag keys must be unique for each resource. Tags are searchable using the Search API.
Tags to be associated with the Lifecycle Configuration. Each tag consists of a key and an optional value. Tag keys must be unique per resource. Tags are searchable using the Search API.
', 'CreateTrainingJobRequest$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'CreateTransformJobRequest$Tags' => '(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'CreateTrialComponentRequest$Tags' => 'A list of tags to associate with the component. You can use Search API to search on the tags.
', 'CreateTrialRequest$Tags' => 'A list of tags to associate with the trial. You can use Search API to search on the tags.
', 'CreateUserProfileRequest$Tags' => 'Each tag consists of a key and an optional value. Tag keys must be unique per resource.
Tags that you specify for the User Profile are also added to all Apps that the User Profile launches.
', 'CreateWorkforceRequest$Tags' => 'An array of key-value pairs that contain metadata to help you categorize and organize our workforce. Each tag consists of a key and a value, both of which you define.
', 'CreateWorkteamRequest$Tags' => 'An array of key-value pairs.
For more information, see Resource Tag and Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'DescribeLabelingJobResponse$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'Endpoint$Tags' => 'A list of the tags associated with the endpoint. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'Experiment$Tags' => 'The list of tags that are associated with the experiment. You can use Search API to search on the tags.
', 'FeatureGroup$Tags' => 'Tags used to define a FeatureGroup.
The tags associated with a hyperparameter tuning job. For more information see Tagging Amazon Web Services resources.
', 'ImportHubContentRequest$Tags' => 'Any tags associated with the hub content.
', 'ListTagsOutput$Tags' => 'An array of Tag objects, each with a tag key and a value.
A list of key-value pairs associated with the model. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'ModelCard$Tags' => 'Key-value pairs used to manage metadata for the model card.
', 'ModelDashboardModelCard$Tags' => 'The tags associated with a model card.
', 'ModelPackage$Tags' => 'A list of the tags associated with the model package. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'ModelPackageGroup$Tags' => 'A list of the tags associated with the model group. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'MonitoringSchedule$Tags' => 'A list of the tags associated with the monitoring schedlue. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
', 'Pipeline$Tags' => 'A list of tags that apply to the pipeline.
', 'ProcessingJob$Tags' => 'An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
', 'Project$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'RegisterDevicesRequest$Tags' => 'The tags associated with devices.
', 'TrainingJob$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
', 'TransformJob$Tags' => 'A list of tags associated with the transform job.
', 'Trial$Tags' => 'The list of tags that are associated with the trial. You can use Search API to search on the tags.
', 'TrialComponent$Tags' => 'The list of tags that are associated with the component. You can use Search API to search on the tags.
', 'UpdateProjectInput$Tags' => 'An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources. In addition, the project must have tag update constraints set in order to include this parameter in the request. For more information, see Amazon Web Services Service Catalog Tag Update Constraints.
', ], ], 'TagValue' => [ 'base' => NULL, 'refs' => [ 'Tag$Value' => 'The tag value.
', ], ], 'TargetAttributeName' => [ 'base' => NULL, 'refs' => [ 'AutoMLChannel$TargetAttributeName' => 'The name of the target variable in supervised learning, usually represented by \'y\'.
', 'TabularJobConfig$TargetAttributeName' => 'The name of the target variable in supervised learning, usually represented by \'y\'.
', 'TimeSeriesConfig$TargetAttributeName' => 'The name of the column representing the target variable that you want to predict for each item in your dataset. The data type of the target variable must be numerical.
', ], ], 'TargetDevice' => [ 'base' => NULL, 'refs' => [ 'CompilationJobSummary$CompilationTargetDevice' => 'The type of device that the model will run on after the compilation job has completed.
', 'OutputConfig$TargetDevice' => 'Identifies the target device or the machine learning instance that you want to run your model on after the compilation has completed. Alternatively, you can specify OS, architecture, and accelerator using TargetPlatform fields. It can be used instead of TargetPlatform.
Currently ml_trn1 is available only in US East (N. Virginia) Region, and ml_inf2 is available only in US East (Ohio) Region.
The name of the column used to provide the class labels. It should not be same as the content column.
', ], ], 'TargetObjectiveMetricValue' => [ 'base' => NULL, 'refs' => [ 'TuningJobCompletionCriteria$TargetObjectiveMetricValue' => 'The value of the objective metric.
', ], ], 'TargetPlatform' => [ 'base' => 'Contains information about a target platform that you want your model to run on, such as OS, architecture, and accelerators. It is an alternative of TargetDevice.
Contains information about a target platform that you want your model to run on, such as OS, architecture, and accelerators. It is an alternative of TargetDevice.
The following examples show how to configure the TargetPlatform and CompilerOptions JSON strings for popular target platforms:
Raspberry Pi 3 Model B+
"TargetPlatform": {"Os": "LINUX", "Arch": "ARM_EABIHF"},
"CompilerOptions": {\'mattr\': [\'+neon\']}
Jetson TX2
"TargetPlatform": {"Os": "LINUX", "Arch": "ARM64", "Accelerator": "NVIDIA"},
"CompilerOptions": {\'gpu-code\': \'sm_62\', \'trt-ver\': \'6.0.1\', \'cuda-ver\': \'10.0\'}
EC2 m5.2xlarge instance OS
"TargetPlatform": {"Os": "LINUX", "Arch": "X86_64", "Accelerator": "NVIDIA"},
"CompilerOptions": {\'mcpu\': \'skylake-avx512\'}
RK3399
"TargetPlatform": {"Os": "LINUX", "Arch": "ARM64", "Accelerator": "MALI"}
ARMv7 phone (CPU)
"TargetPlatform": {"Os": "ANDROID", "Arch": "ARM_EABI"},
"CompilerOptions": {\'ANDROID_PLATFORM\': 25, \'mattr\': [\'+neon\']}
ARMv8 phone (CPU)
"TargetPlatform": {"Os": "ANDROID", "Arch": "ARM64"},
"CompilerOptions": {\'ANDROID_PLATFORM\': 29}
The type of accelerator that the model will run on after the compilation job has completed.
', 'TargetPlatform$Accelerator' => 'Specifies a target platform accelerator (optional).
NVIDIA: Nvidia graphics processing unit. It also requires gpu-code, trt-ver, cuda-ver compiler options
MALI: ARM Mali graphics processor
INTEL_GRAPHICS: Integrated Intel graphics
The type of architecture that the model will run on after the compilation job has completed.
', 'TargetPlatform$Arch' => 'Specifies a target platform architecture.
X86_64: 64-bit version of the x86 instruction set.
X86: 32-bit version of the x86 instruction set.
ARM64: ARMv8 64-bit CPU.
ARM_EABIHF: ARMv7 32-bit, Hard Float.
ARM_EABI: ARMv7 32-bit, Soft Float. Used by Android 32-bit ARM platform.
The type of OS that the model will run on after the compilation job has completed.
', 'TargetPlatform$Os' => 'Specifies a target platform OS.
LINUX: Linux-based operating systems.
ANDROID: Android operating systems. Android API level can be specified using the ANDROID_PLATFORM compiler option. For example, "CompilerOptions": {\'ANDROID_PLATFORM\': 28}
A target tracking scaling policy. Includes support for predefined or customized metrics.
When using the PutScalingPolicy API, this parameter is required when you are creating a policy with the policy type TargetTrackingScaling.
A target tracking scaling policy. Includes support for predefined or customized metrics.
', ], ], 'TaskAvailabilityLifetimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'HumanTaskConfig$TaskAvailabilityLifetimeInSeconds' => 'The length of time that a task remains available for labeling by human workers. The default and maximum values for this parameter depend on the type of workforce you use.
If you choose the Amazon Mechanical Turk workforce, the maximum is 12 hours (43,200 seconds). The default is 6 hours (21,600 seconds).
If you choose a private or vendor workforce, the default value is 30 days (2592,000 seconds) for non-AL mode. For most users, the maximum is also 30 days.
The variant\'s capacity.
', 'PendingProductionVariantSummary$CurrentInstanceCount' => 'The number of instances associated with the variant.
', 'PendingProductionVariantSummary$DesiredInstanceCount' => 'The number of instances requested in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the CreateEndpointConfig operation.
', 'ProductionVariantSummary$CurrentInstanceCount' => 'The number of instances associated with the variant.
', 'ProductionVariantSummary$DesiredInstanceCount' => 'The number of instances requested in the UpdateEndpointWeightsAndCapacities request.
The number of instances of the type specified by InstanceType.
A description of the task for your human workers.
', ], ], 'TaskInput' => [ 'base' => NULL, 'refs' => [ 'RenderableTask$Input' => 'A JSON object that contains values for the variables defined in the template. It is made available to the template under the substitution variable task.input. For example, if you define a variable task.input.text in your template, you can supply the variable in the JSON object as "text": "sample text".
Keywords used to describe the task so that workers on Amazon Mechanical Turk can discover the task.
', ], ], 'TaskTimeLimitInSeconds' => [ 'base' => NULL, 'refs' => [ 'HumanTaskConfig$TaskTimeLimitInSeconds' => 'The amount of time that a worker has to complete a task.
If you create a custom labeling job, the maximum value for this parameter is 8 hours (28,800 seconds).
If you create a labeling job using a built-in task type the maximum for this parameter depends on the task type you use:
For image and text labeling jobs, the maximum is 8 hours (28,800 seconds).
For 3D point cloud and video frame labeling jobs, the maximum is 30 days (2952,000 seconds) for non-AL mode. For most users, the maximum is also 30 days.
A title for the task for your human workers.
', ], ], 'TemplateContent' => [ 'base' => NULL, 'refs' => [ 'UiTemplate$Content' => 'The content of the Liquid template for the worker user interface.
', ], ], 'TemplateContentSha256' => [ 'base' => NULL, 'refs' => [ 'UiTemplateInfo$ContentSha256' => 'The SHA-256 digest of the contents of the template.
', ], ], 'TemplateUrl' => [ 'base' => NULL, 'refs' => [ 'UiTemplateInfo$Url' => 'The URL for the user interface template.
', ], ], 'TensorBoardAppSettings' => [ 'base' => 'The TensorBoard app settings.
', 'refs' => [ 'UserSettings$TensorBoardAppSettings' => 'The TensorBoard app settings.
', ], ], 'TensorBoardOutputConfig' => [ 'base' => 'Configuration of storage locations for the Amazon SageMaker Debugger TensorBoard output data.
', 'refs' => [ 'CreateTrainingJobRequest$TensorBoardOutputConfig' => NULL, 'DescribeTrainingJobResponse$TensorBoardOutputConfig' => NULL, 'TrainingJob$TensorBoardOutputConfig' => NULL, ], ], 'TenthFractionsOfACent' => [ 'base' => NULL, 'refs' => [ 'USD$TenthFractionsOfACent' => 'Fractions of a cent, in tenths.
', ], ], 'TerminationWaitInSeconds' => [ 'base' => NULL, 'refs' => [ 'BlueGreenUpdatePolicy$TerminationWaitInSeconds' => 'Additional waiting time in seconds after the completion of an endpoint deployment before terminating the old endpoint fleet. Default is 0.
', ], ], 'TextClassificationJobConfig' => [ 'base' => 'The collection of settings used by an AutoML job V2 for the text classification problem type.
', 'refs' => [ 'AutoMLProblemTypeConfig$TextClassificationJobConfig' => 'Settings used to configure an AutoML job V2 for the text classification problem type.
', ], ], 'TextGenerationJobConfig' => [ 'base' => 'The collection of settings used by an AutoML job V2 for the text generation problem type.
The text generation models that support fine-tuning in Autopilot are currently accessible exclusively in regions supported by Canvas. Refer to the documentation of Canvas for the full list of its supported Regions.
Settings used to configure an AutoML job V2 for the text generation (LLMs fine-tuning) problem type.
The text generation models that support fine-tuning in Autopilot are currently accessible exclusively in regions supported by Canvas. Refer to the documentation of Canvas for the full list of its supported Regions.
The resolved attributes specific to the text generation problem type.
', 'refs' => [ 'AutoMLProblemTypeResolvedAttributes$TextGenerationResolvedAttributes' => 'The resolved attributes for the text generation problem type.
', ], ], 'ThingName' => [ 'base' => NULL, 'refs' => [ 'DescribeDeviceResponse$IotThingName' => 'The Amazon Web Services Internet of Things (IoT) object thing name associated with the device.
', 'Device$IotThingName' => 'Amazon Web Services Internet of Things (IoT) object name.
', 'DeviceSummary$IotThingName' => 'The Amazon Web Services Internet of Things (IoT) object thing name associated with the device..
', ], ], 'TimeSeriesConfig' => [ 'base' => 'The collection of components that defines the time-series.
', 'refs' => [ 'TimeSeriesForecastingJobConfig$TimeSeriesConfig' => 'The collection of components that defines the time-series.
', ], ], 'TimeSeriesForecastingJobConfig' => [ 'base' => 'The collection of settings used by an AutoML job V2 for the time-series forecasting problem type.
', 'refs' => [ 'AutoMLProblemTypeConfig$TimeSeriesForecastingJobConfig' => 'Settings used to configure an AutoML job V2 for the time-series forecasting problem type.
', ], ], 'TimeSeriesForecastingSettings' => [ 'base' => 'Time series forecast settings for the SageMaker Canvas application.
', 'refs' => [ 'CanvasAppSettings$TimeSeriesForecastingSettings' => 'Time series forecast settings for the SageMaker Canvas application.
', ], ], 'TimeSeriesTransformations' => [ 'base' => 'Transformations allowed on the dataset. Supported transformations are Filling and Aggregation. Filling specifies how to add values to missing values in the dataset. Aggregation defines how to aggregate data that does not align with forecast frequency.
The transformations modifying specific attributes of the time-series, such as filling strategies for missing values.
', ], ], 'Timestamp' => [ 'base' => NULL, 'refs' => [ 'ActionSummary$CreationTime' => 'When the action was created.
', 'ActionSummary$LastModifiedTime' => 'When the action was last modified.
', 'AppImageConfigDetails$CreationTime' => 'When the AppImageConfig was created.
', 'AppImageConfigDetails$LastModifiedTime' => 'When the AppImageConfig was last modified.
', 'ArtifactSummary$CreationTime' => 'When the artifact was created.
', 'ArtifactSummary$LastModifiedTime' => 'When the artifact was last modified.
', 'AssociationSummary$CreationTime' => 'When the association was created.
', 'AutoMLCandidate$CreationTime' => 'The creation time.
', 'AutoMLCandidate$EndTime' => 'The end time.
', 'AutoMLCandidate$LastModifiedTime' => 'The last modified time.
', 'AutoMLJobSummary$CreationTime' => 'When the AutoML job was created.
', 'AutoMLJobSummary$EndTime' => 'The end time of an AutoML job.
', 'AutoMLJobSummary$LastModifiedTime' => 'When the AutoML job was last modified.
', 'CompilationJobSummary$CompilationStartTime' => 'The time when the model compilation job started.
', 'CompilationJobSummary$CompilationEndTime' => 'The time when the model compilation job completed.
', 'ContextSummary$CreationTime' => 'When the context was created.
', 'ContextSummary$LastModifiedTime' => 'When the context was last modified.
', 'CreateTrialComponentRequest$StartTime' => 'When the component started.
', 'CreateTrialComponentRequest$EndTime' => 'When the component ended.
', 'DebugRuleEvaluationStatus$LastModifiedTime' => 'Timestamp when the rule evaluation status was last modified.
', 'DeployedImage$ResolutionTime' => 'The date and time when the image path for the model resolved to the ResolvedImage
When the action was created.
', 'DescribeActionResponse$LastModifiedTime' => 'When the action was last modified.
', 'DescribeAppImageConfigResponse$CreationTime' => 'When the AppImageConfig was created.
', 'DescribeAppImageConfigResponse$LastModifiedTime' => 'When the AppImageConfig was last modified.
', 'DescribeAppResponse$LastHealthCheckTimestamp' => 'The timestamp of the last health check.
', 'DescribeAppResponse$LastUserActivityTimestamp' => 'The timestamp of the last user\'s activity. LastUserActivityTimestamp is also updated when SageMaker performs health checks without user activity. As a result, this value is set to the same value as LastHealthCheckTimestamp.
When the artifact was created.
', 'DescribeArtifactResponse$LastModifiedTime' => 'When the artifact was last modified.
', 'DescribeAutoMLJobResponse$CreationTime' => 'Returns the creation time of the AutoML job.
', 'DescribeAutoMLJobResponse$EndTime' => 'Returns the end time of the AutoML job.
', 'DescribeAutoMLJobResponse$LastModifiedTime' => 'Returns the job\'s last modified time.
', 'DescribeAutoMLJobV2Response$CreationTime' => 'Returns the creation time of the AutoML job V2.
', 'DescribeAutoMLJobV2Response$EndTime' => 'Returns the end time of the AutoML job V2.
', 'DescribeAutoMLJobV2Response$LastModifiedTime' => 'Returns the job\'s last modified time.
', 'DescribeCompilationJobResponse$CompilationStartTime' => 'The time when the model compilation job started the CompilationJob instances.
You are billed for the time between this timestamp and the timestamp in the CompilationEndTime field. In Amazon CloudWatch Logs, the start time might be later than this time. That\'s because it takes time to download the compilation job, which depends on the size of the compilation job container.
The time when the model compilation job on a compilation job instance ended. For a successful or stopped job, this is when the job\'s model artifacts have finished uploading. For a failed job, this is when Amazon SageMaker detected that the job failed.
', 'DescribeContextResponse$CreationTime' => 'When the context was created.
', 'DescribeContextResponse$LastModifiedTime' => 'When the context was last modified.
', 'DescribeDataQualityJobDefinitionResponse$CreationTime' => 'The time that the data quality monitoring job definition was created.
', 'DescribeDeviceFleetResponse$CreationTime' => 'Timestamp of when the device fleet was created.
', 'DescribeDeviceFleetResponse$LastModifiedTime' => 'Timestamp of when the device fleet was last updated.
', 'DescribeDeviceResponse$RegistrationTime' => 'The timestamp of the last registration or de-reregistration.
', 'DescribeDeviceResponse$LatestHeartbeat' => 'The last heartbeat received from the device.
', 'DescribeEdgeDeploymentPlanResponse$CreationTime' => 'The time when the edge deployment plan was created.
', 'DescribeEdgeDeploymentPlanResponse$LastModifiedTime' => 'The time when the edge deployment plan was last updated.
', 'DescribeEdgePackagingJobResponse$CreationTime' => 'The timestamp of when the packaging job was created.
', 'DescribeEdgePackagingJobResponse$LastModifiedTime' => 'The timestamp of when the job was last updated.
', 'DescribeEndpointConfigOutput$CreationTime' => 'A timestamp that shows when the endpoint configuration was created.
', 'DescribeEndpointOutput$CreationTime' => 'A timestamp that shows when the endpoint was created.
', 'DescribeEndpointOutput$LastModifiedTime' => 'A timestamp that shows when the endpoint was last modified.
', 'DescribeExperimentResponse$CreationTime' => 'When the experiment was created.
', 'DescribeExperimentResponse$LastModifiedTime' => 'When the experiment was last modified.
', 'DescribeFlowDefinitionResponse$CreationTime' => 'The timestamp when the flow definition was created.
', 'DescribeHubContentResponse$CreationTime' => 'The date and time that hub content was created.
', 'DescribeHubResponse$CreationTime' => 'The date and time that the hub was created.
', 'DescribeHubResponse$LastModifiedTime' => 'The date and time that the hub was last modified.
', 'DescribeHumanTaskUiResponse$CreationTime' => 'The timestamp when the human task user interface was created.
', 'DescribeHyperParameterTuningJobResponse$CreationTime' => 'The date and time that the tuning job started.
', 'DescribeHyperParameterTuningJobResponse$HyperParameterTuningEndTime' => 'The date and time that the tuning job ended.
', 'DescribeHyperParameterTuningJobResponse$LastModifiedTime' => 'The date and time that the status of the tuning job was modified.
', 'DescribeImageResponse$CreationTime' => 'When the image was created.
', 'DescribeImageResponse$LastModifiedTime' => 'When the image was last modified.
', 'DescribeImageVersionResponse$CreationTime' => 'When the version was created.
', 'DescribeImageVersionResponse$LastModifiedTime' => 'When the version was last modified.
', 'DescribeInferenceExperimentResponse$CreationTime' => 'The timestamp at which you created the inference experiment.
', 'DescribeInferenceExperimentResponse$CompletionTime' => 'The timestamp at which the inference experiment was completed.
', 'DescribeInferenceExperimentResponse$LastModifiedTime' => 'The timestamp at which you last modified the inference experiment.
', 'DescribeInferenceRecommendationsJobResponse$CompletionTime' => 'A timestamp that shows when the job completed.
', 'DescribeLabelingJobResponse$CreationTime' => 'The date and time that the labeling job was created.
', 'DescribeLabelingJobResponse$LastModifiedTime' => 'The date and time that the labeling job was last updated.
', 'DescribeLineageGroupResponse$CreationTime' => 'The creation time of lineage group.
', 'DescribeLineageGroupResponse$LastModifiedTime' => 'The last modified time of the lineage group.
', 'DescribeModelBiasJobDefinitionResponse$CreationTime' => 'The time at which the model bias job was created.
', 'DescribeModelCardExportJobResponse$CreatedAt' => 'The date and time that the model export job was created.
', 'DescribeModelCardExportJobResponse$LastModifiedAt' => 'The date and time that the model export job was last modified.
', 'DescribeModelCardResponse$CreationTime' => 'The date and time the model card was created.
', 'DescribeModelCardResponse$LastModifiedTime' => 'The date and time the model card was last modified.
', 'DescribeModelExplainabilityJobDefinitionResponse$CreationTime' => 'The time at which the model explainability job was created.
', 'DescribeModelOutput$CreationTime' => 'A timestamp that shows when the model was created.
', 'DescribeModelPackageOutput$LastModifiedTime' => 'The last time that the model package was modified.
', 'DescribeModelQualityJobDefinitionResponse$CreationTime' => 'The time at which the model quality job was created.
', 'DescribeMonitoringScheduleResponse$CreationTime' => 'The time at which the monitoring job was created.
', 'DescribeMonitoringScheduleResponse$LastModifiedTime' => 'The time at which the monitoring job was last modified.
', 'DescribePipelineDefinitionForExecutionResponse$CreationTime' => 'The time when the pipeline was created.
', 'DescribePipelineExecutionResponse$CreationTime' => 'The time when the pipeline execution was created.
', 'DescribePipelineExecutionResponse$LastModifiedTime' => 'The time when the pipeline execution was modified last.
', 'DescribePipelineResponse$CreationTime' => 'The time when the pipeline was created.
', 'DescribePipelineResponse$LastModifiedTime' => 'The time when the pipeline was last modified.
', 'DescribePipelineResponse$LastRunTime' => 'The time when the pipeline was last run.
', 'DescribeProcessingJobResponse$ProcessingEndTime' => 'The time at which the processing job completed.
', 'DescribeProcessingJobResponse$ProcessingStartTime' => 'The time at which the processing job started.
', 'DescribeProcessingJobResponse$LastModifiedTime' => 'The time at which the processing job was last modified.
', 'DescribeProcessingJobResponse$CreationTime' => 'The time at which the processing job was created.
', 'DescribeProjectOutput$CreationTime' => 'The time when the project was created.
', 'DescribeProjectOutput$LastModifiedTime' => 'The timestamp when project was last modified.
', 'DescribeStudioLifecycleConfigResponse$CreationTime' => 'The creation time of the Studio Lifecycle Configuration.
', 'DescribeStudioLifecycleConfigResponse$LastModifiedTime' => 'This value is equivalent to CreationTime because Studio Lifecycle Configurations are immutable.
', 'DescribeTrainingJobResponse$CreationTime' => 'A timestamp that indicates when the training job was created.
', 'DescribeTrainingJobResponse$TrainingStartTime' => 'Indicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of TrainingEndTime. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container.
Indicates the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.
A timestamp that indicates when the status of the training job was last modified.
', 'DescribeTransformJobResponse$CreationTime' => 'A timestamp that shows when the transform Job was created.
', 'DescribeTransformJobResponse$TransformStartTime' => 'Indicates when the transform job starts on ML instances. You are billed for the time interval between this time and the value of TransformEndTime.
Indicates when the transform job has been completed, or has stopped or failed. You are billed for the time interval between this time and the value of TransformStartTime.
When the component started.
', 'DescribeTrialComponentResponse$EndTime' => 'When the component ended.
', 'DescribeTrialComponentResponse$CreationTime' => 'When the component was created.
', 'DescribeTrialComponentResponse$LastModifiedTime' => 'When the component was last modified.
', 'DescribeTrialResponse$CreationTime' => 'When the trial was created.
', 'DescribeTrialResponse$LastModifiedTime' => 'When the trial was last modified.
', 'DeviceDeploymentSummary$DeploymentStartTime' => 'The time when the deployment on the device started.
', 'DeviceFleetSummary$CreationTime' => 'Timestamp of when the device fleet was created.
', 'DeviceFleetSummary$LastModifiedTime' => 'Timestamp of when the device fleet was last updated.
', 'DeviceSummary$RegistrationTime' => 'The timestamp of the last registration or de-reregistration.
', 'DeviceSummary$LatestHeartbeat' => 'The last heartbeat received from the device.
', 'EdgeDeploymentPlanSummary$CreationTime' => 'The time when the edge deployment plan was created.
', 'EdgeDeploymentPlanSummary$LastModifiedTime' => 'The time when the edge deployment plan was last updated.
', 'EdgeDeploymentStatus$EdgeDeploymentStageStartTime' => 'The time when the deployment API started.
', 'EdgeModel$LatestSampleTime' => 'The timestamp of the last data sample taken.
', 'EdgeModel$LatestInference' => 'The timestamp of the last inference that was made.
', 'EdgePackagingJobSummary$CreationTime' => 'The timestamp of when the job was created.
', 'EdgePackagingJobSummary$LastModifiedTime' => 'The timestamp of when the edge packaging job was last updated.
', 'Endpoint$CreationTime' => 'The time that the endpoint was created.
', 'Endpoint$LastModifiedTime' => 'The last time the endpoint was modified.
', 'EndpointConfigSummary$CreationTime' => 'A timestamp that shows when the endpoint configuration was created.
', 'EndpointSummary$CreationTime' => 'A timestamp that shows when the endpoint was created.
', 'EndpointSummary$LastModifiedTime' => 'A timestamp that shows when the endpoint was last modified.
', 'Experiment$CreationTime' => 'When the experiment was created.
', 'Experiment$LastModifiedTime' => 'When the experiment was last modified.
', 'ExperimentSummary$CreationTime' => 'When the experiment was created.
', 'ExperimentSummary$LastModifiedTime' => 'When the experiment was last modified.
', 'FeatureGroupSummary$CreationTime' => 'A timestamp indicating the time of creation time of the FeatureGroup.
The timestamp when SageMaker created the flow definition.
', 'GetDeviceFleetReportResponse$ReportGenerated' => 'Timestamp of when the report was generated.
', 'HubContentInfo$CreationTime' => 'The date and time that the hub content was created.
', 'HubInfo$CreationTime' => 'The date and time that the hub was created.
', 'HubInfo$LastModifiedTime' => 'The date and time that the hub was last modified.
', 'HumanTaskUiSummary$CreationTime' => 'A timestamp when SageMaker created the human task user interface.
', 'HyperParameterTrainingJobSummary$CreationTime' => 'The date and time that the training job was created.
', 'HyperParameterTrainingJobSummary$TrainingStartTime' => 'The date and time that the training job started.
', 'HyperParameterTrainingJobSummary$TrainingEndTime' => 'Specifies the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.
The time in timestamp format that AMT detected model convergence, as defined by a lack of significant improvement over time based on criteria developed over a wide range of diverse benchmarking tests.
', 'HyperParameterTuningJobSearchEntity$CreationTime' => 'The time that a hyperparameter tuning job was created.
', 'HyperParameterTuningJobSearchEntity$HyperParameterTuningEndTime' => 'The time that a hyperparameter tuning job ended.
', 'HyperParameterTuningJobSearchEntity$LastModifiedTime' => 'The time that a hyperparameter tuning job was last modified.
', 'HyperParameterTuningJobSummary$CreationTime' => 'The date and time that the tuning job was created.
', 'HyperParameterTuningJobSummary$HyperParameterTuningEndTime' => 'The date and time that the tuning job ended.
', 'HyperParameterTuningJobSummary$LastModifiedTime' => 'The date and time that the tuning job was modified.
', 'Image$CreationTime' => 'When the image was created.
', 'Image$LastModifiedTime' => 'When the image was last modified.
', 'ImageVersion$CreationTime' => 'When the version was created.
', 'ImageVersion$LastModifiedTime' => 'When the version was last modified.
', 'InferenceExperimentSchedule$StartTime' => 'The timestamp at which the inference experiment started or will start.
', 'InferenceExperimentSchedule$EndTime' => 'The timestamp at which the inference experiment ended or will end.
', 'InferenceExperimentSummary$CreationTime' => 'The timestamp at which the inference experiment was created.
', 'InferenceExperimentSummary$CompletionTime' => 'The timestamp at which the inference experiment was completed.
', 'InferenceExperimentSummary$LastModifiedTime' => 'The timestamp when you last modified the inference experiment.
', 'InferenceRecommendationsJob$CompletionTime' => 'A timestamp that shows when the job completed.
', 'LabelingJobForWorkteamSummary$CreationTime' => 'The date and time that the labeling job was created.
', 'LabelingJobSummary$CreationTime' => 'The date and time that the job was created (timestamp).
', 'LabelingJobSummary$LastModifiedTime' => 'The date and time that the job was last modified (timestamp).
', 'LineageGroupSummary$CreationTime' => 'The creation time of the lineage group summary.
', 'LineageGroupSummary$LastModifiedTime' => 'The last modified time of the lineage group summary.
', 'ListActionsRequest$CreatedAfter' => 'A filter that returns only actions created on or after the specified time.
', 'ListActionsRequest$CreatedBefore' => 'A filter that returns only actions created on or before the specified time.
', 'ListAppImageConfigsRequest$CreationTimeBefore' => 'A filter that returns only AppImageConfigs created on or before the specified time.
', 'ListAppImageConfigsRequest$CreationTimeAfter' => 'A filter that returns only AppImageConfigs created on or after the specified time.
', 'ListAppImageConfigsRequest$ModifiedTimeBefore' => 'A filter that returns only AppImageConfigs modified on or before the specified time.
', 'ListAppImageConfigsRequest$ModifiedTimeAfter' => 'A filter that returns only AppImageConfigs modified on or after the specified time.
', 'ListArtifactsRequest$CreatedAfter' => 'A filter that returns only artifacts created on or after the specified time.
', 'ListArtifactsRequest$CreatedBefore' => 'A filter that returns only artifacts created on or before the specified time.
', 'ListAssociationsRequest$CreatedAfter' => 'A filter that returns only associations created on or after the specified time.
', 'ListAssociationsRequest$CreatedBefore' => 'A filter that returns only associations created on or before the specified time.
', 'ListAutoMLJobsRequest$CreationTimeAfter' => 'Request a list of jobs, using a filter for time.
', 'ListAutoMLJobsRequest$CreationTimeBefore' => 'Request a list of jobs, using a filter for time.
', 'ListAutoMLJobsRequest$LastModifiedTimeAfter' => 'Request a list of jobs, using a filter for time.
', 'ListAutoMLJobsRequest$LastModifiedTimeBefore' => 'Request a list of jobs, using a filter for time.
', 'ListCodeRepositoriesInput$LastModifiedTimeAfter' => 'A filter that returns only Git repositories that were last modified after the specified time.
', 'ListCodeRepositoriesInput$LastModifiedTimeBefore' => 'A filter that returns only Git repositories that were last modified before the specified time.
', 'ListContextsRequest$CreatedAfter' => 'A filter that returns only contexts created on or after the specified time.
', 'ListContextsRequest$CreatedBefore' => 'A filter that returns only contexts created on or before the specified time.
', 'ListDataQualityJobDefinitionsRequest$CreationTimeBefore' => 'A filter that returns only data quality monitoring job definitions created before the specified time.
', 'ListDataQualityJobDefinitionsRequest$CreationTimeAfter' => 'A filter that returns only data quality monitoring job definitions created after the specified time.
', 'ListDeviceFleetsRequest$CreationTimeAfter' => 'Filter fleets where packaging job was created after specified time.
', 'ListDeviceFleetsRequest$CreationTimeBefore' => 'Filter fleets where the edge packaging job was created before specified time.
', 'ListDeviceFleetsRequest$LastModifiedTimeAfter' => 'Select fleets where the job was updated after X
', 'ListDeviceFleetsRequest$LastModifiedTimeBefore' => 'Select fleets where the job was updated before X
', 'ListDevicesRequest$LatestHeartbeatAfter' => 'Select fleets where the job was updated after X
', 'ListEdgeDeploymentPlansRequest$CreationTimeAfter' => 'Selects edge deployment plans created after this time.
', 'ListEdgeDeploymentPlansRequest$CreationTimeBefore' => 'Selects edge deployment plans created before this time.
', 'ListEdgeDeploymentPlansRequest$LastModifiedTimeAfter' => 'Selects edge deployment plans that were last updated after this time.
', 'ListEdgeDeploymentPlansRequest$LastModifiedTimeBefore' => 'Selects edge deployment plans that were last updated before this time.
', 'ListEdgePackagingJobsRequest$CreationTimeAfter' => 'Select jobs where the job was created after specified time.
', 'ListEdgePackagingJobsRequest$CreationTimeBefore' => 'Select jobs where the job was created before specified time.
', 'ListEdgePackagingJobsRequest$LastModifiedTimeAfter' => 'Select jobs where the job was updated after specified time.
', 'ListEdgePackagingJobsRequest$LastModifiedTimeBefore' => 'Select jobs where the job was updated before specified time.
', 'ListEndpointConfigsInput$CreationTimeBefore' => 'A filter that returns only endpoint configurations created before the specified time (timestamp).
', 'ListEndpointConfigsInput$CreationTimeAfter' => 'A filter that returns only endpoint configurations with a creation time greater than or equal to the specified time (timestamp).
', 'ListEndpointsInput$CreationTimeBefore' => 'A filter that returns only endpoints that were created before the specified time (timestamp).
', 'ListEndpointsInput$CreationTimeAfter' => 'A filter that returns only endpoints with a creation time greater than or equal to the specified time (timestamp).
', 'ListEndpointsInput$LastModifiedTimeBefore' => 'A filter that returns only endpoints that were modified before the specified timestamp.
', 'ListEndpointsInput$LastModifiedTimeAfter' => 'A filter that returns only endpoints that were modified after the specified timestamp.
', 'ListExperimentsRequest$CreatedAfter' => 'A filter that returns only experiments created after the specified time.
', 'ListExperimentsRequest$CreatedBefore' => 'A filter that returns only experiments created before the specified time.
', 'ListFlowDefinitionsRequest$CreationTimeAfter' => 'A filter that returns only flow definitions with a creation time greater than or equal to the specified timestamp.
', 'ListFlowDefinitionsRequest$CreationTimeBefore' => 'A filter that returns only flow definitions that were created before the specified timestamp.
', 'ListHubContentVersionsRequest$CreationTimeBefore' => 'Only list hub content versions that were created before the time specified.
', 'ListHubContentVersionsRequest$CreationTimeAfter' => 'Only list hub content versions that were created after the time specified.
', 'ListHubContentsRequest$CreationTimeBefore' => 'Only list hub content that was created before the time specified.
', 'ListHubContentsRequest$CreationTimeAfter' => 'Only list hub content that was created after the time specified.
', 'ListHubsRequest$CreationTimeBefore' => 'Only list hubs that were created before the time specified.
', 'ListHubsRequest$CreationTimeAfter' => 'Only list hubs that were created after the time specified.
', 'ListHubsRequest$LastModifiedTimeBefore' => 'Only list hubs that were last modified before the time specified.
', 'ListHubsRequest$LastModifiedTimeAfter' => 'Only list hubs that were last modified after the time specified.
', 'ListHumanTaskUisRequest$CreationTimeAfter' => 'A filter that returns only human task user interfaces with a creation time greater than or equal to the specified timestamp.
', 'ListHumanTaskUisRequest$CreationTimeBefore' => 'A filter that returns only human task user interfaces that were created before the specified timestamp.
', 'ListHyperParameterTuningJobsRequest$CreationTimeAfter' => 'A filter that returns only tuning jobs that were created after the specified time.
', 'ListHyperParameterTuningJobsRequest$CreationTimeBefore' => 'A filter that returns only tuning jobs that were created before the specified time.
', 'ListHyperParameterTuningJobsRequest$LastModifiedTimeAfter' => 'A filter that returns only tuning jobs that were modified after the specified time.
', 'ListHyperParameterTuningJobsRequest$LastModifiedTimeBefore' => 'A filter that returns only tuning jobs that were modified before the specified time.
', 'ListImageVersionsRequest$CreationTimeAfter' => 'A filter that returns only versions created on or after the specified time.
', 'ListImageVersionsRequest$CreationTimeBefore' => 'A filter that returns only versions created on or before the specified time.
', 'ListImageVersionsRequest$LastModifiedTimeAfter' => 'A filter that returns only versions modified on or after the specified time.
', 'ListImageVersionsRequest$LastModifiedTimeBefore' => 'A filter that returns only versions modified on or before the specified time.
', 'ListImagesRequest$CreationTimeAfter' => 'A filter that returns only images created on or after the specified time.
', 'ListImagesRequest$CreationTimeBefore' => 'A filter that returns only images created on or before the specified time.
', 'ListImagesRequest$LastModifiedTimeAfter' => 'A filter that returns only images modified on or after the specified time.
', 'ListImagesRequest$LastModifiedTimeBefore' => 'A filter that returns only images modified on or before the specified time.
', 'ListInferenceExperimentsRequest$CreationTimeAfter' => 'Selects inference experiments which were created after this timestamp.
', 'ListInferenceExperimentsRequest$CreationTimeBefore' => 'Selects inference experiments which were created before this timestamp.
', 'ListInferenceExperimentsRequest$LastModifiedTimeAfter' => 'Selects inference experiments which were last modified after this timestamp.
', 'ListInferenceExperimentsRequest$LastModifiedTimeBefore' => 'Selects inference experiments which were last modified before this timestamp.
', 'ListLabelingJobsForWorkteamRequest$CreationTimeAfter' => 'A filter that returns only labeling jobs created after the specified time (timestamp).
', 'ListLabelingJobsForWorkteamRequest$CreationTimeBefore' => 'A filter that returns only labeling jobs created before the specified time (timestamp).
', 'ListLabelingJobsRequest$CreationTimeAfter' => 'A filter that returns only labeling jobs created after the specified time (timestamp).
', 'ListLabelingJobsRequest$CreationTimeBefore' => 'A filter that returns only labeling jobs created before the specified time (timestamp).
', 'ListLabelingJobsRequest$LastModifiedTimeAfter' => 'A filter that returns only labeling jobs modified after the specified time (timestamp).
', 'ListLabelingJobsRequest$LastModifiedTimeBefore' => 'A filter that returns only labeling jobs modified before the specified time (timestamp).
', 'ListLineageGroupsRequest$CreatedAfter' => 'A timestamp to filter against lineage groups created after a certain point in time.
', 'ListLineageGroupsRequest$CreatedBefore' => 'A timestamp to filter against lineage groups created before a certain point in time.
', 'ListModelBiasJobDefinitionsRequest$CreationTimeBefore' => 'A filter that returns only model bias jobs created before a specified time.
', 'ListModelBiasJobDefinitionsRequest$CreationTimeAfter' => 'A filter that returns only model bias jobs created after a specified time.
', 'ListModelCardExportJobsRequest$CreationTimeAfter' => 'Only list model card export jobs that were created after the time specified.
', 'ListModelCardExportJobsRequest$CreationTimeBefore' => 'Only list model card export jobs that were created before the time specified.
', 'ListModelCardVersionsRequest$CreationTimeAfter' => 'Only list model card versions that were created after the time specified.
', 'ListModelCardVersionsRequest$CreationTimeBefore' => 'Only list model card versions that were created before the time specified.
', 'ListModelCardsRequest$CreationTimeAfter' => 'Only list model cards that were created after the time specified.
', 'ListModelCardsRequest$CreationTimeBefore' => 'Only list model cards that were created before the time specified.
', 'ListModelExplainabilityJobDefinitionsRequest$CreationTimeBefore' => 'A filter that returns only model explainability jobs created before a specified time.
', 'ListModelExplainabilityJobDefinitionsRequest$CreationTimeAfter' => 'A filter that returns only model explainability jobs created after a specified time.
', 'ListModelQualityJobDefinitionsRequest$CreationTimeBefore' => 'A filter that returns only model quality monitoring job definitions created before the specified time.
', 'ListModelQualityJobDefinitionsRequest$CreationTimeAfter' => 'A filter that returns only model quality monitoring job definitions created after the specified time.
', 'ListModelsInput$CreationTimeBefore' => 'A filter that returns only models created before the specified time (timestamp).
', 'ListModelsInput$CreationTimeAfter' => 'A filter that returns only models with a creation time greater than or equal to the specified time (timestamp).
', 'ListMonitoringAlertHistoryRequest$CreationTimeBefore' => 'A filter that returns only alerts created on or before the specified time.
', 'ListMonitoringAlertHistoryRequest$CreationTimeAfter' => 'A filter that returns only alerts created on or after the specified time.
', 'ListMonitoringExecutionsRequest$ScheduledTimeBefore' => 'Filter for jobs scheduled before a specified time.
', 'ListMonitoringExecutionsRequest$ScheduledTimeAfter' => 'Filter for jobs scheduled after a specified time.
', 'ListMonitoringExecutionsRequest$CreationTimeBefore' => 'A filter that returns only jobs created before a specified time.
', 'ListMonitoringExecutionsRequest$CreationTimeAfter' => 'A filter that returns only jobs created after a specified time.
', 'ListMonitoringExecutionsRequest$LastModifiedTimeBefore' => 'A filter that returns only jobs modified after a specified time.
', 'ListMonitoringExecutionsRequest$LastModifiedTimeAfter' => 'A filter that returns only jobs modified before a specified time.
', 'ListMonitoringSchedulesRequest$CreationTimeBefore' => 'A filter that returns only monitoring schedules created before a specified time.
', 'ListMonitoringSchedulesRequest$CreationTimeAfter' => 'A filter that returns only monitoring schedules created after a specified time.
', 'ListMonitoringSchedulesRequest$LastModifiedTimeBefore' => 'A filter that returns only monitoring schedules modified before a specified time.
', 'ListMonitoringSchedulesRequest$LastModifiedTimeAfter' => 'A filter that returns only monitoring schedules modified after a specified time.
', 'ListPipelineExecutionsRequest$CreatedAfter' => 'A filter that returns the pipeline executions that were created after a specified time.
', 'ListPipelineExecutionsRequest$CreatedBefore' => 'A filter that returns the pipeline executions that were created before a specified time.
', 'ListPipelinesRequest$CreatedAfter' => 'A filter that returns the pipelines that were created after a specified time.
', 'ListPipelinesRequest$CreatedBefore' => 'A filter that returns the pipelines that were created before a specified time.
', 'ListProcessingJobsRequest$CreationTimeAfter' => 'A filter that returns only processing jobs created after the specified time.
', 'ListProcessingJobsRequest$CreationTimeBefore' => 'A filter that returns only processing jobs created after the specified time.
', 'ListProcessingJobsRequest$LastModifiedTimeAfter' => 'A filter that returns only processing jobs modified after the specified time.
', 'ListProcessingJobsRequest$LastModifiedTimeBefore' => 'A filter that returns only processing jobs modified before the specified time.
', 'ListProjectsInput$CreationTimeAfter' => 'A filter that returns the projects that were created after a specified time.
', 'ListProjectsInput$CreationTimeBefore' => 'A filter that returns the projects that were created before a specified time.
', 'ListResourceCatalogsRequest$CreationTimeAfter' => ' Use this parameter to search for ResourceCatalogs created after a specific date and time.
Use this parameter to search for ResourceCatalogs created before a specific date and time.
A filter that returns only Lifecycle Configurations created on or before the specified time.
', 'ListStudioLifecycleConfigsRequest$CreationTimeAfter' => 'A filter that returns only Lifecycle Configurations created on or after the specified time.
', 'ListStudioLifecycleConfigsRequest$ModifiedTimeBefore' => 'A filter that returns only Lifecycle Configurations modified before the specified time.
', 'ListStudioLifecycleConfigsRequest$ModifiedTimeAfter' => 'A filter that returns only Lifecycle Configurations modified after the specified time.
', 'ListTrainingJobsRequest$CreationTimeAfter' => 'A filter that returns only training jobs created after the specified time (timestamp).
', 'ListTrainingJobsRequest$CreationTimeBefore' => 'A filter that returns only training jobs created before the specified time (timestamp).
', 'ListTrainingJobsRequest$LastModifiedTimeAfter' => 'A filter that returns only training jobs modified after the specified time (timestamp).
', 'ListTrainingJobsRequest$LastModifiedTimeBefore' => 'A filter that returns only training jobs modified before the specified time (timestamp).
', 'ListTransformJobsRequest$CreationTimeAfter' => 'A filter that returns only transform jobs created after the specified time.
', 'ListTransformJobsRequest$CreationTimeBefore' => 'A filter that returns only transform jobs created before the specified time.
', 'ListTransformJobsRequest$LastModifiedTimeAfter' => 'A filter that returns only transform jobs modified after the specified time.
', 'ListTransformJobsRequest$LastModifiedTimeBefore' => 'A filter that returns only transform jobs modified before the specified time.
', 'ListTrialComponentsRequest$CreatedAfter' => 'A filter that returns only components created after the specified time.
', 'ListTrialComponentsRequest$CreatedBefore' => 'A filter that returns only components created before the specified time.
', 'ListTrialsRequest$CreatedAfter' => 'A filter that returns only trials created after the specified time.
', 'ListTrialsRequest$CreatedBefore' => 'A filter that returns only trials created before the specified time.
', 'MetricData$Timestamp' => 'The date and time that the algorithm emitted the metric.
', 'Model$CreationTime' => 'A timestamp that indicates when the model was created.
', 'ModelCard$CreationTime' => 'The date and time that the model card was created.
', 'ModelCard$LastModifiedTime' => 'The date and time that the model card was last modified.
', 'ModelCardExportJobSummary$CreatedAt' => 'The date and time that the model card export job was created.
', 'ModelCardExportJobSummary$LastModifiedAt' => 'The date and time that the model card export job was last modified..
', 'ModelCardSummary$CreationTime' => 'The date and time that the model card was created.
', 'ModelCardSummary$LastModifiedTime' => 'The date and time that the model card was last modified.
', 'ModelCardVersionSummary$CreationTime' => 'The date and time that the model card version was created.
', 'ModelCardVersionSummary$LastModifiedTime' => 'The time date and time that the model card version was last modified.
', 'ModelDashboardEndpoint$CreationTime' => 'A timestamp that indicates when the endpoint was created.
', 'ModelDashboardEndpoint$LastModifiedTime' => 'The last time the endpoint was modified.
', 'ModelDashboardModelCard$CreationTime' => 'A timestamp that indicates when the model card was created.
', 'ModelDashboardModelCard$LastModifiedTime' => 'A timestamp that indicates when the model card was last updated.
', 'ModelDashboardMonitoringSchedule$CreationTime' => 'A timestamp that indicates when the monitoring schedule was created.
', 'ModelDashboardMonitoringSchedule$LastModifiedTime' => 'A timestamp that indicates when the monitoring schedule was last updated.
', 'ModelPackage$LastModifiedTime' => 'The last time the model package was modified.
', 'ModelSummary$CreationTime' => 'A timestamp that indicates when the model was created.
', 'MonitoringAlertHistorySummary$CreationTime' => 'A timestamp that indicates when the first alert transition occurred in an alert history. An alert transition can be from status InAlert to OK, or from OK to InAlert.
A timestamp that indicates when a monitor alert was created.
', 'MonitoringAlertSummary$LastModifiedTime' => 'A timestamp that indicates when a monitor alert was last updated.
', 'MonitoringExecutionSummary$ScheduledTime' => 'The time the monitoring job was scheduled.
', 'MonitoringExecutionSummary$CreationTime' => 'The time at which the monitoring job was created.
', 'MonitoringExecutionSummary$LastModifiedTime' => 'A timestamp that indicates the last time the monitoring job was modified.
', 'MonitoringJobDefinitionSummary$CreationTime' => 'The time that the monitoring job was created.
', 'MonitoringSchedule$CreationTime' => 'The time that the monitoring schedule was created.
', 'MonitoringSchedule$LastModifiedTime' => 'The last time the monitoring schedule was changed.
', 'MonitoringScheduleSummary$CreationTime' => 'The creation time of the monitoring schedule.
', 'MonitoringScheduleSummary$LastModifiedTime' => 'The last time the monitoring schedule was modified.
', 'PendingDeploymentSummary$StartTime' => 'The start time of the deployment.
', 'Pipeline$CreationTime' => 'The creation time of the pipeline.
', 'Pipeline$LastModifiedTime' => 'The time that the pipeline was last modified.
', 'Pipeline$LastRunTime' => 'The time when the pipeline was last run.
', 'PipelineExecution$CreationTime' => 'The creation time of the pipeline execution.
', 'PipelineExecution$LastModifiedTime' => 'The time that the pipeline execution was last modified.
', 'PipelineExecutionStep$StartTime' => 'The time that the step started executing.
', 'PipelineExecutionStep$EndTime' => 'The time that the step stopped executing.
', 'PipelineExecutionSummary$StartTime' => 'The start time of the pipeline execution.
', 'PipelineSummary$CreationTime' => 'The creation time of the pipeline.
', 'PipelineSummary$LastModifiedTime' => 'The time that the pipeline was last modified.
', 'PipelineSummary$LastExecutionTime' => 'The last time that a pipeline execution began.
', 'ProcessingJob$ProcessingEndTime' => 'The time that the processing job ended.
', 'ProcessingJob$ProcessingStartTime' => 'The time that the processing job started.
', 'ProcessingJob$LastModifiedTime' => 'The time the processing job was last modified.
', 'ProcessingJob$CreationTime' => 'The time the processing job was created.
', 'ProcessingJobSummary$CreationTime' => 'The time at which the processing job was created.
', 'ProcessingJobSummary$ProcessingEndTime' => 'The time at which the processing job completed.
', 'ProcessingJobSummary$LastModifiedTime' => 'A timestamp that indicates the last time the processing job was modified.
', 'ProductionVariantStatus$StartTime' => 'The start time of the current status change.
', 'ProfilerRuleEvaluationStatus$LastModifiedTime' => 'Timestamp when the rule evaluation status was last modified.
', 'Project$CreationTime' => 'A timestamp specifying when the project was created.
', 'Project$LastModifiedTime' => 'A timestamp container for when the project was last modified.
', 'ProjectSummary$CreationTime' => 'The time that the project was created.
', 'QueryFilters$CreatedBefore' => 'Filter the lineage entities connected to the StartArn(s) by created date.
Filter the lineage entities connected to the StartArn(s) after the create date.
Filter the lineage entities connected to the StartArn(s) before the last modified date.
Filter the lineage entities connected to the StartArn(s) after the last modified date.
The time the ResourceCatalog was created.
A timestamp that shows when the training job transitioned to the current secondary status state.
', 'SecondaryStatusTransition$EndTime' => 'A timestamp that shows when the training job transitioned out of this secondary status state into another secondary status state or when the training job has ended.
', 'StudioLifecycleConfigDetails$CreationTime' => 'The creation time of the Studio Lifecycle Configuration.
', 'StudioLifecycleConfigDetails$LastModifiedTime' => 'This value is equivalent to CreationTime because Studio Lifecycle Configurations are immutable.
', 'TrainingJob$CreationTime' => 'A timestamp that indicates when the training job was created.
', 'TrainingJob$TrainingStartTime' => 'Indicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of TrainingEndTime. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container.
Indicates the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.
A timestamp that indicates when the status of the training job was last modified.
', 'TrainingJobSummary$CreationTime' => 'A timestamp that shows when the training job was created.
', 'TrainingJobSummary$TrainingEndTime' => 'A timestamp that shows when the training job ended. This field is set only if the training job has one of the terminal statuses (Completed, Failed, or Stopped).
Timestamp when the training job was last modified.
', 'TransformJob$CreationTime' => 'A timestamp that shows when the transform Job was created.
', 'TransformJob$TransformStartTime' => 'Indicates when the transform job starts on ML instances. You are billed for the time interval between this time and the value of TransformEndTime.
Indicates when the transform job has been completed, or has stopped or failed. You are billed for the time interval between this time and the value of TransformStartTime.
A timestamp that shows when the transform Job was created.
', 'TransformJobSummary$TransformEndTime' => 'Indicates when the transform job ends on compute instances. For successful jobs and stopped jobs, this is the exact time recorded after the results are uploaded. For failed jobs, this is when Amazon SageMaker detected that the job failed.
', 'TransformJobSummary$LastModifiedTime' => 'Indicates when the transform job was last modified.
', 'Trial$CreationTime' => 'When the trial was created.
', 'Trial$LastModifiedTime' => 'Who last modified the trial.
', 'TrialComponent$StartTime' => 'When the component started.
', 'TrialComponent$EndTime' => 'When the component ended.
', 'TrialComponent$CreationTime' => 'When the component was created.
', 'TrialComponent$LastModifiedTime' => 'When the component was last modified.
', 'TrialComponentMetricSummary$TimeStamp' => 'When the metric was last updated.
', 'TrialComponentSimpleSummary$CreationTime' => 'When the component was created.
', 'TrialComponentSummary$StartTime' => 'When the component started.
', 'TrialComponentSummary$EndTime' => 'When the component ended.
', 'TrialComponentSummary$CreationTime' => 'When the component was created.
', 'TrialComponentSummary$LastModifiedTime' => 'When the component was last modified.
', 'TrialSummary$CreationTime' => 'When the trial was created.
', 'TrialSummary$LastModifiedTime' => 'When the trial was last modified.
', 'UpdateTrialComponentRequest$StartTime' => 'When the component started.
', 'UpdateTrialComponentRequest$EndTime' => 'When the component ended.
', 'Workforce$LastUpdatedDate' => 'The most recent date that UpdateWorkforce was used to successfully add one or more IP address ranges (CIDRs) to a private workforce\'s allow list.
', 'Workforce$CreateDate' => 'The date that the workforce is created.
', 'Workteam$CreateDate' => 'The date and time that the work team was created (timestamp).
', 'Workteam$LastUpdatedDate' => 'The date and time that the work team was last updated (timestamp).
', ], ], 'TimestampAttributeName' => [ 'base' => NULL, 'refs' => [ 'TimeSeriesConfig$TimestampAttributeName' => 'The name of the column indicating a point in time at which the target value of a given item is recorded.
', ], ], 'TrafficDurationInSeconds' => [ 'base' => NULL, 'refs' => [ 'Phase$DurationInSeconds' => 'Specifies how long a traffic phase should be. For custom load tests, the value should be between 120 and 3600. This value should not exceed JobDurationInSeconds.
Defines how long each traffic step should be.
', ], ], 'TrafficPattern' => [ 'base' => 'Defines the traffic pattern of the load test.
', 'refs' => [ 'RecommendationJobInputConfig$TrafficPattern' => 'Specifies the traffic pattern of the job.
', ], ], 'TrafficRoutingConfig' => [ 'base' => 'Defines the traffic routing strategy during an endpoint deployment to shift traffic from the old fleet to the new fleet.
', 'refs' => [ 'BlueGreenUpdatePolicy$TrafficRoutingConfiguration' => 'Defines the traffic routing strategy to shift traffic from the old fleet to the new fleet during an endpoint deployment.
', ], ], 'TrafficRoutingConfigType' => [ 'base' => NULL, 'refs' => [ 'TrafficRoutingConfig$Type' => 'Traffic routing strategy type.
ALL_AT_ONCE: Endpoint traffic shifts to the new fleet in a single step.
CANARY: Endpoint traffic shifts to the new fleet in two steps. The first step is the canary, which is a small portion of the traffic. The second step is the remainder of the traffic.
LINEAR: Endpoint traffic shifts to the new fleet in n steps of a configurable size.
Defines the traffic patterns. Choose either PHASES or STAIRS.
The arguments for a container used to run a training job. See How Amazon SageMaker Runs Your Training Image for additional information.
', ], ], 'TrainingContainerEntrypoint' => [ 'base' => NULL, 'refs' => [ 'AlgorithmSpecification$ContainerEntrypoint' => 'The entrypoint script for a Docker container used to run a training job. This script takes precedence over the default train processing instructions. See How Amazon SageMaker Runs Your Training Image for more information.
', ], ], 'TrainingContainerEntrypointString' => [ 'base' => NULL, 'refs' => [ 'TrainingContainerEntrypoint$member' => NULL, ], ], 'TrainingEnvironmentKey' => [ 'base' => NULL, 'refs' => [ 'TrainingEnvironmentMap$key' => NULL, ], ], 'TrainingEnvironmentMap' => [ 'base' => NULL, 'refs' => [ 'CreateTrainingJobRequest$Environment' => 'The environment variables to set in the Docker container.
', 'DescribeTrainingJobResponse$Environment' => 'The environment variables to set in the Docker container.
', 'TrainingJob$Environment' => 'The environment variables to set in the Docker container.
', ], ], 'TrainingEnvironmentValue' => [ 'base' => NULL, 'refs' => [ 'TrainingEnvironmentMap$value' => NULL, ], ], 'TrainingImageConfig' => [ 'base' => 'The configuration to use an image from a private Docker registry for a training job.
', 'refs' => [ 'AlgorithmSpecification$TrainingImageConfig' => 'The configuration to use an image from a private Docker registry for a training job.
', ], ], 'TrainingInputMode' => [ 'base' => 'The training input mode that the algorithm supports. For more information about input modes, see Algorithms.
Pipe mode
If an algorithm supports Pipe mode, Amazon SageMaker streams data directly from Amazon S3 to the container.
File mode
If an algorithm supports File mode, SageMaker downloads the training data from S3 to the provisioned ML storage volume, and mounts the directory to the Docker volume for the training container.
You must provision the ML storage volume with sufficient capacity to accommodate the data downloaded from S3. In addition to the training data, the ML storage volume also stores the output model. The algorithm container uses the ML storage volume to also store intermediate information, if any.
For distributed algorithms, training data is distributed uniformly. Your training duration is predictable if the input data objects sizes are approximately the same. SageMaker does not split the files any further for model training. If the object sizes are skewed, training won\'t be optimal as the data distribution is also skewed when one host in a training cluster is overloaded, thus becoming a bottleneck in training.
FastFile mode
If an algorithm supports FastFile mode, SageMaker streams data directly from S3 to the container with no code changes, and provides file system access to the data. Users can author their training script to interact with these files as if they were stored on disk.
FastFile mode works best when the data is read sequentially. Augmented manifest files aren\'t supported. The startup time is lower when there are fewer files in the S3 bucket provided.
(Optional) The input mode to use for the data channel in a training job. If you don\'t set a value for InputMode, SageMaker uses the value set for TrainingInputMode. Use this parameter to override the TrainingInputMode setting in a AlgorithmSpecification request when you have a channel that needs a different input mode from the training job\'s general setting. To download the data from Amazon Simple Storage Service (Amazon S3) to the provisioned ML storage volume, and mount the directory to a Docker volume, use File input mode. To stream data directly from Amazon S3 to the container, choose Pipe input mode.
To use a model for incremental training, choose File input model.
The number of instances of the type specified by InstanceType. Choose an instance count larger than 1 for distributed training algorithms. See Step 2: Launch a SageMaker Distributed Training Job Using the SageMaker Python SDK for more information.
The number of compute instances of type InstanceType to use. For distributed training, select a value greater than 1.
Specifies the number of instances of the instance group.
', 'ResourceConfig$InstanceCount' => 'The number of ML compute instances to use. For distributed training, provide a value greater than 1.
', ], ], 'TrainingInstanceType' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTuningInstanceConfig$InstanceType' => 'The instance type used for processing of hyperparameter optimization jobs. Choose from general purpose (no GPUs) instance types: ml.m5.xlarge, ml.m5.2xlarge, and ml.m5.4xlarge or compute optimized (no GPUs) instance types: ml.c5.xlarge and ml.c5.2xlarge. For more information about instance types, see instance type descriptions.
', 'HyperParameterTuningResourceConfig$InstanceType' => 'The instance type used to run hyperparameter optimization tuning jobs. See descriptions of instance types for more information.
', 'InstanceGroup$InstanceType' => 'Specifies the instance type of the instance group.
', 'ResourceConfig$InstanceType' => 'The ML compute instance type.
SageMaker Training on Amazon Elastic Compute Cloud (EC2) P4de instances is in preview release starting December 9th, 2022.
Amazon EC2 P4de instances (currently in preview) are powered by 8 NVIDIA A100 GPUs with 80GB high-performance HBM2e GPU memory, which accelerate the speed of training ML models that need to be trained on large datasets of high-resolution data. In this preview release, Amazon SageMaker supports ML training jobs on P4de instances (ml.p4de.24xlarge) to reduce model training time. The ml.p4de.24xlarge instances are available in the following Amazon Web Services Regions.
US East (N. Virginia) (us-east-1)
US West (Oregon) (us-west-2)
To request quota limit increase and start using P4de instances, contact the SageMaker Training service team through your account team.
A list of the instance types that this algorithm can use for training.
', ], ], 'TrainingJob' => [ 'base' => 'Contains information about a training job.
', 'refs' => [ 'SearchRecord$TrainingJob' => 'The properties of a training job.
', 'TrialComponentSourceDetail$TrainingJob' => 'Information about a training job that\'s the source of a trial component.
', ], ], 'TrainingJobArn' => [ 'base' => NULL, 'refs' => [ 'CreateTrainingJobResponse$TrainingJobArn' => 'The Amazon Resource Name (ARN) of the training job.
', 'DescribeProcessingJobResponse$TrainingJobArn' => 'The ARN of a training job associated with this processing job.
', 'DescribeTrainingJobResponse$TrainingJobArn' => 'The Amazon Resource Name (ARN) of the training job.
', 'HyperParameterTrainingJobSummary$TrainingJobArn' => 'The Amazon Resource Name (ARN) of the training job.
', 'ProcessingJob$TrainingJobArn' => 'The ARN of the training job associated with this processing job.
', 'TrainingJob$TrainingJobArn' => 'The Amazon Resource Name (ARN) of the training job.
', 'TrainingJobStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the training job that was run by this step execution.
', 'TrainingJobSummary$TrainingJobArn' => 'The Amazon Resource Name (ARN) of the training job.
', 'UpdateTrainingJobResponse$TrainingJobArn' => 'The Amazon Resource Name (ARN) of the training job.
', ], ], 'TrainingJobDefinition' => [ 'base' => 'Defines the input needed to run a training job using the algorithm.
', 'refs' => [ 'AlgorithmValidationProfile$TrainingJobDefinition' => 'The TrainingJobDefinition object that describes the training job that SageMaker runs to validate your algorithm.
Specifies whether to use early stopping for training jobs launched by the hyperparameter tuning job. Because the Hyperband strategy has its own advanced internal early stopping mechanism, TrainingJobEarlyStoppingType must be OFF to use Hyperband. This parameter can take on one of the following values (the default value is OFF):
Training jobs launched by the hyperparameter tuning job do not use early stopping.
SageMaker stops training jobs launched by the hyperparameter tuning job when they are unlikely to perform better than previously completed training jobs. For more information, see Stop Training Jobs Early.
The name of the training job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
', 'DescribeTrainingJobRequest$TrainingJobName' => 'The name of the training job.
', 'DescribeTrainingJobResponse$TrainingJobName' => 'Name of the model training job.
', 'HyperParameterTrainingJobSummary$TrainingJobName' => 'The name of the training job.
', 'StopTrainingJobRequest$TrainingJobName' => 'The name of the training job to stop.
', 'TrainingJob$TrainingJobName' => 'The name of the training job.
', 'TrainingJobSummary$TrainingJobName' => 'The name of the training job that you want a summary for.
', 'UpdateTrainingJobRequest$TrainingJobName' => 'The name of a training job to update the Debugger profiling configuration.
', 'WarmPoolStatus$ReusedByJob' => 'The name of the matching training job that reused the warm pool.
', ], ], 'TrainingJobSortByOptions' => [ 'base' => NULL, 'refs' => [ 'ListTrainingJobsForHyperParameterTuningJobRequest$SortBy' => 'The field to sort results by. The default is Name.
If the value of this field is FinalObjectiveMetricValue, any training jobs that did not return an objective metric are not listed.
The status of the training job.
SageMaker provides the following training job statuses:
InProgress - The training is in progress.
Completed - The training job has completed.
Failed - The training job has failed. To see the reason for the failure, see the FailureReason field in the response to a DescribeTrainingJobResponse call.
Stopping - The training job is stopping.
Stopped - The training job has stopped.
For more detailed information, see SecondaryStatus.
The status of the training job.
', 'ListTrainingJobsForHyperParameterTuningJobRequest$StatusEquals' => 'A filter that returns only training jobs with the specified status.
', 'ListTrainingJobsRequest$StatusEquals' => 'A filter that retrieves only training jobs with a specific status.
', 'TrainingJob$TrainingJobStatus' => 'The status of the training job.
Training job statuses are:
InProgress - The training is in progress.
Completed - The training job has completed.
Failed - The training job has failed. To see the reason for the failure, see the FailureReason field in the response to a DescribeTrainingJobResponse call.
Stopping - The training job is stopping.
Stopped - The training job has stopped.
For more detailed information, see SecondaryStatus.
The status of the training job.
', ], ], 'TrainingJobStatusCounter' => [ 'base' => NULL, 'refs' => [ 'TrainingJobStatusCounters$Completed' => 'The number of completed training jobs launched by the hyperparameter tuning job.
', 'TrainingJobStatusCounters$InProgress' => 'The number of in-progress training jobs launched by a hyperparameter tuning job.
', 'TrainingJobStatusCounters$RetryableError' => 'The number of training jobs that failed, but can be retried. A failed training job can be retried only if it failed because an internal service error occurred.
', 'TrainingJobStatusCounters$NonRetryableError' => 'The number of training jobs that failed and can\'t be retried. A failed training job can\'t be retried if it failed because a client error occurred.
', 'TrainingJobStatusCounters$Stopped' => 'The number of training jobs launched by a hyperparameter tuning job that were manually stopped.
', ], ], 'TrainingJobStatusCounters' => [ 'base' => 'The numbers of training jobs launched by a hyperparameter tuning job, categorized by status.
', 'refs' => [ 'DescribeHyperParameterTuningJobResponse$TrainingJobStatusCounters' => 'The TrainingJobStatusCounters object that specifies the number of training jobs, categorized by status, that this tuning job launched.
', 'HyperParameterTuningJobSearchEntity$TrainingJobStatusCounters' => NULL, 'HyperParameterTuningJobSummary$TrainingJobStatusCounters' => 'The TrainingJobStatusCounters object that specifies the numbers of training jobs, categorized by status, that this tuning job launched.
', ], ], 'TrainingJobStepMetadata' => [ 'base' => 'Metadata for a training job step.
', 'refs' => [ 'PipelineExecutionStepMetadata$TrainingJob' => 'The Amazon Resource Name (ARN) of the training job that was run by this step execution.
', ], ], 'TrainingJobSummaries' => [ 'base' => NULL, 'refs' => [ 'ListTrainingJobsResponse$TrainingJobSummaries' => 'An array of TrainingJobSummary objects, each listing a training job.
Provides summary information about a training job.
', 'refs' => [ 'TrainingJobSummaries$member' => NULL, ], ], 'TrainingRepositoryAccessMode' => [ 'base' => NULL, 'refs' => [ 'TrainingImageConfig$TrainingRepositoryAccessMode' => 'The method that your training job will use to gain access to the images in your private Docker registry. For access to an image in a private Docker registry, set to Vpc.
An object containing authentication information for a private Docker registry.
', 'refs' => [ 'TrainingImageConfig$TrainingRepositoryAuthConfig' => 'An object containing authentication information for a private Docker registry containing your training images.
', ], ], 'TrainingRepositoryCredentialsProviderArn' => [ 'base' => NULL, 'refs' => [ 'TrainingRepositoryAuthConfig$TrainingRepositoryCredentialsProviderArn' => 'The Amazon Resource Name (ARN) of an Amazon Web Services Lambda function used to give SageMaker access credentials to your private Docker registry.
', ], ], 'TrainingSpecification' => [ 'base' => 'Defines how the algorithm is used for a training job.
', 'refs' => [ 'CreateAlgorithmInput$TrainingSpecification' => 'Specifies details about training jobs run by this algorithm, including the following:
The Amazon ECR path of the container and the version digest of the algorithm.
The hyperparameters that the algorithm supports.
The instance types that the algorithm supports for training.
Whether the algorithm supports distributed training.
The metrics that the algorithm emits to Amazon CloudWatch.
Which metrics that the algorithm emits can be used as the objective metric for hyperparameter tuning jobs.
The input channels that the algorithm supports for training data. For example, an algorithm might support train, validation, and test channels.
Details about training jobs run by this algorithm.
', ], ], 'TrainingTimeInSeconds' => [ 'base' => NULL, 'refs' => [ 'DescribeTrainingJobResponse$TrainingTimeInSeconds' => 'The training time in seconds.
', 'TrainingJob$TrainingTimeInSeconds' => 'The training time in seconds.
', ], ], 'TransformDataSource' => [ 'base' => 'Describes the location of the channel data.
', 'refs' => [ 'TransformInput$DataSource' => 'Describes the location of the channel data, which is, the S3 location of the input data that the model can consume.
', ], ], 'TransformEnvironmentKey' => [ 'base' => NULL, 'refs' => [ 'TransformEnvironmentMap$key' => NULL, ], ], 'TransformEnvironmentMap' => [ 'base' => NULL, 'refs' => [ 'CreateTransformJobRequest$Environment' => 'The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
', 'DescribeTransformJobResponse$Environment' => 'The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
', 'TransformJob$Environment' => 'The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
', 'TransformJobDefinition$Environment' => 'The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
', ], ], 'TransformEnvironmentValue' => [ 'base' => NULL, 'refs' => [ 'TransformEnvironmentMap$value' => NULL, ], ], 'TransformInput' => [ 'base' => 'Describes the input source of a transform job and the way the transform job consumes it.
', 'refs' => [ 'CreateTransformJobRequest$TransformInput' => 'Describes the input source and the way the transform job consumes it.
', 'DescribeTransformJobResponse$TransformInput' => 'Describes the dataset to be transformed and the Amazon S3 location where it is stored.
', 'TransformJob$TransformInput' => NULL, 'TransformJobDefinition$TransformInput' => 'A description of the input source and the way the transform job consumes it.
', ], ], 'TransformInstanceCount' => [ 'base' => NULL, 'refs' => [ 'TransformResources$InstanceCount' => 'The number of ML compute instances to use in the transform job. The default value is 1, and the maximum is 100. For distributed transform jobs, specify a value greater than 1.
The ML compute instance type for the transform job. If you are using built-in algorithms to transform moderately sized datasets, we recommend using ml.m4.xlarge or ml.m5.largeinstance types.
A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.
', 'InferenceSpecification$SupportedTransformInstanceTypes' => 'A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.
This parameter is required for unversioned models, and optional for versioned models.
', ], ], 'TransformJob' => [ 'base' => 'A batch transform job. For information about SageMaker batch transform, see Use Batch Transform.
', 'refs' => [ 'ModelDashboardModel$LastBatchTransformJob' => NULL, 'TrialComponentSourceDetail$TransformJob' => 'Information about a transform job that\'s the source of a trial component.
', ], ], 'TransformJobArn' => [ 'base' => NULL, 'refs' => [ 'CreateTransformJobResponse$TransformJobArn' => 'The Amazon Resource Name (ARN) of the transform job.
', 'DescribeTransformJobResponse$TransformJobArn' => 'The Amazon Resource Name (ARN) of the transform job.
', 'TransformJob$TransformJobArn' => 'The Amazon Resource Name (ARN) of the transform job.
', 'TransformJobStepMetadata$Arn' => 'The Amazon Resource Name (ARN) of the transform job that was run by this step execution.
', 'TransformJobSummary$TransformJobArn' => 'The Amazon Resource Name (ARN) of the transform job.
', ], ], 'TransformJobDefinition' => [ 'base' => 'Defines the input needed to run a transform job using the inference specification specified in the algorithm.
', 'refs' => [ 'AlgorithmValidationProfile$TransformJobDefinition' => 'The TransformJobDefinition object that describes the transform job that SageMaker runs to validate your algorithm.
The TransformJobDefinition object that describes the transform job used for the validation of the model package.
The name of the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
', 'DescribeTransformJobRequest$TransformJobName' => 'The name of the transform job that you want to view details of.
', 'DescribeTransformJobResponse$TransformJobName' => 'The name of the transform job.
', 'StopTransformJobRequest$TransformJobName' => 'The name of the batch transform job to stop.
', 'TransformJob$TransformJobName' => 'The name of the transform job.
', 'TransformJobSummary$TransformJobName' => 'The name of the transform job.
', ], ], 'TransformJobStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeTransformJobResponse$TransformJobStatus' => 'The status of the transform job. If the transform job failed, the reason is returned in the FailureReason field.
A filter that retrieves only transform jobs with a specific status.
', 'TransformJob$TransformJobStatus' => 'The status of the transform job.
Transform job statuses are:
InProgress - The job is in progress.
Completed - The job has completed.
Failed - The transform job has failed. To see the reason for the failure, see the FailureReason field in the response to a DescribeTransformJob call.
Stopping - The transform job is stopping.
Stopped - The transform job has stopped.
The status of the transform job.
', ], ], 'TransformJobStepMetadata' => [ 'base' => 'Metadata for a transform job step.
', 'refs' => [ 'PipelineExecutionStepMetadata$TransformJob' => 'The Amazon Resource Name (ARN) of the transform job that was run by this step execution.
', ], ], 'TransformJobSummaries' => [ 'base' => NULL, 'refs' => [ 'ListTransformJobsResponse$TransformJobSummaries' => 'An array of TransformJobSummary objects.
Provides a summary of a transform job. Multiple TransformJobSummary objects are returned as a list after in response to a ListTransformJobs call.
Describes the results of a transform job.
', 'refs' => [ 'CreateTransformJobRequest$TransformOutput' => 'Describes the results of the transform job.
', 'DescribeTransformJobResponse$TransformOutput' => 'Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
', 'TransformJob$TransformOutput' => NULL, 'TransformJobDefinition$TransformOutput' => 'Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
', ], ], 'TransformResources' => [ 'base' => 'Describes the resources, including ML instance types and ML instance count, to use for transform job.
', 'refs' => [ 'CreateTransformJobRequest$TransformResources' => 'Describes the resources, including ML instance types and ML instance count, to use for the transform job.
', 'DescribeTransformJobResponse$TransformResources' => 'Describes the resources, including ML instance types and ML instance count, to use for the transform job.
', 'TransformJob$TransformResources' => NULL, 'TransformJobDefinition$TransformResources' => 'Identifies the ML compute instances for the transform job.
', ], ], 'TransformS3DataSource' => [ 'base' => 'Describes the S3 data source.
', 'refs' => [ 'TransformDataSource$S3DataSource' => 'The S3 location of the data source that is associated with a channel.
', ], ], 'TransformationAttributeName' => [ 'base' => NULL, 'refs' => [ 'AggregationTransformations$key' => NULL, 'FillingTransformations$key' => NULL, ], ], 'Trial' => [ 'base' => 'The properties of a trial as returned by the Search API.
', 'refs' => [ 'SearchRecord$Trial' => 'The properties of a trial.
', ], ], 'TrialArn' => [ 'base' => NULL, 'refs' => [ 'AssociateTrialComponentResponse$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', 'CreateTrialResponse$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', 'DeleteTrialResponse$TrialArn' => 'The Amazon Resource Name (ARN) of the trial that is being deleted.
', 'DescribeTrialResponse$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', 'DisassociateTrialComponentResponse$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', 'Trial$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', 'TrialSummary$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', 'UpdateTrialResponse$TrialArn' => 'The Amazon Resource Name (ARN) of the trial.
', ], ], 'TrialComponent' => [ 'base' => 'The properties of a trial component as returned by the Search API.
', 'refs' => [ 'SearchRecord$TrialComponent' => 'The properties of a trial component.
', ], ], 'TrialComponentArn' => [ 'base' => NULL, 'refs' => [ 'AssociateTrialComponentResponse$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'CreateTrialComponentResponse$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'DeleteTrialComponentResponse$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the component is being deleted.
', 'DescribeTrialComponentResponse$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'DisassociateTrialComponentResponse$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'TrialComponent$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'TrialComponentSimpleSummary$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'TrialComponentSummary$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', 'UpdateTrialComponentResponse$TrialComponentArn' => 'The Amazon Resource Name (ARN) of the trial component.
', ], ], 'TrialComponentArtifact' => [ 'base' => 'Represents an input or output artifact of a trial component. You specify TrialComponentArtifact as part of the InputArtifacts and OutputArtifacts parameters in the CreateTrialComponent request.
Examples of input artifacts are datasets, algorithms, hyperparameters, source code, and instance types. Examples of output artifacts are metrics, snapshots, logs, and images.
', 'refs' => [ 'TrialComponentArtifacts$value' => NULL, ], ], 'TrialComponentArtifactValue' => [ 'base' => NULL, 'refs' => [ 'TrialComponentArtifact$Value' => 'The location of the artifact.
', ], ], 'TrialComponentArtifacts' => [ 'base' => NULL, 'refs' => [ 'CreateTrialComponentRequest$InputArtifacts' => 'The input artifacts for the component. Examples of input artifacts are datasets, algorithms, hyperparameters, source code, and instance types.
', 'CreateTrialComponentRequest$OutputArtifacts' => 'The output artifacts for the component. Examples of output artifacts are metrics, snapshots, logs, and images.
', 'DescribeTrialComponentResponse$InputArtifacts' => 'The input artifacts of the component.
', 'DescribeTrialComponentResponse$OutputArtifacts' => 'The output artifacts of the component.
', 'TrialComponent$InputArtifacts' => 'The input artifacts of the component.
', 'TrialComponent$OutputArtifacts' => 'The output artifacts of the component.
', 'UpdateTrialComponentRequest$InputArtifacts' => 'Replaces all of the component\'s input artifacts with the specified artifacts or adds new input artifacts. Existing input artifacts are replaced if the trial component is updated with an identical input artifact key.
', 'UpdateTrialComponentRequest$OutputArtifacts' => 'Replaces all of the component\'s output artifacts with the specified artifacts or adds new output artifacts. Existing output artifacts are replaced if the trial component is updated with an identical output artifact key.
', ], ], 'TrialComponentKey256' => [ 'base' => NULL, 'refs' => [ 'ListTrialComponentKey256$member' => NULL, 'TrialComponentParameters$key' => NULL, ], ], 'TrialComponentKey64' => [ 'base' => NULL, 'refs' => [ 'TrialComponentArtifacts$key' => NULL, ], ], 'TrialComponentMetricSummaries' => [ 'base' => NULL, 'refs' => [ 'DescribeTrialComponentResponse$Metrics' => 'The metrics for the component.
', 'TrialComponent$Metrics' => 'The metrics for the component.
', ], ], 'TrialComponentMetricSummary' => [ 'base' => 'A summary of the metrics of a trial component.
', 'refs' => [ 'TrialComponentMetricSummaries$member' => NULL, ], ], 'TrialComponentParameterValue' => [ 'base' => 'The value of a hyperparameter. Only one of NumberValue or StringValue can be specified.
This object is specified in the CreateTrialComponent request.
', 'refs' => [ 'TrialComponentParameters$value' => NULL, ], ], 'TrialComponentParameters' => [ 'base' => NULL, 'refs' => [ 'CreateTrialComponentRequest$Parameters' => 'The hyperparameters for the component.
', 'DescribeTrialComponentResponse$Parameters' => 'The hyperparameters of the component.
', 'TrialComponent$Parameters' => 'The hyperparameters of the component.
', 'UpdateTrialComponentRequest$Parameters' => 'Replaces all of the component\'s hyperparameters with the specified hyperparameters or add new hyperparameters. Existing hyperparameters are replaced if the trial component is updated with an identical hyperparameter key.
', ], ], 'TrialComponentPrimaryStatus' => [ 'base' => NULL, 'refs' => [ 'TrialComponentStatus$PrimaryStatus' => 'The status of the trial component.
', ], ], 'TrialComponentSimpleSummaries' => [ 'base' => NULL, 'refs' => [ 'Trial$TrialComponentSummaries' => 'A list of the components associated with the trial. For each component, a summary of the component\'s properties is included.
', ], ], 'TrialComponentSimpleSummary' => [ 'base' => 'A short summary of a trial component.
', 'refs' => [ 'TrialComponentSimpleSummaries$member' => NULL, ], ], 'TrialComponentSource' => [ 'base' => 'The Amazon Resource Name (ARN) and job type of the source of a trial component.
', 'refs' => [ 'DescribeTrialComponentResponse$Source' => 'The Amazon Resource Name (ARN) of the source and, optionally, the job type.
', 'TrialComponent$Source' => 'The Amazon Resource Name (ARN) and job type of the source of the component.
', 'TrialComponentSimpleSummary$TrialComponentSource' => NULL, 'TrialComponentSources$member' => NULL, 'TrialComponentSummary$TrialComponentSource' => NULL, ], ], 'TrialComponentSourceArn' => [ 'base' => NULL, 'refs' => [ 'TrialComponentMetricSummary$SourceArn' => 'The Amazon Resource Name (ARN) of the source.
', 'TrialComponentSource$SourceArn' => 'The source Amazon Resource Name (ARN).
', 'TrialComponentSourceDetail$SourceArn' => 'The Amazon Resource Name (ARN) of the source.
', ], ], 'TrialComponentSourceDetail' => [ 'base' => 'Detailed information about the source of a trial component. Either ProcessingJob or TrainingJob is returned.
Details of the source of the component.
', ], ], 'TrialComponentSources' => [ 'base' => NULL, 'refs' => [ 'DescribeTrialComponentResponse$Sources' => 'A list of ARNs and, if applicable, job types for multiple sources of an experiment run.
', ], ], 'TrialComponentStatus' => [ 'base' => 'The status of the trial component.
', 'refs' => [ 'CreateTrialComponentRequest$Status' => 'The status of the component. States include:
InProgress
Completed
Failed
The status of the component. States include:
InProgress
Completed
Failed
The status of the component. States include:
InProgress
Completed
Failed
The new status of the component.
', ], ], 'TrialComponentStatusMessage' => [ 'base' => NULL, 'refs' => [ 'TrialComponentStatus$Message' => 'If the component failed, a message describing why.
', ], ], 'TrialComponentSummaries' => [ 'base' => NULL, 'refs' => [ 'ListTrialComponentsResponse$TrialComponentSummaries' => 'A list of the summaries of your trial components.
', ], ], 'TrialComponentSummary' => [ 'base' => 'A summary of the properties of a trial component. To get all the properties, call the DescribeTrialComponent API and provide the TrialComponentName.
The source of the trial.
', 'refs' => [ 'DescribeTrialResponse$Source' => 'The Amazon Resource Name (ARN) of the source and, optionally, the job type.
', 'Trial$Source' => NULL, 'TrialSummary$TrialSource' => NULL, ], ], 'TrialSourceArn' => [ 'base' => NULL, 'refs' => [ 'TrialSource$SourceArn' => 'The Amazon Resource Name (ARN) of the source.
', ], ], 'TrialSummaries' => [ 'base' => NULL, 'refs' => [ 'ListTrialsResponse$TrialSummaries' => 'A list of the summaries of your trials.
', ], ], 'TrialSummary' => [ 'base' => 'A summary of the properties of a trial. To get the complete set of properties, call the DescribeTrial API and provide the TrialName.
Time to live duration, where the record is hard deleted after the expiration time is reached; ExpiresAt = EventTime + TtlDuration. For information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
Time to live duration, where the record is hard deleted after the expiration time is reached; ExpiresAt = EventTime + TtlDuration. For information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
Time to live duration, where the record is hard deleted after the expiration time is reached; ExpiresAt = EventTime + TtlDuration. For information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
TtlDuration time unit.
TtlDuration time value.
The job completion criteria.
', 'refs' => [ 'HyperParameterTuningJobConfig$TuningJobCompletionCriteria' => 'The tuning job\'s completion criteria.
', ], ], 'TuningJobStepMetaData' => [ 'base' => 'Metadata for a tuning step.
', 'refs' => [ 'PipelineExecutionStepMetadata$TuningJob' => 'The Amazon Resource Name (ARN) of the tuning job that was run by this step execution.
', ], ], 'USD' => [ 'base' => 'Represents an amount of money in United States dollars.
', 'refs' => [ 'PublicWorkforceTaskPrice$AmountInUsd' => 'Defines the amount of money paid to an Amazon Mechanical Turk worker in United States dollars.
', ], ], 'UiConfig' => [ 'base' => 'Provided configuration information for the worker UI for a labeling job. Provide either HumanTaskUiArn or UiTemplateS3Uri.
For named entity recognition, 3D point cloud and video frame labeling jobs, use HumanTaskUiArn.
For all other Ground Truth built-in task types and custom task types, use UiTemplateS3Uri to specify the location of a worker task template in Amazon S3.
Information about the user interface that workers use to complete the labeling task.
', ], ], 'UiTemplate' => [ 'base' => 'The Liquid template for the worker user interface.
', 'refs' => [ 'CreateHumanTaskUiRequest$UiTemplate' => NULL, 'RenderUiTemplateRequest$UiTemplate' => 'A Template object containing the worker UI template to render.
Container for user interface template information.
', 'refs' => [ 'DescribeHumanTaskUiResponse$UiTemplate' => NULL, ], ], 'UpdateActionRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateActionResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateAppImageConfigRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateAppImageConfigResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateArtifactRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateArtifactResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateCodeRepositoryInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateCodeRepositoryOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateContextRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateContextResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateDeviceFleetRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateDevicesRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateDomainRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateDomainResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateEndpointInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateEndpointOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateEndpointWeightsAndCapacitiesInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateEndpointWeightsAndCapacitiesOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateFeatureGroupRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateFeatureGroupResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateFeatureMetadataRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateHubRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateHubResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateImageRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateImageResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateImageVersionRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateImageVersionResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateInferenceExperimentRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateInferenceExperimentResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateModelCardRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateModelCardResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateModelPackageInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateModelPackageOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateMonitoringAlertRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateMonitoringAlertResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateMonitoringScheduleRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateMonitoringScheduleResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateNotebookInstanceInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateNotebookInstanceLifecycleConfigInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateNotebookInstanceLifecycleConfigOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateNotebookInstanceOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdatePipelineExecutionRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdatePipelineExecutionResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdatePipelineRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdatePipelineResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateProjectInput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateProjectOutput' => [ 'base' => NULL, 'refs' => [], ], 'UpdateSpaceRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateSpaceResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateTrainingJobRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateTrainingJobResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateTrialComponentRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateTrialComponentResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateTrialRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateTrialResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateUserProfileRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateUserProfileResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateWorkforceRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateWorkforceResponse' => [ 'base' => NULL, 'refs' => [], ], 'UpdateWorkteamRequest' => [ 'base' => NULL, 'refs' => [], ], 'UpdateWorkteamResponse' => [ 'base' => NULL, 'refs' => [], ], 'Url' => [ 'base' => NULL, 'refs' => [ 'AutoMLContainerDefinition$ModelDataUrl' => 'The location of the model artifacts. For more information, see ContainerDefinition.
', 'ClarifyShapBaselineConfig$ShapBaselineUri' => 'The uniform resource identifier (URI) of the S3 bucket where the SHAP baseline file is stored. The format of the SHAP baseline file should be the same format as the format of the training dataset. For example, if the training dataset is in CSV format, and each record in the training dataset has four features, and all features are numerical, then the baseline file should also have this same format. Each record should contain only the features. If you are using a virtual private cloud (VPC), the ShapBaselineUri should be accessible to the VPC. For more information about setting up endpoints with Amazon Virtual Private Cloud, see Give SageMaker access to Resources in your Amazon Virtual Private Cloud.
The S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix). The S3 path is required for SageMaker built-in algorithms, but not if you use your own algorithms. For more information on built-in algorithms, see Common Parameters.
The model artifacts must be in an S3 bucket that is in the same region as the model or endpoint you are creating.
If you provide a value for this parameter, SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you provide. Amazon Web Services STS is activated in your Amazon Web Services account by default. If you previously deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see Activating and Deactivating Amazon Web Services STS in an Amazon Web Services Region in the Amazon Web Services Identity and Access Management User Guide.
If you use a built-in algorithm to create a model, SageMaker requires that you provide a S3 path to the model artifacts in ModelDataUrl.
The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
The model artifacts must be in an S3 bucket that is in the same region as the model package.
The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
The model artifacts must be in an S3 bucket that is in the same Amazon Web Services region as the algorithm.
Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
', 'refs' => [ 'AssociationSummary$CreatedBy' => NULL, 'DescribeActionResponse$CreatedBy' => NULL, 'DescribeActionResponse$LastModifiedBy' => NULL, 'DescribeArtifactResponse$CreatedBy' => NULL, 'DescribeArtifactResponse$LastModifiedBy' => NULL, 'DescribeContextResponse$CreatedBy' => NULL, 'DescribeContextResponse$LastModifiedBy' => NULL, 'DescribeExperimentResponse$CreatedBy' => 'Who created the experiment.
', 'DescribeExperimentResponse$LastModifiedBy' => 'Who last modified the experiment.
', 'DescribeLineageGroupResponse$CreatedBy' => NULL, 'DescribeLineageGroupResponse$LastModifiedBy' => NULL, 'DescribeModelCardResponse$CreatedBy' => NULL, 'DescribeModelCardResponse$LastModifiedBy' => NULL, 'DescribeModelPackageGroupOutput$CreatedBy' => NULL, 'DescribeModelPackageOutput$CreatedBy' => NULL, 'DescribeModelPackageOutput$LastModifiedBy' => NULL, 'DescribePipelineExecutionResponse$CreatedBy' => NULL, 'DescribePipelineExecutionResponse$LastModifiedBy' => NULL, 'DescribePipelineResponse$CreatedBy' => NULL, 'DescribePipelineResponse$LastModifiedBy' => NULL, 'DescribeProjectOutput$CreatedBy' => NULL, 'DescribeProjectOutput$LastModifiedBy' => NULL, 'DescribeTrialComponentResponse$CreatedBy' => 'Who created the trial component.
', 'DescribeTrialComponentResponse$LastModifiedBy' => 'Who last modified the component.
', 'DescribeTrialResponse$CreatedBy' => 'Who created the trial.
', 'DescribeTrialResponse$LastModifiedBy' => 'Who last modified the trial.
', 'Experiment$CreatedBy' => 'Who created the experiment.
', 'Experiment$LastModifiedBy' => NULL, 'ModelCard$CreatedBy' => NULL, 'ModelCard$LastModifiedBy' => NULL, 'ModelDashboardModelCard$CreatedBy' => NULL, 'ModelDashboardModelCard$LastModifiedBy' => NULL, 'ModelPackage$CreatedBy' => 'Information about the user who created or modified an experiment, trial, trial component, lineage group, or project.
', 'ModelPackage$LastModifiedBy' => 'Information about the user who created or modified an experiment, trial, trial component, lineage group, or project.
', 'ModelPackageGroup$CreatedBy' => NULL, 'Pipeline$CreatedBy' => NULL, 'Pipeline$LastModifiedBy' => NULL, 'PipelineExecution$CreatedBy' => NULL, 'PipelineExecution$LastModifiedBy' => NULL, 'Project$CreatedBy' => 'Who created the project.
', 'Project$LastModifiedBy' => NULL, 'Trial$CreatedBy' => 'Who created the trial.
', 'Trial$LastModifiedBy' => NULL, 'TrialComponent$CreatedBy' => 'Who created the trial component.
', 'TrialComponent$LastModifiedBy' => NULL, 'TrialComponentSimpleSummary$CreatedBy' => NULL, 'TrialComponentSummary$CreatedBy' => 'Who created the trial component.
', 'TrialComponentSummary$LastModifiedBy' => 'Who last modified the component.
', ], ], 'UserProfileArn' => [ 'base' => NULL, 'refs' => [ 'CreateUserProfileResponse$UserProfileArn' => 'The user profile Amazon Resource Name (ARN).
', 'DescribeUserProfileResponse$UserProfileArn' => 'The user profile Amazon Resource Name (ARN).
', 'UpdateUserProfileResponse$UserProfileArn' => 'The user profile Amazon Resource Name (ARN).
', ], ], 'UserProfileDetails' => [ 'base' => 'The user profile details.
', 'refs' => [ 'UserProfileList$member' => NULL, ], ], 'UserProfileList' => [ 'base' => NULL, 'refs' => [ 'ListUserProfilesResponse$UserProfiles' => 'The list of user profiles.
', ], ], 'UserProfileName' => [ 'base' => NULL, 'refs' => [ 'AppDetails$UserProfileName' => 'The user profile name.
', 'CreateAppRequest$UserProfileName' => 'The user profile name. If this value is not set, then SpaceName must be set.
The name of the UserProfile to sign-in as.
', 'CreateUserProfileRequest$UserProfileName' => 'A name for the UserProfile. This value is not case sensitive.
', 'DeleteAppRequest$UserProfileName' => 'The user profile name. If this value is not set, then SpaceName must be set.
The user profile name.
', 'DescribeAppRequest$UserProfileName' => 'The user profile name. If this value is not set, then SpaceName must be set.
The user profile name.
', 'DescribeUserProfileRequest$UserProfileName' => 'The user profile name. This value is not case sensitive.
', 'DescribeUserProfileResponse$UserProfileName' => 'The user profile name.
', 'ListAppsRequest$UserProfileNameEquals' => 'A parameter to search by user profile name. If SpaceNameEquals is set, then this value cannot be set.
A parameter by which to filter the results.
', 'UpdateUserProfileRequest$UserProfileName' => 'The user profile name.
', 'UserProfileDetails$UserProfileName' => 'The user profile name.
', ], ], 'UserProfileSortKey' => [ 'base' => NULL, 'refs' => [ 'ListUserProfilesRequest$SortBy' => 'The parameter by which to sort the results. The default is CreationTime.
', ], ], 'UserProfileStatus' => [ 'base' => NULL, 'refs' => [ 'DescribeUserProfileResponse$Status' => 'The status.
', 'UserProfileDetails$Status' => 'The status.
', ], ], 'UserSettings' => [ 'base' => 'A collection of settings that apply to users of Amazon SageMaker Studio. These settings are specified when the CreateUserProfile API is called, and as DefaultUserSettings when the CreateDomain API is called.
SecurityGroups is aggregated when specified in both calls. For all other settings in UserSettings, the values specified in CreateUserProfile take precedence over those specified in CreateDomain.
The default settings to use to create a user profile when UserSettings isn\'t specified in the call to the CreateUserProfile API.
SecurityGroups is aggregated when specified in both calls. For all other settings in UserSettings, the values specified in CreateUserProfile take precedence over those specified in CreateDomain.
A collection of settings.
', 'DescribeDomainResponse$DefaultUserSettings' => 'Settings which are applied to UserProfiles in this domain if settings are not explicitly specified in a given UserProfile.
', 'DescribeUserProfileResponse$UserSettings' => 'A collection of settings.
', 'UpdateDomainRequest$DefaultUserSettings' => 'A collection of settings.
', 'UpdateUserProfileRequest$UserSettings' => 'A collection of settings.
', ], ], 'UsersPerStep' => [ 'base' => NULL, 'refs' => [ 'Stairs$UsersPerStep' => 'Specifies how many new users to spawn in each step.
', ], ], 'UtilizationMetric' => [ 'base' => NULL, 'refs' => [ 'RecommendationMetrics$CpuUtilization' => 'The expected CPU utilization at maximum invocations per minute for the instance.
NaN indicates that the value is not available.
The expected memory utilization at maximum invocations per minute for the instance.
NaN indicates that the value is not available.
The percentage of how much utilization you want an instance to use before autoscaling. The default value is 50%.
', 'GetScalingConfigurationRecommendationResponse$TargetCpuUtilizationPerCore' => 'The percentage of how much utilization you want an instance to use before autoscaling, which you specified in the request. The default value is 50%.
', ], ], 'ValidationFraction' => [ 'base' => NULL, 'refs' => [ 'AutoMLDataSplitConfig$ValidationFraction' => 'The validation fraction (optional) is a float that specifies the portion of the training dataset to be used for validation. The default value is 0.2, and values must be greater than 0 and less than 1. We recommend setting this value to be less than 0.5.
', ], ], 'VariantName' => [ 'base' => NULL, 'refs' => [ 'DesiredWeightAndCapacity$VariantName' => 'The name of the variant to update.
', 'PendingProductionVariantSummary$VariantName' => 'The name of the variant.
', 'ProductionVariant$VariantName' => 'The name of the production variant.
', 'ProductionVariantSummary$VariantName' => 'The name of the variant.
', ], ], 'VariantProperty' => [ 'base' => 'Specifies a production variant property type for an Endpoint.
If you are updating an endpoint with the RetainAllVariantProperties option of UpdateEndpointInput set to true, the VariantProperty objects listed in the ExcludeRetainedVariantProperties parameter of UpdateEndpointInput override the existing variant properties of the endpoint.
When you are updating endpoint resources with RetainAllVariantProperties, whose value is set to true, ExcludeRetainedVariantProperties specifies the list of type VariantProperty to override with the values provided by EndpointConfig. If you don\'t specify a value for ExcludeRetainedVariantProperties, no variant properties are overridden.
The type of variant property. The supported values are:
DesiredInstanceCount: Overrides the existing variant instance counts using the InitialInstanceCount values in the ProductionVariants of CreateEndpointConfig.
DesiredWeight: Overrides the existing variant weights using the InitialVariantWeight values in the ProductionVariants of CreateEndpointConfig.
DataCaptureConfig: (Not currently supported.)
The endpoint variant status which describes the current deployment stage status or operational status.
Creating: Creating inference resources for the production variant.
Deleting: Terminating inference resources for the production variant.
Updating: Updating capacity for the production variant.
ActivatingTraffic: Turning on traffic for the production variant.
Baking: Waiting period to monitor the CloudWatch alarms in the automatic rollback configuration.
A message that describes the status of the production variant.
', ], ], 'VariantWeight' => [ 'base' => NULL, 'refs' => [ 'DesiredWeightAndCapacity$DesiredWeight' => 'The variant\'s weight.
', 'PendingProductionVariantSummary$CurrentWeight' => 'The weight associated with the variant.
', 'PendingProductionVariantSummary$DesiredWeight' => 'The requested weight for the variant in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the CreateEndpointConfig operation.
', 'ProductionVariant$InitialVariantWeight' => 'Determines initial traffic distribution among all of the models that you specify in the endpoint configuration. The traffic to a production variant is determined by the ratio of the VariantWeight to the sum of all VariantWeight values across all ProductionVariants. If unspecified, it defaults to 1.0.
The weight associated with the variant.
', 'ProductionVariantSummary$DesiredWeight' => 'The requested weight, as specified in the UpdateEndpointWeightsAndCapacities request.
Configuration for your vector collection type.
', 'refs' => [ 'CollectionConfig$VectorConfig' => 'Configuration for your vector collection type.
Dimension: The number of elements in your vector.
The stability of the image version, specified by the maintainer.
NOT_PROVIDED: The maintainers did not provide a status for image version stability.
STABLE: The image version is stable.
TO_BE_ARCHIVED: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.
ARCHIVED: The image version is archived. Archived image versions are not searchable and are no longer actively supported.
The stability of the image version specified by the maintainer.
NOT_PROVIDED: The maintainers did not provide a status for image version stability.
STABLE: The image version is stable.
TO_BE_ARCHIVED: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.
ARCHIVED: The image version is archived. Archived image versions are not searchable and are no longer actively supported.
The availability of the image version specified by the maintainer.
NOT_PROVIDED: The maintainers did not provide a status for image version stability.
STABLE: The image version is stable.
TO_BE_ARCHIVED: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.
ARCHIVED: The image version is archived. Archived image versions are not searchable and are no longer actively supported.
Version Id of the pipeline definition file. If not specified, Amazon SageMaker will retrieve the latest version.
', ], ], 'VersionedArnOrName' => [ 'base' => NULL, 'refs' => [ 'ContainerDefinition$ModelPackageName' => 'The name or Amazon Resource Name (ARN) of the model package to use to create the model.
', 'DeleteModelPackageInput$ModelPackageName' => 'The name or Amazon Resource Name (ARN) of the model package to delete.
When you specify a name, the name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
', 'DescribeModelPackageInput$ModelPackageName' => 'The name or Amazon Resource Name (ARN) of the model package to describe.
When you specify a name, the name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
', ], ], 'Vertex' => [ 'base' => 'A lineage entity connected to the starting entity(ies).
', 'refs' => [ 'Vertices$member' => NULL, ], ], 'Vertices' => [ 'base' => NULL, 'refs' => [ 'QueryLineageResponse$Vertices' => 'A list of vertices connected to the start entity(ies) in the lineage graph.
', ], ], 'VolumeSizeInGB' => [ 'base' => NULL, 'refs' => [ 'HyperParameterTuningInstanceConfig$VolumeSizeInGB' => 'The volume size in GB of the data to be processed for hyperparameter optimization (optional).
', 'ResourceConfig$VolumeSizeInGB' => 'The size of the ML storage volume that you want to provision.
ML storage volumes store model artifacts and incremental states. Training algorithms might also use the ML storage volume for scratch space. If you want to store the training data in the ML storage volume, choose File as the TrainingInputMode in the algorithm specification.
When using an ML instance with NVMe SSD volumes, SageMaker doesn\'t provision Amazon EBS General Purpose SSD (gp2) storage. Available storage is fixed to the NVMe-type instance\'s storage capacity. SageMaker configures storage paths for training datasets, checkpoints, model artifacts, and outputs to use the entire capacity of the instance storage. For example, ML instance families with the NVMe-type instance storage include ml.p4d, ml.g4dn, and ml.g5.
When using an ML instance with the EBS-only storage option and without instance storage, you must define the size of EBS volume through VolumeSizeInGB in the ResourceConfig API. For example, ML instance families that use EBS volumes include ml.c5 and ml.p2.
To look up instance types and their instance storage types and volumes, see Amazon EC2 Instance Types.
To find the default local paths defined by the SageMaker training platform, see Amazon SageMaker Training Storage Folders for Training Datasets, Checkpoints, Model Artifacts, and Outputs.
', ], ], 'VpcConfig' => [ 'base' => 'Specifies a VPC that your training jobs and hosted models have access to. Control access to and from your training and model containers by configuring the VPC. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud and Protect Training Jobs by Using an Amazon Virtual Private Cloud.
', 'refs' => [ 'AutoMLSecurityConfig$VpcConfig' => 'The VPC configuration.
', 'CreateModelInput$VpcConfig' => 'A VpcConfig object that specifies the VPC that you want your model to connect to. Control access to and from your model container by configuring the VPC. VpcConfig is used in hosting services and in batch transform. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud and Protect Data in Batch Transform Jobs by Using an Amazon Virtual Private Cloud.
A VpcConfig object that specifies the VPC that you want your training job to connect to. Control access to and from your training container by configuring the VPC. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
', 'DescribeModelOutput$VpcConfig' => 'A VpcConfig object that specifies the VPC that this model has access to. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud
', 'DescribeTrainingJobResponse$VpcConfig' => 'A VpcConfig object that specifies the VPC that this training job has access to. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
', 'HyperParameterTrainingJobDefinition$VpcConfig' => 'The VpcConfig object that specifies the VPC that you want the training jobs that this hyperparameter tuning job launches to connect to. Control access to and from your training container by configuring the VPC. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
', 'LabelingJobResourceConfig$VpcConfig' => NULL, 'Model$VpcConfig' => NULL, 'MonitoringNetworkConfig$VpcConfig' => NULL, 'NetworkConfig$VpcConfig' => NULL, 'TrainingJob$VpcConfig' => 'A VpcConfig object that specifies the VPC that this training job has access to. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
', ], ], 'VpcId' => [ 'base' => NULL, 'refs' => [ 'CreateDomainRequest$VpcId' => 'The ID of the Amazon Virtual Private Cloud (VPC) that Studio uses for communication.
', 'DescribeDomainResponse$VpcId' => 'The ID of the Amazon Virtual Private Cloud (VPC) that Studio uses for communication.
', ], ], 'VpcSecurityGroupIds' => [ 'base' => NULL, 'refs' => [ 'VpcConfig$SecurityGroupIds' => 'The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
The length of the baking period, during which SageMaker monitors alarms for each batch on the new fleet.
', 'TrafficRoutingConfig$WaitIntervalInSeconds' => 'The waiting time (in seconds) between incremental steps to turn on traffic on the new endpoint fleet.
', ], ], 'WarmPoolResourceStatus' => [ 'base' => NULL, 'refs' => [ 'ListTrainingJobsRequest$WarmPoolStatusEquals' => 'A filter that retrieves only training jobs with a specific warm pool status.
', 'WarmPoolStatus$Status' => 'The status of the warm pool.
InUse: The warm pool is in use for the training job.
Available: The warm pool is available to reuse for a matching training job.
Reused: The warm pool moved to a matching training job for reuse.
Terminated: The warm pool is no longer available. Warm pools are unavailable if they are terminated by a user, terminated for a patch update, or terminated for exceeding the specified KeepAlivePeriodInSeconds.
Status and billing information about the warm pool.
', 'refs' => [ 'DescribeTrainingJobResponse$WarmPoolStatus' => 'The status of the warm pool associated with the training job.
', 'TrainingJobSummary$WarmPoolStatus' => 'The status of the warm pool associated with the training job.
', ], ], 'Workforce' => [ 'base' => 'A single private workforce, which is automatically created when you create your first private work team. You can create one private work force in each Amazon Web Services Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
', 'refs' => [ 'DescribeWorkforceResponse$Workforce' => 'A single private workforce, which is automatically created when you create your first private work team. You can create one private work force in each Amazon Web Services Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
', 'UpdateWorkforceResponse$Workforce' => 'A single private workforce. You can create one private work force in each Amazon Web Services Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
', 'Workforces$member' => NULL, ], ], 'WorkforceArn' => [ 'base' => NULL, 'refs' => [ 'CreateWorkforceResponse$WorkforceArn' => 'The Amazon Resource Name (ARN) of the workforce.
', 'Workforce$WorkforceArn' => 'The Amazon Resource Name (ARN) of the private workforce.
', 'Workteam$WorkforceArn' => 'The Amazon Resource Name (ARN) of the workforce.
', ], ], 'WorkforceFailureReason' => [ 'base' => NULL, 'refs' => [ 'Workforce$FailureReason' => 'The reason your workforce failed.
', ], ], 'WorkforceName' => [ 'base' => NULL, 'refs' => [ 'CreateWorkforceRequest$WorkforceName' => 'The name of the private workforce.
', 'CreateWorkteamRequest$WorkforceName' => 'The name of the workforce.
', 'DeleteWorkforceRequest$WorkforceName' => 'The name of the workforce.
', 'DescribeWorkforceRequest$WorkforceName' => 'The name of the private workforce whose access you want to restrict. WorkforceName is automatically set to default when a workforce is created and cannot be modified.
A filter you can use to search for workforces using part of the workforce name.
', 'UpdateWorkforceRequest$WorkforceName' => 'The name of the private workforce that you want to update. You can find your workforce name by using the ListWorkforces operation.
', 'Workforce$WorkforceName' => 'The name of the private workforce.
', ], ], 'WorkforceSecurityGroupId' => [ 'base' => NULL, 'refs' => [ 'WorkforceSecurityGroupIds$member' => NULL, ], ], 'WorkforceSecurityGroupIds' => [ 'base' => NULL, 'refs' => [ 'WorkforceVpcConfigRequest$SecurityGroupIds' => 'The VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be for the same VPC as specified in the subnet.
', 'WorkforceVpcConfigResponse$SecurityGroupIds' => 'The VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be for the same VPC as specified in the subnet.
', ], ], 'WorkforceStatus' => [ 'base' => NULL, 'refs' => [ 'Workforce$Status' => 'The status of your workforce.
', ], ], 'WorkforceSubnetId' => [ 'base' => NULL, 'refs' => [ 'WorkforceSubnets$member' => NULL, ], ], 'WorkforceSubnets' => [ 'base' => NULL, 'refs' => [ 'WorkforceVpcConfigRequest$Subnets' => 'The ID of the subnets in the VPC that you want to connect.
', 'WorkforceVpcConfigResponse$Subnets' => 'The ID of the subnets in the VPC that you want to connect.
', ], ], 'WorkforceVpcConfigRequest' => [ 'base' => 'The VPC object you use to create or update a workforce.
', 'refs' => [ 'CreateWorkforceRequest$WorkforceVpcConfig' => 'Use this parameter to configure a workforce using VPC.
', 'UpdateWorkforceRequest$WorkforceVpcConfig' => 'Use this parameter to update your VPC configuration for a workforce.
', ], ], 'WorkforceVpcConfigResponse' => [ 'base' => 'A VpcConfig object that specifies the VPC that you want your workforce to connect to.
', 'refs' => [ 'Workforce$WorkforceVpcConfig' => 'The configuration of a VPC workforce.
', ], ], 'WorkforceVpcEndpointId' => [ 'base' => NULL, 'refs' => [ 'WorkforceVpcConfigResponse$VpcEndpointId' => 'The IDs for the VPC service endpoints of your VPC workforce when it is created and updated.
', ], ], 'WorkforceVpcId' => [ 'base' => NULL, 'refs' => [ 'WorkforceVpcConfigRequest$VpcId' => 'The ID of the VPC that the workforce uses for communication.
', 'WorkforceVpcConfigResponse$VpcId' => 'The ID of the VPC that the workforce uses for communication.
', ], ], 'Workforces' => [ 'base' => NULL, 'refs' => [ 'ListWorkforcesResponse$Workforces' => 'A list containing information about your workforce.
', ], ], 'WorkspaceSettings' => [ 'base' => 'The workspace settings for the SageMaker Canvas application.
', 'refs' => [ 'CanvasAppSettings$WorkspaceSettings' => 'The workspace settings for the SageMaker Canvas application.
', ], ], 'Workteam' => [ 'base' => 'Provides details about a labeling work team.
', 'refs' => [ 'DescribeWorkteamResponse$Workteam' => 'A Workteam instance that contains information about the work team.
A Workteam object that describes the updated work team.
The Amazon Resource Name (ARN) of the work team. You can use this ARN to identify the work team.
', 'DescribeSubscribedWorkteamRequest$WorkteamArn' => 'The Amazon Resource Name (ARN) of the subscribed work team to describe.
', 'HumanLoopConfig$WorkteamArn' => 'Amazon Resource Name (ARN) of a team of workers. To learn more about the types of workforces and work teams you can create and use with Amazon A2I, see Create and Manage Workforces.
', 'HumanTaskConfig$WorkteamArn' => 'The Amazon Resource Name (ARN) of the work team assigned to complete the tasks.
', 'LabelingJobSummary$WorkteamArn' => 'The Amazon Resource Name (ARN) of the work team assigned to the job.
', 'ListLabelingJobsForWorkteamRequest$WorkteamArn' => 'The Amazon Resource Name (ARN) of the work team for which you want to see labeling jobs for.
', 'SubscribedWorkteam$WorkteamArn' => 'The Amazon Resource Name (ARN) of the vendor that you have subscribed.
', 'Workteam$WorkteamArn' => 'The Amazon Resource Name (ARN) that identifies the work team.
', ], ], 'WorkteamName' => [ 'base' => NULL, 'refs' => [ 'CreateWorkteamRequest$WorkteamName' => 'The name of the work team. Use this name to identify the work team.
', 'DeleteWorkteamRequest$WorkteamName' => 'The name of the work team to delete.
', 'DescribeWorkteamRequest$WorkteamName' => 'The name of the work team to return a description of.
', 'ListSubscribedWorkteamsRequest$NameContains' => 'A string in the work team name. This filter returns only work teams whose name contains the specified string.
', 'ListWorkteamsRequest$NameContains' => 'A string in the work team\'s name. This filter returns only work teams whose name contains the specified string.
', 'UpdateWorkteamRequest$WorkteamName' => 'The name of the work team to update.
', 'Workteam$WorkteamName' => 'The name of the work team.
', ], ], 'Workteams' => [ 'base' => NULL, 'refs' => [ 'ListWorkteamsResponse$Workteams' => 'An array of Workteam objects, each describing a work team.