chore(schema): update (#3706)

Co-authored-by: github-actions <github-actions@github.com>

samtranslator/schema/schema.json

@@ -207629,8 +207629,6 @@
       "additionalProperties": false,
       "properties": {
         "AvailabilityStatus": {
-          "markdownDescription": "The availaiblity status of a visual's menu options.",
-          "title": "AvailabilityStatus",
           "type": "string"
         }
       },
@@ -224569,7 +224567,7 @@
               "type": "boolean"
             },
             "EnableHttpEndpoint": {
-              "markdownDescription": "Specifies whether to enable the HTTP endpoint for the DB cluster. By default, the HTTP endpoint isn't enabled.\n\nWhen enabled, the HTTP endpoint provides a connectionless web service API (RDS Data API) for running SQL queries on the DB cluster. You can also query your database from inside the RDS console with the RDS query editor.\n\nRDS Data API is supported with the following DB clusters:\n\n- Aurora PostgreSQL Serverless v2 and provisioned\n- Aurora PostgreSQL and Aurora MySQL Serverless v1\n\nFor more information, see [Using RDS Data API](https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/data-api.html) in the *Amazon Aurora User Guide* .\n\nValid for Cluster Type: Aurora DB clusters only",
+              "markdownDescription": "Specifies whether to enable the HTTP endpoint for the DB cluster. By default, the HTTP endpoint isn't enabled.\n\nWhen enabled, the HTTP endpoint provides a connectionless web service API (RDS Data API) for running SQL queries on the DB cluster. You can also query your database from inside the RDS console with the RDS query editor.\n\nFor more information, see [Using RDS Data API](https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/data-api.html) in the *Amazon Aurora User Guide* .\n\nValid for Cluster Type: Aurora DB clusters only",
               "title": "EnableHttpEndpoint",
               "type": "boolean"
             },
@@ -248169,7 +248167,7 @@
           "title": "ModelAccessConfig"
         },
         "S3DataType": {
-          "markdownDescription": "If you choose `S3Prefix` , `S3Uri` identifies a key name prefix. SageMaker uses all objects that match the specified key name prefix for model training.\n\nIf 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.\n\nIf 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` .",
+          "markdownDescription": "If you choose `S3Prefix` , `S3Uri` identifies a key name prefix. SageMaker uses all objects that match the specified key name prefix for model training.\n\nIf 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.\n\nIf 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` .",
           "title": "S3DataType",
           "type": "string"
         },
@@ -250635,7 +250633,7 @@
           "type": "string"
         },
         "Image": {
-          "markdownDescription": "The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.\n\nIf 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](https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html) .",
+          "markdownDescription": "The Amazon EC2 Container Registry path where inference code is stored.\n\nIf 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](https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html) .",
           "title": "Image",
           "type": "string"
         },
@@ -250724,7 +250722,7 @@
       "additionalProperties": false,
       "properties": {
         "S3DataType": {
-          "markdownDescription": "If you choose `S3Prefix` , `S3Uri` identifies a key name prefix. SageMaker uses all objects that match the specified key name prefix for model training.\n\nIf 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.\n\nIf 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` .",
+          "markdownDescription": "If you choose `S3Prefix` , `S3Uri` identifies a key name prefix. SageMaker uses all objects that match the specified key name prefix for model training.\n\nIf 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.\n\nIf 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` .",
           "title": "S3DataType",
           "type": "string"
         },