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+ + + + + + + + + + \ No newline at end of file diff --git a/v0.2.1/api/builder/index.html b/v0.2.1/api/builder/index.html new file mode 100644 index 0000000..0b41c09 --- /dev/null +++ b/v0.2.1/api/builder/index.html @@ -0,0 +1,2706 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + Dataloader Builder - Loadax Documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + Skip to content + + +
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DataloaderBuilder

+

Most of the time, you just want to create a dataloader, set a few options, and be done with it. The DataloaderBuilder is a convenient way to do this. It is a fluent builder that allows you to chain together methods to create a dataloader instead of configuring each option individually.

+
Creating a dataloader
from loadax import DataloaderBuilder, InMemoryDataset, Batcher
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+batcher = Batcher(lambda x: x)
+dataloader = DataloaderBuilder(batcher).batch_size(2).build(dataset)
+
+for batch in dataloader:
+    print(batch)
+
+#> [1, 2]
+#> [3, 4]
+#> [5]
+
+ + +
+ + + + +
+

+ Bases: Generic[DatasetItem, Batch]

+ + +

A dataloader is a primitive for efficiently loading data from a dataset.

+

A dataloader is effectively a smart iterator that optimizes getting data from the +dataset. The dataloader is responsible for ensuring the data is batched, ready +when it is needed, and loaded into mmemory in a way that is efficient. All of this +should be done without hijacking the main thread and preventing you from doing the +important parts of your training loop.

+

The dataloader is built by chaining methods on the DataLoader class. The +methods are designed to be chained in a fluent style, allowing you to build +a dataloader with the desired configuration.

+ + +
+ Example + 
from loadax import DataloaderBuilder, InMemoryDataset, Batcher
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+batcher = Batcher(lambda x: x)
+dataloader = DataloaderBuilder(batcher).batch_size(2).build(dataset)
+iterator = iter(dataloader)
+for batch in iterator:
+    print(batch)
+
+#> [1, 2]
+#> [3, 4]
+#> [5]
+
+
+ +

Attributes:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameTypeDescription
batcher + Batcher + +
+

The batcher to use for batching.

+
+
strategy + BatchStrategy + +
+

The batch strategy to use for computing batches.

+
+
num_workers + int + +
+

The number of workers to use for parallel data loading.

+
+
prefetch_factor + int + +
+

The prefetch factor to use for prefetching.

+
+
sharding_strategy + JaxShardingStrategy + +
+

The sharding strategy to use for +distributed data loading.

+
+
shard_id + int + +
+

The ID of the shard to load the data from.

+
+
num_shards + int + +
+

The number of shards to distribute the data across.

+
+
+ +

A dataloader is effectively a smart iterator that optimizes getting data from +the dataset. The dataloader is responsible for ensuring the data is batched, +ready when it is needed, and loaded into mmemory in a way that is efficient. +All of this should be done without hijacking the main thread and preventing you +from doing the important parts of your training loop.

+

The dataloader is built by chaining methods on the DataLoader class. The +methods are designed to be chained in a fluent style, allowing you to build +a dataloader with the desired configuration.

+ + +

Parameters:

+ + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
batcher + Batcher + +
+

The batcher to use for batching.

+
+ 		+ required +
+ +
+ Source code in src/loadax/dataloader/builder.py + 
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def __init__(self, batcher: Batcher[DatasetItem, Batch]):
+    """A dataloader is a primitive for efficiently loading data from a dataset.
+
+    A dataloader is effectively a smart iterator that optimizes getting data from
+    the dataset. The dataloader is responsible for ensuring the data is batched,
+    ready when it is needed, and loaded into mmemory in a way that is efficient.
+    All of this should be done without hijacking the main thread and preventing you
+    from doing the important parts of your training loop.
+
+    The dataloader is built by chaining methods on the `DataLoader` class. The
+    methods are designed to be chained in a fluent style, allowing you to build
+    a dataloader with the desired configuration.
+
+    Args:
+        batcher (Batcher): The batcher to use for batching.
+    """
+    self.batcher = batcher
+
+
+ + + +
+ + + + + + + + + +
+ + +

+ batch_size + + +

+
batch_size(batch_size: int) -> DataloaderBuilder[DatasetItem, Batch]
+
+ +
+ +

Set the batch size for the dataloader.

+

This method sets the batch size for the dataloader. The batch size is the +number of items to include in a batch. The batch size should be a multiple +of the number of workers, otherwise the dataloader will not be able to +prefetch batches efficiently.

+

Currently, the dataloader only supports fixed batch sizes. This means that +with the exception of the last batch, all other batches will have the same +size. This may change in the future with the introduction of dynamic batch +sizes.

+ + +
+ Example + 
from loadax import DataloaderBuilder, InMemoryDataset, Batcher
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+batcher = Batcher(lambda x: x)
+dataloader = DataloaderBuilder(batcher).batch_size(2).build(dataset)
+iterator = iter(dataloader)
+for batch in iterator:
+    print(batch)
+
+#> [1, 2]
+#> [3, 4]
+#> [5]
+
+
+ +

Parameters:

+ + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
batch_size + int + +
+

The batch size to use for the dataloader.

+
+ 		+ required +
+ + +

Returns:

+ + + + + + + + + + + + + +
Name TypeDescription
Dataloader + DataloaderBuilder[DatasetItem, Batch] + +
+

The dataloader with the batch size set.

+
+
+ +
+ Source code in src/loadax/dataloader/builder.py + 
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def batch_size(self, batch_size: int) -> "DataloaderBuilder[DatasetItem, Batch]":
+    """Set the batch size for the dataloader.
+
+    This method sets the batch size for the dataloader. The batch size is the
+    number of items to include in a batch. The batch size should be a multiple
+    of the number of workers, otherwise the dataloader will not be able to
+    prefetch batches efficiently.
+
+    Currently, the dataloader only supports fixed batch sizes. This means that
+    with the exception of the last batch, all other batches will have the same
+    size. This may change in the future with the introduction of dynamic batch
+    sizes.
+
+    Example:
+        ```python
+        from loadax import DataloaderBuilder, InMemoryDataset, Batcher
+
+        dataset = InMemoryDataset([1, 2, 3, 4, 5])
+        batcher = Batcher(lambda x: x)
+        dataloader = DataloaderBuilder(batcher).batch_size(2).build(dataset)
+        iterator = iter(dataloader)
+        for batch in iterator:
+            print(batch)
+
+        #> [1, 2]
+        #> [3, 4]
+        #> [5]
+        ```
+
+    Args:
+        batch_size (int): The batch size to use for the dataloader.
+
+    Returns:
+        Dataloader: The dataloader with the batch size set.
+    """
+    self.strategy = FixedBatchStrategy(batch_size)
+    return self
+
+
+
+ +
+ +
+ + +

+ workers + + +

+
workers(num_workers: int) -> DataloaderBuilder[DatasetItem, Batch]
+
+ +
+ +

Set the number of workers for the dataloader.

+

This method sets the number of workers for the dataloader. The number of +workers determines the number of parallel threads that will be used to +load data. The number of workers should be a multiple of the batch size, +otherwise the dataloader will not be able to prefetch batches efficiently.

+ + +
+ Example + 
from loadax import DataloaderBuilder, InMemoryDataset, Batcher
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+batcher = Batcher(lambda x: x)
+dataloader = DataloaderBuilder(batcher)
+                .batch_size(2)
+                .workers(2)
+                .build(dataset)
+iterator = iter(dataloader)
+for batch in iterator:
+    print(batch)
+
+#> [1, 2]
+#> [3, 4]
+#> [5]
+
+
+ +

Parameters:

+ + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
num_workers + int + +
+

The number of workers to use for the dataloader.

+
+ 		+ required +
+ + +

Returns:

+ + + + + + + + + + + + + +
Name TypeDescription
Dataloader + DataloaderBuilder[DatasetItem, Batch] + +
+

The dataloader with the number of workers set.

+
+
+ +
+ Source code in src/loadax/dataloader/builder.py + 
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def workers(self, num_workers: int) -> "DataloaderBuilder[DatasetItem, Batch]":
+    """Set the number of workers for the dataloader.
+
+    This method sets the number of workers for the dataloader. The number of
+    workers determines the number of parallel threads that will be used to
+    load data. The number of workers should be a multiple of the batch size,
+    otherwise the dataloader will not be able to prefetch batches efficiently.
+
+    Example:
+        ```python
+        from loadax import DataloaderBuilder, InMemoryDataset, Batcher
+
+        dataset = InMemoryDataset([1, 2, 3, 4, 5])
+        batcher = Batcher(lambda x: x)
+        dataloader = DataloaderBuilder(batcher)
+                        .batch_size(2)
+                        .workers(2)
+                        .build(dataset)
+        iterator = iter(dataloader)
+        for batch in iterator:
+            print(batch)
+
+        #> [1, 2]
+        #> [3, 4]
+        #> [5]
+        ```
+
+    Args:
+        num_workers (int): The number of workers to use for the dataloader.
+
+    Returns:
+        Dataloader: The dataloader with the number of workers set.
+    """
+    self.num_workers = num_workers
+    return self
+
+
+
+ +
+ +
+ + +

+ prefetch + + +

+
prefetch(factor: int) -> DataloaderBuilder[DatasetItem, Batch]
+
+ +
+ +

Set the prefetch factor for the dataloader.

+

This method sets the prefetch factor for the dataloader. The prefetch +factor determines the number of batches to prefetch ahead of time. The +prefetch factor is a multiplier and should be a multiple of the number +of workers, otherwise the dataloader will not be able to prefetch batches +efficiently.

+ + +
+ Example + 
from loadax import DataloaderBuilder, InMemoryDataset, Batcher
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+batcher = Batcher(lambda x: x)
+dataloader = DataloaderBuilder(batcher)
+                .batch_size(2)
+                .prefetch(2)
+                .build(dataset)
+iterator = iter(dataloader)
+for batch in iterator:
+    print(batch)
+
+#> [1, 2]
+#> [3, 4]
+#> [5]
+
+
+ +

Parameters:

+ + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
factor + int + +
+

The prefetch factor to use for the dataloader.

+
+ 		+ required +
+ + +

Returns:

+ + + + + + + + + + + + + +
Name TypeDescription
Dataloader + DataloaderBuilder[DatasetItem, Batch] + +
+

The dataloader with the prefetch factor set.

+
+
+ +
+ Source code in src/loadax/dataloader/builder.py + 
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def prefetch(self, factor: int) -> "DataloaderBuilder[DatasetItem, Batch]":
+    """Set the prefetch factor for the dataloader.
+
+    This method sets the prefetch factor for the dataloader. The prefetch
+    factor determines the number of batches to prefetch ahead of time. The
+    prefetch factor is a multiplier and should be a multiple of the number
+    of workers, otherwise the dataloader will not be able to prefetch batches
+    efficiently.
+
+    Example:
+        ```python
+        from loadax import DataloaderBuilder, InMemoryDataset, Batcher
+
+        dataset = InMemoryDataset([1, 2, 3, 4, 5])
+        batcher = Batcher(lambda x: x)
+        dataloader = DataloaderBuilder(batcher)
+                        .batch_size(2)
+                        .prefetch(2)
+                        .build(dataset)
+        iterator = iter(dataloader)
+        for batch in iterator:
+            print(batch)
+
+        #> [1, 2]
+        #> [3, 4]
+        #> [5]
+        ```
+
+    Args:
+        factor (int): The prefetch factor to use for the dataloader.
+
+    Returns:
+        Dataloader: The dataloader with the prefetch factor set.
+    """
+    self.prefetch_factor = factor if factor > 0 else 1
+    return self
+
+
+
+ +
+ +
+ + +

+ shard + + +

+
shard(mesh: Mesh, data_axis_name: str | None = None, num_shards: int | None = None, shard_id: int | None = None) -> DataloaderBuilder[DatasetItem, Batch]
+
+ +
+ +

Set the mesh and partition spec for the dataloader.

+

This will distribute the dataloading across multiple nodes within the same +distributed network. This is useful for training large models on multiple +nodes. You can then load the data into multiple devices on each node and +train the model in parallel.

+ + +
+ Example + 
from loadax import DataloaderBuilder, InMemoryDataset, Batcher
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+batcher = Batcher(lambda x: x)
+dataloader = DataloaderBuilder(batcher)
+                    .batch_size(2)
+                    .shard(mesh, data_axis_name='data')
+                    .build(dataset)
+iterator = iter(dataloader)
+for batch in iterator:
+    print(batch)
+
+#> [1, 2]
+#> [3, 4]
+#> [5]
+
+
+ +

Parameters:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
mesh + Mesh + +
+

The mesh to use for sharding.

+
+ 		+ required +
data_axis_name + str | None + +
+

The name of the data axis to use for sharding.

+
+ 		+ None +
num_shards + int + +
+

The number of shards to distribute the data across. +If not specified, the dataloader will choose automatically using +jax.process_count().

+
+ 		+ None +
shard_id + int + +
+

The ID of the shard to load the data from. +If not specified, the dataloader will choose automatically using +jax.process_index().

+
+ 		+ None +
+ + +

Returns:

+ + + + + + + + + + + + + +
Name TypeDescription
Dataloader + DataloaderBuilder[DatasetItem, Batch] + +
+

The dataloader with the mesh and partition spec set.

+
+
+ +
+ Source code in src/loadax/dataloader/builder.py + 
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def shard(
+    self,
+    mesh: Mesh,
+    data_axis_name: str | None = None,
+    num_shards: int | None = None,
+    shard_id: int | None = None,
+) -> "DataloaderBuilder[DatasetItem, Batch]":
+    """Set the mesh and partition spec for the dataloader.
+
+    This will distribute the dataloading across multiple nodes within the same
+    distributed network. This is useful for training large models on multiple
+    nodes. You can then load the data into multiple devices on each node and
+    train the model in parallel.
+
+    Example:
+        ```python
+        from loadax import DataloaderBuilder, InMemoryDataset, Batcher
+
+        dataset = InMemoryDataset([1, 2, 3, 4, 5])
+        batcher = Batcher(lambda x: x)
+        dataloader = DataloaderBuilder(batcher)
+                            .batch_size(2)
+                            .shard(mesh, data_axis_name='data')
+                            .build(dataset)
+        iterator = iter(dataloader)
+        for batch in iterator:
+            print(batch)
+
+        #> [1, 2]
+        #> [3, 4]
+        #> [5]
+        ```
+
+    Args:
+        mesh (Mesh): The mesh to use for sharding.
+        data_axis_name (str | None): The name of the data axis to use for sharding.
+        num_shards (int): The number of shards to distribute the data across.
+            If not specified, the dataloader will choose automatically using
+            jax.process_count().
+        shard_id (int): The ID of the shard to load the data from.
+            If not specified, the dataloader will choose automatically using
+            jax.process_index().
+
+    Returns:
+        Dataloader: The dataloader with the mesh and partition spec set.
+    """
+    if num_shards and num_shards <= 1:
+        self.sharding_strategy = NoShardingStrategy()
+    else:
+        self.sharding_strategy = DistributedShardingStrategy(
+            mesh, data_shard_axis=data_axis_name
+        )
+    self.shard_id = shard_id
+    self.num_shards = num_shards
+    return self
+
+
+
+ +
+ +
+ + +

+ build + + +

+
build(dataset: Dataset[DatasetItem]) -> Dataloader[DatasetItem, Batch]
+
+ +
+ +

Construct the dataloader from the current configuration.

+

This method constructs the dataloader from the current configuration. The +dataloader is constructed based on the current configuration of the dataloader. +If the dataloader is not configured to use multiprocessing, it will use the +naive dataloader. If the dataloader is configured to use multiprocessing, it +will use the multiprocessing dataloader.

+

The default configuration of the dataloader is to use a fixed batch size of +1 and to use a single worker. This means that there is not parallelism in +loading the data, but the data will still be prefetched with 2 batches in +advance on the single worker. This is a good default configuration for most +use cases, unless you have a fast training loop and potentially many devices.

+ + +
+ Example + 
from loadax import DataloaderBuilder, InMemoryDataset, Batcher
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+batcher = Batcher(lambda x: x)
+dataloader = DataloaderBuilder(batcher)
+                .batch_size(2)
+                .workers(2)
+                .build(dataset)
+iterator = iter(dataloader)
+for batch in iterator:
+    print(batch)
+
+#> [1, 2]
+#> [3, 4]
+#> [5]
+
+
+ +

Parameters:

+ + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
dataset + Dataset + +
+

The dataset to load data from.

+
+ 		+ required +
+ + +

Returns:

+ + + + + + + + + + + + + +
Name TypeDescription
Dataloader + Dataloader[DatasetItem, Batch] + +
+

The dataloader constructed from the current configuration.

+
+
+ +
+ Source code in src/loadax/dataloader/builder.py + 
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def build(self, dataset: Dataset[DatasetItem]) -> Dataloader[DatasetItem, Batch]:
+    """Construct the dataloader from the current configuration.
+
+    This method constructs the dataloader from the current configuration. The
+    dataloader is constructed based on the current configuration of the dataloader.
+    If the dataloader is not configured to use multiprocessing, it will use the
+    naive dataloader. If the dataloader is configured to use multiprocessing, it
+    will use the multiprocessing dataloader.
+
+    The default configuration of the dataloader is to use a fixed batch size of
+    1 and to use a single worker. This means that there is not parallelism in
+    loading the data, but the data will still be prefetched with 2 batches in
+    advance on the single worker. This is a good default configuration for most
+    use cases, unless you have a fast training loop and potentially many devices.
+
+    Example:
+        ```python
+        from loadax import DataloaderBuilder, InMemoryDataset, Batcher
+
+        dataset = InMemoryDataset([1, 2, 3, 4, 5])
+        batcher = Batcher(lambda x: x)
+        dataloader = DataloaderBuilder(batcher)
+                        .batch_size(2)
+                        .workers(2)
+                        .build(dataset)
+        iterator = iter(dataloader)
+        for batch in iterator:
+            print(batch)
+
+        #> [1, 2]
+        #> [3, 4]
+        #> [5]
+        ```
+
+    Args:
+        dataset (Dataset): The dataset to load data from.
+
+    Returns:
+        Dataloader: The dataloader constructed from the current configuration.
+    """
+    strategy = self.strategy if self.strategy else FixedBatchStrategy(1)
+
+    return Dataloader(
+        dataset=dataset,
+        strategy=strategy,
+        batcher=self.batcher,
+        num_workers=self.num_workers or 1,
+        prefetch_factor=self.prefetch_factor or 1,
+        sharding_strategy=self.sharding_strategy,
+        shard_id=self.shard_id,
+        num_shards=self.num_shards,
+    )
+
+
+
+ +
+ + + +
+ +
+ +
+ + + + + + + + + + + + + + + +
+
+ + + + + +
+ + + +
+ + + +
+
+
+
+ +
+ + + + + + + + + + \ No newline at end of file diff --git a/v0.2.1/api/dataset/dataset/index.html b/v0.2.1/api/dataset/dataset/index.html new file mode 100644 index 0000000..cc5732e --- /dev/null +++ b/v0.2.1/api/dataset/dataset/index.html @@ -0,0 +1,1845 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + Dataset - Loadax Documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + Skip to content + + +
+
+ + + +
+ + + + + + +
+ + +
+ +
+ + + + + + + + + +
+
+ + + +
+
+
+ + + + + + + +
+
+
+ + + +
+
+
+ + + + + +
+
+
+ + + +
+
+ + + + + + + + +

Dataset

+

A dataset is a simple interface that defines how to load data from a source. All datasets must implement this +interface, and it is the responsibility of the dataset to load the data from the underlying source. Because +datasets support random access, they should also know their size.

+
Creating a dataset
from loadax import Dataset
+
+class MyDataset(Dataset[int]):
+    def __init__(self, items: list[int]):
+        self.items = items
+
+    def get(self, index: int) -> int:
+        return self.items[index]
+
+    def __len__(self) -> int:
+        return len(self.items)
+
+dataset = MyDataset([1, 2, 3, 4, 5])
+
+for i in range(len(dataset)):
+    print(dataset.get(i))
+
+#> 1
+#> 2
+#> 3
+#> 4
+#> 5
+
+ + +
+ + + + +
+

+ Bases: ABC, Generic[DatasetItem]

+ + +

Dataset is a protocol for datasets.

+

Any loadax dataset must implement the Dataset protocol. This protocol defines the +basic functionality needed for a random access dataset. This includes the ability +to get an item at a given index, as well as the ability to iterate over the dataset.

+ + +
+ Example + 
from loadax import InMemoryDataset
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+print(dataset.get(0))
+
+#> 1
+
+
+ +

Attributes:

+ + + + + + + + + + + + + + + + + + + + +
NameTypeDescription
dataset + Dataset + +
+

The dataset to iterate over.

+
+
current + int + +
+

The current index of the iterator.

+
+
+ +

Any loadax dataset must implement the Dataset protocol. This protocol defines +thebasic functionality needed for a random access dataset. This includes the +ability to get an item at a given index, as well as the ability to iterate over +the dataset.

+ + +
+ Example + 
from loadax import InMemoryDataset
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+print(dataset.get(0))
+
+#> 1
+
+
+
+ Source code in src/loadax/dataset/protocol.py + 
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def __init__(self) -> None:
+    """Dataset is a protocol for datasets.
+
+    Any loadax dataset must implement the Dataset protocol. This protocol defines
+    thebasic functionality needed for a random access dataset. This includes the
+    ability to get an item at a given index, as well as the ability to iterate over
+    the dataset.
+
+    Example:
+        ```python
+        from loadax import InMemoryDataset
+
+        dataset = InMemoryDataset([1, 2, 3, 4, 5])
+        print(dataset.get(0))
+
+        #> 1
+        ```
+    """
+    raise NotImplementedError
+
+
+ + + +
+ + + + + + + + + +
+ + +

+ get + + + + abstractmethod + + +

+
get(index: int) -> DatasetItem | None
+
+ +
+ +

Get the item at the given index.

+

This method returns the item at the given index in the dataset. If the +index is negative, it respects python's negative indexing semantics. +If the index is out of bounds, it returns None.

+ + +
+ Example + 
from loadax import InMemoryDataset
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+print(dataset.get(0))
+
+#> 1
+
+
+ +

Parameters:

+ + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
index + int + +
+

The index of the item to get.

+
+ 		+ required +
+ + +

Returns:

+ + + + + + + + + + + + + +
TypeDescription
+ DatasetItem | None + +
+

DatasetItem | None: The item at the given index, or None if the index is +out of bounds.

+
+
+ +
+ Source code in src/loadax/dataset/protocol.py + 
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@abstractmethod
+def get(self, index: int) -> DatasetItem | None:
+    """Get the item at the given index.
+
+    This method returns the item at the given index in the dataset. If the
+    index is negative, it respects python's negative indexing semantics.
+    If the index is out of bounds, it returns None.
+
+    Example:
+        ```python
+        from loadax import InMemoryDataset
+
+        dataset = InMemoryDataset([1, 2, 3, 4, 5])
+        print(dataset.get(0))
+
+        #> 1
+        ```
+
+    Args:
+        index (int): The index of the item to get.
+
+    Returns:
+        DatasetItem | None: The item at the given index, or None if the index is
+            out of bounds.
+    """
+    raise NotImplementedError
+
+
+
+ +
+ +
+ + +

+ is_empty + + +

+
is_empty() -> bool
+
+ +
+ +

Check if the dataset is empty.

+

This method returns True if the dataset is empty, and False otherwise.

+ + +
+ Example + 
from loadax import InMemoryDataset
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+print(dataset.is_empty())
+
+#> False
+
+
+ +

Returns:

+ + + + + + + + + + + + + +
Name TypeDescription
bool + bool + +
+

True if the dataset is empty, and False otherwise.

+
+
+ +
+ Source code in src/loadax/dataset/protocol.py + 
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def is_empty(self) -> bool:
+    """Check if the dataset is empty.
+
+    This method returns True if the dataset is empty, and False otherwise.
+
+    Example:
+        ```python
+        from loadax import InMemoryDataset
+
+        dataset = InMemoryDataset([1, 2, 3, 4, 5])
+        print(dataset.is_empty())
+
+        #> False
+        ```
+
+    Returns:
+        bool: True if the dataset is empty, and False otherwise.
+    """
+    return len(self) == 0
+
+
+
+ +
+ + + +
+ +
+ +
+ + + + + + + + + + + + + + + +
+
+ + + + + +
+ + + +
+ + + +
+
+
+
+ +
+ + + + + + + + + + \ No newline at end of file diff --git a/v0.2.1/api/dataset/in-memory/index.html b/v0.2.1/api/dataset/in-memory/index.html new file mode 100644 index 0000000..5399f8c --- /dev/null +++ b/v0.2.1/api/dataset/in-memory/index.html @@ -0,0 +1,1729 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + InMemoryDataset - Loadax Documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + Skip to content + + +
+
+ + + +
+ + + + + + +
+ + +
+ +
+ + + + + + + + + +
+
+ + + +
+
+
+ + + + + + + +
+
+
+ + + +
+
+
+ + + + + +
+
+
+ + + +
+
+ + + + + + + + +

InMemoryDataset

+

The InMemoryDataset is a simple dataset that stores all underlying items in a list in memory. This is a simple +dataset and is only useful for small datasets and debugging.

+
Creating an in-memory dataset
from loadax import InMemoryDataset
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+
+for i in range(len(dataset)):
+    print(dataset.get(i))
+
+#> 1
+#> 2
+#> 3
+#> 4
+#> 5
+
+ + +
+ + + + +
+

+ Bases: Dataset[DatasetItem]

+ + +

InMemoryDataset is a simple in-memory dataset.

+

This dataset stores all underlying items in a list in memory. This is a simple +implementation, in your training loop if you are using non-trivial dataset +it is better to use another dataset. This dataset type does not get much benefit +from dataloaders, but it is useful for debugging and for simple use cases.

+ + +
+ Example +
+
+
+

dataset = InMemoryDataset([1, 2, 3, 4, 5]) +print(dataset.get(0))

+
+
+
+
+ +

Attributes:

+ + + + + + + + + + + + + + + +
NameTypeDescription
items + list[DatasetItem] + +
+

The underlying items in the dataset.

+
+
+ +

This dataset stores all underlying items in a list in memory. This is a simple +implementation, in your training loop if you are using non-trivial dataset +it is better to use another dataset. This dataset type does not get much benefit +from dataloaders, but it is useful for debugging and for simple use cases.

+ + +
+ Example +
+
+
+

dataset = InMemoryDataset([1, 2, 3, 4, 5]) +print(dataset.get(0))

+
+
+
+
+ +

Parameters:

+ + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
items + list[DatasetItem] + +
+

The underlying items in the dataset.

+
+ 		+ required +
+ +
+ Source code in src/loadax/dataset/in_memory.py + 
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def __init__(self, items: list[DatasetItem]):
+    """InMemoryDataset is a simple in-memory dataset.
+
+    This dataset stores all underlying items in a list in memory. This is a simple
+    implementation, in your training loop if you are using non-trivial dataset
+    it is better to use another dataset. This dataset type does not get much benefit
+    from dataloaders, but it is useful for debugging and for simple use cases.
+
+    Example:
+        >>> dataset = InMemoryDataset([1, 2, 3, 4, 5])
+        >>> print(dataset.get(0))
+
+    Args:
+        items (list[DatasetItem]): The underlying items in the dataset.
+    """
+    self.items = items
+
+
+ + + +
+ + + + + + + + + +
+ + +

+ get + + +

+
get(index: int) -> DatasetItem | None
+
+ +
+ +

Get the item at the given index.

+

This method returns the item at the given index in the dataset. If the +index is negative, it respects python's negative indexing semantics. +If the index is out of bounds, it returns None.

+ + +
+ Example +
+
+
+

dataset = InMemoryDataset([1, 2, 3, 4, 5]) +print(dataset.get(0))

+
+
+
+
+ +

Parameters:

+ + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
index + int + +
+

The index of the item to get.

+
+ 		+ required +
+ + +

Returns:

+ + + + + + + + + + + + + +
TypeDescription
+ DatasetItem | None + +
+

DatasetItem | None: The item at the given index, or None if the index is +out of bounds.

+
+
+ +
+ Source code in src/loadax/dataset/in_memory.py + 
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def get(self, index: int) -> DatasetItem | None:
+    """Get the item at the given index.
+
+    This method returns the item at the given index in the dataset. If the
+    index is negative, it respects python's negative indexing semantics.
+    If the index is out of bounds, it returns None.
+
+    Example:
+        >>> dataset = InMemoryDataset([1, 2, 3, 4, 5])
+        >>> print(dataset.get(0))
+
+    Args:
+        index (int): The index of the item to get.
+
+    Returns:
+        DatasetItem | None: The item at the given index, or None if the index is
+            out of bounds.
+    """
+    if index >= len(self.items):
+        return None
+
+    if index < 0:
+        index = len(self.items) + index
+    return self.items[index]
+
+
+
+ +
+ + + +
+ +
+ +
+ + + + + + + + + + + + + + + +
+
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+ + + + + + + + + + \ No newline at end of file diff --git a/v0.2.1/api/dataset/integration/huggingface/index.html b/v0.2.1/api/dataset/integration/huggingface/index.html new file mode 100644 index 0000000..679e9f9 --- /dev/null +++ b/v0.2.1/api/dataset/integration/huggingface/index.html @@ -0,0 +1,1922 @@ + + + + + + + + + + + + + + + + + + + + + + + + + HuggingFace - Loadax Documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + Skip to content + + +
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Huggingface Integration

+

Loadax provides integration with Huggingface Datasets. This integration allows you to load datasets from the Huggingface hub and use them with loadax.

+

Loading a Dataset

+

To load a dataset from the Huggingface hub, you can use the from_hub method of the HuggingFaceDataset class. This method takes in the path to the dataset on the Huggingface hub, the name of the dataset, and the split of the dataset. The dataset is lazily loaded from the Huggingface cache.

+
from loadax.dataset.huggingface import HuggingFaceDataset
+
+dataset = HuggingFaceDataset.from_hub("stanfordnlp/imdb", split="train")
+
+

Alternatively, you can construct a HuggingFaceDataset object directly from a Huggingface Dataset object. This is useful if you want to do some preprocessing and store the results in the Huggingface dataset cache.

+
from loadax.dataset.huggingface import HuggingFaceDataset
+import datasets as hf_datasets
+
+train_data = hf_datasets.load_dataset("stanfordnlp/imdb", split="train")
+train_dataset = HuggingFaceDataset(train_data)
+
+

Sharding a Dataset

+

Currently, leveraging the Huggingface native sharding functionality is not supported. This is a work in progress, +loadax will support it in the future, but for now avoid dataset.shard and use the ShardingStrategy interface +or allow DataloaderBuilder to automatically shard the dataset. This is because huggingface's sharding algorithm is +not guaranteed to be consistent with the sharding strategy that loadax leverages to optimize for JAX's device +placement.

+ + +
+ + + + +
+

+ Bases: Dataset[DatasetItem]

+ + +

Huggingface Dataset Integration.

+ + +

Parameters:

+ + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
dataset + Dataset + +
+

Huggingface Dataset

+
+ 		+ required +
+ + + +

Parameters:

+ + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
dataset + Dataset + +
+

Huggingface Dataset

+
+ 		+ required +
+ +
+ Source code in src/loadax/dataset/huggingface/dataset.py + 
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def __init__(self, dataset: datasets.Dataset) -> None:
+    """Create a loadax datset from a Huggingface Dataset.
+
+    Args:
+        dataset: Huggingface Dataset
+    """
+    self.dataset = dataset
+
+
+ + + +
+ + + + + + + + + +
+ + +

+ get + + +

+
get(index: int) -> DatasetItem | None
+
+ +
+ +

Get the item at the given index.

+ + +

Examples:

+ 
from loadax.dataset.huggingface import HuggingFaceDataset
+import datasets as hf_datasets
+
+train_data = hf_datasets.load_dataset("stanfordnlp/imdb", split="train")
+
+train_dataset = HuggingFaceDataset(train_data)
+
+data = train_dataset.get(0)
+print(data)
+
+

Args: + index: The index of the item to get.

+ + +

Returns:

+ + + + + + + + + + + + + + + + + +
TypeDescription
+ DatasetItem | None + +
+

DatasetItem | None: The item at the given index, or None if the value cannot

+
+
+ DatasetItem | None + +
+

be resolved.

+
+
+ +
+ Source code in src/loadax/dataset/huggingface/dataset.py + 
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def get(self, index: int) -> DatasetItem | None:
+    """Get the item at the given index.
+
+    Examples:
+        ```python
+        from loadax.dataset.huggingface import HuggingFaceDataset
+        import datasets as hf_datasets
+
+        train_data = hf_datasets.load_dataset("stanfordnlp/imdb", split="train")
+
+        train_dataset = HuggingFaceDataset(train_data)
+
+        data = train_dataset.get(0)
+        print(data)
+        ```
+    Args:
+        index: The index of the item to get.
+
+    Returns:
+        DatasetItem | None: The item at the given index, or None if the value cannot
+        be resolved.
+    """
+    item: DatasetItem | None = self.dataset[index]
+    return item
+
+
+
+ +
+ +
+ + +

+ from_hub + + + + staticmethod + + +

+
from_hub(path: str, name: str | None = None, split: str | None = None, *, trust_remote_code: bool = False) -> HuggingFaceDataset[DatasetItem]
+
+ +
+ +

Load a loadax dataset from the HuggingFace hub.

+ + +

Parameters:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
path + str + +
+

The path to the dataset on the HuggingFace hub.

+
+ 		+ required +
name + str | None + +
+

The name of the dataset on the HuggingFace hub.

+
+ 		+ None +
split + str | None + +
+

The split of the dataset on the HuggingFace hub.

+
+ 		+ None +
trust_remote_code + bool + +
+

Whether to trust the remote code.

+
+ 		+ False +
+ + +

Returns:

+ + + + + + + + + + + + + +
TypeDescription
+ HuggingFaceDataset[DatasetItem] + +
+

HuggingFaceDataset[DatasetItem]: The loadax dataset.

+
+
+ + +
+ Example + 
from loadax.dataset.huggingface import HuggingFaceDataset
+
+dataset = HuggingFaceDataset.from_hub("stanfordnlp/imdb")
+
+
+
+ Source code in src/loadax/dataset/huggingface/dataset.py + 
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@staticmethod
+def from_hub(
+    path: str,
+    name: str | None = None,
+    split: str | None = None,
+    *,
+    trust_remote_code: bool = False,
+) -> "HuggingFaceDataset[DatasetItem]":
+    """Load a loadax dataset from the HuggingFace hub.
+
+    Args:
+        path: The path to the dataset on the HuggingFace hub.
+        name: The name of the dataset on the HuggingFace hub.
+        split: The split of the dataset on the HuggingFace hub.
+        trust_remote_code: Whether to trust the remote code.
+
+    Returns:
+        HuggingFaceDataset[DatasetItem]: The loadax dataset.
+
+    Example:
+        ```python
+        from loadax.dataset.huggingface import HuggingFaceDataset
+
+        dataset = HuggingFaceDataset.from_hub("stanfordnlp/imdb")
+        ```
+    """
+    dataset = datasets.load_dataset(
+        path=path, name=name, split=split, trust_remote_code=trust_remote_code
+    )
+
+    dataset.set_format(type="numpy")
+
+    assert isinstance(
+        dataset, datasets.Dataset
+    ), f"loaded dataset must be a Dataset, got {type(dataset)}"
+
+    return HuggingFaceDataset[DatasetItem](dataset)
+
+
+
+ +
+ + + +
+ +
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+ + + + + + + + + + \ No newline at end of file diff --git a/v0.2.1/api/dataset/range/index.html b/v0.2.1/api/dataset/range/index.html new file mode 100644 index 0000000..25c6da8 --- /dev/null +++ b/v0.2.1/api/dataset/range/index.html @@ -0,0 +1,1717 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + RangeDataset - Loadax Documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + Skip to content + + +
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+ + + + + + + + +

RangeDataset

+

The RangeDataset is a simple dataset that returns a range of integers. This is useful for testing and debugging.

+
Creating a range dataset
from loadax import RangeDataset
+
+dataset = RangeDataset(start=0, end=10, step=2)
+
+for i in range(len(dataset)):
+    print(dataset.get(i))
+
+#> 0
+#> 2
+#> 4
+#> 6
+#> 8
+
+ + +
+ + + + +
+

+ Bases: Dataset[int]

+ + +

Dataset that returns a range of integers.

+

This dataset is useful for testing and debugging.

+ + +

Attributes:

+ + + + + + + + + + + + + + + + + + + + + + + + + +
NameTypeDescription
start + +
+

The start of the range.

+
+
end + +
+

The end of the range.

+
+
step + +
+

The step size of the range.

+
+
+ +

This dataset is useful for testing and debugging.

+ + +

Parameters:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
start + int + +
+

The start of the range.

+
+ 		+ required +
end + int + +
+

The end of the range.

+
+ 		+ required +
step + int + +
+

The step size of the range.

+
+ 		+ 1 +
+ +
+ Source code in src/loadax/dataset/range.py + 
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def __init__(self, start: int, end: int, step: int = 1):
+    """Dataset that returns a range of integers.
+
+    This dataset is useful for testing and debugging.
+
+    Args:
+        start: The start of the range.
+        end: The end of the range.
+        step: The step size of the range.
+    """
+    self.start = start
+    self.end = end
+    self.step = step
+
+    if self.start >= self.end:
+        raise ValueError("start must be less than end")
+    if self.step <= 0:
+        raise ValueError("step must be greater than 0")
+
+
+ + + +
+ + + + + + + + + +
+ + +

+ get + + +

+
get(index: int) -> int | None
+
+ +
+ +

Get the item at the given index.

+ + +

Parameters:

+ + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
index + int + +
+

The index of the item to get.

+
+ 		+ required +
+ + +

Returns:

+ + + + + + + + + + + + + +
TypeDescription
+ int | None + +
+

The item at the given index, or None if the index is out of range.

+
+
+ +
+ Source code in src/loadax/dataset/range.py + 
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def get(self, index: int) -> int | None:
+    """Get the item at the given index.
+
+    Args:
+        index: The index of the item to get.
+
+    Returns:
+        The item at the given index, or None if the index is out of range.
+    """
+    if index < 0:
+        index = len(self) + index
+
+    if 0 <= index < len(self):
+        return self.start + index * self.step
+
+    return None
+
+
+
+ +
+ + + +
+ +
+ +
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+ + + + + + + + + + \ No newline at end of file diff --git a/v0.2.1/api/dataset/transformations/combined/index.html b/v0.2.1/api/dataset/transformations/combined/index.html new file mode 100644 index 0000000..63884ee --- /dev/null +++ b/v0.2.1/api/dataset/transformations/combined/index.html @@ -0,0 +1,1705 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + CombinedDataset - Loadax Documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + Skip to content + + +
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+ + + + + + + + +

CombinedDataset

+

A combined dataset is a simple dataset that combines multiple underlying datasets. The combined dataset will return the items from the first underlying dataset, then the items from the second underlying dataset, and so on.

+
Creating a combined dataset
from loadax import CombinedDataset, InMemoryDataset
+
+dataset1 = InMemoryDataset([1, 2, 3, 4, 5])
+dataset2 = InMemoryDataset([6, 7, 8, 9, 10])
+combined_dataset = CombinedDataset(dataset1, dataset2)
+
+for i in range(len(combined_dataset)):
+    print(combined_dataset.get(i))
+
+#> 1
+#> 2
+#> 3
+#> 4
+#> 5
+#> 6
+#> 7
+#> 8
+#> 9
+#> 10
+
+ + +
+ + + + +
+

+ Bases: Dataset[DatasetItem]

+ + +

Combine multiple datasets into a single dataset.

+ +

This is a simple concatenation of the datasets. The datasets are +concatenated in the order they are passed to the constructor. If the +dataset elements need to be interleaved, you can either use a ShuffledDataset, +SampledDatasetWithoutReplacement or SampledDatasetWithReplacement.

+ + +
+ Example + 
from loadax import CombinedDataset, InMemoryDataset
+
+dataset1 = InMemoryDataset([1, 2, 3])
+dataset2 = InMemoryDataset([4, 5, 6])
+combined_dataset = CombinedDataset([dataset1, dataset2])
+
+
+ +

Parameters:

+ + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
datasets + list[Dataset] + +
+

The datasets to combine.

+
+ 		+ required +
+ +
+ Source code in src/loadax/dataset/transform/combined.py + 
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def __init__(self, datasets: list[Dataset[DatasetItem]]):
+    """Combine multiple datasets into a single dataset.
+
+    This is a simple concatenation of the datasets. The datasets are
+    concatenated in the order they are passed to the constructor. If the
+    dataset elements need to be interleaved, you can either use a `ShuffledDataset`,
+    `SampledDatasetWithoutReplacement` or `SampledDatasetWithReplacement`.
+
+    Example:
+        ```python
+        from loadax import CombinedDataset, InMemoryDataset
+
+        dataset1 = InMemoryDataset([1, 2, 3])
+        dataset2 = InMemoryDataset([4, 5, 6])
+        combined_dataset = CombinedDataset([dataset1, dataset2])
+        ```
+
+    Args:
+        datasets (list[Dataset]): The datasets to combine.
+    """
+    self.datasets = datasets
+
+
+ + + +
+ + + + + + + + + +
+ + +

+ get + + +

+
get(index: int) -> DatasetItem | None
+
+ +
+ +

Get the item at the given index.

+ + +
+ Example + 
from loadax import CombinedDataset, InMemoryDataset
+
+dataset1 = InMemoryDataset([1, 2, 3])
+dataset2 = InMemoryDataset([4, 5, 6])
+combined_dataset = CombinedDataset([dataset1, dataset2])
+print(combined_dataset.get(0))
+#> 1
+
+
+ +

Parameters:

+ + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
index + int + +
+

The index of the item to get.

+
+ 		+ required +
+ + +

Returns:

+ + + + + + + + + + + + + +
TypeDescription
+ DatasetItem | None + +
+

DatasetItem | None: The item at the given index, or None if the index is +out of bounds.

+
+
+ +
+ Source code in src/loadax/dataset/transform/combined.py + 
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def get(self, index: int) -> DatasetItem | None:
+    """Get the item at the given index.
+
+    Example:
+        ```python
+        from loadax import CombinedDataset, InMemoryDataset
+
+        dataset1 = InMemoryDataset([1, 2, 3])
+        dataset2 = InMemoryDataset([4, 5, 6])
+        combined_dataset = CombinedDataset([dataset1, dataset2])
+        print(combined_dataset.get(0))
+        #> 1
+        ```
+
+    Args:
+        index (int): The index of the item to get.
+
+    Returns:
+        DatasetItem | None: The item at the given index, or None if the index is
+            out of bounds.
+    """
+    current_index = 0
+    for dataset in self.datasets:
+        if index < current_index + len(dataset):
+            return dataset.get(index - current_index)
+        current_index += len(dataset)
+    return None
+
+
+
+ +
+ + + +
+ +
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+ + + + + + + + + + + + + + + +
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+ + + + + + + + + + \ No newline at end of file diff --git a/v0.2.1/api/dataset/transformations/mapped/index.html b/v0.2.1/api/dataset/transformations/mapped/index.html new file mode 100644 index 0000000..51e86e4 --- /dev/null +++ b/v0.2.1/api/dataset/transformations/mapped/index.html @@ -0,0 +1,1739 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + MappedDataset - Loadax Documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + Skip to content + + +
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+ + + + + + + + +

MappedDataset

+

A mapped dataset is a transformation that applies a functional transformation to the underlying dataset. The transformation is applied lazily, the underlying dataset is preserved. Because loadax performs dataloading in the background, this means it is acceptable to perform lightweight data augmentation or transformations on the dataset.

+

If you have some complicated transformations you may still want to perform them ahead of time.

+
Creating a mapped dataset
from loadax import MappedDataset, InMemoryDataset
+
+def transform(x):
+    return x * 2
+
+dataset = MappedDataset(InMemoryDataset([1, 2, 3, 4, 5]), transform)
+
+for i in range(len(dataset)):
+    print(dataset.get(i))
+
+#> 2
+#> 4
+#> 6
+#> 8
+#> 10
+
+ + +
+ + + + +
+

+ Bases: Dataset[MappedItem]

+ + +

Dataset that applies a function to the items of another dataset.

+

This dataset transformation lazily applies a function to the items of another +dataset. This is useful for cases where you need to augment the data before using +it in a training loop.

+ + +
+ Example + 
from loadax.dataset import RangeDataset
+from loadax.dataset.transform import MappedDataset
+
+def slow_fn(x):
+    time.sleep(0.1)
+    return x * 2
+
+dataset = MappedDataset(RangeDataset(0, 20), slow_fn)
+
+
+ +

Attributes:

+ + + + + + + + + + + + + + + + + + + + +
NameTypeDescription
dataset + +
+

The dataset to apply the function to.

+
+
map_fn + +
+

The function to apply to the items of the dataset.

+
+
+ +

This dataset transformation lazily applies a function to the items of another +dataset. This is useful for cases where you need to augment the data before +usingit in a training loop.

+ + +
+ Example + 
from loadax.dataset import RangeDataset
+from loadax.dataset.transform import MappedDataset
+
+def slow_fn(x):
+    time.sleep(0.1)
+    return x * 2
+
+dataset = MappedDataset(RangeDataset(0, 20), slow_fn)
+
+
+ +

Parameters:

+ + + + + + + + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
dataset + Dataset[DatasetItem] + +
+

The dataset to apply the function to.

+
+ 		+ required +
map_fn + Callable[[DatasetItem], MappedItem] + +
+

The function to apply to the items of the dataset.

+
+ 		+ required +
+ +
+ Source code in src/loadax/dataset/transform/mapped.py + 
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def __init__(
+    self, dataset: Dataset[DatasetItem], map_fn: Callable[[DatasetItem], MappedItem]
+):
+    """Dataset that applies a function to the items of another dataset.
+
+    This dataset transformation lazily applies a function to the items of another
+    dataset. This is useful for cases where you need to augment the data before
+    usingit in a training loop.
+
+    Example:
+        ```python
+        from loadax.dataset import RangeDataset
+        from loadax.dataset.transform import MappedDataset
+
+        def slow_fn(x):
+            time.sleep(0.1)
+            return x * 2
+
+        dataset = MappedDataset(RangeDataset(0, 20), slow_fn)
+        ```
+
+    Args:
+        dataset: The dataset to apply the function to.
+        map_fn: The function to apply to the items of the dataset.
+    """
+    self.dataset = dataset
+    self.map_fn = map_fn
+
+
+ + + +
+ + + + + + + + + +
+ + +

+ get + + +

+
get(index: int) -> MappedItem | None
+
+ +
+ +

Get the item at the given index.

+ + +

Parameters:

+ + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
index + int + +
+

The index of the item to get.

+
+ 		+ required +
+ + +

Returns:

+ + + + + + + + + + + + + +
TypeDescription
+ MappedItem | None + +
+

The item at the given index, or None if the index is out of range.

+
+
+ +
+ Source code in src/loadax/dataset/transform/mapped.py + 
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def get(self, index: int) -> MappedItem | None:
+    """Get the item at the given index.
+
+    Args:
+        index: The index of the item to get.
+
+    Returns:
+        The item at the given index, or None if the index is out of range.
+    """
+    item = self.dataset.get(index)
+    if item is None:
+        return None
+    return self.map_fn(item)
+
+
+
+ +
+ + + +
+ +
+ +
+ + + + + + + + + + + + + + + +
+
+ + + + + +
+ + + +
+ + + +
+
+
+
+ +
+ + + + + + + + + + \ No newline at end of file diff --git a/v0.2.1/api/dataset/transformations/partial/index.html b/v0.2.1/api/dataset/transformations/partial/index.html new file mode 100644 index 0000000..7a4f37c --- /dev/null +++ b/v0.2.1/api/dataset/transformations/partial/index.html @@ -0,0 +1,1959 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + PartialDataset - Loadax Documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + Skip to content + + +
+
+ + + +
+ + + + + + +
+ + +
+ +
+ + + + + + + + + +
+
+ + + +
+
+
+ + + + + + + +
+
+
+ + + +
+
+
+ + + + + +
+
+
+ + + +
+
+ + + + + + + + +

PartialDataset

+

A partial dataset is a simple dataset that returns a subset of the underlying dataset. This is useful for testing and debugging.

+
Creating a partial dataset
from loadax import PartialDataset, InMemoryDataset
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+partial_dataset = PartialDataset(dataset, 2, 4)
+
+for i in range(len(partial_dataset)):
+    print(partial_dataset.get(i))
+
+#> 2
+#> 3
+#> 4
+
+ + +
+ + + + +
+

+ Bases: Dataset[DatasetItem]

+ + +

Create a partial subset of an existing dataset.

+ +

This dataset allows accessing a subset of the original dataset. The +subset is defined by the start and end indices.

+ + +
+ Example + 
from loadax import InMemoryDataset, PartialDataset
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+partial_dataset = PartialDataset(dataset, 1, 4)
+
+
+ +

Parameters:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
dataset + Dataset + +
+

The dataset to create the partial subset from.

+
+ 		+ required +
start_index + int + +
+

The start index of the subset.

+
+ 		+ required +
end_index + int + +
+

The end index of the subset.

+
+ 		+ required +
+ +
+ Source code in src/loadax/dataset/transform/partial.py + 
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def __init__(
+    self, dataset: Dataset[DatasetItem], start_index: int, end_index: int
+) -> None:
+    """Create a partial subset of an existing dataset.
+
+    This dataset allows accessing a subset of the original dataset. The
+    subset is defined by the start and end indices.
+
+    Example:
+        ```python
+        from loadax import InMemoryDataset, PartialDataset
+
+        dataset = InMemoryDataset([1, 2, 3, 4, 5])
+        partial_dataset = PartialDataset(dataset, 1, 4)
+        ```
+
+    Args:
+        dataset (Dataset): The dataset to create the partial subset from.
+        start_index (int): The start index of the subset.
+        end_index (int): The end index of the subset.
+    """
+    self.dataset = dataset
+    self.start_index = start_index
+    self.end_index = min(end_index, len(dataset))
+
+
+ + + +
+ + + + + + + + + +
+ + +

+ split + + + + staticmethod + + +

+
split(dataset: Dataset[DatasetItem], num_parts: int) -> Sequence[Dataset[DatasetItem]]
+
+ +
+ +

Split a dataset into multiple parts.

+

This method splits a dataset into multiple parts of equal size. The +number of parts is determined by the num_parts argument. The last +part may contain fewer items if the dataset is not evenly divisible +by the number of parts.

+ + +
+ Example + 
from loadax import InMemoryDataset, PartialDataset
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+partial_datasets = PartialDataset.split(dataset, 3)
+
+for partial_dataset in partial_datasets:
+    print(partial_dataset.get(0))
+
+#> 1
+#> 3
+#> 5
+
+
+ +

Parameters:

+ + + + + + + + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
dataset + Dataset + +
+

The dataset to split.

+
+ 		+ required +
num_parts + int + +
+

The number of parts to split the dataset into.

+
+ 		+ required +
+ + +

Returns:

+ + + + + + + + + + + + + +
TypeDescription
+ Sequence[Dataset[DatasetItem]] + +
+

list[Dataset[DatasetItem]]: A list of partial datasets.

+
+
+ +
+ Source code in src/loadax/dataset/transform/partial.py + 
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@staticmethod
+def split(
+    dataset: Dataset[DatasetItem], num_parts: int
+) -> Sequence[Dataset[DatasetItem]]:
+    """Split a dataset into multiple parts.
+
+    This method splits a dataset into multiple parts of equal size. The
+    number of parts is determined by the `num_parts` argument. The last
+    part may contain fewer items if the dataset is not evenly divisible
+    by the number of parts.
+
+    Example:
+        ```python
+        from loadax import InMemoryDataset, PartialDataset
+
+        dataset = InMemoryDataset([1, 2, 3, 4, 5])
+        partial_datasets = PartialDataset.split(dataset, 3)
+
+        for partial_dataset in partial_datasets:
+            print(partial_dataset.get(0))
+
+        #> 1
+        #> 3
+        #> 5
+        ```
+
+    Args:
+        dataset (Dataset): The dataset to split.
+        num_parts (int): The number of parts to split the dataset into.
+
+    Returns:
+        list[Dataset[DatasetItem]]: A list of partial datasets.
+    """
+    total_len = len(dataset)
+    batch_size = total_len // num_parts
+    remainder = total_len % num_parts
+    datasets: list[Dataset[DatasetItem]] = []
+
+    current = 0
+    for i in range(num_parts):
+        start = current
+        end = start + batch_size + (1 if i < remainder else 0)
+        datasets.append(PartialDataset[DatasetItem](dataset, start, end))
+        current = end
+
+    return datasets
+
+
+
+ +
+ +
+ + +

+ get + + +

+
get(index: int) -> DatasetItem | None
+
+ +
+ +

Get the item at the given index.

+

This method returns the item at the given index in the dataset. If the +index is negative, it respects python's negative indexing semantics. +If the index is out of bounds, it returns None.

+ + +
+ Example + 
from loadax import InMemoryDataset, PartialDataset
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+partial_dataset = PartialDataset(dataset, 1, 4)
+print(partial_dataset.get(0))
+
+#> 2
+
+
+ +

Parameters:

+ + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
index + int + +
+

The index of the item to get.

+
+ 		+ required +
+ + +

Returns:

+ + + + + + + + + + + + + +
TypeDescription
+ DatasetItem | None + +
+

DatasetItem | None: The item at the given index, or None if the index is +out of bounds.

+
+
+ +
+ Source code in src/loadax/dataset/transform/partial.py + 
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def get(self, index: int) -> DatasetItem | None:
+    """Get the item at the given index.
+
+    This method returns the item at the given index in the dataset. If the
+    index is negative, it respects python's negative indexing semantics.
+    If the index is out of bounds, it returns None.
+
+    Example:
+        ```python
+        from loadax import InMemoryDataset, PartialDataset
+
+        dataset = InMemoryDataset([1, 2, 3, 4, 5])
+        partial_dataset = PartialDataset(dataset, 1, 4)
+        print(partial_dataset.get(0))
+
+        #> 2
+        ```
+
+    Args:
+        index (int): The index of the item to get.
+
+    Returns:
+        DatasetItem | None: The item at the given index, or None if the index is
+            out of bounds.
+    """
+    if index < 0:
+        index += len(self)
+    if index < 0 or index >= len(self):
+        return None
+    return self.dataset.get(index + self.start_index)
+
+
+
+ +
+ + + +
+ +
+ +
+ + + + + + + + + + + + + + + +
+
+ + + + + +
+ + + +
+ + + +
+
+
+
+ +
+ + + + + + + + + + \ No newline at end of file diff --git a/v0.2.1/api/dataset/transformations/sampled/index.html b/v0.2.1/api/dataset/transformations/sampled/index.html new file mode 100644 index 0000000..569323f --- /dev/null +++ b/v0.2.1/api/dataset/transformations/sampled/index.html @@ -0,0 +1,2243 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + SampledDataset - Loadax Documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + Skip to content + + +
+
+ + + +
+ + + + + + +
+ + +
+ +
+ + + + + + + + + +
+
+ + + +
+
+
+ + + + + + + +
+
+
+ + + +
+
+
+ + + + + +
+
+
+ + + +
+
+ + + + + + + + +

SampledDataset

+

A sampled dataset is a simple dataset that returns a subset of the underlying dataset. The sampling is performed lazily and does not actually sample the underlying storage. If your underlying storage does not perform well with random access, you may want to consider performing the sampling in advance. However, for almost all use cases, this should not be necessary.

+

The sampling procedure is deterministic and leverages JAX's random number generation.

+
Creating a sampled dataset
from loadax import SampledDatasetWithReplacement, InMemoryDataset
+import jax
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+key = jax.random.PRNGKey(0)
+sampled_dataset = SampledDatasetWithReplacement(dataset, 3, key)
+
+ + +
+ + + + +
+

+ Bases: Dataset[DatasetItem]

+ + +

Sample a subset of the items in the source dataset without replacement.

+

This dataset allows sampling a subset of the items in the source dataset without +replacement. The sampling eagerly shuffles the indices of the source dataset and +then selects the first sample_size indices. This is a simple implementation +that does not perform any kind of sampling with replacement.

+

The sampling does not alter the underlying storage of the source dataset. If your +underlying storage does not perform well with random access, you may want to +consider performing the sampling in advance. However, for almost all use cases, +this should not be necessary.

+

The lazy sampling enables better reproducibility and determinism, while also +being extremely efficient as only the indices need to be sampled. This also means +that sampling is not IO bound as the indices can be stored in memory.

+ + +
+ Example + 
import jax
+from loadax import SampledDatasetWithoutReplacement, InMemoryDataset
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+key = jax.random.PRNGKey(0)
+sampled_dataset = SampledDatasetWithoutReplacement(dataset, 3, key)
+
+
+ +

Attributes:

+ + + + + + + + + + + + + + + + + + + + + + + + + +
NameTypeDescription
dataset + Dataset + +
+

The underlying dataset to sample from.

+
+
sample_size + int + +
+

The size of the sample to take.

+
+
indices + list[int] + +
+

The indices to sample from.

+
+
+ +

This dataset allows sampling a subset of the items in the source dataset without +replacement. The sampling eagerly shuffles the indices of the source dataset and +then selects the first sample_size indices. This is a simple implementation +that does not perform any kind of sampling with replacement.

+

The sampling does not alter the underlying storage of the source dataset. If +your underlying storage does not perform well with random access, you may want +to consider performing the sampling in advance. However, for almost all use +cases,this should not be necessary.

+

The lazy sampling enables better reproducibility and determinism, while also +being extremely efficient as only the indices need to be sampled. This also +means that sampling is not IO bound as the indices can be stored in memory.

+ + +
+ Example + 
import jax
+from loadax import SampledDatasetWithoutReplacement, InMemoryDataset
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+key = jax.random.PRNGKey(0)
+sampled_dataset = SampledDatasetWithoutReplacement(dataset, 3, key)
+
+
+ +

Parameters:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
dataset + Dataset + +
+

The dataset to sample from.

+
+ 		+ required +
sample_size + int + +
+

The size of the sample to take.

+
+ 		+ required +
key + KeyArray + +
+

The key to use for sampling.

+
+ 		+ required +
+ +
+ Source code in src/loadax/dataset/transform/sampled.py + 
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def __init__(self, dataset: Dataset[DatasetItem], sample_size: int, key: jax.Array):
+    """Sample a subset of the items in the source dataset without replacement.
+
+    This dataset allows sampling a subset of the items in the source dataset without
+    replacement. The sampling eagerly shuffles the indices of the source dataset and
+    then selects the first `sample_size` indices. This is a simple implementation
+    that does not perform any kind of sampling with replacement.
+
+    The sampling does not alter the underlying storage of the source dataset. If
+    your underlying storage does not perform well with random access, you may want
+    to consider performing the sampling in advance. However, for almost all use
+    cases,this should not be necessary.
+
+    The lazy sampling enables better reproducibility and determinism, while also
+    being extremely efficient as only the indices need to be sampled. This also
+    means that sampling is not IO bound as the indices can be stored in memory.
+
+    Example:
+        ```python
+        import jax
+        from loadax import SampledDatasetWithoutReplacement, InMemoryDataset
+
+        dataset = InMemoryDataset([1, 2, 3, 4, 5])
+        key = jax.random.PRNGKey(0)
+        sampled_dataset = SampledDatasetWithoutReplacement(dataset, 3, key)
+        ```
+
+    Args:
+        dataset (Dataset): The dataset to sample from.
+        sample_size (int): The size of the sample to take.
+        key (jax.random.KeyArray): The key to use for sampling.
+    """
+    self.dataset = dataset
+    self.sample_size = sample_size
+    self.indices: list[int] = []
+    self.key = key
+
+
+ + + +
+ + + + + + + + + +
+ + +

+ get + + +

+
get(index: int) -> DatasetItem | None
+
+ +
+ +

Get the item at the given index.

+

This method returns the item at the given index in the dataset. If the +index is negative, it respects python's negative indexing semantics. +If the index is out of bounds, it returns None.

+ + +
+ Example + 
import jax
+from loadax import SampledDatasetWithoutReplacement, InMemoryDataset
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+key = jax.random.PRNGKey(0)
+sampled_dataset = SampledDatasetWithoutReplacement(dataset, 3, key)
+
+
+ +

Parameters:

+ + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
index + int + +
+

The index of the item to get.

+
+ 		+ required +
+ + +

Returns:

+ + + + + + + + + + + + + +
TypeDescription
+ DatasetItem | None + +
+

DatasetItem | None: The item at the given index, or None if the index is +out of bounds.

+
+
+ +
+ Source code in src/loadax/dataset/transform/sampled.py + 
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def get(self, index: int) -> DatasetItem | None:
+    """Get the item at the given index.
+
+    This method returns the item at the given index in the dataset. If the
+    index is negative, it respects python's negative indexing semantics.
+    If the index is out of bounds, it returns None.
+
+    Example:
+        ```python
+        import jax
+        from loadax import SampledDatasetWithoutReplacement, InMemoryDataset
+
+        dataset = InMemoryDataset([1, 2, 3, 4, 5])
+        key = jax.random.PRNGKey(0)
+        sampled_dataset = SampledDatasetWithoutReplacement(dataset, 3, key)
+        ```
+
+    Args:
+        index (int): The index of the item to get.
+
+    Returns:
+        DatasetItem | None: The item at the given index, or None if the index is
+            out of bounds.
+    """
+    if index >= self.sample_size or len(self.dataset) == 0:
+        return None
+    return self.dataset.get(self._index())
+
+
+
+ +
+ + + +
+ +
+ +
+ +
+ + + + +
+

+ Bases: Dataset[DatasetItem]

+ + +

Sample a subset of the items in the source dataset with replacement.

+

This dataset allows sampling a subset of the items in the source dataset with +replacement. The sampling lazily selects random indices from the source dataset.

+

The sampling does not alter the underlying storage of the source dataset. If your +underlying storage does not perform well with random access, you may want to +consider performing the sampling in advance. However, for almost all use cases, +this should not be necessary.

+ + +
+ Example + 
import jax
+from loadax import SampledDatasetWithReplacement, InMemoryDataset
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+key = jax.random.PRNGKey(0)
+sampled_dataset = SampledDatasetWithReplacement(dataset, 3, key)
+
+
+ +

Attributes:

+ + + + + + + + + + + + + + + + + + + + +
NameTypeDescription
dataset + Dataset + +
+

The underlying dataset to sample from.

+
+
sample_size + int + +
+

The size of the sample to take.

+
+
+ +

This dataset allows sampling a subset of the items in the source dataset with +replacement. The sampling lazily selects random indices from the source dataset.

+

The sampling does not alter the underlying storage of the source dataset. If +your underlying storage does not perform well with random access, you may want +to consider performing the sampling in advance. However, for almost all use +cases, this should not be necessary.

+ + +
+ Example + 
import jax
+from loadax import SampledDatasetWithReplacement, InMemoryDataset
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+key = jax.random.PRNGKey(0)
+sampled_dataset = SampledDatasetWithReplacement(dataset, 3, key)
+
+
+ +

Parameters:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
dataset + Dataset + +
+

The dataset to sample from.

+
+ 		+ required +
sample_size + int + +
+

The size of the sample to take.

+
+ 		+ required +
key + KeyArray + +
+

The key to use for sampling.

+
+ 		+ required +
+ +
+ Source code in src/loadax/dataset/transform/sampled.py + 
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def __init__(self, dataset: Dataset[DatasetItem], sample_size: int, key: jax.Array):
+    """Sample a subset of the items in the source dataset with replacement.
+
+    This dataset allows sampling a subset of the items in the source dataset with
+    replacement. The sampling lazily selects random indices from the source dataset.
+
+    The sampling does not alter the underlying storage of the source dataset. If
+    your underlying storage does not perform well with random access, you may want
+    to consider performing the sampling in advance. However, for almost all use
+    cases, this should not be necessary.
+
+    Example:
+        ```python
+        import jax
+        from loadax import SampledDatasetWithReplacement, InMemoryDataset
+
+        dataset = InMemoryDataset([1, 2, 3, 4, 5])
+        key = jax.random.PRNGKey(0)
+        sampled_dataset = SampledDatasetWithReplacement(dataset, 3, key)
+        ```
+
+    Args:
+        dataset (Dataset): The dataset to sample from.
+        sample_size (int): The size of the sample to take.
+        key (jax.random.KeyArray): The key to use for sampling.
+    """
+    self.dataset = dataset
+    self.sample_size = sample_size
+    self.key = key
+
+
+ + + +
+ + + + + + + + + +
+ + +

+ get + + +

+
get(index: int) -> DatasetItem | None
+
+ +
+ +

Get the item at the given index.

+

This method returns the item at the given index in the dataset. If the +index is negative, it respects python's negative indexing semantics. +If the index is out of bounds, it returns None.

+ + +
+ Example + 
import jax
+from loadax import SampledDatasetWithReplacement, InMemoryDataset
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+key = jax.random.PRNGKey(0)
+sampled_dataset = SampledDatasetWithReplacement(dataset, 3, key)
+print(sampled_dataset.get(0))
+#> 1
+
+
+ +

Parameters:

+ + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
index + int + +
+

The index of the item to get.

+
+ 		+ required +
+ + +

Returns:

+ + + + + + + + + + + + + +
TypeDescription
+ DatasetItem | None + +
+

DatasetItem | None: The item at the given index, or None if the index is +out of bounds.

+
+
+ +
+ Source code in src/loadax/dataset/transform/sampled.py + 
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def get(self, index: int) -> DatasetItem | None:
+    """Get the item at the given index.
+
+    This method returns the item at the given index in the dataset. If the
+    index is negative, it respects python's negative indexing semantics.
+    If the index is out of bounds, it returns None.
+
+    Example:
+        ```python
+        import jax
+        from loadax import SampledDatasetWithReplacement, InMemoryDataset
+
+        dataset = InMemoryDataset([1, 2, 3, 4, 5])
+        key = jax.random.PRNGKey(0)
+        sampled_dataset = SampledDatasetWithReplacement(dataset, 3, key)
+        print(sampled_dataset.get(0))
+        #> 1
+        ```
+
+    Args:
+        index (int): The index of the item to get.
+
+    Returns:
+        DatasetItem | None: The item at the given index, or None if the index is
+            out of bounds.
+    """
+    if index >= self.sample_size or len(self.dataset) == 0:
+        return None
+
+    self.key, subkey = jax.random.split(self.key)
+    random_index = jax.random.randint(subkey, (), 0, len(self.dataset))
+    return self.dataset.get(int(random_index))
+
+
+
+ +
+ + + +
+ +
+ +
+ + + + + + + + + + + + + + + +
+
+ + + + + +
+ + + +
+ + + +
+
+
+
+ +
+ + + + + + + + + + \ No newline at end of file diff --git a/v0.2.1/api/dataset/transformations/shuffled/index.html b/v0.2.1/api/dataset/transformations/shuffled/index.html new file mode 100644 index 0000000..3dbf59e --- /dev/null +++ b/v0.2.1/api/dataset/transformations/shuffled/index.html @@ -0,0 +1,1789 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + ShuffledDataset - Loadax Documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + Skip to content + + +
+
+ + + +
+ + + + + + +
+ + +
+ +
+ + + + + + + + + +
+
+ + + +
+
+
+ + + + + + + +
+
+
+ + + +
+
+
+ + + + + +
+
+
+ + + +
+
+ + + + + + + + +

ShuffledDataset

+

A shuffled dataset is a simple dataset that shuffles the items in the underlying dataset. The shuffling is performed lazily and does not actually shuffle the underlying storage. If your underlying storage does not perform well with random access, you may want to consider performing the shuffling in advance. However, for almost all use cases, this should not be necessary.

+

The shuffling procedure is deterministic and leverages JAX's random number generation.

+
Creating a shuffled dataset
from loadax import ShuffledDataset, InMemoryDataset
+import jax
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+key = jax.random.PRNGKey(0)
+shuffled_dataset = ShuffledDataset(dataset, key)
+
+ + +
+ + + + +
+

+ Bases: Dataset[DatasetItem]

+ + +

Shuffle the items in the source dataset.

+

The shuffling is performed lazily and does not actually shuffle the underlying +storage. If your underlying storage does not perform well with random access, +you may want to consider performing the shuffling in advance. However, for +almost all use cases, this should not be necessary.

+

The lazy shuffling enables better reproducibility and determinism, while also +being extremely efficient as only the indices need to be shuffled. This also +means that shuffling is not IO bound as the indices can be stored in memory.

+ + +
+ Example + 
import jax
+from loadax import ShuffledDataset, InMemoryDataset
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+key = jax.random.PRNGKey(0)
+shuffled_dataset = ShuffledDataset(dataset, key)
+
+
+ +

Attributes:

+ + + + + + + + + + + + + + + + + + + + +
NameTypeDescription
dataset + Dataset + +
+

The underlying dataset to shuffle.

+
+
indices + list[int] + +
+

The indices to shuffle.

+
+
+ +

The shuffling is performed lazily and does not actually shuffle the underlying +storage. If your underlying storage does not perform well with random access, +you may want to consider performing the shuffling in advance. However, for +almost all use cases, this should not be necessary.

+

The lazy shuffling enables better reproducibility and determinism, while also +being extremely efficient as only the indices need to be shuffled. This also +means that shuffling is not IO bound as the indices can be stored in memory.

+ + +
+ Example + 
import jax
+from loadax import ShuffledDataset, InMemoryDataset
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+key = jax.random.PRNGKey(0)
+shuffled_dataset = ShuffledDataset(dataset, key)
+
+
+ +

Parameters:

+ + + + + + + + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
dataset + Dataset + +
+

The dataset to shuffle.

+
+ 		+ required +
key + KeyArray + +
+

The key to use for shuffling.

+
+ 		+ required +
+ +
+ Source code in src/loadax/dataset/transform/shuffled.py + 
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def __init__(self, dataset: Dataset[DatasetItem], key: jax.Array):
+    """Shuffle the items in the source dataset.
+
+    The shuffling is performed lazily and does not actually shuffle the underlying
+    storage. If your underlying storage does not perform well with random access,
+    you may want to consider performing the shuffling in advance. However, for
+    almost all use cases, this should not be necessary.
+
+    The lazy shuffling enables better reproducibility and determinism, while also
+    being extremely efficient as only the indices need to be shuffled. This also
+    means that shuffling is not IO bound as the indices can be stored in memory.
+
+    Example:
+        ```python
+        import jax
+        from loadax import ShuffledDataset, InMemoryDataset
+
+        dataset = InMemoryDataset([1, 2, 3, 4, 5])
+        key = jax.random.PRNGKey(0)
+        shuffled_dataset = ShuffledDataset(dataset, key)
+        ```
+
+    Args:
+        dataset (Dataset): The dataset to shuffle.
+        key (jax.random.KeyArray): The key to use for shuffling.
+    """
+    self.dataset = dataset
+    self.key = key
+    self.indices = list(jax.random.permutation(self.key, len(dataset)))
+
+
+ + + +
+ + + + + + + + + +
+ + +

+ get + + +

+
get(index: int) -> DatasetItem | None
+
+ +
+ +

Get the item at the given index.

+

This method returns the item at the given index in the dataset. If the +index is negative, it respects python's negative indexing semantics. +If the index is out of bounds, it returns None.

+ + +
+ Example + 
import jax
+from loadax import ShuffledDataset, InMemoryDataset
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+key = jax.random.PRNGKey(0)
+shuffled_dataset = ShuffledDataset(dataset, key)
+print(shuffled_dataset.get(0))
+#> 3
+
+
+ +

Parameters:

+ + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
index + int + +
+

The index of the item to get.

+
+ 		+ required +
+ + +

Returns:

+ + + + + + + + + + + + + +
TypeDescription
+ DatasetItem | None + +
+

DatasetItem | None: The item at the given index, or None if the index is +out of bounds.

+
+
+ +
+ Source code in src/loadax/dataset/transform/shuffled.py + 
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def get(self, index: int) -> DatasetItem | None:
+    """Get the item at the given index.
+
+    This method returns the item at the given index in the dataset. If the
+    index is negative, it respects python's negative indexing semantics.
+    If the index is out of bounds, it returns None.
+
+    Example:
+        ```python
+        import jax
+        from loadax import ShuffledDataset, InMemoryDataset
+
+        dataset = InMemoryDataset([1, 2, 3, 4, 5])
+        key = jax.random.PRNGKey(0)
+        shuffled_dataset = ShuffledDataset(dataset, key)
+        print(shuffled_dataset.get(0))
+        #> 3
+        ```
+
+    Args:
+        index (int): The index of the item to get.
+
+    Returns:
+        DatasetItem | None: The item at the given index, or None if the index is
+            out of bounds.
+    """
+    if index < 0 or index >= len(self.indices):
+        return None
+    return self.dataset.get(self.indices[index])
+
+
+
+ +
+ + + +
+ +
+ +
+ + + + + + + + + + + + + + + +
+
+ + + + + +
+ + + +
+ + + +
+
+
+
+ +
+ + + + + + + + + + \ No newline at end of file diff --git a/v0.2.1/api/loader/index.html b/v0.2.1/api/loader/index.html new file mode 100644 index 0000000..3733146 --- /dev/null +++ b/v0.2.1/api/loader/index.html @@ -0,0 +1,1954 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + Dataloader - Loadax Documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + Skip to content + + +
+
+ + + +
+ + + + + + +
+ + +
+ +
+ + + + + + + + + +
+
+ + + +
+
+
+ + + + + + + +
+
+
+ + + +
+
+
+ + + + + +
+
+
+ + + +
+
+ + + + + + + + +

Dataloader

+

The Dataloader is the main interface for loading data into your training loop. The Dataloader is responsible for +defining how to efficiently load data from a dataset and allocate it to the appropriate devices, batches, and +all of the other features that make up proper data loading.

+

The Dataloader works by spawning background workers to prefetch data into a cache, and then filling batches from +the cache as they become available. The use of background workers allows the dataloader to be highly efficient +and not block the main thread, which is important for training loops. Loadax takes care of the parllelization +details for you, so your dataloading is fast, reliable, and simple. The background cache will load out of order, +as utilizes mutlithreading to load data in parallel, however the actual batches will be in order. This is because +loadax ensures deterministic ordering of batches, and the background workers will load batches in the order that +they are requested.

+
Creating a dataloader
from loadax import Dataloader, InMemoryDataset, Batcher
+from loadax.strategy import FixedBatchStrategy
+from loadax.dataloader.sharding import NoShardingStrategy
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+batcher = Batcher(lambda x: x)
+dataloader = Dataloader(
+    dataset=dataset,
+    batcher=batcher,
+    strategy=FixedBatchStrategy(batch_size=2),
+    num_workers=2,
+    prefetch_factor=2,
+    sharding_strategy=NoShardingStrategy(),
+)
+for batch in dataloader:
+    print(batch)
+
+#> [1, 2]
+#> [3, 4]
+#> [5]
+
+ + +
+ + + + +
+

+ Bases: NaiveDataloader[DatasetItem, Batch]

+ + +

Dataloader that leverages threading for non-blocking data loading.

+ + + +
+ Example + 
from loadax import Dataloader, InMemoryDataset, Batcher
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+batcher = Batcher(lambda x: x)
+dataloader = Dataloader(
+    dataset=dataset,
+    batcher=batcher,
+    strategy=FixedBatchStrategy(batch_size=2),
+    num_workers=2,
+    prefetch_factor=2,
+    sharding_strategy=NoShardingStrategy(),
+)
+for batch in dataloader:
+    print(batch)
+
+#> [1, 2]
+#> [3, 4]
+#> [5]
+
+
+ +

Parameters:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
dataset + Dataset + +
+

The dataset to load data from.

+
+ 		+ required +
batcher + Batcher + +
+

The batcher to use for batching.

+
+ 		+ required +
strategy + BatchStrategy + +
+

The batch strategy to use for prefetching.

+
+ 		+ required +
num_workers + int + +
+

The number of workers to use for parallel data loading.

+
+ 		+ required +
prefetch_factor + int + +
+

The prefetch factor to use for prefetching.

+
+ 		+ required +
sharding_strategy + JaxShardingStrategy + +
+

The sharding strategy for +distributed data loading.

+
+ 		+ required +
shard_id + int | None + +
+

The ID of this shard (node). +If None, then the shard_id will be determined based on the +current process index and the number of shards.

+
+ 		+ None +
num_shards + int | None + +
+

The total number of shards (nodes). +If None, then the number of shards will be determined based on +the number of processes.

+
+ 		+ None +
+ +
+ Source code in src/loadax/dataloader/loader.py + 
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def __init__(
+    self,
+    dataset: Dataset[DatasetItem],
+    batcher: Batcher[DatasetItem, Batch],
+    strategy: BatchStrategy[DatasetItem],
+    num_workers: int,
+    prefetch_factor: int,
+    sharding_strategy: ShardingStrategy,
+    shard_id: int | None = None,
+    num_shards: int | None = None,
+):
+    """A dataloader that leverages threading for non-blocking data loading.
+
+    Example:
+        ```python
+        from loadax import Dataloader, InMemoryDataset, Batcher
+
+        dataset = InMemoryDataset([1, 2, 3, 4, 5])
+        batcher = Batcher(lambda x: x)
+        dataloader = Dataloader(
+            dataset=dataset,
+            batcher=batcher,
+            strategy=FixedBatchStrategy(batch_size=2),
+            num_workers=2,
+            prefetch_factor=2,
+            sharding_strategy=NoShardingStrategy(),
+        )
+        for batch in dataloader:
+            print(batch)
+
+        #> [1, 2]
+        #> [3, 4]
+        #> [5]
+        ```
+
+    Args:
+        dataset (Dataset): The dataset to load data from.
+        batcher (Batcher): The batcher to use for batching.
+        strategy (BatchStrategy): The batch strategy to use for prefetching.
+        num_workers (int): The number of workers to use for parallel data loading.
+        prefetch_factor (int): The prefetch factor to use for prefetching.
+        sharding_strategy (JaxShardingStrategy): The sharding strategy for
+            distributed data loading.
+        shard_id (int | None): The ID of this shard (node).
+            If None, then the shard_id will be determined based on the
+            current process index and the number of shards.
+        num_shards (int | None): The total number of shards (nodes).
+            If None, then the number of shards will be determined based on
+            the number of processes.
+    """
+    super().__init__(dataset, batcher, strategy)
+    assert num_workers > 0, "num_workers must be at least 1"
+    self.num_workers = num_workers
+
+    assert prefetch_factor > 0, "prefetch_factor must be at least 1"
+    self.prefetch_factor = prefetch_factor
+
+    self.sharding_strategy = sharding_strategy
+
+    # Check that both shard_id and num_shards are provided or neither are provided
+
+    assert (shard_id is None and num_shards is None) or (
+        shard_id is not None and num_shards is not None
+    ), "Either both shard_id and num_shards must be provided or neither"
+
+    assert num_shards is None or num_shards > 0, "num_shards must be greater than 0"
+    self.num_shards = num_shards or jax.process_count()
+
+    self.shard_id = shard_id or (jax.process_index() % self.num_shards)
+    assert (
+        self.shard_id < self.num_shards
+    ), f"shard_id {self.shard_id} must be in the range [0, {self.num_shards})"
+
+    # Determine the shard indices for this node
+    self.shard_indices = self.sharding_strategy.get_shard_indices(
+        dataset_size=len(dataset),
+        shard_id=self.shard_id,
+        num_shards=self.num_shards,
+    )
+
+
+ + + +
+ + + + + + + + + + + +
+ +
+ +
+ +
+ + + + +
+

+ Bases: DataloaderIteratorProtocol[DatasetItem, Batch]

+ + +

Iterator for the threaded dataloader.

+ + + +

Parameters:

+ + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
dataloader + Dataloader + +
+

The dataloader to iterate over.

+
+ 		+ required +
+ +
+ Source code in src/loadax/dataloader/loader.py + 
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def __init__(self, dataloader: "Dataloader[DatasetItem, Batch]"):
+    """Iterator for the dataloader.
+
+    Args:
+        dataloader (Dataloader): The dataloader to iterate over.
+    """
+    self.dataloader = dataloader
+    self.executor = ThreadPoolExecutor(max_workers=self.dataloader.num_workers)
+    self.current_index = 0
+    self.cache: dict[int, DatasetItem] = {}
+    self.futures: dict[int, Future[tuple[int, DatasetItem | None]]] = {}
+    self.cache_lock = threading.Lock()
+    self.index_lock = threading.Lock()
+
+    self.shard_indices = list(self.dataloader.shard_indices)
+    self.total_indices = len(self.shard_indices)
+
+    self._shutdown_finalizer = weakref.finalize(self, self._shutdown_executor)
+
+    self._start_prefetching()
+
+
+ + + +
+ + + + + + + + + +
+ + +

+ progress + + +

+
progress() -> Progress
+
+ +
+ +

Get the progress of the dataloader.

+ +
+ Source code in src/loadax/dataloader/loader.py + 
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+120
+121
def progress(self) -> Progress:
+    """Get the progress of the dataloader."""
+    return Progress(self.current_index, len(self.dataloader.shard_indices))
+
+
+
+ +
+ + + +
+ +
+ +
+ + + + + + + + + + + + + + + +
+
+ + + + + +
+ + + +
+ + + +
+
+
+
+ +
+ + + + + + + + + + \ No newline at end of file diff --git a/v0.2.1/api/naive/index.html b/v0.2.1/api/naive/index.html new file mode 100644 index 0000000..ec070a9 --- /dev/null +++ b/v0.2.1/api/naive/index.html @@ -0,0 +1,1763 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + Naive Dataloader - Loadax Documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + Skip to content + + +
+
+ + + +
+ + + + + + +
+ + +
+ +
+ + + + + + + + + +
+
+ + + +
+
+
+ + + + + + + +
+
+
+ + + +
+
+
+ + + + + +
+
+
+ + + +
+
+ + + + + + + + +

Naive Dataloader

+

The naive dataloader is the simplest form of a dataloader. Do not use this dataloader unless you have a specific reason to do so. It is fine for a quick experiment or for debuugging, but the naive dataloader can block your training loop, does not have sharding support, and is not recommended for production use. As a result, if you use the DataLoader builder to create your dataloader, the naive dataloader will never be used.

+ + +
+ + + + +
+

+ Bases: DataloaderProtocol[DatasetItem, Batch], Generic[DatasetItem, Batch]

+ + +

A naive dataloader that does not offload work to background processes.

+

This dataloader is a simple implementation of a dataloader that does not offload +work to background processes. It is useful for debugging and testing. This will +slow down your training loop, but is useful for debugging and really simple +training loops.

+ + +

Attributes:

+ + + + + + + + + + + + + + + + + + + + + + + + + +
NameTypeDescription
dataset + +
+

The dataset to load.

+
+
batcher + +
+

The batcher to use to collate the data.

+
+
strategy + +
+

The batch strategy to use to determine how much data goes into a +batch.

+
+
+ +

This dataloader is a simple implementation of a dataloader that does not +offload work to background processes. It is useful for debugging and testing. +This will slow down your training loop, but is useful for debugging and really +simple training loops.

+ + +

Parameters:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
dataset + Dataset[DatasetItem] + +
+

The dataset to load.

+
+ 		+ required +
batcher + Batcher[DatasetItem, Batch] + +
+

The batcher to use to collate the data.

+
+ 		+ required +
strategy + BatchStrategy[DatasetItem] + +
+

The batch strategy to use to determine how much data goes into a +batch.

+
+ 		+ required +
+ +
+ Source code in src/loadax/dataloader/naive.py + 
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def __init__(
+    self,
+    dataset: Dataset[DatasetItem],
+    batcher: Batcher[DatasetItem, Batch],
+    strategy: BatchStrategy[DatasetItem],
+):
+    """A naive dataloader that does not offload work to background processes.
+
+    This dataloader is a simple implementation of a dataloader that does not
+    offload work to background processes. It is useful for debugging and testing.
+    This will slow down your training loop, but is useful for debugging and really
+    simple training loops.
+
+    Args:
+        dataset: The dataset to load.
+        batcher: The batcher to use to collate the data.
+        strategy: The batch strategy to use to determine how much data goes into a
+            batch.
+    """
+    self.dataset = dataset
+    self.batcher = batcher
+    self.strategy = strategy
+
+
+ + + +
+ + + + + + + + + +
+ + +

+ num_items + + +

+
num_items() -> int
+
+ +
+ +

Get the number of items in the dataset.

+

This method returns the number of items in the dataset.

+ + +

Returns:

+ + + + + + + + + + + + + +
TypeDescription
+ int + +
+

The number of items in the dataset.

+
+
+ +
+ Source code in src/loadax/dataloader/naive.py + 
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def num_items(self) -> int:
+    """Get the number of items in the dataset.
+
+    This method returns the number of items in the dataset.
+
+    Returns:
+        The number of items in the dataset.
+    """
+    return len(self.dataset)
+
+
+
+ +
+ +
+ + +

+ num_batches + + +

+
num_batches() -> int
+
+ +
+ +

Get the number of batches in the dataset.

+

This method returns the number of batches in the dataset based +on your batch strategy.

+ + +

Returns:

+ + + + + + + + + + + + + +
TypeDescription
+ int + +
+

The number of batches in the dataset.

+
+
+ +
+ Source code in src/loadax/dataloader/naive.py + 
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def num_batches(self) -> int:
+    """Get the number of batches in the dataset.
+
+    This method returns the number of batches in the dataset based
+    on your batch strategy.
+
+    Returns:
+        The number of batches in the dataset.
+    """
+    return self.num_items() // self.strategy.batch_size
+
+
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+ +
+ + + +
+ +
+ +
+ + + + + + + + + + + + + + + +
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+ + + + + + + + + + \ No newline at end of file diff --git a/v0.2.1/api/progress/index.html b/v0.2.1/api/progress/index.html new file mode 100644 index 0000000..4884e77 --- /dev/null +++ b/v0.2.1/api/progress/index.html @@ -0,0 +1,1493 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + Progress - Loadax Documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + Skip to content + + +
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+ + + + + + + + +

Progress

+

Progress is a simple interface that allows you to track the progress of a dataloader. Because a dataloader is a stateful iterator, you can use the progress() method to get the current progress of the iterator. This means no more +manual calculations of the progress, dealing with batch sizes, or forgetting to update your progress tracking.

+
Tracking progress
from loadax import Dataloader, InMemoryDataset, Batcher
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+batcher = Batcher(lambda x: x)
+dataloader = Dataloader(batcher).batch_size(2).build(dataset)
+
+iterator = iter(dataloader)
+
+for batch in iterator:
+    print(batch)
+    iterator.progress()
+
+#> [1, 2]
+#> Progress(items_processed=2, items_total=5)
+#> [3, 4]
+#> Progress(items_processed=4, items_total=5)
+#> [5]
+#> Progress(items_processed=5, items_total=5)
+
+ + +
+ + + + +
+ + +

Progress metadata for a dataloader.

+

This metadata indicates how far the dataloader has progressed. This is useful for +debugging and monitoring the progress of a dataloader.

+ + +

Attributes:

+ + + + + + + + + + + + + + + + + + + + +
NameTypeDescription
items_processed + int + +
+

The number of items processed so far.

+
+
items_total + int + +
+

The total number of items in the dataset.

+
+
+ + + + +
+ + + + + + + + + + + +
+ +
+ +
+ + + + + + + + + + + + + + + +
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+ +
+ + + + + + + + + + \ No newline at end of file diff --git a/v0.2.1/api/sharding/presets/index.html b/v0.2.1/api/sharding/presets/index.html new file mode 100644 index 0000000..8d91832 --- /dev/null +++ b/v0.2.1/api/sharding/presets/index.html @@ -0,0 +1,1745 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + Presets - Loadax Documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + Skip to content + + +
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+ + + +
+ + + + + + +
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+ + + + + + + + +

Sharding Presets

+

Loadax provides a few common sharding configurations that can be used out of the box. These presets are strong starting points for your sharding configuration, but you can also create your own sharding configurations using JAX's Mesh and NamedSharding primitives.

+

FSDP Sharding

+

The FSDP sharding preset is a simple configuration that shards the model across multiple hosts and devices, and the data across multiple hosts. In FSDP training, the model parameters are split across multiple devices and each model shard recieves unique data. This configuration is useful for training models that are too large to fit on a single device.

+
Creating an FSDP sharding preset
from loadax import DataloaderBuilder, InMemoryDataset, Batcher
+from loadax.sharding_utilities import fsdp_sharding
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+batcher = Batcher(lambda x: x)
+
+mesh, axis_names = fsdp_sharding()
+
+dataloader = DataloaderBuilder(batcher)
+    .batch_size(2)
+    .shard(mesh, axis_names[0])
+    .build(dataset)
+
+ + +
+ + + + +
+ +

Default sharding configuration for FSDP.

+

FSDP is a distributed training technique where both the model's parameters and the +data are sharded across multipled devices and potentially multiple nodes. This +configuration ensures that each node manages a subset of the data and holds a +partition of the model's parameters. By sharding the model, FSDP enables training +of models that are too large to fit on a single device, optimize memory usage and +computational efficiency.

+

Loadax's default FSDP sharding configuration leverages JAX's parallelization +primitives to minimize network traffic and optimize data loading. The model's +parameters are distributed across devices within each data shard, allowing for +scalable training across different architectures and network topologies. The data +is partitioned such that each node can precompute what data it needs to load, +reducing network traffic and improving data loading efficiency.

+

In the case of single-node training, this configuration is still valid and only +utilizes a single data shard. The data is still able to be used across all local +devices, this is just to mean that the sharding splits are not pre-computed.

+

This configuration is useful for FSDP training, but you can also create your own +sharding configurations. See the documentation for more information.

+ + +

Returns:

+ + + + + + + + + + + + + + + + + +
Name TypeDescription
mesh + Mesh + +
+

The mesh to use for sharding.

+
+
axis_names + tuple[str] + +
+

The axis names to use for sharding. The first axis +name is used for the data sharding, and the second axis name is used for +the model sharding.

+
+
+ +
+ Source code in src/loadax/sharding_utilities.py + 
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def fsdp_sharding() -> ShardingPreset:
+    """Default sharding configuration for FSDP.
+
+    FSDP is a distributed training technique where both the model's parameters and the
+    data are sharded across multipled devices and potentially multiple nodes. This
+    configuration ensures that each node manages a subset of the data and holds a
+    partition of the model's parameters. By sharding the model, FSDP enables training
+    of models that are too large to fit on a single device, optimize memory usage and
+    computational efficiency.
+
+    Loadax's default FSDP sharding configuration leverages JAX's parallelization
+    primitives to minimize network traffic and optimize data loading. The model's
+    parameters are distributed across devices within each data shard, allowing for
+    scalable training across different architectures and network topologies. The data
+    is partitioned such that each node can precompute what data it needs to load,
+    reducing network traffic and improving data loading efficiency.
+
+    In the case of single-node training, this configuration is still valid and only
+    utilizes a single data shard. The data is still able to be used across all local
+    devices, this is just to mean that the sharding splits are not pre-computed.
+
+    This configuration is useful for FSDP training, but you can also create your own
+    sharding configurations. See the documentation for more information.
+
+    Returns:
+        mesh (Mesh): The mesh to use for sharding.
+        axis_names (tuple[str]): The axis names to use for sharding. The first axis
+            name is used for the data sharding, and the second axis name is used for
+            the model sharding.
+    """
+    num_total_devices = len(jax.devices())
+    num_data_shards = jax.process_count()
+    num_model_shards = num_total_devices // num_data_shards
+
+    assert (
+        num_total_devices % num_data_shards == 0
+    ), "Number of devices must be divisible by number of data shards"
+
+    devices: np.ndarray[Any, Any] = np.array(jax.devices()).reshape(
+        (num_data_shards, num_model_shards)
+    )
+    axis_names = ("data", "model")
+    mesh = Mesh(devices, axis_names)
+
+    return mesh, axis_names
+
+
+
+ +

DDP Sharding

+

The DDP sharding preset is a simple configuration that replicates the model across multiple devices and each replica recieves unique data. This configuration is ideal for training smaller models when you have multiple devices available.

+
DDP Sharding
from loadax import DataloaderBuilder, InMemoryDataset, Batcher
+from loadax.sharding_utilities import ddp_sharding
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+batcher = Batcher(lambda x: x)
+
+mesh, axis_names = ddp_sharding()
+
+dataloader = DataloaderBuilder(batcher)
+    .batch_size(2)
+    .shard(mesh, axis_names[0])
+    .build(dataset)
+
+ + +
+ + + + +
+ +

Default sharding configuration for DDP.

+

DDP is a distributed training technique where the model's parameters are fully +replicated across all devices, and the data is divided into shards, each processed +by a separate node. This setup allows each device to handle unique subsets of the +data while maintaining synchronized copies of the entire model. DDP is effective +for scenarios where model size fits within the memory constraints of individual +devices but benefits from data parallelism to accelerate training.

+

Loadax's default DDP sharding configuration ensures that data is efficiently +partitioned across nodes, and each device within a node holds a complete copy of the +model's parameters. This configuration leverages JAX's parallelization capabilities +to synchronize parameter updates across all replicas, ensuring consistency and +facilitating scalable training.

+

In the case of single-node training, this configuration is equivalent to DP training +and does works perfectly fine for single-node training.

+

This configuration is useful for DDP training, but you can also create your own +sharding configurations. See the documentation for more information.

+ +
+ Source code in src/loadax/sharding_utilities.py + 
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def ddp_sharding() -> ShardingPreset:
+    """Default sharding configuration for DDP.
+
+    DDP is a distributed training technique where the model's parameters are fully
+    replicated across all devices, and the data is divided into shards, each processed
+    by a separate node. This setup allows each device to handle unique subsets of the
+    data while maintaining synchronized copies of the entire model. DDP is effective
+    for scenarios where model size fits within the memory constraints of individual
+    devices but benefits from data parallelism to accelerate training.
+
+    Loadax's default DDP sharding configuration ensures that data is efficiently
+    partitioned across nodes, and each device within a node holds a complete copy of the
+    model's parameters. This configuration leverages JAX's parallelization capabilities
+    to synchronize parameter updates across all replicas, ensuring consistency and
+    facilitating scalable training.
+
+    In the case of single-node training, this configuration is equivalent to DP training
+    and does works perfectly fine for single-node training.
+
+    This configuration is useful for DDP training, but you can also create your own
+    sharding configurations. See the documentation for more information.
+    """
+    num_total_devices = len(jax.devices())
+    num_data_shards = jax.process_count()
+
+    assert (
+        num_total_devices % num_data_shards == 0
+    ), "Number of devices must be divisible by number of data shards"
+
+    devices: np.ndarray[Any, Any] = np.array(jax.devices()).reshape((num_data_shards,))
+    axis_names = ("data",)
+    mesh = Mesh(devices, axis_names)
+
+    return mesh, axis_names
+
+
+
+ +
+ + + + + + + + + + + + + + + +
+
+ + + + + +
+ + + +
+ + + +
+
+
+
+ +
+ + + + + + + + + + \ No newline at end of file diff --git a/v0.2.1/api/sharding/sharding-strategy/index.html b/v0.2.1/api/sharding/sharding-strategy/index.html new file mode 100644 index 0000000..ddda97d --- /dev/null +++ b/v0.2.1/api/sharding/sharding-strategy/index.html @@ -0,0 +1,2839 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + Sharding Strategy - Loadax Documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + Skip to content + + +
+
+ + + +
+ + + + + + +
+ + +
+ +
+ + + + + + + + + +
+
+ + + +
+
+
+ + + + + + + +
+
+
+ + + +
+
+
+ + + + + +
+
+
+ + + +
+
+ + + + + + + + +

Sharding Strategy

+

A sharding strategy is a simple interface that defines how to shard data across multiple devices and potentially +multiple hosts. In the case of single-node training, this is not necessary, but in the case of distributed training, +the ShardingStrategy informs loadax of how to partition the dataset across multiple hosts. Because loadax can use this +information to pre-compute which data needs to be loaded on each host, it can then only load the data that is needed +on each host, which can significantly improve data loading performance and reduce network traffic.

+
Creating a sharding strategy
from loadax import InMemoryDataset, NoShardingStrategy
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+sharding_strategy = NoShardingStrategy()
+
+for shard in sharding_strategy.get_shard_indices(dataset_size=5, shard_id=0, num_shards=1):
+    print(shard)
+
+#> range(0, 5)
+
+ + +
+ + + + +
+

+ Bases: ABC

+ + +

Abstract base class for sharding strategies.

+ + + + +
+ + + + + + + + + +
+ + +

+ get_shard_indices + + + + abstractmethod + + +

+
get_shard_indices(dataset_size: int, shard_id: int, num_shards: int) -> range
+
+ +
+ +

Get the data indices for a specific shard.

+ + +

Parameters:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
dataset_size + int + +
+

The size of the dataset.

+
+ 		+ required +
shard_id + int + +
+

The ID of the shard.

+
+ 		+ required +
num_shards + int + +
+

The total number of shards.

+
+ 		+ required +
+ + +

Returns:

+ + + + + + + + + + + + + +
Name TypeDescription
range + range + +
+

The data indices for the shard.

+
+
+ +
+ Source code in src/loadax/dataloader/sharding.py + 
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@abstractmethod
+def get_shard_indices(
+    self, dataset_size: int, shard_id: int, num_shards: int
+) -> range:
+    """Get the data indices for a specific shard.
+
+    Args:
+        dataset_size: The size of the dataset.
+        shard_id: The ID of the shard.
+        num_shards: The total number of shards.
+
+    Returns:
+        range: The data indices for the shard.
+    """
+    pass
+
+
+
+ +
+ +
+ + +

+ needs_sharding + + + + abstractmethod + + +

+
needs_sharding() -> bool
+
+ +
+ +

Check if the dataloader needs to be sharded.

+ +
+ Source code in src/loadax/dataloader/sharding.py + 
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@abstractmethod
+def needs_sharding(self) -> bool:
+    """Check if the dataloader needs to be sharded."""
+    pass
+
+
+
+ +
+ +
+ + +

+ distribute_global_batch + + + + abstractmethod + + +

+
distribute_global_batch(local_batch: ndarray, *, data_axis: str | None = None) -> ndarray
+
+ +
+ +

Distribute a local batch across the entire cluster.

+

Take a local batch and stitch it together into a global batch with all processes +contributing their local batch to the global batch. This is useful for +distributed training where the data is not replicated across the entire cluster.

+ + +

Parameters:

+ + + + + + + + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
local_batch + ndarray + +
+

The local batch to distribute.

+
+ 		+ required +
data_axis + str | None + +
+

The axis name for the data sharding. +If None, then the data axis must have been provided to the +sharding_strategy. Defaults to None.

+
+ 		+ None +
+ + +

Returns:

+ + + + + + + + + + + + + +
TypeDescription
+ ndarray + +
+

np.ndarray: The global batch.

+
+
+ +
+ Source code in src/loadax/dataloader/sharding.py + 
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@abstractmethod
+def distribute_global_batch(
+    self, local_batch: jnp.ndarray, *, data_axis: str | None = None
+) -> jnp.ndarray:
+    """Distribute a local batch across the entire cluster.
+
+    Take a local batch and stitch it together into a global batch with all processes
+    contributing their local batch to the global batch. This is useful for
+    distributed training where the data is not replicated across the entire cluster.
+
+    Args:
+        local_batch: The local batch to distribute.
+        data_axis: The axis name for the data sharding.
+            If None, then the data axis must have been provided to the
+            sharding_strategy. Defaults to None.
+
+    Returns:
+        np.ndarray: The global batch.
+    """
+    pass
+
+
+
+ +
+ +
+ + +

+ named_sharding + + +

+
named_sharding(*names: str | None) -> NamedSharding
+
+ +
+ +

Get a NamedSharding object for the given axis names.

+

This is just a useful convenience method for creating NamedSharding objects, +just provide the axis names as they exist in the mesh to create the +NamedSharding object.

+ + +

Parameters:

+ + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
*names + str | None + +
+

The axis names to use for the NamedSharding object.

+
+ 		+ () +
+ + +

Returns:

+ + + + + + + + + + + + + +
TypeDescription
+ NamedSharding + +
+

jax.NamedSharding: The NamedSharding object for the given axis names.

+
+
+ +
+ Source code in src/loadax/dataloader/sharding.py + 
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def named_sharding(self, *names: str | None) -> jax.NamedSharding:
+    """Get a NamedSharding object for the given axis names.
+
+    This is just a useful convenience method for creating NamedSharding objects,
+    just provide the axis names as they exist in the mesh to create the
+    NamedSharding object.
+
+    Args:
+        *names (str | None): The axis names to use for the NamedSharding object.
+
+    Returns:
+        jax.NamedSharding: The NamedSharding object for the given axis names.
+    """
+    return jax.NamedSharding(self.mesh, PartitionSpec(*names))  # type: ignore # jax PartitionSpec has missing types in current version
+
+
+
+ +
+ + + +
+ +
+ +
+ +
+ + + + +
+

+ Bases: ShardingStrategy

+ + +

A sharding strategy that does not shard the data.

+

This is the default sharding strategy used on single node training. This also +is useful if you are doing ensemble training where each node should get the exact +same batch of data.

+ + + + +
+ + + + + + + + + +
+ + +

+ get_shard_indices + + +

+
get_shard_indices(dataset_size: int, shard_id: int, num_shards: int) -> range
+
+ +
+ +

Get the data indices for a specific shard.

+ +
+ Source code in src/loadax/dataloader/sharding.py + 
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def get_shard_indices(
+    self, dataset_size: int, shard_id: int, num_shards: int
+) -> range:
+    """Get the data indices for a specific shard."""
+    return range(dataset_size)
+
+
+
+ +
+ +
+ + +

+ needs_sharding + + +

+
needs_sharding() -> bool
+
+ +
+ +

Check if the dataloader needs to be sharded.

+ +
+ Source code in src/loadax/dataloader/sharding.py + 
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def needs_sharding(self) -> bool:
+    """Check if the dataloader needs to be sharded."""
+    return False
+
+
+
+ +
+ +
+ + +

+ distribute_global_batch + + +

+
distribute_global_batch(local_batch: ndarray, *, data_axis: str | None = None) -> ndarray
+
+ +
+ +

Distribute a local batch across the entire cluster.

+

Take a local batch and stitch it together into a global batch with all processes +contributing their local batch to the global batch. This is useful for +distributed training where the data is not replicated across the entire cluster.

+ + +

Parameters:

+ + + + + + + + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
local_batch + ndarray + +
+

The local batch to distribute.

+
+ 		+ required +
data_axis + str | None + +
+

The axis name for the data sharding. +If None, then the data axis must have been provided to the +sharding_strategy. Defaults to None.

+
+ 		+ None +
+ + +

Returns:

+ + + + + + + + + + + + + +
TypeDescription
+ ndarray + +
+

np.ndarray: The global batch.

+
+
+ +
+ Source code in src/loadax/dataloader/sharding.py + 
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def distribute_global_batch(
+    self, local_batch: jnp.ndarray, *, data_axis: str | None = None
+) -> jnp.ndarray:
+    """Distribute a local batch across the entire cluster.
+
+    Take a local batch and stitch it together into a global batch with all processes
+    contributing their local batch to the global batch. This is useful for
+    distributed training where the data is not replicated across the entire cluster.
+
+    Args:
+        local_batch: The local batch to distribute.
+        data_axis: The axis name for the data sharding.
+            If None, then the data axis must have been provided to the
+            sharding_strategy. Defaults to None.
+
+    Returns:
+        np.ndarray: The global batch.
+    """
+    return local_batch
+
+
+
+ +
+ + + +
+ +
+ +
+ +
+ + + + +
+

+ Bases: ShardingStrategy

+ + +

Define a distributed sharding strategy for the dataloader.

+

This sharding strategy is useful for distributed training where each node +should only load a partition of the dataset. This is done by dividing the +dataset into equally sized shards and assigning each worker node a +subset of the shards.

+

The most common way to use this sharding strategy is to have each jax process +load a local_batch which is a partition of the batch at any given step, +because in most distributed training setups, the data is not replicated across +the entire cluster. This means that we can pre-compute which process needs which +data and then we can just load the data for that process. Upon loading the +local_batch, we can then use the distribute_global_batch method to distribute +the local_batch across the entire cluster. This name is atually a bit misleading, +because the local_batchis not actually distributed across the entire cluster, +but rather is just stitched into a global_batch that is distributed across the +entire cluster. This enables you to write your jax code in a way that is agnostic +to the distribution of the data.

+ + + +

Parameters:

+ + + + + + + + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
mesh + Mesh + +
+

The mesh to use for sharding.

+
+ 		+ required +
data_shard_axis + str | None + +
+

The axis name for the data sharding. +This is used to determine how to compute the global batch from +the node-local batches. If None, then the data sharding axis +will be required to be supplied when using distribute_global_batch.

+
+ 		+ None +
+ +
+ Source code in src/loadax/dataloader/sharding.py + 
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def __init__(self, mesh: Mesh, data_shard_axis: str | None = None):
+    """Create a new distributed sharding strategy.
+
+    Args:
+        mesh (Mesh): The mesh to use for sharding.
+        data_shard_axis (str | None): The axis name for the data sharding.
+            This is used to determine how to compute the global batch from
+            the node-local batches. If None, then the data sharding axis
+            will be required to be supplied when using `distribute_global_batch`.
+    """
+    self.mesh = mesh
+    self.data_axis = data_shard_axis
+
+
+ + + +
+ + + + + + + + + +
+ + +

+ get_shard_indices + + +

+
get_shard_indices(dataset_size: int, shard_id: int, num_shards: int) -> range
+
+ +
+ +

Get the data indices for a specific shard.

+ + +

Parameters:

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
dataset_size + int + +
+

The size of the dataset.

+
+ 		+ required +
shard_id + int + +
+

The ID of the shard.

+
+ 		+ required +
num_shards + int + +
+

The total number of shards.

+
+ 		+ required +
+ + +

Returns:

+ + + + + + + + + + + + + +
Name TypeDescription
range + range + +
+

The data indices for the shard.

+
+
+ +
+ Source code in src/loadax/dataloader/sharding.py + 
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def get_shard_indices(
+    self, dataset_size: int, shard_id: int, num_shards: int
+) -> range:
+    """Get the data indices for a specific shard.
+
+    Args:
+        dataset_size: The size of the dataset.
+        shard_id: The ID of the shard.
+        num_shards: The total number of shards.
+
+    Returns:
+        range: The data indices for the shard.
+    """
+    if num_shards <= 1:
+        return range(dataset_size)
+
+    base_shard_size = dataset_size // num_shards
+    remainder = dataset_size % num_shards
+
+    # distribute the remainder evenly across the first 'remainder' shards
+    if shard_id < remainder:
+        shard_size = base_shard_size + 1
+        start_index = shard_id * shard_size
+    else:
+        shard_size = base_shard_size
+        start_index = (
+            remainder * (base_shard_size + 1) + (shard_id - remainder) * shard_size
+        )
+
+    end_index = start_index + shard_size
+    return range(start_index, end_index)
+
+
+
+ +
+ +
+ + +

+ needs_sharding + + +

+
needs_sharding() -> bool
+
+ +
+ +

Check if the dataloader needs to be sharded.

+ +
+ Source code in src/loadax/dataloader/sharding.py + 
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+181
+182
def needs_sharding(self) -> bool:
+    """Check if the dataloader needs to be sharded."""
+    return True
+
+
+
+ +
+ +
+ + +

+ distribute_global_batch + + +

+
distribute_global_batch(local_batch: ndarray, *, data_axis: str | None = None) -> ndarray
+
+ +
+ +

Distribute a local batch across the entire cluster.

+

Take a local batch and stitch it together into a global batch with all processes +contributing their local batch to the global batch. This is useful for +distributed training where the data is not replicated across the entire cluster.

+ + +

Parameters:

+ + + + + + + + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
local_batch + ndarray + +
+

The local batch to distribute.

+
+ 		+ required +
data_axis + str | None + +
+

The axis name for the data sharding. +If None, then the data axis must have been provided to the +sharding_strategy. Defaults to None.

+
+ 		+ None +
+ + +

Returns:

+ + + + + + + + + + + + + +
TypeDescription
+ ndarray + +
+

np.ndarray: The global batch.

+
+
+ +
+ Source code in src/loadax/dataloader/sharding.py + 
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def distribute_global_batch(
+    self, local_batch: jnp.ndarray, *, data_axis: str | None = None
+) -> jnp.ndarray:
+    """Distribute a local batch across the entire cluster.
+
+    Take a local batch and stitch it together into a global batch with all processes
+    contributing their local batch to the global batch. This is useful for
+    distributed training where the data is not replicated across the entire cluster.
+
+    Args:
+        local_batch: The local batch to distribute.
+        data_axis: The axis name for the data sharding.
+            If None, then the data axis must have been provided to the
+            sharding_strategy. Defaults to None.
+
+    Returns:
+        np.ndarray: The global batch.
+    """
+    # local_batch: the batch of data on the local process
+    # data_axis: the axis name for the data sharding
+
+    data_axis = data_axis or self.data_axis
+    if not data_axis:
+        raise ValueError(
+            "data_axis must be provided when using distribute_global_batch"
+        )
+
+    if jax.process_count() == 1:
+        return jnp.asarray(local_batch)
+
+    data_sharding = self.named_sharding(data_axis)
+    global_batch_size = local_batch.shape[0] * jax.process_count()
+    global_batch_shape = (global_batch_size,) + local_batch.shape[1:]
+
+    def data_callback(index: Any) -> jnp.ndarray:
+        # index: the global index for the sharded array
+        # We need to return the local data corresponding to this index
+        # Since each process only has its local data, we check if the index
+        # corresponds to our process
+
+        # Calculate the start and end indices for this process
+        per_process_batch_size = local_batch.shape[0]
+        start = jax.process_index() * per_process_batch_size
+        end = start + per_process_batch_size
+
+        # Check if the requested index overlaps with our local data
+        index_start = index[0].start or 0
+        index_stop = index[0].stop or global_batch_size
+
+        # If the requested index is within our local data range, return
+        # the corresponding data
+        if start <= index_start < end:
+            local_index_start = index_start - start
+            local_index_stop = min(index_stop - start, per_process_batch_size)
+            return local_batch[local_index_start:local_index_stop]
+        else:
+            # Return an empty array if the index does not correspond to our data
+            return jnp.zeros((0,) + local_batch.shape[1:], dtype=local_batch.dtype)
+
+    global_batch = jax.make_array_from_callback(
+        global_batch_shape, data_sharding, data_callback
+    )
+    return global_batch
+
+
+
+ +
+ + + +
+ +
+ +
+ + + + + + + + + + + + + + + +
+
+ + + + + +
+ + + +
+ + + +
+
+
+
+ +
+ + + + + + + + + + \ No newline at end of file diff --git a/v0.2.1/api/strategy/batch/index.html b/v0.2.1/api/strategy/batch/index.html new file mode 100644 index 0000000..e359739 --- /dev/null +++ b/v0.2.1/api/strategy/batch/index.html @@ -0,0 +1,1769 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + Batch Strategy - Loadax Documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + Skip to content + + +
+
+ + + +
+ + + + + + +
+ + +
+ +
+ + + + + + + + + +
+
+ + + +
+
+
+ + + + + + + +
+
+
+ + + +
+
+
+ + + + + +
+
+
+ + + +
+
+ + + + + + + + +

Batch Strategy

+

A batch strategy is a simple interface that defines how to collate batches from a dataset. The batch strategy is +responsible for determining how to batch data from a stream of elements. Currently, loadax only supports the +FixedBatchStrategy, which batches data into fixed size batches. However, in the future, loadax will support +other batch strategies such as variable batch sizes, and even variable batch sizes that are determined by the +data itself.

+
Creating a batch strategy
from loadax import Batcher, InMemoryDataset, FixedBatchStrategy
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+batcher = Batcher(lambda x: x)
+batch_strategy = FixedBatchStrategy(batch_size=2)
+
+for batch in batch_strategy.batch(dataset):
+    print(batch)
+
+#> [1, 2]
+#> [3, 4]
+#> [5]
+
+ + +
+ + + + +
+

+ Bases: Protocol, Generic[DatasetItem]

+ + +

The method for determining how much data goes into a batch.

+

This protocol defines the interface for determining how much data goes into a batch +as it is loaded from the dataset.

+ + +

Attributes:

+ + + + + + + + + + + + + + + +
NameTypeDescription
batch_size + int + +
+

The size of the batch.

+
+
+ + + + +
+ + + + + + + + + +
+ + +

+ add + + +

+
add(item: DatasetItem) -> None
+
+ +
+ +

Add an item to the batch.

+ + +

Parameters:

+ + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
item + DatasetItem + +
+

The item to add to the batch.

+
+ 		+ required +
+ +
+ Source code in src/loadax/strategy.py + 
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def add(self, item: DatasetItem) -> None:
+    """Add an item to the batch.
+
+    Args:
+        item: The item to add to the batch.
+    """
+    ...
+
+
+
+ +
+ +
+ + +

+ batch + + +

+
batch(*, force: bool) -> list[DatasetItem] | None
+
+ +
+ +

Get the batch.

+

This method method returns the batch if it is full, or None if the batch is not +full.

+ + +

Parameters:

+ + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
force + bool + +
+

Whether to force the batch to be returned even if it is not full.

+
+ 		+ required +
+ + +

Returns:

+ + + + + + + + + + + + + +
TypeDescription
+ list[DatasetItem] | None + +
+

The batch, or None if the batch is not full.

+
+
+ +
+ Source code in src/loadax/strategy.py + 
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def batch(self, *, force: bool) -> list[DatasetItem] | None:
+    """Get the batch.
+
+    This method method returns the batch if it is full, or None if the batch is not
+    full.
+
+    Args:
+        force: Whether to force the batch to be returned even if it is not full.
+
+    Returns:
+        The batch, or None if the batch is not full.
+    """
+    ...
+
+
+
+ +
+ +
+ + +

+ clone + + +

+
clone() -> BatchStrategy[DatasetItem]
+
+ +
+ +

Clone the batch strategy.

+

This is likely not necessary but exists in advanced use cases such as sharing +a batch strategy between multiple processes.

+ + +

Returns:

+ + + + + + + + + + + + + +
TypeDescription
+ BatchStrategy[DatasetItem] + +
+

A clone of the batch strategy.

+
+
+ +
+ Source code in src/loadax/strategy.py + 
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def clone(self) -> "BatchStrategy[DatasetItem]":
+    """Clone the batch strategy.
+
+    This is likely not necessary but exists in advanced use cases such as sharing
+    a batch strategy between multiple processes.
+
+    Returns:
+        A clone of the batch strategy.
+    """
+    ...
+
+
+
+ +
+ + + +
+ +
+ +
+ + + + + + + + + + + + + + + +
+
+ + + + + +
+ + + +
+ + + +
+
+
+
+ +
+ + + + + + + + + + \ No newline at end of file diff --git a/v0.2.1/api/strategy/fixed/index.html b/v0.2.1/api/strategy/fixed/index.html new file mode 100644 index 0000000..75c9a39 --- /dev/null +++ b/v0.2.1/api/strategy/fixed/index.html @@ -0,0 +1,1853 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + Fixed Batch Strategy - Loadax Documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + Skip to content + + +
+
+ + + +
+ + + + + + +
+ + +
+ +
+ + + + + + + + + +
+
+ + + +
+
+
+ + + + + + + +
+
+
+ + + +
+
+
+ + + + + +
+
+
+ + + +
+
+ + + + + + + + +

Fixed Batch Strategy

+

The FixedBatchStrategy is a simple batch strategy that batches data into fixed size batches. This ensures all +batches are the same size, except for the last batch which may be smaller.

+
Creating a fixed batch strategy
from loadax import Batcher, InMemoryDataset, FixedBatchStrategy
+
+dataset = InMemoryDataset([1, 2, 3, 4, 5])
+batcher = Batcher(lambda x: x)
+batch_strategy = FixedBatchStrategy(batch_size=2)
+
+for batch in batch_strategy.batch(dataset):
+    print(batch)
+
+#> [1, 2]
+#> [3, 4]
+#> [5]
+
+ + +
+ + + + +
+

+ Bases: BatchStrategy[DatasetItem]

+ + +

A batch strategy that batches items into a fixed size batch.

+

This batch strategy batches items into a fixed size batch. It will always return +the same batch size, and will return None if the batch is not full. This is +almost always what you want.

+ + +

Attributes:

+ + + + + + + + + + + + + + + + + + + + +
NameTypeDescription
batch_size + +
+

The size of the batch.

+
+
items + deque[DatasetItem] + +
+

The items in the batch.

+
+
+ +

This batch strategy batches items into a fixed size batch. It will always return +the same batch size, and will return None if the batch is not full. This is +almost always what you want.

+ + +

Parameters:

+ + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
batch_size + int + +
+

The size of the batch.

+
+ 		+ required +
+ +
+ Source code in src/loadax/strategy.py + 
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def __init__(self, batch_size: int):
+    """A batch strategy that batches items into a fixed size batch.
+
+    This batch strategy batches items into a fixed size batch. It will always return
+    the same batch size, and will return None if the batch is not full. This is
+    almost always what you want.
+
+    Args:
+        batch_size: The size of the batch.
+    """
+    self.batch_size = batch_size
+    self.items: deque[DatasetItem] = deque()
+
+
+ + + +
+ + + + + + + + + +
+ + +

+ add + + +

+
add(item: DatasetItem) -> None
+
+ +
+ +

Add an item to the batch.

+ + +

Parameters:

+ + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
item + DatasetItem + +
+

The item to add to the batch.

+
+ 		+ required +
+ +
+ Source code in src/loadax/strategy.py + 
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def add(self, item: DatasetItem) -> None:
+    """Add an item to the batch.
+
+    Args:
+        item: The item to add to the batch.
+    """
+    self.items.append(item)
+
+
+
+ +
+ +
+ + +

+ batch + + +

+
batch(*, force: bool) -> list[DatasetItem] | None
+
+ +
+ +

Get the batch.

+

This method method returns the batch if it is full, or None if the batch is not +full.

+ + +

Parameters:

+ + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
force + bool + +
+

Whether to force the batch to be returned even if it is not full.

+
+ 		+ required +
+ + +

Returns:

+ + + + + + + + + + + + + +
TypeDescription
+ list[DatasetItem] | None + +
+

The batch, or None if the batch is not full.

+
+
+ +
+ Source code in src/loadax/strategy.py + 
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def batch(self, *, force: bool) -> list[DatasetItem] | None:
+    """Get the batch.
+
+    This method method returns the batch if it is full, or None if the batch is not
+    full.
+
+    Args:
+        force: Whether to force the batch to be returned even if it is not full.
+
+    Returns:
+        The batch, or None if the batch is not full.
+    """
+    if len(self.items) >= self.batch_size:
+        return [self.items.popleft() for _ in range(self.batch_size)]
+    elif force and self.items:
+        return list(self.items)
+    return None
+
+
+
+ +
+ +
+ + +

+ clone + + +

+
clone() -> FixedBatchStrategy[DatasetItem]
+
+ +
+ +

Clone the batch strategy.

+

This is likely not necessary but exists in advanced use cases such as sharing +a batch strategy between multiple processes.

+ + +

Returns:

+ + + + + + + + + + + + + +
TypeDescription
+ FixedBatchStrategy[DatasetItem] + +
+

A clone of the batch strategy.

+
+
+ +
+ Source code in src/loadax/strategy.py + 
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def clone(self) -> "FixedBatchStrategy[DatasetItem]":
+    """Clone the batch strategy.
+
+    This is likely not necessary but exists in advanced use cases such as sharing
+    a batch strategy between multiple processes.
+
+    Returns:
+        A clone of the batch strategy.
+    """
+    new_strategy: FixedBatchStrategy[DatasetItem] = FixedBatchStrategy(
+        self.batch_size
+    )
+    new_strategy.items = self.items.copy()
+    return new_strategy
+
+
+
+ +
+ + + +
+ +
+ +
+ + + + + + + + + + + + + + + +
+
+ + + + + +
+ + + +
+ + + +
+
+
+
+ +
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g,o=r.pipe(Z(),ie(!0));z([t.pipe(Ae(jt)),r],(i,a)=>a).pipe(ee("value")).subscribe(({value:i})=>t.next({type:2,data:i})),r.pipe(ee("focus")).subscribe(({focus:i})=>{i&&Je("search",i)}),h(e.form,"reset").pipe(U(o)).subscribe(()=>e.focus());let n=R("header [for=__search]");return h(n,"click").subscribe(()=>e.focus()),is(e,{worker$:t}).pipe(w(i=>r.next(i)),_(()=>r.complete()),m(i=>$({ref:e},i)),G(1))}function ci(e,{worker$:t,query$:r}){let o=new g,n=rn(e.parentElement).pipe(b(Boolean)),i=e.parentElement,a=R(":scope > :first-child",e),s=R(":scope > :last-child",e);ze("search").subscribe(l=>s.setAttribute("role",l?"list":"presentation")),o.pipe(re(r),Ur(t.pipe(Ae(jt)))).subscribe(([{items:l},{value:f}])=>{switch(l.length){case 0:a.textContent=f.length?Ee("search.result.none"):Ee("search.result.placeholder");break;case 1:a.textContent=Ee("search.result.one");break;default:let u=sr(l.length);a.textContent=Ee("search.result.other",u)}});let p=o.pipe(w(()=>s.innerHTML=""),v(({items:l})=>O(I(...l.slice(0,10)),I(...l.slice(10)).pipe(Be(4),Vr(n),v(([f])=>f)))),m(Mn),pe());return p.subscribe(l=>s.appendChild(l)),p.pipe(ne(l=>{let f=fe("details",l);return typeof f=="undefined"?S:h(f,"toggle").pipe(U(o),m(()=>f))})).subscribe(l=>{l.open===!1&&l.offsetTop<=i.scrollTop&&i.scrollTo({top:l.offsetTop})}),t.pipe(b(dr),m(({data:l})=>l)).pipe(w(l=>o.next(l)),_(()=>o.complete()),m(l=>$({ref:e},l)))}function as(e,{query$:t}){return t.pipe(m(({value:r})=>{let o=ye();return o.hash="",r=r.replace(/\s+/g,"+").replace(/&/g,"%26").replace(/=/g,"%3D"),o.search=`q=${r}`,{url:o}}))}function pi(e,t){let r=new g,o=r.pipe(Z(),ie(!0));return r.subscribe(({url:n})=>{e.setAttribute("data-clipboard-text",e.href),e.href=`${n}`}),h(e,"click").pipe(U(o)).subscribe(n=>n.preventDefault()),as(e,t).pipe(w(n=>r.next(n)),_(()=>r.complete()),m(n=>$({ref:e},n)))}function li(e,{worker$:t,keyboard$:r}){let o=new g,n=Se("search-query"),i=O(h(n,"keydown"),h(n,"focus")).pipe(ve(se),m(()=>n.value),K());return o.pipe(He(i),m(([{suggest:s},p])=>{let c=p.split(/([\s-]+)/);if(s!=null&&s.length&&c[c.length-1]){let l=s[s.length-1];l.startsWith(c[c.length-1])&&(c[c.length-1]=l)}else c.length=0;return c})).subscribe(s=>e.innerHTML=s.join("").replace(/\s/g," ")),r.pipe(b(({mode:s})=>s==="search")).subscribe(s=>{switch(s.type){case"ArrowRight":e.innerText.length&&n.selectionStart===n.value.length&&(n.value=e.innerText);break}}),t.pipe(b(dr),m(({data:s})=>s)).pipe(w(s=>o.next(s)),_(()=>o.complete()),m(()=>({ref:e})))}function mi(e,{index$:t,keyboard$:r}){let o=xe();try{let n=ii(o.search,t),i=Se("search-query",e),a=Se("search-result",e);h(e,"click").pipe(b(({target:p})=>p instanceof Element&&!!p.closest("a"))).subscribe(()=>Je("search",!1)),r.pipe(b(({mode:p})=>p==="search")).subscribe(p=>{let c=Ie();switch(p.type){case"Enter":if(c===i){let l=new Map;for(let f of P(":first-child [href]",a)){let 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z([t,r.pipe(Q(ye()),b(o=>!!o.searchParams.get("h")))]).pipe(m(([o,n])=>ni(o.config)(n.searchParams.get("h"))),m(o=>{var a;let n=new Map,i=document.createNodeIterator(e,NodeFilter.SHOW_TEXT);for(let s=i.nextNode();s;s=i.nextNode())if((a=s.parentElement)!=null&&a.offsetHeight){let p=s.textContent,c=o(p);c.length>p.length&&n.set(s,c)}for(let[s,p]of n){let{childNodes:c}=x("span",null,p);s.replaceWith(...Array.from(c))}return{ref:e,nodes:n}}))}function ss(e,{viewport$:t,main$:r}){let o=e.closest(".md-grid"),n=o.offsetTop-o.parentElement.offsetTop;return z([r,t]).pipe(m(([{offset:i,height:a},{offset:{y:s}}])=>(a=a+Math.min(n,Math.max(0,s-i))-n,{height:a,locked:s>=i+n})),K((i,a)=>i.height===a.height&&i.locked===a.locked))}function Xr(e,o){var n=o,{header$:t}=n,r=ao(n,["header$"]);let i=R(".md-sidebar__scrollwrap",e),{y:a}=Ve(i);return C(()=>{let s=new g,p=s.pipe(Z(),ie(!0)),c=s.pipe(Le(0,me));return c.pipe(re(t)).subscribe({next([{height:l},{height:f}]){i.style.height=`${l-2*a}px`,e.style.top=`${f}px`},complete(){i.style.height="",e.style.top=""}}),c.pipe(Ae()).subscribe(()=>{for(let l of P(".md-nav__link--active[href]",e)){if(!l.clientHeight)continue;let f=l.closest(".md-sidebar__scrollwrap");if(typeof f!="undefined"){let u=l.offsetTop-f.offsetTop,{height:d}=ce(f);f.scrollTo({top:u-d/2})}}}),ue(P("label[tabindex]",e)).pipe(ne(l=>h(l,"click").pipe(ve(se),m(()=>l),U(p)))).subscribe(l=>{let f=R(`[id="${l.htmlFor}"]`);R(`[aria-labelledby="${l.id}"]`).setAttribute("aria-expanded",`${f.checked}`)}),ss(e,r).pipe(w(l=>s.next(l)),_(()=>s.complete()),m(l=>$({ref:e},l)))})}function ui(e,t){if(typeof t!="undefined"){let r=`https://api.github.com/repos/${e}/${t}`;return st(je(`${r}/releases/latest`).pipe(de(()=>S),m(o=>({version:o.tag_name})),De({})),je(r).pipe(de(()=>S),m(o=>({stars:o.stargazers_count,forks:o.forks_count})),De({}))).pipe(m(([o,n])=>$($({},o),n)))}else{let r=`https://api.github.com/users/${e}`;return je(r).pipe(m(o=>({repositories:o.public_repos})),De({}))}}function di(e,t){let r=`https://${e}/api/v4/projects/${encodeURIComponent(t)}`;return st(je(`${r}/releases/permalink/latest`).pipe(de(()=>S),m(({tag_name:o})=>({version:o})),De({})),je(r).pipe(de(()=>S),m(({star_count:o,forks_count:n})=>({stars:o,forks:n})),De({}))).pipe(m(([o,n])=>$($({},o),n)))}function hi(e){let t=e.match(/^.+github\.com\/([^/]+)\/?([^/]+)?/i);if(t){let[,r,o]=t;return ui(r,o)}if(t=e.match(/^.+?([^/]*gitlab[^/]+)\/(.+?)\/?$/i),t){let[,r,o]=t;return di(r,o)}return S}var cs;function ps(e){return cs||(cs=C(()=>{let t=__md_get("__source",sessionStorage);if(t)return I(t);if(ae("consent").length){let o=__md_get("__consent");if(!(o&&o.github))return S}return hi(e.href).pipe(w(o=>__md_set("__source",o,sessionStorage)))}).pipe(de(()=>S),b(t=>Object.keys(t).length>0),m(t=>({facts:t})),G(1)))}function bi(e){let t=R(":scope > :last-child",e);return C(()=>{let r=new g;return r.subscribe(({facts:o})=>{t.appendChild(Ln(o)),t.classList.add("md-source__repository--active")}),ps(e).pipe(w(o=>r.next(o)),_(()=>r.complete()),m(o=>$({ref:e},o)))})}function ls(e,{viewport$:t,header$:r}){return ge(document.body).pipe(v(()=>mr(e,{header$:r,viewport$:t})),m(({offset:{y:o}})=>({hidden:o>=10})),ee("hidden"))}function vi(e,t){return C(()=>{let r=new g;return r.subscribe({next({hidden:o}){e.hidden=o},complete(){e.hidden=!1}}),(B("navigation.tabs.sticky")?I({hidden:!1}):ls(e,t)).pipe(w(o=>r.next(o)),_(()=>r.complete()),m(o=>$({ref:e},o)))})}function ms(e,{viewport$:t,header$:r}){let o=new Map,n=P(".md-nav__link",e);for(let s of n){let p=decodeURIComponent(s.hash.substring(1)),c=fe(`[id="${p}"]`);typeof c!="undefined"&&o.set(s,c)}let i=r.pipe(ee("height"),m(({height:s})=>{let p=Se("main"),c=R(":scope > :first-child",p);return s+.8*(c.offsetTop-p.offsetTop)}),pe());return ge(document.body).pipe(ee("height"),v(s=>C(()=>{let p=[];return 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n=t.pipe(m(({offset:{y:a}})=>a),Be(2,1),m(([a,s])=>a>s&&s>0),K()),i=r.pipe(m(({active:a})=>a));return z([i,n]).pipe(m(([a,s])=>!(a&&s)),K(),U(o.pipe(Ce(1))),ie(!0),ct({delay:250}),m(a=>({hidden:a})))}function yi(e,{viewport$:t,header$:r,main$:o,target$:n}){let i=new g,a=i.pipe(Z(),ie(!0));return i.subscribe({next({hidden:s}){e.hidden=s,s?(e.setAttribute("tabindex","-1"),e.blur()):e.removeAttribute("tabindex")},complete(){e.style.top="",e.hidden=!0,e.removeAttribute("tabindex")}}),r.pipe(U(a),ee("height")).subscribe(({height:s})=>{e.style.top=`${s+16}px`}),h(e,"click").subscribe(s=>{s.preventDefault(),window.scrollTo({top:0})}),fs(e,{viewport$:t,main$:o,target$:n}).pipe(w(s=>i.next(s)),_(()=>i.complete()),m(s=>$({ref:e},s)))}function xi({document$:e,viewport$:t}){e.pipe(v(()=>P(".md-ellipsis")),ne(r=>tt(r).pipe(U(e.pipe(Ce(1))),b(o=>o),m(()=>r),Te(1))),b(r=>r.offsetWidth{let o=r.innerText,n=r.closest("a")||r;return n.title=o,B("content.tooltips")?mt(n,{viewport$:t}).pipe(U(e.pipe(Ce(1))),_(()=>n.removeAttribute("title"))):S})).subscribe(),B("content.tooltips")&&e.pipe(v(()=>P(".md-status")),ne(r=>mt(r,{viewport$:t}))).subscribe()}function Ei({document$:e,tablet$:t}){e.pipe(v(()=>P(".md-toggle--indeterminate")),w(r=>{r.indeterminate=!0,r.checked=!1}),ne(r=>h(r,"change").pipe(Dr(()=>r.classList.contains("md-toggle--indeterminate")),m(()=>r))),re(t)).subscribe(([r,o])=>{r.classList.remove("md-toggle--indeterminate"),o&&(r.checked=!1)})}function us(){return/(iPad|iPhone|iPod)/.test(navigator.userAgent)}function wi({document$:e}){e.pipe(v(()=>P("[data-md-scrollfix]")),w(t=>t.removeAttribute("data-md-scrollfix")),b(us),ne(t=>h(t,"touchstart").pipe(m(()=>t)))).subscribe(t=>{let r=t.scrollTop;r===0?t.scrollTop=1:r+t.offsetHeight===t.scrollHeight&&(t.scrollTop=r-1)})}function Ti({viewport$:e,tablet$:t}){z([ze("search"),t]).pipe(m(([r,o])=>r&&!o),v(r=>I(r).pipe(Ge(r?400:100))),re(e)).subscribe(([r,{offset:{y:o}}])=>{if(r)document.body.setAttribute("data-md-scrolllock",""),document.body.style.top=`-${o}px`;else{let n=-1*parseInt(document.body.style.top,10);document.body.removeAttribute("data-md-scrolllock"),document.body.style.top="",n&&window.scrollTo(0,n)}})}Object.entries||(Object.entries=function(e){let t=[];for(let r of Object.keys(e))t.push([r,e[r]]);return t});Object.values||(Object.values=function(e){let t=[];for(let r of Object.keys(e))t.push(e[r]);return t});typeof Element!="undefined"&&(Element.prototype.scrollTo||(Element.prototype.scrollTo=function(e,t){typeof e=="object"?(this.scrollLeft=e.left,this.scrollTop=e.top):(this.scrollLeft=e,this.scrollTop=t)}),Element.prototype.replaceWith||(Element.prototype.replaceWith=function(...e){let t=this.parentNode;if(t){e.length===0&&t.removeChild(this);for(let r=e.length-1;r>=0;r--){let o=e[r];typeof 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t!="undefined"&<(t);break;case"n":case".":let r=fe("link[rel=next]");typeof r!="undefined"&<(r);break;case"Enter":let o=Ie();o instanceof HTMLLabelElement&&o.click()}});xi({viewport$:Oe,document$:ot});Ei({document$:ot,tablet$:hr});wi({document$:ot});Ti({viewport$:Oe,tablet$:hr});var rt=Qn(Se("header"),{viewport$:Oe}),Ft=ot.pipe(m(()=>Se("main")),v(e=>Bn(e,{viewport$:Oe,header$:rt})),G(1)),hs=O(...ae("consent").map(e=>xn(e,{target$:Mt})),...ae("dialog").map(e=>zn(e,{alert$:to})),...ae("header").map(e=>Kn(e,{viewport$:Oe,header$:rt,main$:Ft})),...ae("palette").map(e=>Gn(e)),...ae("progress").map(e=>Jn(e,{progress$:ro})),...ae("search").map(e=>mi(e,{index$:Li,keyboard$:eo})),...ae("source").map(e=>bi(e))),bs=C(()=>O(...ae("announce").map(e=>yn(e)),...ae("content").map(e=>Nn(e,{viewport$:Oe,target$:Mt,print$:Mi})),...ae("content").map(e=>B("search.highlight")?fi(e,{index$:Li,location$:Wt}):S),...ae("header-title").map(e=>Yn(e,{viewport$:Oe,header$:rt})),...ae("sidebar").map(e=>e.getAttribute("data-md-type")==="navigation"?Nr(Oi,()=>Xr(e,{viewport$:Oe,header$:rt,main$:Ft})):Nr(hr,()=>Xr(e,{viewport$:Oe,header$:rt,main$:Ft}))),...ae("tabs").map(e=>vi(e,{viewport$:Oe,header$:rt})),...ae("toc").map(e=>gi(e,{viewport$:Oe,header$:rt,main$:Ft,target$:Mt})),...ae("top").map(e=>yi(e,{viewport$:Oe,header$:rt,main$:Ft,target$:Mt})))),_i=ot.pipe(v(()=>bs),Re(hs),G(1));_i.subscribe();window.document$=ot;window.location$=Wt;window.target$=Mt;window.keyboard$=eo;window.viewport$=Oe;window.tablet$=hr;window.screen$=Oi;window.print$=Mi;window.alert$=to;window.progress$=ro;window.component$=_i;})(); +//# sourceMappingURL=bundle.56dfad97.min.js.map + diff --git a/v0.2.1/assets/javascripts/bundle.56dfad97.min.js.map b/v0.2.1/assets/javascripts/bundle.56dfad97.min.js.map new file mode 100644 index 0000000..eb83bdb --- /dev/null +++ b/v0.2.1/assets/javascripts/bundle.56dfad97.min.js.map @@ -0,0 +1,7 @@ +{ + "version": 3, + "sources": ["node_modules/focus-visible/dist/focus-visible.js", "node_modules/escape-html/index.js", "node_modules/clipboard/dist/clipboard.js", "src/templates/assets/javascripts/bundle.ts", "node_modules/tslib/tslib.es6.mjs", "node_modules/rxjs/src/internal/util/isFunction.ts", "node_modules/rxjs/src/internal/util/createErrorClass.ts", "node_modules/rxjs/src/internal/util/UnsubscriptionError.ts", "node_modules/rxjs/src/internal/util/arrRemove.ts", "node_modules/rxjs/src/internal/Subscription.ts", "node_modules/rxjs/src/internal/config.ts", "node_modules/rxjs/src/internal/scheduler/timeoutProvider.ts", "node_modules/rxjs/src/internal/util/reportUnhandledError.ts", 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"node_modules/rxjs/src/internal/observable/timer.ts", "node_modules/rxjs/src/internal/observable/merge.ts", "node_modules/rxjs/src/internal/observable/never.ts", "node_modules/rxjs/src/internal/util/argsOrArgArray.ts", "node_modules/rxjs/src/internal/operators/filter.ts", "node_modules/rxjs/src/internal/observable/zip.ts", "node_modules/rxjs/src/internal/operators/audit.ts", "node_modules/rxjs/src/internal/operators/auditTime.ts", "node_modules/rxjs/src/internal/operators/bufferCount.ts", "node_modules/rxjs/src/internal/operators/catchError.ts", "node_modules/rxjs/src/internal/operators/scanInternals.ts", "node_modules/rxjs/src/internal/operators/combineLatest.ts", "node_modules/rxjs/src/internal/operators/combineLatestWith.ts", "node_modules/rxjs/src/internal/operators/debounce.ts", "node_modules/rxjs/src/internal/operators/debounceTime.ts", "node_modules/rxjs/src/internal/operators/defaultIfEmpty.ts", "node_modules/rxjs/src/internal/operators/take.ts", 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"sourcesContent": ["(function (global, factory) {\n typeof exports === 'object' && typeof module !== 'undefined' ? factory() :\n typeof define === 'function' && define.amd ? define(factory) :\n (factory());\n}(this, (function () { 'use strict';\n\n /**\n * Applies the :focus-visible polyfill at the given scope.\n * A scope in this case is either the top-level Document or a Shadow Root.\n *\n * @param {(Document|ShadowRoot)} scope\n * @see https://github.com/WICG/focus-visible\n */\n function applyFocusVisiblePolyfill(scope) {\n var hadKeyboardEvent = true;\n var hadFocusVisibleRecently = false;\n var hadFocusVisibleRecentlyTimeout = null;\n\n var inputTypesAllowlist = {\n text: true,\n search: true,\n url: true,\n tel: true,\n email: true,\n password: true,\n number: true,\n date: true,\n month: true,\n week: true,\n time: true,\n datetime: true,\n 'datetime-local': true\n };\n\n /**\n * Helper function for legacy browsers and iframes which sometimes focus\n * elements like document, body, and non-interactive SVG.\n * @param {Element} el\n */\n function isValidFocusTarget(el) {\n if (\n el &&\n el !== document &&\n el.nodeName !== 'HTML' &&\n el.nodeName !== 'BODY' &&\n 'classList' in el &&\n 'contains' in el.classList\n ) {\n return true;\n }\n return false;\n }\n\n /**\n * Computes whether the given element should automatically trigger the\n * `focus-visible` class being added, i.e. whether it should always match\n * `:focus-visible` when focused.\n * @param {Element} el\n * @return {boolean}\n */\n function focusTriggersKeyboardModality(el) {\n var type = el.type;\n var tagName = el.tagName;\n\n if (tagName === 'INPUT' && inputTypesAllowlist[type] && !el.readOnly) {\n return true;\n }\n\n if (tagName === 'TEXTAREA' && !el.readOnly) {\n return true;\n }\n\n if (el.isContentEditable) {\n return true;\n }\n\n return false;\n }\n\n /**\n * Add the `focus-visible` class to the given element if it was not added by\n * the author.\n * @param {Element} el\n */\n function addFocusVisibleClass(el) {\n if (el.classList.contains('focus-visible')) {\n return;\n }\n el.classList.add('focus-visible');\n el.setAttribute('data-focus-visible-added', '');\n }\n\n /**\n * Remove the `focus-visible` class from the given element if it was not\n * originally added by the author.\n * @param {Element} el\n */\n function removeFocusVisibleClass(el) {\n if (!el.hasAttribute('data-focus-visible-added')) {\n return;\n }\n el.classList.remove('focus-visible');\n el.removeAttribute('data-focus-visible-added');\n }\n\n /**\n * If the most recent user interaction was via the keyboard;\n * and the key press did not include a meta, alt/option, or control key;\n * then the modality is keyboard. Otherwise, the modality is not keyboard.\n * Apply `focus-visible` to any current active element and keep track\n * of our keyboard modality state with `hadKeyboardEvent`.\n * @param {KeyboardEvent} e\n */\n function onKeyDown(e) {\n if (e.metaKey || e.altKey || e.ctrlKey) {\n return;\n }\n\n if (isValidFocusTarget(scope.activeElement)) {\n addFocusVisibleClass(scope.activeElement);\n }\n\n hadKeyboardEvent = true;\n }\n\n /**\n * If at any point a user clicks with a pointing device, ensure that we change\n * the modality away from keyboard.\n * This avoids the situation where a user presses a key on an already focused\n * element, and then clicks on a different element, focusing it with a\n * pointing device, while we still think we're in keyboard modality.\n * @param {Event} e\n */\n function onPointerDown(e) {\n hadKeyboardEvent = false;\n }\n\n /**\n * On `focus`, add the `focus-visible` class to the target if:\n * - the target received focus as a result of keyboard navigation, or\n * - the event target is an element that will likely require interaction\n * via the keyboard (e.g. a text box)\n * @param {Event} e\n */\n function onFocus(e) {\n // Prevent IE from focusing the document or HTML element.\n if (!isValidFocusTarget(e.target)) {\n return;\n }\n\n if (hadKeyboardEvent || focusTriggersKeyboardModality(e.target)) {\n addFocusVisibleClass(e.target);\n }\n }\n\n /**\n * On `blur`, remove the `focus-visible` class from the target.\n * @param {Event} e\n */\n function onBlur(e) {\n if (!isValidFocusTarget(e.target)) {\n return;\n }\n\n if (\n e.target.classList.contains('focus-visible') ||\n e.target.hasAttribute('data-focus-visible-added')\n ) {\n // To detect a tab/window switch, we look for a blur event followed\n // rapidly by a visibility change.\n // If we don't see a visibility change within 100ms, it's probably a\n // regular focus change.\n hadFocusVisibleRecently = true;\n window.clearTimeout(hadFocusVisibleRecentlyTimeout);\n hadFocusVisibleRecentlyTimeout = window.setTimeout(function() {\n hadFocusVisibleRecently = false;\n }, 100);\n removeFocusVisibleClass(e.target);\n }\n }\n\n /**\n * If the user changes tabs, keep track of whether or not the previously\n * focused element had .focus-visible.\n * @param {Event} e\n */\n function onVisibilityChange(e) {\n if (document.visibilityState === 'hidden') {\n // If the tab becomes active again, the browser will handle calling focus\n // on the element (Safari actually calls it twice).\n // If this tab change caused a blur on an element with focus-visible,\n // re-apply the class when the user switches back to the tab.\n if (hadFocusVisibleRecently) {\n hadKeyboardEvent = true;\n }\n addInitialPointerMoveListeners();\n }\n }\n\n /**\n * Add a group of listeners to detect usage of any pointing devices.\n * These listeners will be added when the polyfill first loads, and anytime\n * the window is blurred, so that they are active when the window regains\n * focus.\n */\n function addInitialPointerMoveListeners() {\n document.addEventListener('mousemove', onInitialPointerMove);\n document.addEventListener('mousedown', onInitialPointerMove);\n document.addEventListener('mouseup', onInitialPointerMove);\n document.addEventListener('pointermove', onInitialPointerMove);\n document.addEventListener('pointerdown', onInitialPointerMove);\n document.addEventListener('pointerup', onInitialPointerMove);\n document.addEventListener('touchmove', onInitialPointerMove);\n document.addEventListener('touchstart', onInitialPointerMove);\n document.addEventListener('touchend', onInitialPointerMove);\n }\n\n function removeInitialPointerMoveListeners() {\n document.removeEventListener('mousemove', onInitialPointerMove);\n document.removeEventListener('mousedown', onInitialPointerMove);\n document.removeEventListener('mouseup', onInitialPointerMove);\n document.removeEventListener('pointermove', onInitialPointerMove);\n document.removeEventListener('pointerdown', onInitialPointerMove);\n document.removeEventListener('pointerup', onInitialPointerMove);\n document.removeEventListener('touchmove', onInitialPointerMove);\n document.removeEventListener('touchstart', onInitialPointerMove);\n document.removeEventListener('touchend', onInitialPointerMove);\n }\n\n /**\n * When the polfyill first loads, assume the user is in keyboard modality.\n * If any event is received from a pointing device (e.g. mouse, pointer,\n * touch), turn off keyboard modality.\n * This accounts for situations where focus enters the page from the URL bar.\n * @param {Event} e\n */\n function onInitialPointerMove(e) {\n // Work around a Safari quirk that fires a mousemove on whenever the\n // window blurs, even if you're tabbing out of the page. \u00AF\\_(\u30C4)_/\u00AF\n if (e.target.nodeName && e.target.nodeName.toLowerCase() === 'html') {\n return;\n }\n\n hadKeyboardEvent = false;\n removeInitialPointerMoveListeners();\n }\n\n // For some kinds of state, we are interested in changes at the global scope\n // only. For example, global pointer input, global key presses and global\n // visibility change should affect the state at every scope:\n document.addEventListener('keydown', onKeyDown, true);\n document.addEventListener('mousedown', onPointerDown, true);\n document.addEventListener('pointerdown', onPointerDown, true);\n document.addEventListener('touchstart', onPointerDown, true);\n document.addEventListener('visibilitychange', onVisibilityChange, true);\n\n addInitialPointerMoveListeners();\n\n // For focus and blur, we specifically care about state changes in the local\n // scope. This is because focus / blur events that originate from within a\n // shadow root are not re-dispatched from the host element if it was already\n // the active element in its own scope:\n scope.addEventListener('focus', onFocus, true);\n scope.addEventListener('blur', onBlur, true);\n\n // We detect that a node is a ShadowRoot by ensuring that it is a\n // DocumentFragment and also has a host property. This check covers native\n // implementation and polyfill implementation transparently. If we only cared\n // about the native implementation, we could just check if the scope was\n // an instance of a ShadowRoot.\n if (scope.nodeType === Node.DOCUMENT_FRAGMENT_NODE && scope.host) {\n // Since a ShadowRoot is a special kind of DocumentFragment, it does not\n // have a root element to add a class to. So, we add this attribute to the\n // host element instead:\n scope.host.setAttribute('data-js-focus-visible', '');\n } else if (scope.nodeType === Node.DOCUMENT_NODE) {\n document.documentElement.classList.add('js-focus-visible');\n document.documentElement.setAttribute('data-js-focus-visible', '');\n }\n }\n\n // It is important to wrap all references to global window and document in\n // these checks to support server-side rendering use cases\n // @see https://github.com/WICG/focus-visible/issues/199\n if (typeof window !== 'undefined' && typeof document !== 'undefined') {\n // Make the polyfill helper globally available. This can be used as a signal\n // to interested libraries that wish to coordinate with the polyfill for e.g.,\n // applying the polyfill to a shadow root:\n window.applyFocusVisiblePolyfill = applyFocusVisiblePolyfill;\n\n // Notify interested libraries of the polyfill's presence, in case the\n // polyfill was loaded lazily:\n var event;\n\n try {\n event = new CustomEvent('focus-visible-polyfill-ready');\n } catch (error) {\n // IE11 does not support using CustomEvent as a constructor directly:\n event = document.createEvent('CustomEvent');\n event.initCustomEvent('focus-visible-polyfill-ready', false, false, {});\n }\n\n window.dispatchEvent(event);\n }\n\n if (typeof document !== 'undefined') {\n // Apply the polyfill to the global document, so that no JavaScript\n // coordination is required to use the polyfill in the top-level document:\n applyFocusVisiblePolyfill(document);\n }\n\n})));\n", "/*!\n * escape-html\n * Copyright(c) 2012-2013 TJ Holowaychuk\n * Copyright(c) 2015 Andreas Lubbe\n * Copyright(c) 2015 Tiancheng \"Timothy\" Gu\n * MIT Licensed\n */\n\n'use strict';\n\n/**\n * Module variables.\n * @private\n */\n\nvar matchHtmlRegExp = /[\"'&<>]/;\n\n/**\n * Module exports.\n * @public\n */\n\nmodule.exports = escapeHtml;\n\n/**\n * Escape special characters in the given string of html.\n *\n * @param {string} string The string to escape for inserting into HTML\n * @return {string}\n * @public\n */\n\nfunction escapeHtml(string) {\n var str = '' + string;\n var match = matchHtmlRegExp.exec(str);\n\n if (!match) {\n return str;\n }\n\n var escape;\n var html = '';\n var index = 0;\n var lastIndex = 0;\n\n for (index = match.index; index < str.length; index++) {\n switch (str.charCodeAt(index)) {\n case 34: // \"\n escape = '"';\n break;\n case 38: // &\n escape = '&';\n break;\n case 39: // '\n escape = ''';\n break;\n case 60: // <\n escape = '<';\n break;\n case 62: // >\n escape = '>';\n break;\n default:\n continue;\n }\n\n if (lastIndex !== index) {\n html += str.substring(lastIndex, index);\n }\n\n lastIndex = index + 1;\n html += escape;\n }\n\n return lastIndex !== index\n ? html + str.substring(lastIndex, index)\n : html;\n}\n", "/*!\n * clipboard.js v2.0.11\n * https://clipboardjs.com/\n *\n * Licensed MIT \u00A9 Zeno Rocha\n */\n(function webpackUniversalModuleDefinition(root, factory) {\n\tif(typeof exports === 'object' && typeof module === 'object')\n\t\tmodule.exports = factory();\n\telse if(typeof define === 'function' && define.amd)\n\t\tdefine([], factory);\n\telse if(typeof exports === 'object')\n\t\texports[\"ClipboardJS\"] = factory();\n\telse\n\t\troot[\"ClipboardJS\"] = factory();\n})(this, function() {\nreturn /******/ (function() { // webpackBootstrap\n/******/ \tvar __webpack_modules__ = ({\n\n/***/ 686:\n/***/ (function(__unused_webpack_module, __webpack_exports__, __webpack_require__) {\n\n\"use strict\";\n\n// EXPORTS\n__webpack_require__.d(__webpack_exports__, {\n \"default\": function() { return /* binding */ clipboard; }\n});\n\n// EXTERNAL MODULE: ./node_modules/tiny-emitter/index.js\nvar tiny_emitter = __webpack_require__(279);\nvar tiny_emitter_default = /*#__PURE__*/__webpack_require__.n(tiny_emitter);\n// EXTERNAL MODULE: ./node_modules/good-listener/src/listen.js\nvar listen = __webpack_require__(370);\nvar listen_default = /*#__PURE__*/__webpack_require__.n(listen);\n// EXTERNAL MODULE: ./node_modules/select/src/select.js\nvar src_select = __webpack_require__(817);\nvar select_default = /*#__PURE__*/__webpack_require__.n(src_select);\n;// CONCATENATED MODULE: ./src/common/command.js\n/**\n * Executes a given operation type.\n * @param {String} type\n * @return {Boolean}\n */\nfunction command(type) {\n try {\n return document.execCommand(type);\n } catch (err) {\n return false;\n }\n}\n;// CONCATENATED MODULE: ./src/actions/cut.js\n\n\n/**\n * Cut action wrapper.\n * @param {String|HTMLElement} target\n * @return {String}\n */\n\nvar ClipboardActionCut = function ClipboardActionCut(target) {\n var selectedText = select_default()(target);\n command('cut');\n return selectedText;\n};\n\n/* harmony default export */ var actions_cut = (ClipboardActionCut);\n;// CONCATENATED MODULE: ./src/common/create-fake-element.js\n/**\n * Creates a fake textarea element with a value.\n * @param {String} value\n * @return {HTMLElement}\n */\nfunction createFakeElement(value) {\n var isRTL = document.documentElement.getAttribute('dir') === 'rtl';\n var fakeElement = document.createElement('textarea'); // Prevent zooming on iOS\n\n fakeElement.style.fontSize = '12pt'; // Reset box model\n\n fakeElement.style.border = '0';\n fakeElement.style.padding = '0';\n fakeElement.style.margin = '0'; // Move element out of screen horizontally\n\n fakeElement.style.position = 'absolute';\n fakeElement.style[isRTL ? 'right' : 'left'] = '-9999px'; // Move element to the same position vertically\n\n var yPosition = window.pageYOffset || document.documentElement.scrollTop;\n fakeElement.style.top = \"\".concat(yPosition, \"px\");\n fakeElement.setAttribute('readonly', '');\n fakeElement.value = value;\n return fakeElement;\n}\n;// CONCATENATED MODULE: ./src/actions/copy.js\n\n\n\n/**\n * Create fake copy action wrapper using a fake element.\n * @param {String} target\n * @param {Object} options\n * @return {String}\n */\n\nvar fakeCopyAction = function fakeCopyAction(value, options) {\n var fakeElement = createFakeElement(value);\n options.container.appendChild(fakeElement);\n var selectedText = select_default()(fakeElement);\n command('copy');\n fakeElement.remove();\n return selectedText;\n};\n/**\n * Copy action wrapper.\n * @param {String|HTMLElement} target\n * @param {Object} options\n * @return {String}\n */\n\n\nvar ClipboardActionCopy = function ClipboardActionCopy(target) {\n var options = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {\n container: document.body\n };\n var selectedText = '';\n\n if (typeof target === 'string') {\n selectedText = fakeCopyAction(target, options);\n } else if (target instanceof HTMLInputElement && !['text', 'search', 'url', 'tel', 'password'].includes(target === null || target === void 0 ? void 0 : target.type)) {\n // If input type doesn't support `setSelectionRange`. Simulate it. https://developer.mozilla.org/en-US/docs/Web/API/HTMLInputElement/setSelectionRange\n selectedText = fakeCopyAction(target.value, options);\n } else {\n selectedText = select_default()(target);\n command('copy');\n }\n\n return selectedText;\n};\n\n/* harmony default export */ var actions_copy = (ClipboardActionCopy);\n;// CONCATENATED MODULE: ./src/actions/default.js\nfunction _typeof(obj) { \"@babel/helpers - typeof\"; if (typeof Symbol === \"function\" && typeof Symbol.iterator === \"symbol\") { _typeof = function _typeof(obj) { return typeof obj; }; } else { _typeof = function _typeof(obj) { return obj && typeof Symbol === \"function\" && obj.constructor === Symbol && obj !== Symbol.prototype ? \"symbol\" : typeof obj; }; } return _typeof(obj); }\n\n\n\n/**\n * Inner function which performs selection from either `text` or `target`\n * properties and then executes copy or cut operations.\n * @param {Object} options\n */\n\nvar ClipboardActionDefault = function ClipboardActionDefault() {\n var options = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : {};\n // Defines base properties passed from constructor.\n var _options$action = options.action,\n action = _options$action === void 0 ? 'copy' : _options$action,\n container = options.container,\n target = options.target,\n text = options.text; // Sets the `action` to be performed which can be either 'copy' or 'cut'.\n\n if (action !== 'copy' && action !== 'cut') {\n throw new Error('Invalid \"action\" value, use either \"copy\" or \"cut\"');\n } // Sets the `target` property using an element that will be have its content copied.\n\n\n if (target !== undefined) {\n if (target && _typeof(target) === 'object' && target.nodeType === 1) {\n if (action === 'copy' && target.hasAttribute('disabled')) {\n throw new Error('Invalid \"target\" attribute. Please use \"readonly\" instead of \"disabled\" attribute');\n }\n\n if (action === 'cut' && (target.hasAttribute('readonly') || target.hasAttribute('disabled'))) {\n throw new Error('Invalid \"target\" attribute. You can\\'t cut text from elements with \"readonly\" or \"disabled\" attributes');\n }\n } else {\n throw new Error('Invalid \"target\" value, use a valid Element');\n }\n } // Define selection strategy based on `text` property.\n\n\n if (text) {\n return actions_copy(text, {\n container: container\n });\n } // Defines which selection strategy based on `target` property.\n\n\n if (target) {\n return action === 'cut' ? actions_cut(target) : actions_copy(target, {\n container: container\n });\n }\n};\n\n/* harmony default export */ var actions_default = (ClipboardActionDefault);\n;// CONCATENATED MODULE: ./src/clipboard.js\nfunction clipboard_typeof(obj) { \"@babel/helpers - typeof\"; if (typeof Symbol === \"function\" && typeof Symbol.iterator === \"symbol\") { clipboard_typeof = function _typeof(obj) { return typeof obj; }; } else { clipboard_typeof = function _typeof(obj) { return obj && typeof Symbol === \"function\" && obj.constructor === Symbol && obj !== Symbol.prototype ? \"symbol\" : typeof obj; }; } return clipboard_typeof(obj); }\n\nfunction _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError(\"Cannot call a class as a function\"); } }\n\nfunction _defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if (\"value\" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } }\n\nfunction _createClass(Constructor, protoProps, staticProps) { if (protoProps) _defineProperties(Constructor.prototype, protoProps); if (staticProps) _defineProperties(Constructor, staticProps); return Constructor; }\n\nfunction _inherits(subClass, superClass) { if (typeof superClass !== \"function\" && superClass !== null) { throw new TypeError(\"Super expression must either be null or a function\"); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, writable: true, configurable: true } }); if (superClass) _setPrototypeOf(subClass, superClass); }\n\nfunction _setPrototypeOf(o, p) { _setPrototypeOf = Object.setPrototypeOf || function _setPrototypeOf(o, p) { o.__proto__ = p; return o; }; return _setPrototypeOf(o, p); }\n\nfunction _createSuper(Derived) { var hasNativeReflectConstruct = _isNativeReflectConstruct(); return function _createSuperInternal() { var Super = _getPrototypeOf(Derived), result; if (hasNativeReflectConstruct) { var NewTarget = _getPrototypeOf(this).constructor; result = Reflect.construct(Super, arguments, NewTarget); } else { result = Super.apply(this, arguments); } return _possibleConstructorReturn(this, result); }; }\n\nfunction _possibleConstructorReturn(self, call) { if (call && (clipboard_typeof(call) === \"object\" || typeof call === \"function\")) { return call; } return _assertThisInitialized(self); }\n\nfunction _assertThisInitialized(self) { if (self === void 0) { throw new ReferenceError(\"this hasn't been initialised - super() hasn't been called\"); } return self; }\n\nfunction _isNativeReflectConstruct() { if (typeof Reflect === \"undefined\" || !Reflect.construct) return false; if (Reflect.construct.sham) return false; if (typeof Proxy === \"function\") return true; try { Date.prototype.toString.call(Reflect.construct(Date, [], function () {})); return true; } catch (e) { return false; } }\n\nfunction _getPrototypeOf(o) { _getPrototypeOf = Object.setPrototypeOf ? Object.getPrototypeOf : function _getPrototypeOf(o) { return o.__proto__ || Object.getPrototypeOf(o); }; return _getPrototypeOf(o); }\n\n\n\n\n\n\n/**\n * Helper function to retrieve attribute value.\n * @param {String} suffix\n * @param {Element} element\n */\n\nfunction getAttributeValue(suffix, element) {\n var attribute = \"data-clipboard-\".concat(suffix);\n\n if (!element.hasAttribute(attribute)) {\n return;\n }\n\n return element.getAttribute(attribute);\n}\n/**\n * Base class which takes one or more elements, adds event listeners to them,\n * and instantiates a new `ClipboardAction` on each click.\n */\n\n\nvar Clipboard = /*#__PURE__*/function (_Emitter) {\n _inherits(Clipboard, _Emitter);\n\n var _super = _createSuper(Clipboard);\n\n /**\n * @param {String|HTMLElement|HTMLCollection|NodeList} trigger\n * @param {Object} options\n */\n function Clipboard(trigger, options) {\n var _this;\n\n _classCallCheck(this, Clipboard);\n\n _this = _super.call(this);\n\n _this.resolveOptions(options);\n\n _this.listenClick(trigger);\n\n return _this;\n }\n /**\n * Defines if attributes would be resolved using internal setter functions\n * or custom functions that were passed in the constructor.\n * @param {Object} options\n */\n\n\n _createClass(Clipboard, [{\n key: \"resolveOptions\",\n value: function resolveOptions() {\n var options = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : {};\n this.action = typeof options.action === 'function' ? options.action : this.defaultAction;\n this.target = typeof options.target === 'function' ? options.target : this.defaultTarget;\n this.text = typeof options.text === 'function' ? options.text : this.defaultText;\n this.container = clipboard_typeof(options.container) === 'object' ? options.container : document.body;\n }\n /**\n * Adds a click event listener to the passed trigger.\n * @param {String|HTMLElement|HTMLCollection|NodeList} trigger\n */\n\n }, {\n key: \"listenClick\",\n value: function listenClick(trigger) {\n var _this2 = this;\n\n this.listener = listen_default()(trigger, 'click', function (e) {\n return _this2.onClick(e);\n });\n }\n /**\n * Defines a new `ClipboardAction` on each click event.\n * @param {Event} e\n */\n\n }, {\n key: \"onClick\",\n value: function onClick(e) {\n var trigger = e.delegateTarget || e.currentTarget;\n var action = this.action(trigger) || 'copy';\n var text = actions_default({\n action: action,\n container: this.container,\n target: this.target(trigger),\n text: this.text(trigger)\n }); // Fires an event based on the copy operation result.\n\n this.emit(text ? 'success' : 'error', {\n action: action,\n text: text,\n trigger: trigger,\n clearSelection: function clearSelection() {\n if (trigger) {\n trigger.focus();\n }\n\n window.getSelection().removeAllRanges();\n }\n });\n }\n /**\n * Default `action` lookup function.\n * @param {Element} trigger\n */\n\n }, {\n key: \"defaultAction\",\n value: function defaultAction(trigger) {\n return getAttributeValue('action', trigger);\n }\n /**\n * Default `target` lookup function.\n * @param {Element} trigger\n */\n\n }, {\n key: \"defaultTarget\",\n value: function defaultTarget(trigger) {\n var selector = getAttributeValue('target', trigger);\n\n if (selector) {\n return document.querySelector(selector);\n }\n }\n /**\n * Allow fire programmatically a copy action\n * @param {String|HTMLElement} target\n * @param {Object} options\n * @returns Text copied.\n */\n\n }, {\n key: \"defaultText\",\n\n /**\n * Default `text` lookup function.\n * @param {Element} trigger\n */\n value: function defaultText(trigger) {\n return getAttributeValue('text', trigger);\n }\n /**\n * Destroy lifecycle.\n */\n\n }, {\n key: \"destroy\",\n value: function destroy() {\n this.listener.destroy();\n }\n }], [{\n key: \"copy\",\n value: function copy(target) {\n var options = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {\n container: document.body\n };\n return actions_copy(target, options);\n }\n /**\n * Allow fire programmatically a cut action\n * @param {String|HTMLElement} target\n * @returns Text cutted.\n */\n\n }, {\n key: \"cut\",\n value: function cut(target) {\n return actions_cut(target);\n }\n /**\n * Returns the support of the given action, or all actions if no action is\n * given.\n * @param {String} [action]\n */\n\n }, {\n key: \"isSupported\",\n value: function isSupported() {\n var action = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : ['copy', 'cut'];\n var actions = typeof action === 'string' ? [action] : action;\n var support = !!document.queryCommandSupported;\n actions.forEach(function (action) {\n support = support && !!document.queryCommandSupported(action);\n });\n return support;\n }\n }]);\n\n return Clipboard;\n}((tiny_emitter_default()));\n\n/* harmony default export */ var clipboard = (Clipboard);\n\n/***/ }),\n\n/***/ 828:\n/***/ (function(module) {\n\nvar DOCUMENT_NODE_TYPE = 9;\n\n/**\n * A polyfill for Element.matches()\n */\nif (typeof Element !== 'undefined' && !Element.prototype.matches) {\n var proto = Element.prototype;\n\n proto.matches = proto.matchesSelector ||\n proto.mozMatchesSelector ||\n proto.msMatchesSelector ||\n proto.oMatchesSelector ||\n proto.webkitMatchesSelector;\n}\n\n/**\n * Finds the closest parent that matches a selector.\n *\n * @param {Element} element\n * @param {String} selector\n * @return {Function}\n */\nfunction closest (element, selector) {\n while (element && element.nodeType !== DOCUMENT_NODE_TYPE) {\n if (typeof element.matches === 'function' &&\n element.matches(selector)) {\n return element;\n }\n element = element.parentNode;\n }\n}\n\nmodule.exports = closest;\n\n\n/***/ }),\n\n/***/ 438:\n/***/ (function(module, __unused_webpack_exports, __webpack_require__) {\n\nvar closest = __webpack_require__(828);\n\n/**\n * Delegates event to a selector.\n *\n * @param {Element} element\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @param {Boolean} useCapture\n * @return {Object}\n */\nfunction _delegate(element, selector, type, callback, useCapture) {\n var listenerFn = listener.apply(this, arguments);\n\n element.addEventListener(type, listenerFn, useCapture);\n\n return {\n destroy: function() {\n element.removeEventListener(type, listenerFn, useCapture);\n }\n }\n}\n\n/**\n * Delegates event to a selector.\n *\n * @param {Element|String|Array} [elements]\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @param {Boolean} useCapture\n * @return {Object}\n */\nfunction delegate(elements, selector, type, callback, useCapture) {\n // Handle the regular Element usage\n if (typeof elements.addEventListener === 'function') {\n return _delegate.apply(null, arguments);\n }\n\n // Handle Element-less usage, it defaults to global delegation\n if (typeof type === 'function') {\n // Use `document` as the first parameter, then apply arguments\n // This is a short way to .unshift `arguments` without running into deoptimizations\n return _delegate.bind(null, document).apply(null, arguments);\n }\n\n // Handle Selector-based usage\n if (typeof elements === 'string') {\n elements = document.querySelectorAll(elements);\n }\n\n // Handle Array-like based usage\n return Array.prototype.map.call(elements, function (element) {\n return _delegate(element, selector, type, callback, useCapture);\n });\n}\n\n/**\n * Finds closest match and invokes callback.\n *\n * @param {Element} element\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @return {Function}\n */\nfunction listener(element, selector, type, callback) {\n return function(e) {\n e.delegateTarget = closest(e.target, selector);\n\n if (e.delegateTarget) {\n callback.call(element, e);\n }\n }\n}\n\nmodule.exports = delegate;\n\n\n/***/ }),\n\n/***/ 879:\n/***/ (function(__unused_webpack_module, exports) {\n\n/**\n * Check if argument is a HTML element.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.node = function(value) {\n return value !== undefined\n && value instanceof HTMLElement\n && value.nodeType === 1;\n};\n\n/**\n * Check if argument is a list of HTML elements.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.nodeList = function(value) {\n var type = Object.prototype.toString.call(value);\n\n return value !== undefined\n && (type === '[object NodeList]' || type === '[object HTMLCollection]')\n && ('length' in value)\n && (value.length === 0 || exports.node(value[0]));\n};\n\n/**\n * Check if argument is a string.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.string = function(value) {\n return typeof value === 'string'\n || value instanceof String;\n};\n\n/**\n * Check if argument is a function.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.fn = function(value) {\n var type = Object.prototype.toString.call(value);\n\n return type === '[object Function]';\n};\n\n\n/***/ }),\n\n/***/ 370:\n/***/ (function(module, __unused_webpack_exports, __webpack_require__) {\n\nvar is = __webpack_require__(879);\nvar delegate = __webpack_require__(438);\n\n/**\n * Validates all params and calls the right\n * listener function based on its target type.\n *\n * @param {String|HTMLElement|HTMLCollection|NodeList} target\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listen(target, type, callback) {\n if (!target && !type && !callback) {\n throw new Error('Missing required arguments');\n }\n\n if (!is.string(type)) {\n throw new TypeError('Second argument must be a String');\n }\n\n if (!is.fn(callback)) {\n throw new TypeError('Third argument must be a Function');\n }\n\n if (is.node(target)) {\n return listenNode(target, type, callback);\n }\n else if (is.nodeList(target)) {\n return listenNodeList(target, type, callback);\n }\n else if (is.string(target)) {\n return listenSelector(target, type, callback);\n }\n else {\n throw new TypeError('First argument must be a String, HTMLElement, HTMLCollection, or NodeList');\n }\n}\n\n/**\n * Adds an event listener to a HTML element\n * and returns a remove listener function.\n *\n * @param {HTMLElement} node\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenNode(node, type, callback) {\n node.addEventListener(type, callback);\n\n return {\n destroy: function() {\n node.removeEventListener(type, callback);\n }\n }\n}\n\n/**\n * Add an event listener to a list of HTML elements\n * and returns a remove listener function.\n *\n * @param {NodeList|HTMLCollection} nodeList\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenNodeList(nodeList, type, callback) {\n Array.prototype.forEach.call(nodeList, function(node) {\n node.addEventListener(type, callback);\n });\n\n return {\n destroy: function() {\n Array.prototype.forEach.call(nodeList, function(node) {\n node.removeEventListener(type, callback);\n });\n }\n }\n}\n\n/**\n * Add an event listener to a selector\n * and returns a remove listener function.\n *\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenSelector(selector, type, callback) {\n return delegate(document.body, selector, type, callback);\n}\n\nmodule.exports = listen;\n\n\n/***/ }),\n\n/***/ 817:\n/***/ (function(module) {\n\nfunction select(element) {\n var selectedText;\n\n if (element.nodeName === 'SELECT') {\n element.focus();\n\n selectedText = element.value;\n }\n else if (element.nodeName === 'INPUT' || element.nodeName === 'TEXTAREA') {\n var isReadOnly = element.hasAttribute('readonly');\n\n if (!isReadOnly) {\n element.setAttribute('readonly', '');\n }\n\n element.select();\n element.setSelectionRange(0, element.value.length);\n\n if (!isReadOnly) {\n element.removeAttribute('readonly');\n }\n\n selectedText = element.value;\n }\n else {\n if (element.hasAttribute('contenteditable')) {\n element.focus();\n }\n\n var selection = window.getSelection();\n var range = document.createRange();\n\n range.selectNodeContents(element);\n selection.removeAllRanges();\n selection.addRange(range);\n\n selectedText = selection.toString();\n }\n\n return selectedText;\n}\n\nmodule.exports = select;\n\n\n/***/ }),\n\n/***/ 279:\n/***/ (function(module) {\n\nfunction E () {\n // Keep this empty so it's easier to inherit from\n // (via https://github.com/lipsmack from https://github.com/scottcorgan/tiny-emitter/issues/3)\n}\n\nE.prototype = {\n on: function (name, callback, ctx) {\n var e = this.e || (this.e = {});\n\n (e[name] || (e[name] = [])).push({\n fn: callback,\n ctx: ctx\n });\n\n return this;\n },\n\n once: function (name, callback, ctx) {\n var self = this;\n function listener () {\n self.off(name, listener);\n callback.apply(ctx, arguments);\n };\n\n listener._ = callback\n return this.on(name, listener, ctx);\n },\n\n emit: function (name) {\n var data = [].slice.call(arguments, 1);\n var evtArr = ((this.e || (this.e = {}))[name] || []).slice();\n var i = 0;\n var len = evtArr.length;\n\n for (i; i < len; i++) {\n evtArr[i].fn.apply(evtArr[i].ctx, data);\n }\n\n return this;\n },\n\n off: function (name, callback) {\n var e = this.e || (this.e = {});\n var evts = e[name];\n var liveEvents = [];\n\n if (evts && callback) {\n for (var i = 0, len = evts.length; i < len; i++) {\n if (evts[i].fn !== callback && evts[i].fn._ !== callback)\n liveEvents.push(evts[i]);\n }\n }\n\n // Remove event from queue to prevent memory leak\n // Suggested by https://github.com/lazd\n // Ref: https://github.com/scottcorgan/tiny-emitter/commit/c6ebfaa9bc973b33d110a84a307742b7cf94c953#commitcomment-5024910\n\n (liveEvents.length)\n ? e[name] = liveEvents\n : delete e[name];\n\n return this;\n }\n};\n\nmodule.exports = E;\nmodule.exports.TinyEmitter = E;\n\n\n/***/ })\n\n/******/ \t});\n/************************************************************************/\n/******/ \t// The module cache\n/******/ \tvar __webpack_module_cache__ = {};\n/******/ \t\n/******/ \t// The require function\n/******/ \tfunction __webpack_require__(moduleId) {\n/******/ \t\t// Check if module is in cache\n/******/ \t\tif(__webpack_module_cache__[moduleId]) {\n/******/ \t\t\treturn __webpack_module_cache__[moduleId].exports;\n/******/ \t\t}\n/******/ \t\t// Create a new module (and put it into the cache)\n/******/ \t\tvar module = __webpack_module_cache__[moduleId] = {\n/******/ \t\t\t// no module.id needed\n/******/ \t\t\t// no module.loaded needed\n/******/ \t\t\texports: {}\n/******/ \t\t};\n/******/ \t\n/******/ \t\t// Execute the module function\n/******/ \t\t__webpack_modules__[moduleId](module, module.exports, __webpack_require__);\n/******/ \t\n/******/ \t\t// Return the exports of the module\n/******/ \t\treturn module.exports;\n/******/ \t}\n/******/ \t\n/************************************************************************/\n/******/ \t/* webpack/runtime/compat get default export */\n/******/ \t!function() {\n/******/ \t\t// getDefaultExport function for compatibility with non-harmony modules\n/******/ \t\t__webpack_require__.n = function(module) {\n/******/ \t\t\tvar getter = module && module.__esModule ?\n/******/ \t\t\t\tfunction() { return module['default']; } :\n/******/ \t\t\t\tfunction() { return module; };\n/******/ \t\t\t__webpack_require__.d(getter, { a: getter });\n/******/ \t\t\treturn getter;\n/******/ \t\t};\n/******/ \t}();\n/******/ \t\n/******/ \t/* webpack/runtime/define property getters */\n/******/ \t!function() {\n/******/ \t\t// define getter functions for harmony exports\n/******/ \t\t__webpack_require__.d = function(exports, definition) {\n/******/ \t\t\tfor(var key in definition) {\n/******/ \t\t\t\tif(__webpack_require__.o(definition, key) && !__webpack_require__.o(exports, key)) {\n/******/ \t\t\t\t\tObject.defineProperty(exports, key, { enumerable: true, get: definition[key] });\n/******/ \t\t\t\t}\n/******/ \t\t\t}\n/******/ \t\t};\n/******/ \t}();\n/******/ \t\n/******/ \t/* webpack/runtime/hasOwnProperty shorthand */\n/******/ \t!function() {\n/******/ \t\t__webpack_require__.o = function(obj, prop) { return Object.prototype.hasOwnProperty.call(obj, prop); }\n/******/ \t}();\n/******/ \t\n/************************************************************************/\n/******/ \t// module exports must be returned from runtime so entry inlining is disabled\n/******/ \t// startup\n/******/ \t// Load entry module and return exports\n/******/ \treturn __webpack_require__(686);\n/******/ })()\n.default;\n});", "/*\n * Copyright (c) 2016-2024 Martin Donath \n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport \"focus-visible\"\n\nimport {\n EMPTY,\n NEVER,\n Observable,\n Subject,\n defer,\n delay,\n filter,\n map,\n merge,\n mergeWith,\n shareReplay,\n switchMap\n} from \"rxjs\"\n\nimport { configuration, feature } from \"./_\"\nimport {\n at,\n getActiveElement,\n getOptionalElement,\n requestJSON,\n setLocation,\n setToggle,\n watchDocument,\n watchKeyboard,\n watchLocation,\n watchLocationTarget,\n watchMedia,\n watchPrint,\n watchScript,\n watchViewport\n} from \"./browser\"\nimport {\n getComponentElement,\n getComponentElements,\n mountAnnounce,\n mountBackToTop,\n mountConsent,\n mountContent,\n mountDialog,\n mountHeader,\n mountHeaderTitle,\n mountPalette,\n mountProgress,\n mountSearch,\n mountSearchHiglight,\n mountSidebar,\n mountSource,\n mountTableOfContents,\n mountTabs,\n watchHeader,\n watchMain\n} from \"./components\"\nimport {\n SearchIndex,\n setupClipboardJS,\n setupInstantNavigation,\n setupVersionSelector\n} from \"./integrations\"\nimport {\n patchEllipsis,\n patchIndeterminate,\n patchScrollfix,\n patchScrolllock\n} from \"./patches\"\nimport \"./polyfills\"\n\n/* ----------------------------------------------------------------------------\n * Functions - @todo refactor\n * ------------------------------------------------------------------------- */\n\n/**\n * Fetch search index\n *\n * @returns Search index observable\n */\nfunction fetchSearchIndex(): Observable {\n if (location.protocol === \"file:\") {\n return watchScript(\n `${new URL(\"search/search_index.js\", config.base)}`\n )\n .pipe(\n // @ts-ignore - @todo fix typings\n map(() => __index),\n shareReplay(1)\n )\n } else {\n return requestJSON(\n new URL(\"search/search_index.json\", config.base)\n )\n }\n}\n\n/* ----------------------------------------------------------------------------\n * Application\n * ------------------------------------------------------------------------- */\n\n/* Yay, JavaScript is available */\ndocument.documentElement.classList.remove(\"no-js\")\ndocument.documentElement.classList.add(\"js\")\n\n/* Set up navigation observables and subjects */\nconst document$ = watchDocument()\nconst location$ = watchLocation()\nconst target$ = watchLocationTarget(location$)\nconst keyboard$ = watchKeyboard()\n\n/* Set up media observables */\nconst viewport$ = watchViewport()\nconst tablet$ = watchMedia(\"(min-width: 960px)\")\nconst screen$ = watchMedia(\"(min-width: 1220px)\")\nconst print$ = watchPrint()\n\n/* Retrieve search index, if search is enabled */\nconst config = configuration()\nconst index$ = document.forms.namedItem(\"search\")\n ? fetchSearchIndex()\n : NEVER\n\n/* Set up Clipboard.js integration */\nconst alert$ = new Subject()\nsetupClipboardJS({ alert$ })\n\n/* Set up progress indicator */\nconst progress$ = new Subject()\n\n/* Set up instant navigation, if enabled */\nif (feature(\"navigation.instant\"))\n setupInstantNavigation({ location$, viewport$, progress$ })\n .subscribe(document$)\n\n/* Set up version selector */\nif (config.version?.provider === \"mike\")\n setupVersionSelector({ document$ })\n\n/* Always close drawer and search on navigation */\nmerge(location$, target$)\n .pipe(\n delay(125)\n )\n .subscribe(() => {\n setToggle(\"drawer\", false)\n setToggle(\"search\", false)\n })\n\n/* Set up global keyboard handlers */\nkeyboard$\n .pipe(\n filter(({ mode }) => mode === \"global\")\n )\n .subscribe(key => {\n switch (key.type) {\n\n /* Go to previous page */\n case \"p\":\n case \",\":\n const prev = getOptionalElement(\"link[rel=prev]\")\n if (typeof prev !== \"undefined\")\n setLocation(prev)\n break\n\n /* Go to next page */\n case \"n\":\n case \".\":\n const next = getOptionalElement(\"link[rel=next]\")\n if (typeof next !== \"undefined\")\n setLocation(next)\n break\n\n /* Expand navigation, see https://bit.ly/3ZjG5io */\n case \"Enter\":\n const active = getActiveElement()\n if (active instanceof HTMLLabelElement)\n active.click()\n }\n })\n\n/* Set up patches */\npatchEllipsis({ viewport$, document$ })\npatchIndeterminate({ document$, tablet$ })\npatchScrollfix({ document$ })\npatchScrolllock({ viewport$, tablet$ })\n\n/* Set up header and main area observable */\nconst header$ = watchHeader(getComponentElement(\"header\"), { viewport$ })\nconst main$ = document$\n .pipe(\n map(() => getComponentElement(\"main\")),\n switchMap(el => watchMain(el, { viewport$, header$ })),\n shareReplay(1)\n )\n\n/* Set up control component observables */\nconst control$ = merge(\n\n /* Consent */\n ...getComponentElements(\"consent\")\n .map(el => mountConsent(el, { target$ })),\n\n /* Dialog */\n ...getComponentElements(\"dialog\")\n .map(el => mountDialog(el, { alert$ })),\n\n /* Header */\n ...getComponentElements(\"header\")\n .map(el => mountHeader(el, { viewport$, header$, main$ })),\n\n /* Color palette */\n ...getComponentElements(\"palette\")\n .map(el => mountPalette(el)),\n\n /* Progress bar */\n ...getComponentElements(\"progress\")\n .map(el => mountProgress(el, { progress$ })),\n\n /* Search */\n ...getComponentElements(\"search\")\n .map(el => mountSearch(el, { index$, keyboard$ })),\n\n /* Repository information */\n ...getComponentElements(\"source\")\n .map(el => mountSource(el))\n)\n\n/* Set up content component observables */\nconst content$ = defer(() => merge(\n\n /* Announcement bar */\n ...getComponentElements(\"announce\")\n .map(el => mountAnnounce(el)),\n\n /* Content */\n ...getComponentElements(\"content\")\n .map(el => mountContent(el, { viewport$, target$, print$ })),\n\n /* Search highlighting */\n ...getComponentElements(\"content\")\n .map(el => feature(\"search.highlight\")\n ? mountSearchHiglight(el, { index$, location$ })\n : EMPTY\n ),\n\n /* Header title */\n ...getComponentElements(\"header-title\")\n .map(el => mountHeaderTitle(el, { viewport$, header$ })),\n\n /* Sidebar */\n ...getComponentElements(\"sidebar\")\n .map(el => el.getAttribute(\"data-md-type\") === \"navigation\"\n ? at(screen$, () => mountSidebar(el, { viewport$, header$, main$ }))\n : at(tablet$, () => mountSidebar(el, { viewport$, header$, main$ }))\n ),\n\n /* Navigation tabs */\n ...getComponentElements(\"tabs\")\n .map(el => mountTabs(el, { viewport$, header$ })),\n\n /* Table of contents */\n ...getComponentElements(\"toc\")\n .map(el => mountTableOfContents(el, {\n viewport$, header$, main$, target$\n })),\n\n /* Back-to-top button */\n ...getComponentElements(\"top\")\n .map(el => mountBackToTop(el, { viewport$, header$, main$, target$ }))\n))\n\n/* Set up component observables */\nconst component$ = document$\n .pipe(\n switchMap(() => content$),\n mergeWith(control$),\n shareReplay(1)\n )\n\n/* Subscribe to all components */\ncomponent$.subscribe()\n\n/* ----------------------------------------------------------------------------\n * Exports\n * ------------------------------------------------------------------------- */\n\nwindow.document$ = document$ /* Document observable */\nwindow.location$ = location$ /* Location subject */\nwindow.target$ = target$ /* Location target observable */\nwindow.keyboard$ = keyboard$ /* Keyboard observable */\nwindow.viewport$ = viewport$ /* Viewport observable */\nwindow.tablet$ = tablet$ /* Media tablet observable */\nwindow.screen$ = screen$ /* Media screen observable */\nwindow.print$ = print$ /* Media print observable */\nwindow.alert$ = alert$ /* Alert subject */\nwindow.progress$ = progress$ /* Progress indicator subject */\nwindow.component$ = component$ /* Component observable */\n", "/******************************************************************************\nCopyright (c) Microsoft Corporation.\n\nPermission to use, copy, modify, and/or distribute this software for any\npurpose with or without fee is hereby granted.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH\nREGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY\nAND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,\nINDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM\nLOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR\nOTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR\nPERFORMANCE OF THIS SOFTWARE.\n***************************************************************************** */\n/* global Reflect, Promise, SuppressedError, Symbol, Iterator */\n\nvar extendStatics = function(d, b) {\n extendStatics = Object.setPrototypeOf ||\n ({ __proto__: [] } instanceof Array && function (d, b) { d.__proto__ = b; }) ||\n function (d, b) { for (var p in b) if (Object.prototype.hasOwnProperty.call(b, p)) d[p] = b[p]; };\n return extendStatics(d, b);\n};\n\nexport function __extends(d, b) {\n if (typeof b !== \"function\" && b !== null)\n throw new TypeError(\"Class extends value \" + String(b) + \" is not a constructor or null\");\n extendStatics(d, b);\n function __() { this.constructor = d; }\n d.prototype = b === null ? Object.create(b) : (__.prototype = b.prototype, new __());\n}\n\nexport var __assign = function() {\n __assign = Object.assign || function __assign(t) {\n for (var s, i = 1, n = arguments.length; i < n; i++) {\n s = arguments[i];\n for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p)) t[p] = s[p];\n }\n return t;\n }\n return __assign.apply(this, arguments);\n}\n\nexport function __rest(s, e) {\n var t = {};\n for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p) && e.indexOf(p) < 0)\n t[p] = s[p];\n if (s != null && typeof Object.getOwnPropertySymbols === \"function\")\n for (var i = 0, p = Object.getOwnPropertySymbols(s); i < p.length; i++) {\n if (e.indexOf(p[i]) < 0 && Object.prototype.propertyIsEnumerable.call(s, p[i]))\n t[p[i]] = s[p[i]];\n }\n return t;\n}\n\nexport function __decorate(decorators, target, key, desc) {\n var c = arguments.length, r = c < 3 ? target : desc === null ? desc = Object.getOwnPropertyDescriptor(target, key) : desc, d;\n if (typeof Reflect === \"object\" && typeof Reflect.decorate === \"function\") r = Reflect.decorate(decorators, target, key, desc);\n else for (var i = decorators.length - 1; i >= 0; i--) if (d = decorators[i]) r = (c < 3 ? d(r) : c > 3 ? d(target, key, r) : d(target, key)) || r;\n return c > 3 && r && Object.defineProperty(target, key, r), r;\n}\n\nexport function __param(paramIndex, decorator) {\n return function (target, key) { decorator(target, key, paramIndex); }\n}\n\nexport function __esDecorate(ctor, descriptorIn, decorators, contextIn, initializers, extraInitializers) {\n function accept(f) { if (f !== void 0 && typeof f !== \"function\") throw new TypeError(\"Function expected\"); return f; }\n var kind = contextIn.kind, key = kind === \"getter\" ? \"get\" : kind === \"setter\" ? \"set\" : \"value\";\n var target = !descriptorIn && ctor ? contextIn[\"static\"] ? ctor : ctor.prototype : null;\n var descriptor = descriptorIn || (target ? Object.getOwnPropertyDescriptor(target, contextIn.name) : {});\n var _, done = false;\n for (var i = decorators.length - 1; i >= 0; i--) {\n var context = {};\n for (var p in contextIn) context[p] = p === \"access\" ? {} : contextIn[p];\n for (var p in contextIn.access) context.access[p] = contextIn.access[p];\n context.addInitializer = function (f) { if (done) throw new TypeError(\"Cannot add initializers after decoration has completed\"); extraInitializers.push(accept(f || null)); };\n var result = (0, decorators[i])(kind === \"accessor\" ? { get: descriptor.get, set: descriptor.set } : descriptor[key], context);\n if (kind === \"accessor\") {\n if (result === void 0) continue;\n if (result === null || typeof result !== \"object\") throw new TypeError(\"Object expected\");\n if (_ = accept(result.get)) descriptor.get = _;\n if (_ = accept(result.set)) descriptor.set = _;\n if (_ = accept(result.init)) initializers.unshift(_);\n }\n else if (_ = accept(result)) {\n if (kind === \"field\") initializers.unshift(_);\n else descriptor[key] = _;\n }\n }\n if (target) Object.defineProperty(target, contextIn.name, descriptor);\n done = true;\n};\n\nexport function __runInitializers(thisArg, initializers, value) {\n var useValue = arguments.length > 2;\n for (var i = 0; i < initializers.length; i++) {\n value = useValue ? initializers[i].call(thisArg, value) : initializers[i].call(thisArg);\n }\n return useValue ? value : void 0;\n};\n\nexport function __propKey(x) {\n return typeof x === \"symbol\" ? x : \"\".concat(x);\n};\n\nexport function __setFunctionName(f, name, prefix) {\n if (typeof name === \"symbol\") name = name.description ? \"[\".concat(name.description, \"]\") : \"\";\n return Object.defineProperty(f, \"name\", { configurable: true, value: prefix ? \"\".concat(prefix, \" \", name) : name });\n};\n\nexport function __metadata(metadataKey, metadataValue) {\n if (typeof Reflect === \"object\" && typeof Reflect.metadata === \"function\") return Reflect.metadata(metadataKey, metadataValue);\n}\n\nexport function __awaiter(thisArg, _arguments, P, generator) {\n function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }\n return new (P || (P = Promise))(function (resolve, reject) {\n function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }\n function rejected(value) { try { step(generator[\"throw\"](value)); } catch (e) { reject(e); } }\n function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }\n step((generator = generator.apply(thisArg, _arguments || [])).next());\n });\n}\n\nexport function __generator(thisArg, body) {\n var _ = { label: 0, sent: function() { if (t[0] & 1) throw t[1]; return t[1]; }, trys: [], ops: [] }, f, y, t, g = Object.create((typeof Iterator === \"function\" ? Iterator : Object).prototype);\n return g.next = verb(0), g[\"throw\"] = verb(1), g[\"return\"] = verb(2), typeof Symbol === \"function\" && (g[Symbol.iterator] = function() { return this; }), g;\n function verb(n) { return function (v) { return step([n, v]); }; }\n function step(op) {\n if (f) throw new TypeError(\"Generator is already executing.\");\n while (g && (g = 0, op[0] && (_ = 0)), _) try {\n if (f = 1, y && (t = op[0] & 2 ? y[\"return\"] : op[0] ? y[\"throw\"] || ((t = y[\"return\"]) && t.call(y), 0) : y.next) && !(t = t.call(y, op[1])).done) return t;\n if (y = 0, t) op = [op[0] & 2, t.value];\n switch (op[0]) {\n case 0: case 1: t = op; break;\n case 4: _.label++; return { value: op[1], done: false };\n case 5: _.label++; y = op[1]; op = [0]; continue;\n case 7: op = _.ops.pop(); _.trys.pop(); continue;\n default:\n if (!(t = _.trys, t = t.length > 0 && t[t.length - 1]) && (op[0] === 6 || op[0] === 2)) { _ = 0; continue; }\n if (op[0] === 3 && (!t || (op[1] > t[0] && op[1] < t[3]))) { _.label = op[1]; break; }\n if (op[0] === 6 && _.label < t[1]) { _.label = t[1]; t = op; break; }\n if (t && _.label < t[2]) { _.label = t[2]; _.ops.push(op); break; }\n if (t[2]) _.ops.pop();\n _.trys.pop(); continue;\n }\n op = body.call(thisArg, _);\n } catch (e) { op = [6, e]; y = 0; } finally { f = t = 0; }\n if (op[0] & 5) throw op[1]; return { value: op[0] ? op[1] : void 0, done: true };\n }\n}\n\nexport var __createBinding = Object.create ? (function(o, m, k, k2) {\n if (k2 === undefined) k2 = k;\n var desc = Object.getOwnPropertyDescriptor(m, k);\n if (!desc || (\"get\" in desc ? !m.__esModule : desc.writable || desc.configurable)) {\n desc = { enumerable: true, get: function() { return m[k]; } };\n }\n Object.defineProperty(o, k2, desc);\n}) : (function(o, m, k, k2) {\n if (k2 === undefined) k2 = k;\n o[k2] = m[k];\n});\n\nexport function __exportStar(m, o) {\n for (var p in m) if (p !== \"default\" && !Object.prototype.hasOwnProperty.call(o, p)) __createBinding(o, m, p);\n}\n\nexport function __values(o) {\n var s = typeof Symbol === \"function\" && Symbol.iterator, m = s && o[s], i = 0;\n if (m) return m.call(o);\n if (o && typeof o.length === \"number\") return {\n next: function () {\n if (o && i >= o.length) o = void 0;\n return { value: o && o[i++], done: !o };\n }\n };\n throw new TypeError(s ? \"Object is not iterable.\" : \"Symbol.iterator is not defined.\");\n}\n\nexport function __read(o, n) {\n var m = typeof Symbol === \"function\" && o[Symbol.iterator];\n if (!m) return o;\n var i = m.call(o), r, ar = [], e;\n try {\n while ((n === void 0 || n-- > 0) && !(r = i.next()).done) ar.push(r.value);\n }\n catch (error) { e = { error: error }; }\n finally {\n try {\n if (r && !r.done && (m = i[\"return\"])) m.call(i);\n }\n finally { if (e) throw e.error; }\n }\n return ar;\n}\n\n/** @deprecated */\nexport function __spread() {\n for (var ar = [], i = 0; i < arguments.length; i++)\n ar = ar.concat(__read(arguments[i]));\n return ar;\n}\n\n/** @deprecated */\nexport function __spreadArrays() {\n for (var s = 0, i = 0, il = arguments.length; i < il; i++) s += arguments[i].length;\n for (var r = Array(s), k = 0, i = 0; i < il; i++)\n for (var a = arguments[i], j = 0, jl = a.length; j < jl; j++, k++)\n r[k] = a[j];\n return r;\n}\n\nexport function __spreadArray(to, from, pack) {\n if (pack || arguments.length === 2) for (var i = 0, l = from.length, ar; i < l; i++) {\n if (ar || !(i in from)) {\n if (!ar) ar = Array.prototype.slice.call(from, 0, i);\n ar[i] = from[i];\n }\n }\n return to.concat(ar || Array.prototype.slice.call(from));\n}\n\nexport function __await(v) {\n return this instanceof __await ? (this.v = v, this) : new __await(v);\n}\n\nexport function __asyncGenerator(thisArg, _arguments, generator) {\n if (!Symbol.asyncIterator) throw new TypeError(\"Symbol.asyncIterator is not defined.\");\n var g = generator.apply(thisArg, _arguments || []), i, q = [];\n return i = Object.create((typeof AsyncIterator === \"function\" ? AsyncIterator : Object).prototype), verb(\"next\"), verb(\"throw\"), verb(\"return\", awaitReturn), i[Symbol.asyncIterator] = function () { return this; }, i;\n function awaitReturn(f) { return function (v) { return Promise.resolve(v).then(f, reject); }; }\n function verb(n, f) { if (g[n]) { i[n] = function (v) { return new Promise(function (a, b) { q.push([n, v, a, b]) > 1 || resume(n, v); }); }; if (f) i[n] = f(i[n]); } }\n function resume(n, v) { try { step(g[n](v)); } catch (e) { settle(q[0][3], e); } }\n function step(r) { r.value instanceof __await ? Promise.resolve(r.value.v).then(fulfill, reject) : settle(q[0][2], r); }\n function fulfill(value) { resume(\"next\", value); }\n function reject(value) { resume(\"throw\", value); }\n function settle(f, v) { if (f(v), q.shift(), q.length) resume(q[0][0], q[0][1]); }\n}\n\nexport function __asyncDelegator(o) {\n var i, p;\n return i = {}, verb(\"next\"), verb(\"throw\", function (e) { throw e; }), verb(\"return\"), i[Symbol.iterator] = function () { return this; }, i;\n function verb(n, f) { i[n] = o[n] ? function (v) { return (p = !p) ? { value: __await(o[n](v)), done: false } : f ? f(v) : v; } : f; }\n}\n\nexport function __asyncValues(o) {\n if (!Symbol.asyncIterator) throw new TypeError(\"Symbol.asyncIterator is not defined.\");\n var m = o[Symbol.asyncIterator], i;\n return m ? m.call(o) : (o = typeof __values === \"function\" ? __values(o) : o[Symbol.iterator](), i = {}, verb(\"next\"), verb(\"throw\"), verb(\"return\"), i[Symbol.asyncIterator] = function () { return this; }, i);\n function verb(n) { i[n] = o[n] && function (v) { return new Promise(function (resolve, reject) { v = o[n](v), settle(resolve, reject, v.done, v.value); }); }; }\n function settle(resolve, reject, d, v) { Promise.resolve(v).then(function(v) { resolve({ value: v, done: d }); }, reject); }\n}\n\nexport function __makeTemplateObject(cooked, raw) {\n if (Object.defineProperty) { Object.defineProperty(cooked, \"raw\", { value: raw }); } else { cooked.raw = raw; }\n return cooked;\n};\n\nvar __setModuleDefault = Object.create ? (function(o, v) {\n Object.defineProperty(o, \"default\", { enumerable: true, value: v });\n}) : function(o, v) {\n o[\"default\"] = v;\n};\n\nexport function __importStar(mod) {\n if (mod && mod.__esModule) return mod;\n var result = {};\n if (mod != null) for (var k in mod) if (k !== \"default\" && Object.prototype.hasOwnProperty.call(mod, k)) __createBinding(result, mod, k);\n __setModuleDefault(result, mod);\n return result;\n}\n\nexport function __importDefault(mod) {\n return (mod && mod.__esModule) ? mod : { default: mod };\n}\n\nexport function __classPrivateFieldGet(receiver, state, kind, f) {\n if (kind === \"a\" && !f) throw new TypeError(\"Private accessor was defined without a getter\");\n if (typeof state === \"function\" ? receiver !== state || !f : !state.has(receiver)) throw new TypeError(\"Cannot read private member from an object whose class did not declare it\");\n return kind === \"m\" ? f : kind === \"a\" ? f.call(receiver) : f ? f.value : state.get(receiver);\n}\n\nexport function __classPrivateFieldSet(receiver, state, value, kind, f) {\n if (kind === \"m\") throw new TypeError(\"Private method is not writable\");\n if (kind === \"a\" && !f) throw new TypeError(\"Private accessor was defined without a setter\");\n if (typeof state === \"function\" ? receiver !== state || !f : !state.has(receiver)) throw new TypeError(\"Cannot write private member to an object whose class did not declare it\");\n return (kind === \"a\" ? f.call(receiver, value) : f ? f.value = value : state.set(receiver, value)), value;\n}\n\nexport function __classPrivateFieldIn(state, receiver) {\n if (receiver === null || (typeof receiver !== \"object\" && typeof receiver !== \"function\")) throw new TypeError(\"Cannot use 'in' operator on non-object\");\n return typeof state === \"function\" ? receiver === state : state.has(receiver);\n}\n\nexport function __addDisposableResource(env, value, async) {\n if (value !== null && value !== void 0) {\n if (typeof value !== \"object\" && typeof value !== \"function\") throw new TypeError(\"Object expected.\");\n var dispose, inner;\n if (async) {\n if (!Symbol.asyncDispose) throw new TypeError(\"Symbol.asyncDispose is not defined.\");\n dispose = value[Symbol.asyncDispose];\n }\n if (dispose === void 0) {\n if (!Symbol.dispose) throw new TypeError(\"Symbol.dispose is not defined.\");\n dispose = value[Symbol.dispose];\n if (async) inner = dispose;\n }\n if (typeof dispose !== \"function\") throw new TypeError(\"Object not disposable.\");\n if (inner) dispose = function() { try { inner.call(this); } catch (e) { return Promise.reject(e); } };\n env.stack.push({ value: value, dispose: dispose, async: async });\n }\n else if (async) {\n env.stack.push({ async: true });\n }\n return value;\n}\n\nvar _SuppressedError = typeof SuppressedError === \"function\" ? SuppressedError : function (error, suppressed, message) {\n var e = new Error(message);\n return e.name = \"SuppressedError\", e.error = error, e.suppressed = suppressed, e;\n};\n\nexport function __disposeResources(env) {\n function fail(e) {\n env.error = env.hasError ? new _SuppressedError(e, env.error, \"An error was suppressed during disposal.\") : e;\n env.hasError = true;\n }\n var r, s = 0;\n function next() {\n while (r = env.stack.pop()) {\n try {\n if (!r.async && s === 1) return s = 0, env.stack.push(r), Promise.resolve().then(next);\n if (r.dispose) {\n var result = r.dispose.call(r.value);\n if (r.async) return s |= 2, Promise.resolve(result).then(next, function(e) { fail(e); return next(); });\n }\n else s |= 1;\n }\n catch (e) {\n fail(e);\n }\n }\n if (s === 1) return env.hasError ? Promise.reject(env.error) : Promise.resolve();\n if (env.hasError) throw env.error;\n }\n return next();\n}\n\nexport default {\n __extends,\n __assign,\n __rest,\n __decorate,\n __param,\n __metadata,\n __awaiter,\n __generator,\n __createBinding,\n __exportStar,\n __values,\n __read,\n __spread,\n __spreadArrays,\n __spreadArray,\n __await,\n __asyncGenerator,\n __asyncDelegator,\n __asyncValues,\n __makeTemplateObject,\n __importStar,\n __importDefault,\n __classPrivateFieldGet,\n __classPrivateFieldSet,\n __classPrivateFieldIn,\n __addDisposableResource,\n __disposeResources,\n};\n", "/**\n * Returns true if the object is a function.\n * @param value The value to check\n */\nexport function isFunction(value: any): value is (...args: any[]) => any {\n return typeof value === 'function';\n}\n", "/**\n * Used to create Error subclasses until the community moves away from ES5.\n *\n * This is because compiling from TypeScript down to ES5 has issues with subclassing Errors\n * as well as other built-in types: https://github.com/Microsoft/TypeScript/issues/12123\n *\n * @param createImpl A factory function to create the actual constructor implementation. The returned\n * function should be a named function that calls `_super` internally.\n */\nexport function createErrorClass(createImpl: (_super: any) => any): T {\n const _super = (instance: any) => {\n Error.call(instance);\n instance.stack = new Error().stack;\n };\n\n const ctorFunc = createImpl(_super);\n ctorFunc.prototype = Object.create(Error.prototype);\n ctorFunc.prototype.constructor = ctorFunc;\n return ctorFunc;\n}\n", "import { createErrorClass } from './createErrorClass';\n\nexport interface UnsubscriptionError extends Error {\n readonly errors: any[];\n}\n\nexport interface UnsubscriptionErrorCtor {\n /**\n * @deprecated Internal implementation detail. Do not construct error instances.\n * Cannot be tagged as internal: https://github.com/ReactiveX/rxjs/issues/6269\n */\n new (errors: any[]): UnsubscriptionError;\n}\n\n/**\n * An error thrown when one or more errors have occurred during the\n * `unsubscribe` of a {@link Subscription}.\n */\nexport const UnsubscriptionError: UnsubscriptionErrorCtor = createErrorClass(\n (_super) =>\n function UnsubscriptionErrorImpl(this: any, errors: (Error | string)[]) {\n _super(this);\n this.message = errors\n ? `${errors.length} errors occurred during unsubscription:\n${errors.map((err, i) => `${i + 1}) ${err.toString()}`).join('\\n ')}`\n : '';\n this.name = 'UnsubscriptionError';\n this.errors = errors;\n }\n);\n", "/**\n * Removes an item from an array, mutating it.\n * @param arr The array to remove the item from\n * @param item The item to remove\n */\nexport function arrRemove(arr: T[] | undefined | null, item: T) {\n if (arr) {\n const index = arr.indexOf(item);\n 0 <= index && arr.splice(index, 1);\n }\n}\n", "import { isFunction } from './util/isFunction';\nimport { UnsubscriptionError } from './util/UnsubscriptionError';\nimport { SubscriptionLike, TeardownLogic, Unsubscribable } from './types';\nimport { arrRemove } from './util/arrRemove';\n\n/**\n * Represents a disposable resource, such as the execution of an Observable. A\n * Subscription has one important method, `unsubscribe`, that takes no argument\n * and just disposes the resource held by the subscription.\n *\n * Additionally, subscriptions may be grouped together through the `add()`\n * method, which will attach a child Subscription to the current Subscription.\n * When a Subscription is unsubscribed, all its children (and its grandchildren)\n * will be unsubscribed as well.\n *\n * @class Subscription\n */\nexport class Subscription implements SubscriptionLike {\n /** @nocollapse */\n public static EMPTY = (() => {\n const empty = new Subscription();\n empty.closed = true;\n return empty;\n })();\n\n /**\n * A flag to indicate whether this Subscription has already been unsubscribed.\n */\n public closed = false;\n\n private _parentage: Subscription[] | Subscription | null = null;\n\n /**\n * The list of registered finalizers to execute upon unsubscription. Adding and removing from this\n * list occurs in the {@link #add} and {@link #remove} methods.\n */\n private _finalizers: Exclude[] | null = null;\n\n /**\n * @param initialTeardown A function executed first as part of the finalization\n * process that is kicked off when {@link #unsubscribe} is called.\n */\n constructor(private initialTeardown?: () => void) {}\n\n /**\n * Disposes the resources held by the subscription. May, for instance, cancel\n * an ongoing Observable execution or cancel any other type of work that\n * started when the Subscription was created.\n * @return {void}\n */\n unsubscribe(): void {\n let errors: any[] | undefined;\n\n if (!this.closed) {\n this.closed = true;\n\n // Remove this from it's parents.\n const { _parentage } = this;\n if (_parentage) {\n this._parentage = null;\n if (Array.isArray(_parentage)) {\n for (const parent of _parentage) {\n parent.remove(this);\n }\n } else {\n _parentage.remove(this);\n }\n }\n\n const { initialTeardown: initialFinalizer } = this;\n if (isFunction(initialFinalizer)) {\n try {\n initialFinalizer();\n } catch (e) {\n errors = e instanceof UnsubscriptionError ? e.errors : [e];\n }\n }\n\n const { _finalizers } = this;\n if (_finalizers) {\n this._finalizers = null;\n for (const finalizer of _finalizers) {\n try {\n execFinalizer(finalizer);\n } catch (err) {\n errors = errors ?? [];\n if (err instanceof UnsubscriptionError) {\n errors = [...errors, ...err.errors];\n } else {\n errors.push(err);\n }\n }\n }\n }\n\n if (errors) {\n throw new UnsubscriptionError(errors);\n }\n }\n }\n\n /**\n * Adds a finalizer to this subscription, so that finalization will be unsubscribed/called\n * when this subscription is unsubscribed. If this subscription is already {@link #closed},\n * because it has already been unsubscribed, then whatever finalizer is passed to it\n * will automatically be executed (unless the finalizer itself is also a closed subscription).\n *\n * Closed Subscriptions cannot be added as finalizers to any subscription. Adding a closed\n * subscription to a any subscription will result in no operation. (A noop).\n *\n * Adding a subscription to itself, or adding `null` or `undefined` will not perform any\n * operation at all. (A noop).\n *\n * `Subscription` instances that are added to this instance will automatically remove themselves\n * if they are unsubscribed. Functions and {@link Unsubscribable} objects that you wish to remove\n * will need to be removed manually with {@link #remove}\n *\n * @param teardown The finalization logic to add to this subscription.\n */\n add(teardown: TeardownLogic): void {\n // Only add the finalizer if it's not undefined\n // and don't add a subscription to itself.\n if (teardown && teardown !== this) {\n if (this.closed) {\n // If this subscription is already closed,\n // execute whatever finalizer is handed to it automatically.\n execFinalizer(teardown);\n } else {\n if (teardown instanceof Subscription) {\n // We don't add closed subscriptions, and we don't add the same subscription\n // twice. Subscription unsubscribe is idempotent.\n if (teardown.closed || teardown._hasParent(this)) {\n return;\n }\n teardown._addParent(this);\n }\n (this._finalizers = this._finalizers ?? []).push(teardown);\n }\n }\n }\n\n /**\n * Checks to see if a this subscription already has a particular parent.\n * This will signal that this subscription has already been added to the parent in question.\n * @param parent the parent to check for\n */\n private _hasParent(parent: Subscription) {\n const { _parentage } = this;\n return _parentage === parent || (Array.isArray(_parentage) && _parentage.includes(parent));\n }\n\n /**\n * Adds a parent to this subscription so it can be removed from the parent if it\n * unsubscribes on it's own.\n *\n * NOTE: THIS ASSUMES THAT {@link _hasParent} HAS ALREADY BEEN CHECKED.\n * @param parent The parent subscription to add\n */\n private _addParent(parent: Subscription) {\n const { _parentage } = this;\n this._parentage = Array.isArray(_parentage) ? (_parentage.push(parent), _parentage) : _parentage ? [_parentage, parent] : parent;\n }\n\n /**\n * Called on a child when it is removed via {@link #remove}.\n * @param parent The parent to remove\n */\n private _removeParent(parent: Subscription) {\n const { _parentage } = this;\n if (_parentage === parent) {\n this._parentage = null;\n } else if (Array.isArray(_parentage)) {\n arrRemove(_parentage, parent);\n }\n }\n\n /**\n * Removes a finalizer from this subscription that was previously added with the {@link #add} method.\n *\n * Note that `Subscription` instances, when unsubscribed, will automatically remove themselves\n * from every other `Subscription` they have been added to. This means that using the `remove` method\n * is not a common thing and should be used thoughtfully.\n *\n * If you add the same finalizer instance of a function or an unsubscribable object to a `Subscription` instance\n * more than once, you will need to call `remove` the same number of times to remove all instances.\n *\n * All finalizer instances are removed to free up memory upon unsubscription.\n *\n * @param teardown The finalizer to remove from this subscription\n */\n remove(teardown: Exclude): void {\n const { _finalizers } = this;\n _finalizers && arrRemove(_finalizers, teardown);\n\n if (teardown instanceof Subscription) {\n teardown._removeParent(this);\n }\n }\n}\n\nexport const EMPTY_SUBSCRIPTION = Subscription.EMPTY;\n\nexport function isSubscription(value: any): value is Subscription {\n return (\n value instanceof Subscription ||\n (value && 'closed' in value && isFunction(value.remove) && isFunction(value.add) && isFunction(value.unsubscribe))\n );\n}\n\nfunction execFinalizer(finalizer: Unsubscribable | (() => void)) {\n if (isFunction(finalizer)) {\n finalizer();\n } else {\n finalizer.unsubscribe();\n }\n}\n", "import { Subscriber } from './Subscriber';\nimport { ObservableNotification } from './types';\n\n/**\n * The {@link GlobalConfig} object for RxJS. It is used to configure things\n * like how to react on unhandled errors.\n */\nexport const config: GlobalConfig = {\n onUnhandledError: null,\n onStoppedNotification: null,\n Promise: undefined,\n useDeprecatedSynchronousErrorHandling: false,\n useDeprecatedNextContext: false,\n};\n\n/**\n * The global configuration object for RxJS, used to configure things\n * like how to react on unhandled errors. Accessible via {@link config}\n * object.\n */\nexport interface GlobalConfig {\n /**\n * A registration point for unhandled errors from RxJS. These are errors that\n * cannot were not handled by consuming code in the usual subscription path. For\n * example, if you have this configured, and you subscribe to an observable without\n * providing an error handler, errors from that subscription will end up here. This\n * will _always_ be called asynchronously on another job in the runtime. This is because\n * we do not want errors thrown in this user-configured handler to interfere with the\n * behavior of the library.\n */\n onUnhandledError: ((err: any) => void) | null;\n\n /**\n * A registration point for notifications that cannot be sent to subscribers because they\n * have completed, errored or have been explicitly unsubscribed. By default, next, complete\n * and error notifications sent to stopped subscribers are noops. However, sometimes callers\n * might want a different behavior. For example, with sources that attempt to report errors\n * to stopped subscribers, a caller can configure RxJS to throw an unhandled error instead.\n * This will _always_ be called asynchronously on another job in the runtime. This is because\n * we do not want errors thrown in this user-configured handler to interfere with the\n * behavior of the library.\n */\n onStoppedNotification: ((notification: ObservableNotification, subscriber: Subscriber) => void) | null;\n\n /**\n * The promise constructor used by default for {@link Observable#toPromise toPromise} and {@link Observable#forEach forEach}\n * methods.\n *\n * @deprecated As of version 8, RxJS will no longer support this sort of injection of a\n * Promise constructor. If you need a Promise implementation other than native promises,\n * please polyfill/patch Promise as you see appropriate. Will be removed in v8.\n */\n Promise?: PromiseConstructorLike;\n\n /**\n * If true, turns on synchronous error rethrowing, which is a deprecated behavior\n * in v6 and higher. This behavior enables bad patterns like wrapping a subscribe\n * call in a try/catch block. It also enables producer interference, a nasty bug\n * where a multicast can be broken for all observers by a downstream consumer with\n * an unhandled error. DO NOT USE THIS FLAG UNLESS IT'S NEEDED TO BUY TIME\n * FOR MIGRATION REASONS.\n *\n * @deprecated As of version 8, RxJS will no longer support synchronous throwing\n * of unhandled errors. All errors will be thrown on a separate call stack to prevent bad\n * behaviors described above. Will be removed in v8.\n */\n useDeprecatedSynchronousErrorHandling: boolean;\n\n /**\n * If true, enables an as-of-yet undocumented feature from v5: The ability to access\n * `unsubscribe()` via `this` context in `next` functions created in observers passed\n * to `subscribe`.\n *\n * This is being removed because the performance was severely problematic, and it could also cause\n * issues when types other than POJOs are passed to subscribe as subscribers, as they will likely have\n * their `this` context overwritten.\n *\n * @deprecated As of version 8, RxJS will no longer support altering the\n * context of next functions provided as part of an observer to Subscribe. Instead,\n * you will have access to a subscription or a signal or token that will allow you to do things like\n * unsubscribe and test closed status. Will be removed in v8.\n */\n useDeprecatedNextContext: boolean;\n}\n", "import type { TimerHandle } from './timerHandle';\ntype SetTimeoutFunction = (handler: () => void, timeout?: number, ...args: any[]) => TimerHandle;\ntype ClearTimeoutFunction = (handle: TimerHandle) => void;\n\ninterface TimeoutProvider {\n setTimeout: SetTimeoutFunction;\n clearTimeout: ClearTimeoutFunction;\n delegate:\n | {\n setTimeout: SetTimeoutFunction;\n clearTimeout: ClearTimeoutFunction;\n }\n | undefined;\n}\n\nexport const timeoutProvider: TimeoutProvider = {\n // When accessing the delegate, use the variable rather than `this` so that\n // the functions can be called without being bound to the provider.\n setTimeout(handler: () => void, timeout?: number, ...args) {\n const { delegate } = timeoutProvider;\n if (delegate?.setTimeout) {\n return delegate.setTimeout(handler, timeout, ...args);\n }\n return setTimeout(handler, timeout, ...args);\n },\n clearTimeout(handle) {\n const { delegate } = timeoutProvider;\n return (delegate?.clearTimeout || clearTimeout)(handle as any);\n },\n delegate: undefined,\n};\n", "import { config } from '../config';\nimport { timeoutProvider } from '../scheduler/timeoutProvider';\n\n/**\n * Handles an error on another job either with the user-configured {@link onUnhandledError},\n * or by throwing it on that new job so it can be picked up by `window.onerror`, `process.on('error')`, etc.\n *\n * This should be called whenever there is an error that is out-of-band with the subscription\n * or when an error hits a terminal boundary of the subscription and no error handler was provided.\n *\n * @param err the error to report\n */\nexport function reportUnhandledError(err: any) {\n timeoutProvider.setTimeout(() => {\n const { onUnhandledError } = config;\n if (onUnhandledError) {\n // Execute the user-configured error handler.\n onUnhandledError(err);\n } else {\n // Throw so it is picked up by the runtime's uncaught error mechanism.\n throw err;\n }\n });\n}\n", "/* tslint:disable:no-empty */\nexport function noop() { }\n", "import { CompleteNotification, NextNotification, ErrorNotification } from './types';\n\n/**\n * A completion object optimized for memory use and created to be the\n * same \"shape\" as other notifications in v8.\n * @internal\n */\nexport const COMPLETE_NOTIFICATION = (() => createNotification('C', undefined, undefined) as CompleteNotification)();\n\n/**\n * Internal use only. Creates an optimized error notification that is the same \"shape\"\n * as other notifications.\n * @internal\n */\nexport function errorNotification(error: any): ErrorNotification {\n return createNotification('E', undefined, error) as any;\n}\n\n/**\n * Internal use only. Creates an optimized next notification that is the same \"shape\"\n * as other notifications.\n * @internal\n */\nexport function nextNotification(value: T) {\n return createNotification('N', value, undefined) as NextNotification;\n}\n\n/**\n * Ensures that all notifications created internally have the same \"shape\" in v8.\n *\n * TODO: This is only exported to support a crazy legacy test in `groupBy`.\n * @internal\n */\nexport function createNotification(kind: 'N' | 'E' | 'C', value: any, error: any) {\n return {\n kind,\n value,\n error,\n };\n}\n", "import { config } from '../config';\n\nlet context: { errorThrown: boolean; error: any } | null = null;\n\n/**\n * Handles dealing with errors for super-gross mode. Creates a context, in which\n * any synchronously thrown errors will be passed to {@link captureError}. Which\n * will record the error such that it will be rethrown after the call back is complete.\n * TODO: Remove in v8\n * @param cb An immediately executed function.\n */\nexport function errorContext(cb: () => void) {\n if (config.useDeprecatedSynchronousErrorHandling) {\n const isRoot = !context;\n if (isRoot) {\n context = { errorThrown: false, error: null };\n }\n cb();\n if (isRoot) {\n const { errorThrown, error } = context!;\n context = null;\n if (errorThrown) {\n throw error;\n }\n }\n } else {\n // This is the general non-deprecated path for everyone that\n // isn't crazy enough to use super-gross mode (useDeprecatedSynchronousErrorHandling)\n cb();\n }\n}\n\n/**\n * Captures errors only in super-gross mode.\n * @param err the error to capture\n */\nexport function captureError(err: any) {\n if (config.useDeprecatedSynchronousErrorHandling && context) {\n context.errorThrown = true;\n context.error = err;\n }\n}\n", "import { isFunction } from './util/isFunction';\nimport { Observer, ObservableNotification } from './types';\nimport { isSubscription, Subscription } from './Subscription';\nimport { config } from './config';\nimport { reportUnhandledError } from './util/reportUnhandledError';\nimport { noop } from './util/noop';\nimport { nextNotification, errorNotification, COMPLETE_NOTIFICATION } from './NotificationFactories';\nimport { timeoutProvider } from './scheduler/timeoutProvider';\nimport { captureError } from './util/errorContext';\n\n/**\n * Implements the {@link Observer} interface and extends the\n * {@link Subscription} class. While the {@link Observer} is the public API for\n * consuming the values of an {@link Observable}, all Observers get converted to\n * a Subscriber, in order to provide Subscription-like capabilities such as\n * `unsubscribe`. Subscriber is a common type in RxJS, and crucial for\n * implementing operators, but it is rarely used as a public API.\n *\n * @class Subscriber\n */\nexport class Subscriber extends Subscription implements Observer {\n /**\n * A static factory for a Subscriber, given a (potentially partial) definition\n * of an Observer.\n * @param next The `next` callback of an Observer.\n * @param error The `error` callback of an\n * Observer.\n * @param complete The `complete` callback of an\n * Observer.\n * @return A Subscriber wrapping the (partially defined)\n * Observer represented by the given arguments.\n * @nocollapse\n * @deprecated Do not use. Will be removed in v8. There is no replacement for this\n * method, and there is no reason to be creating instances of `Subscriber` directly.\n * If you have a specific use case, please file an issue.\n */\n static create(next?: (x?: T) => void, error?: (e?: any) => void, complete?: () => void): Subscriber {\n return new SafeSubscriber(next, error, complete);\n }\n\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n protected isStopped: boolean = false;\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n protected destination: Subscriber | Observer; // this `any` is the escape hatch to erase extra type param (e.g. R)\n\n /**\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n * There is no reason to directly create an instance of Subscriber. This type is exported for typings reasons.\n */\n constructor(destination?: Subscriber | Observer) {\n super();\n if (destination) {\n this.destination = destination;\n // Automatically chain subscriptions together here.\n // if destination is a Subscription, then it is a Subscriber.\n if (isSubscription(destination)) {\n destination.add(this);\n }\n } else {\n this.destination = EMPTY_OBSERVER;\n }\n }\n\n /**\n * The {@link Observer} callback to receive notifications of type `next` from\n * the Observable, with a value. The Observable may call this method 0 or more\n * times.\n * @param {T} [value] The `next` value.\n * @return {void}\n */\n next(value?: T): void {\n if (this.isStopped) {\n handleStoppedNotification(nextNotification(value), this);\n } else {\n this._next(value!);\n }\n }\n\n /**\n * The {@link Observer} callback to receive notifications of type `error` from\n * the Observable, with an attached `Error`. Notifies the Observer that\n * the Observable has experienced an error condition.\n * @param {any} [err] The `error` exception.\n * @return {void}\n */\n error(err?: any): void {\n if (this.isStopped) {\n handleStoppedNotification(errorNotification(err), this);\n } else {\n this.isStopped = true;\n this._error(err);\n }\n }\n\n /**\n * The {@link Observer} callback to receive a valueless notification of type\n * `complete` from the Observable. Notifies the Observer that the Observable\n * has finished sending push-based notifications.\n * @return {void}\n */\n complete(): void {\n if (this.isStopped) {\n handleStoppedNotification(COMPLETE_NOTIFICATION, this);\n } else {\n this.isStopped = true;\n this._complete();\n }\n }\n\n unsubscribe(): void {\n if (!this.closed) {\n this.isStopped = true;\n super.unsubscribe();\n this.destination = null!;\n }\n }\n\n protected _next(value: T): void {\n this.destination.next(value);\n }\n\n protected _error(err: any): void {\n try {\n this.destination.error(err);\n } finally {\n this.unsubscribe();\n }\n }\n\n protected _complete(): void {\n try {\n this.destination.complete();\n } finally {\n this.unsubscribe();\n }\n }\n}\n\n/**\n * This bind is captured here because we want to be able to have\n * compatibility with monoid libraries that tend to use a method named\n * `bind`. In particular, a library called Monio requires this.\n */\nconst _bind = Function.prototype.bind;\n\nfunction bind any>(fn: Fn, thisArg: any): Fn {\n return _bind.call(fn, thisArg);\n}\n\n/**\n * Internal optimization only, DO NOT EXPOSE.\n * @internal\n */\nclass ConsumerObserver implements Observer {\n constructor(private partialObserver: Partial>) {}\n\n next(value: T): void {\n const { partialObserver } = this;\n if (partialObserver.next) {\n try {\n partialObserver.next(value);\n } catch (error) {\n handleUnhandledError(error);\n }\n }\n }\n\n error(err: any): void {\n const { partialObserver } = this;\n if (partialObserver.error) {\n try {\n partialObserver.error(err);\n } catch (error) {\n handleUnhandledError(error);\n }\n } else {\n handleUnhandledError(err);\n }\n }\n\n complete(): void {\n const { partialObserver } = this;\n if (partialObserver.complete) {\n try {\n partialObserver.complete();\n } catch (error) {\n handleUnhandledError(error);\n }\n }\n }\n}\n\nexport class SafeSubscriber extends Subscriber {\n constructor(\n observerOrNext?: Partial> | ((value: T) => void) | null,\n error?: ((e?: any) => void) | null,\n complete?: (() => void) | null\n ) {\n super();\n\n let partialObserver: Partial>;\n if (isFunction(observerOrNext) || !observerOrNext) {\n // The first argument is a function, not an observer. The next\n // two arguments *could* be observers, or they could be empty.\n partialObserver = {\n next: (observerOrNext ?? undefined) as (((value: T) => void) | undefined),\n error: error ?? undefined,\n complete: complete ?? undefined,\n };\n } else {\n // The first argument is a partial observer.\n let context: any;\n if (this && config.useDeprecatedNextContext) {\n // This is a deprecated path that made `this.unsubscribe()` available in\n // next handler functions passed to subscribe. This only exists behind a flag\n // now, as it is *very* slow.\n context = Object.create(observerOrNext);\n context.unsubscribe = () => this.unsubscribe();\n partialObserver = {\n next: observerOrNext.next && bind(observerOrNext.next, context),\n error: observerOrNext.error && bind(observerOrNext.error, context),\n complete: observerOrNext.complete && bind(observerOrNext.complete, context),\n };\n } else {\n // The \"normal\" path. Just use the partial observer directly.\n partialObserver = observerOrNext;\n }\n }\n\n // Wrap the partial observer to ensure it's a full observer, and\n // make sure proper error handling is accounted for.\n this.destination = new ConsumerObserver(partialObserver);\n }\n}\n\nfunction handleUnhandledError(error: any) {\n if (config.useDeprecatedSynchronousErrorHandling) {\n captureError(error);\n } else {\n // Ideal path, we report this as an unhandled error,\n // which is thrown on a new call stack.\n reportUnhandledError(error);\n }\n}\n\n/**\n * An error handler used when no error handler was supplied\n * to the SafeSubscriber -- meaning no error handler was supplied\n * do the `subscribe` call on our observable.\n * @param err The error to handle\n */\nfunction defaultErrorHandler(err: any) {\n throw err;\n}\n\n/**\n * A handler for notifications that cannot be sent to a stopped subscriber.\n * @param notification The notification being sent\n * @param subscriber The stopped subscriber\n */\nfunction handleStoppedNotification(notification: ObservableNotification, subscriber: Subscriber) {\n const { onStoppedNotification } = config;\n onStoppedNotification && timeoutProvider.setTimeout(() => onStoppedNotification(notification, subscriber));\n}\n\n/**\n * The observer used as a stub for subscriptions where the user did not\n * pass any arguments to `subscribe`. Comes with the default error handling\n * behavior.\n */\nexport const EMPTY_OBSERVER: Readonly> & { closed: true } = {\n closed: true,\n next: noop,\n error: defaultErrorHandler,\n complete: noop,\n};\n", "/**\n * Symbol.observable or a string \"@@observable\". Used for interop\n *\n * @deprecated We will no longer be exporting this symbol in upcoming versions of RxJS.\n * Instead polyfill and use Symbol.observable directly *or* use https://www.npmjs.com/package/symbol-observable\n */\nexport const observable: string | symbol = (() => (typeof Symbol === 'function' && Symbol.observable) || '@@observable')();\n", "/**\n * This function takes one parameter and just returns it. Simply put,\n * this is like `(x: T): T => x`.\n *\n * ## Examples\n *\n * This is useful in some cases when using things like `mergeMap`\n *\n * ```ts\n * import { interval, take, map, range, mergeMap, identity } from 'rxjs';\n *\n * const source$ = interval(1000).pipe(take(5));\n *\n * const result$ = source$.pipe(\n * map(i => range(i)),\n * mergeMap(identity) // same as mergeMap(x => x)\n * );\n *\n * result$.subscribe({\n * next: console.log\n * });\n * ```\n *\n * Or when you want to selectively apply an operator\n *\n * ```ts\n * import { interval, take, identity } from 'rxjs';\n *\n * const shouldLimit = () => Math.random() < 0.5;\n *\n * const source$ = interval(1000);\n *\n * const result$ = source$.pipe(shouldLimit() ? take(5) : identity);\n *\n * result$.subscribe({\n * next: console.log\n * });\n * ```\n *\n * @param x Any value that is returned by this function\n * @returns The value passed as the first parameter to this function\n */\nexport function identity(x: T): T {\n return x;\n}\n", "import { identity } from './identity';\nimport { UnaryFunction } from '../types';\n\nexport function pipe(): typeof identity;\nexport function pipe(fn1: UnaryFunction): UnaryFunction;\nexport function pipe(fn1: UnaryFunction, fn2: UnaryFunction): UnaryFunction;\nexport function pipe(fn1: UnaryFunction, fn2: UnaryFunction, fn3: UnaryFunction): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction,\n fn8: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction,\n fn8: UnaryFunction,\n fn9: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction,\n fn8: UnaryFunction,\n fn9: UnaryFunction,\n ...fns: UnaryFunction[]\n): UnaryFunction;\n\n/**\n * pipe() can be called on one or more functions, each of which can take one argument (\"UnaryFunction\")\n * and uses it to return a value.\n * It returns a function that takes one argument, passes it to the first UnaryFunction, and then\n * passes the result to the next one, passes that result to the next one, and so on. \n */\nexport function pipe(...fns: Array>): UnaryFunction {\n return pipeFromArray(fns);\n}\n\n/** @internal */\nexport function pipeFromArray(fns: Array>): UnaryFunction {\n if (fns.length === 0) {\n return identity as UnaryFunction;\n }\n\n if (fns.length === 1) {\n return fns[0];\n }\n\n return function piped(input: T): R {\n return fns.reduce((prev: any, fn: UnaryFunction) => fn(prev), input as any);\n };\n}\n", "import { Operator } from './Operator';\nimport { SafeSubscriber, Subscriber } from './Subscriber';\nimport { isSubscription, Subscription } from './Subscription';\nimport { TeardownLogic, OperatorFunction, Subscribable, Observer } from './types';\nimport { observable as Symbol_observable } from './symbol/observable';\nimport { pipeFromArray } from './util/pipe';\nimport { config } from './config';\nimport { isFunction } from './util/isFunction';\nimport { errorContext } from './util/errorContext';\n\n/**\n * A representation of any set of values over any amount of time. This is the most basic building block\n * of RxJS.\n *\n * @class Observable\n */\nexport class Observable implements Subscribable {\n /**\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n */\n source: Observable | undefined;\n\n /**\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n */\n operator: Operator | undefined;\n\n /**\n * @constructor\n * @param {Function} subscribe the function that is called when the Observable is\n * initially subscribed to. This function is given a Subscriber, to which new values\n * can be `next`ed, or an `error` method can be called to raise an error, or\n * `complete` can be called to notify of a successful completion.\n */\n constructor(subscribe?: (this: Observable, subscriber: Subscriber) => TeardownLogic) {\n if (subscribe) {\n this._subscribe = subscribe;\n }\n }\n\n // HACK: Since TypeScript inherits static properties too, we have to\n // fight against TypeScript here so Subject can have a different static create signature\n /**\n * Creates a new Observable by calling the Observable constructor\n * @owner Observable\n * @method create\n * @param {Function} subscribe? the subscriber function to be passed to the Observable constructor\n * @return {Observable} a new observable\n * @nocollapse\n * @deprecated Use `new Observable()` instead. Will be removed in v8.\n */\n static create: (...args: any[]) => any = (subscribe?: (subscriber: Subscriber) => TeardownLogic) => {\n return new Observable(subscribe);\n };\n\n /**\n * Creates a new Observable, with this Observable instance as the source, and the passed\n * operator defined as the new observable's operator.\n * @method lift\n * @param operator the operator defining the operation to take on the observable\n * @return a new observable with the Operator applied\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n * If you have implemented an operator using `lift`, it is recommended that you create an\n * operator by simply returning `new Observable()` directly. See \"Creating new operators from\n * scratch\" section here: https://rxjs.dev/guide/operators\n */\n lift(operator?: Operator): Observable {\n const observable = new Observable();\n observable.source = this;\n observable.operator = operator;\n return observable;\n }\n\n subscribe(observerOrNext?: Partial> | ((value: T) => void)): Subscription;\n /** @deprecated Instead of passing separate callback arguments, use an observer argument. Signatures taking separate callback arguments will be removed in v8. Details: https://rxjs.dev/deprecations/subscribe-arguments */\n subscribe(next?: ((value: T) => void) | null, error?: ((error: any) => void) | null, complete?: (() => void) | null): Subscription;\n /**\n * Invokes an execution of an Observable and registers Observer handlers for notifications it will emit.\n *\n * Use it when you have all these Observables, but still nothing is happening.\n *\n * `subscribe` is not a regular operator, but a method that calls Observable's internal `subscribe` function. It\n * might be for example a function that you passed to Observable's constructor, but most of the time it is\n * a library implementation, which defines what will be emitted by an Observable, and when it be will emitted. This means\n * that calling `subscribe` is actually the moment when Observable starts its work, not when it is created, as it is often\n * the thought.\n *\n * Apart from starting the execution of an Observable, this method allows you to listen for values\n * that an Observable emits, as well as for when it completes or errors. You can achieve this in two\n * of the following ways.\n *\n * The first way is creating an object that implements {@link Observer} interface. It should have methods\n * defined by that interface, but note that it should be just a regular JavaScript object, which you can create\n * yourself in any way you want (ES6 class, classic function constructor, object literal etc.). In particular, do\n * not attempt to use any RxJS implementation details to create Observers - you don't need them. Remember also\n * that your object does not have to implement all methods. If you find yourself creating a method that doesn't\n * do anything, you can simply omit it. Note however, if the `error` method is not provided and an error happens,\n * it will be thrown asynchronously. Errors thrown asynchronously cannot be caught using `try`/`catch`. Instead,\n * use the {@link onUnhandledError} configuration option or use a runtime handler (like `window.onerror` or\n * `process.on('error)`) to be notified of unhandled errors. Because of this, it's recommended that you provide\n * an `error` method to avoid missing thrown errors.\n *\n * The second way is to give up on Observer object altogether and simply provide callback functions in place of its methods.\n * This means you can provide three functions as arguments to `subscribe`, where the first function is equivalent\n * of a `next` method, the second of an `error` method and the third of a `complete` method. Just as in case of an Observer,\n * if you do not need to listen for something, you can omit a function by passing `undefined` or `null`,\n * since `subscribe` recognizes these functions by where they were placed in function call. When it comes\n * to the `error` function, as with an Observer, if not provided, errors emitted by an Observable will be thrown asynchronously.\n *\n * You can, however, subscribe with no parameters at all. This may be the case where you're not interested in terminal events\n * and you also handled emissions internally by using operators (e.g. using `tap`).\n *\n * Whichever style of calling `subscribe` you use, in both cases it returns a Subscription object.\n * This object allows you to call `unsubscribe` on it, which in turn will stop the work that an Observable does and will clean\n * up all resources that an Observable used. Note that cancelling a subscription will not call `complete` callback\n * provided to `subscribe` function, which is reserved for a regular completion signal that comes from an Observable.\n *\n * Remember that callbacks provided to `subscribe` are not guaranteed to be called asynchronously.\n * It is an Observable itself that decides when these functions will be called. For example {@link of}\n * by default emits all its values synchronously. Always check documentation for how given Observable\n * will behave when subscribed and if its default behavior can be modified with a `scheduler`.\n *\n * #### Examples\n *\n * Subscribe with an {@link guide/observer Observer}\n *\n * ```ts\n * import { of } from 'rxjs';\n *\n * const sumObserver = {\n * sum: 0,\n * next(value) {\n * console.log('Adding: ' + value);\n * this.sum = this.sum + value;\n * },\n * error() {\n * // We actually could just remove this method,\n * // since we do not really care about errors right now.\n * },\n * complete() {\n * console.log('Sum equals: ' + this.sum);\n * }\n * };\n *\n * of(1, 2, 3) // Synchronously emits 1, 2, 3 and then completes.\n * .subscribe(sumObserver);\n *\n * // Logs:\n * // 'Adding: 1'\n * // 'Adding: 2'\n * // 'Adding: 3'\n * // 'Sum equals: 6'\n * ```\n *\n * Subscribe with functions ({@link deprecations/subscribe-arguments deprecated})\n *\n * ```ts\n * import { of } from 'rxjs'\n *\n * let sum = 0;\n *\n * of(1, 2, 3).subscribe(\n * value => {\n * console.log('Adding: ' + value);\n * sum = sum + value;\n * },\n * undefined,\n * () => console.log('Sum equals: ' + sum)\n * );\n *\n * // Logs:\n * // 'Adding: 1'\n * // 'Adding: 2'\n * // 'Adding: 3'\n * // 'Sum equals: 6'\n * ```\n *\n * Cancel a subscription\n *\n * ```ts\n * import { interval } from 'rxjs';\n *\n * const subscription = interval(1000).subscribe({\n * next(num) {\n * console.log(num)\n * },\n * complete() {\n * // Will not be called, even when cancelling subscription.\n * console.log('completed!');\n * }\n * });\n *\n * setTimeout(() => {\n * subscription.unsubscribe();\n * console.log('unsubscribed!');\n * }, 2500);\n *\n * // Logs:\n * // 0 after 1s\n * // 1 after 2s\n * // 'unsubscribed!' after 2.5s\n * ```\n *\n * @param {Observer|Function} observerOrNext (optional) Either an observer with methods to be called,\n * or the first of three possible handlers, which is the handler for each value emitted from the subscribed\n * Observable.\n * @param {Function} error (optional) A handler for a terminal event resulting from an error. If no error handler is provided,\n * the error will be thrown asynchronously as unhandled.\n * @param {Function} complete (optional) A handler for a terminal event resulting from successful completion.\n * @return {Subscription} a subscription reference to the registered handlers\n * @method subscribe\n */\n subscribe(\n observerOrNext?: Partial> | ((value: T) => void) | null,\n error?: ((error: any) => void) | null,\n complete?: (() => void) | null\n ): Subscription {\n const subscriber = isSubscriber(observerOrNext) ? observerOrNext : new SafeSubscriber(observerOrNext, error, complete);\n\n errorContext(() => {\n const { operator, source } = this;\n subscriber.add(\n operator\n ? // We're dealing with a subscription in the\n // operator chain to one of our lifted operators.\n operator.call(subscriber, source)\n : source\n ? // If `source` has a value, but `operator` does not, something that\n // had intimate knowledge of our API, like our `Subject`, must have\n // set it. We're going to just call `_subscribe` directly.\n this._subscribe(subscriber)\n : // In all other cases, we're likely wrapping a user-provided initializer\n // function, so we need to catch errors and handle them appropriately.\n this._trySubscribe(subscriber)\n );\n });\n\n return subscriber;\n }\n\n /** @internal */\n protected _trySubscribe(sink: Subscriber): TeardownLogic {\n try {\n return this._subscribe(sink);\n } catch (err) {\n // We don't need to return anything in this case,\n // because it's just going to try to `add()` to a subscription\n // above.\n sink.error(err);\n }\n }\n\n /**\n * Used as a NON-CANCELLABLE means of subscribing to an observable, for use with\n * APIs that expect promises, like `async/await`. You cannot unsubscribe from this.\n *\n * **WARNING**: Only use this with observables you *know* will complete. If the source\n * observable does not complete, you will end up with a promise that is hung up, and\n * potentially all of the state of an async function hanging out in memory. To avoid\n * this situation, look into adding something like {@link timeout}, {@link take},\n * {@link takeWhile}, or {@link takeUntil} amongst others.\n *\n * #### Example\n *\n * ```ts\n * import { interval, take } from 'rxjs';\n *\n * const source$ = interval(1000).pipe(take(4));\n *\n * async function getTotal() {\n * let total = 0;\n *\n * await source$.forEach(value => {\n * total += value;\n * console.log('observable -> ' + value);\n * });\n *\n * return total;\n * }\n *\n * getTotal().then(\n * total => console.log('Total: ' + total)\n * );\n *\n * // Expected:\n * // 'observable -> 0'\n * // 'observable -> 1'\n * // 'observable -> 2'\n * // 'observable -> 3'\n * // 'Total: 6'\n * ```\n *\n * @param next a handler for each value emitted by the observable\n * @return a promise that either resolves on observable completion or\n * rejects with the handled error\n */\n forEach(next: (value: T) => void): Promise;\n\n /**\n * @param next a handler for each value emitted by the observable\n * @param promiseCtor a constructor function used to instantiate the Promise\n * @return a promise that either resolves on observable completion or\n * rejects with the handled error\n * @deprecated Passing a Promise constructor will no longer be available\n * in upcoming versions of RxJS. This is because it adds weight to the library, for very\n * little benefit. If you need this functionality, it is recommended that you either\n * polyfill Promise, or you create an adapter to convert the returned native promise\n * to whatever promise implementation you wanted. Will be removed in v8.\n */\n forEach(next: (value: T) => void, promiseCtor: PromiseConstructorLike): Promise;\n\n forEach(next: (value: T) => void, promiseCtor?: PromiseConstructorLike): Promise {\n promiseCtor = getPromiseCtor(promiseCtor);\n\n return new promiseCtor((resolve, reject) => {\n const subscriber = new SafeSubscriber({\n next: (value) => {\n try {\n next(value);\n } catch (err) {\n reject(err);\n subscriber.unsubscribe();\n }\n },\n error: reject,\n complete: resolve,\n });\n this.subscribe(subscriber);\n }) as Promise;\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): TeardownLogic {\n return this.source?.subscribe(subscriber);\n }\n\n /**\n * An interop point defined by the es7-observable spec https://github.com/zenparsing/es-observable\n * @method Symbol.observable\n * @return {Observable} this instance of the observable\n */\n [Symbol_observable]() {\n return this;\n }\n\n /* tslint:disable:max-line-length */\n pipe(): Observable;\n pipe(op1: OperatorFunction): Observable;\n pipe(op1: OperatorFunction, op2: OperatorFunction): Observable;\n pipe(op1: OperatorFunction, op2: OperatorFunction, op3: OperatorFunction): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction,\n op8: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction,\n op8: OperatorFunction,\n op9: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction,\n op8: OperatorFunction,\n op9: OperatorFunction,\n ...operations: OperatorFunction[]\n ): Observable;\n /* tslint:enable:max-line-length */\n\n /**\n * Used to stitch together functional operators into a chain.\n * @method pipe\n * @return {Observable} the Observable result of all of the operators having\n * been called in the order they were passed in.\n *\n * ## Example\n *\n * ```ts\n * import { interval, filter, map, scan } from 'rxjs';\n *\n * interval(1000)\n * .pipe(\n * filter(x => x % 2 === 0),\n * map(x => x + x),\n * scan((acc, x) => acc + x)\n * )\n * .subscribe(x => console.log(x));\n * ```\n */\n pipe(...operations: OperatorFunction[]): Observable {\n return pipeFromArray(operations)(this);\n }\n\n /* tslint:disable:max-line-length */\n /** @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise */\n toPromise(): Promise;\n /** @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise */\n toPromise(PromiseCtor: typeof Promise): Promise;\n /** @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise */\n toPromise(PromiseCtor: PromiseConstructorLike): Promise;\n /* tslint:enable:max-line-length */\n\n /**\n * Subscribe to this Observable and get a Promise resolving on\n * `complete` with the last emission (if any).\n *\n * **WARNING**: Only use this with observables you *know* will complete. If the source\n * observable does not complete, you will end up with a promise that is hung up, and\n * potentially all of the state of an async function hanging out in memory. To avoid\n * this situation, look into adding something like {@link timeout}, {@link take},\n * {@link takeWhile}, or {@link takeUntil} amongst others.\n *\n * @method toPromise\n * @param [promiseCtor] a constructor function used to instantiate\n * the Promise\n * @return A Promise that resolves with the last value emit, or\n * rejects on an error. If there were no emissions, Promise\n * resolves with undefined.\n * @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise\n */\n toPromise(promiseCtor?: PromiseConstructorLike): Promise {\n promiseCtor = getPromiseCtor(promiseCtor);\n\n return new promiseCtor((resolve, reject) => {\n let value: T | undefined;\n this.subscribe(\n (x: T) => (value = x),\n (err: any) => reject(err),\n () => resolve(value)\n );\n }) as Promise;\n }\n}\n\n/**\n * Decides between a passed promise constructor from consuming code,\n * A default configured promise constructor, and the native promise\n * constructor and returns it. If nothing can be found, it will throw\n * an error.\n * @param promiseCtor The optional promise constructor to passed by consuming code\n */\nfunction getPromiseCtor(promiseCtor: PromiseConstructorLike | undefined) {\n return promiseCtor ?? config.Promise ?? Promise;\n}\n\nfunction isObserver(value: any): value is Observer {\n return value && isFunction(value.next) && isFunction(value.error) && isFunction(value.complete);\n}\n\nfunction isSubscriber(value: any): value is Subscriber {\n return (value && value instanceof Subscriber) || (isObserver(value) && isSubscription(value));\n}\n", "import { Observable } from '../Observable';\nimport { Subscriber } from '../Subscriber';\nimport { OperatorFunction } from '../types';\nimport { isFunction } from './isFunction';\n\n/**\n * Used to determine if an object is an Observable with a lift function.\n */\nexport function hasLift(source: any): source is { lift: InstanceType['lift'] } {\n return isFunction(source?.lift);\n}\n\n/**\n * Creates an `OperatorFunction`. Used to define operators throughout the library in a concise way.\n * @param init The logic to connect the liftedSource to the subscriber at the moment of subscription.\n */\nexport function operate(\n init: (liftedSource: Observable, subscriber: Subscriber) => (() => void) | void\n): OperatorFunction {\n return (source: Observable) => {\n if (hasLift(source)) {\n return source.lift(function (this: Subscriber, liftedSource: Observable) {\n try {\n return init(liftedSource, this);\n } catch (err) {\n this.error(err);\n }\n });\n }\n throw new TypeError('Unable to lift unknown Observable type');\n };\n}\n", "import { Subscriber } from '../Subscriber';\n\n/**\n * Creates an instance of an `OperatorSubscriber`.\n * @param destination The downstream subscriber.\n * @param onNext Handles next values, only called if this subscriber is not stopped or closed. Any\n * error that occurs in this function is caught and sent to the `error` method of this subscriber.\n * @param onError Handles errors from the subscription, any errors that occur in this handler are caught\n * and send to the `destination` error handler.\n * @param onComplete Handles completion notification from the subscription. Any errors that occur in\n * this handler are sent to the `destination` error handler.\n * @param onFinalize Additional teardown logic here. This will only be called on teardown if the\n * subscriber itself is not already closed. This is called after all other teardown logic is executed.\n */\nexport function createOperatorSubscriber(\n destination: Subscriber,\n onNext?: (value: T) => void,\n onComplete?: () => void,\n onError?: (err: any) => void,\n onFinalize?: () => void\n): Subscriber {\n return new OperatorSubscriber(destination, onNext, onComplete, onError, onFinalize);\n}\n\n/**\n * A generic helper for allowing operators to be created with a Subscriber and\n * use closures to capture necessary state from the operator function itself.\n */\nexport class OperatorSubscriber extends Subscriber {\n /**\n * Creates an instance of an `OperatorSubscriber`.\n * @param destination The downstream subscriber.\n * @param onNext Handles next values, only called if this subscriber is not stopped or closed. Any\n * error that occurs in this function is caught and sent to the `error` method of this subscriber.\n * @param onError Handles errors from the subscription, any errors that occur in this handler are caught\n * and send to the `destination` error handler.\n * @param onComplete Handles completion notification from the subscription. Any errors that occur in\n * this handler are sent to the `destination` error handler.\n * @param onFinalize Additional finalization logic here. This will only be called on finalization if the\n * subscriber itself is not already closed. This is called after all other finalization logic is executed.\n * @param shouldUnsubscribe An optional check to see if an unsubscribe call should truly unsubscribe.\n * NOTE: This currently **ONLY** exists to support the strange behavior of {@link groupBy}, where unsubscription\n * to the resulting observable does not actually disconnect from the source if there are active subscriptions\n * to any grouped observable. (DO NOT EXPOSE OR USE EXTERNALLY!!!)\n */\n constructor(\n destination: Subscriber,\n onNext?: (value: T) => void,\n onComplete?: () => void,\n onError?: (err: any) => void,\n private onFinalize?: () => void,\n private shouldUnsubscribe?: () => boolean\n ) {\n // It's important - for performance reasons - that all of this class's\n // members are initialized and that they are always initialized in the same\n // order. This will ensure that all OperatorSubscriber instances have the\n // same hidden class in V8. This, in turn, will help keep the number of\n // hidden classes involved in property accesses within the base class as\n // low as possible. If the number of hidden classes involved exceeds four,\n // the property accesses will become megamorphic and performance penalties\n // will be incurred - i.e. inline caches won't be used.\n //\n // The reasons for ensuring all instances have the same hidden class are\n // further discussed in this blog post from Benedikt Meurer:\n // https://benediktmeurer.de/2018/03/23/impact-of-polymorphism-on-component-based-frameworks-like-react/\n super(destination);\n this._next = onNext\n ? function (this: OperatorSubscriber, value: T) {\n try {\n onNext(value);\n } catch (err) {\n destination.error(err);\n }\n }\n : super._next;\n this._error = onError\n ? function (this: OperatorSubscriber, err: any) {\n try {\n onError(err);\n } catch (err) {\n // Send any errors that occur down stream.\n destination.error(err);\n } finally {\n // Ensure finalization.\n this.unsubscribe();\n }\n }\n : super._error;\n this._complete = onComplete\n ? function (this: OperatorSubscriber) {\n try {\n onComplete();\n } catch (err) {\n // Send any errors that occur down stream.\n destination.error(err);\n } finally {\n // Ensure finalization.\n this.unsubscribe();\n }\n }\n : super._complete;\n }\n\n unsubscribe() {\n if (!this.shouldUnsubscribe || this.shouldUnsubscribe()) {\n const { closed } = this;\n super.unsubscribe();\n // Execute additional teardown if we have any and we didn't already do so.\n !closed && this.onFinalize?.();\n }\n }\n}\n", "import { Subscription } from '../Subscription';\n\ninterface AnimationFrameProvider {\n schedule(callback: FrameRequestCallback): Subscription;\n requestAnimationFrame: typeof requestAnimationFrame;\n cancelAnimationFrame: typeof cancelAnimationFrame;\n delegate:\n | {\n requestAnimationFrame: typeof requestAnimationFrame;\n cancelAnimationFrame: typeof cancelAnimationFrame;\n }\n | undefined;\n}\n\nexport const animationFrameProvider: AnimationFrameProvider = {\n // When accessing the delegate, use the variable rather than `this` so that\n // the functions can be called without being bound to the provider.\n schedule(callback) {\n let request = requestAnimationFrame;\n let cancel: typeof cancelAnimationFrame | undefined = cancelAnimationFrame;\n const { delegate } = animationFrameProvider;\n if (delegate) {\n request = delegate.requestAnimationFrame;\n cancel = delegate.cancelAnimationFrame;\n }\n const handle = request((timestamp) => {\n // Clear the cancel function. The request has been fulfilled, so\n // attempting to cancel the request upon unsubscription would be\n // pointless.\n cancel = undefined;\n callback(timestamp);\n });\n return new Subscription(() => cancel?.(handle));\n },\n requestAnimationFrame(...args) {\n const { delegate } = animationFrameProvider;\n return (delegate?.requestAnimationFrame || requestAnimationFrame)(...args);\n },\n cancelAnimationFrame(...args) {\n const { delegate } = animationFrameProvider;\n return (delegate?.cancelAnimationFrame || cancelAnimationFrame)(...args);\n },\n delegate: undefined,\n};\n", "import { createErrorClass } from './createErrorClass';\n\nexport interface ObjectUnsubscribedError extends Error {}\n\nexport interface ObjectUnsubscribedErrorCtor {\n /**\n * @deprecated Internal implementation detail. Do not construct error instances.\n * Cannot be tagged as internal: https://github.com/ReactiveX/rxjs/issues/6269\n */\n new (): ObjectUnsubscribedError;\n}\n\n/**\n * An error thrown when an action is invalid because the object has been\n * unsubscribed.\n *\n * @see {@link Subject}\n * @see {@link BehaviorSubject}\n *\n * @class ObjectUnsubscribedError\n */\nexport const ObjectUnsubscribedError: ObjectUnsubscribedErrorCtor = createErrorClass(\n (_super) =>\n function ObjectUnsubscribedErrorImpl(this: any) {\n _super(this);\n this.name = 'ObjectUnsubscribedError';\n this.message = 'object unsubscribed';\n }\n);\n", "import { Operator } from './Operator';\nimport { Observable } from './Observable';\nimport { Subscriber } from './Subscriber';\nimport { Subscription, EMPTY_SUBSCRIPTION } from './Subscription';\nimport { Observer, SubscriptionLike, TeardownLogic } from './types';\nimport { ObjectUnsubscribedError } from './util/ObjectUnsubscribedError';\nimport { arrRemove } from './util/arrRemove';\nimport { errorContext } from './util/errorContext';\n\n/**\n * A Subject is a special type of Observable that allows values to be\n * multicasted to many Observers. Subjects are like EventEmitters.\n *\n * Every Subject is an Observable and an Observer. You can subscribe to a\n * Subject, and you can call next to feed values as well as error and complete.\n */\nexport class Subject extends Observable implements SubscriptionLike {\n closed = false;\n\n private currentObservers: Observer[] | null = null;\n\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n observers: Observer[] = [];\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n isStopped = false;\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n hasError = false;\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n thrownError: any = null;\n\n /**\n * Creates a \"subject\" by basically gluing an observer to an observable.\n *\n * @nocollapse\n * @deprecated Recommended you do not use. Will be removed at some point in the future. Plans for replacement still under discussion.\n */\n static create: (...args: any[]) => any = (destination: Observer, source: Observable): AnonymousSubject => {\n return new AnonymousSubject(destination, source);\n };\n\n constructor() {\n // NOTE: This must be here to obscure Observable's constructor.\n super();\n }\n\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n lift(operator: Operator): Observable {\n const subject = new AnonymousSubject(this, this);\n subject.operator = operator as any;\n return subject as any;\n }\n\n /** @internal */\n protected _throwIfClosed() {\n if (this.closed) {\n throw new ObjectUnsubscribedError();\n }\n }\n\n next(value: T) {\n errorContext(() => {\n this._throwIfClosed();\n if (!this.isStopped) {\n if (!this.currentObservers) {\n this.currentObservers = Array.from(this.observers);\n }\n for (const observer of this.currentObservers) {\n observer.next(value);\n }\n }\n });\n }\n\n error(err: any) {\n errorContext(() => {\n this._throwIfClosed();\n if (!this.isStopped) {\n this.hasError = this.isStopped = true;\n this.thrownError = err;\n const { observers } = this;\n while (observers.length) {\n observers.shift()!.error(err);\n }\n }\n });\n }\n\n complete() {\n errorContext(() => {\n this._throwIfClosed();\n if (!this.isStopped) {\n this.isStopped = true;\n const { observers } = this;\n while (observers.length) {\n observers.shift()!.complete();\n }\n }\n });\n }\n\n unsubscribe() {\n this.isStopped = this.closed = true;\n this.observers = this.currentObservers = null!;\n }\n\n get observed() {\n return this.observers?.length > 0;\n }\n\n /** @internal */\n protected _trySubscribe(subscriber: Subscriber): TeardownLogic {\n this._throwIfClosed();\n return super._trySubscribe(subscriber);\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n this._throwIfClosed();\n this._checkFinalizedStatuses(subscriber);\n return this._innerSubscribe(subscriber);\n }\n\n /** @internal */\n protected _innerSubscribe(subscriber: Subscriber) {\n const { hasError, isStopped, observers } = this;\n if (hasError || isStopped) {\n return EMPTY_SUBSCRIPTION;\n }\n this.currentObservers = null;\n observers.push(subscriber);\n return new Subscription(() => {\n this.currentObservers = null;\n arrRemove(observers, subscriber);\n });\n }\n\n /** @internal */\n protected _checkFinalizedStatuses(subscriber: Subscriber) {\n const { hasError, thrownError, isStopped } = this;\n if (hasError) {\n subscriber.error(thrownError);\n } else if (isStopped) {\n subscriber.complete();\n }\n }\n\n /**\n * Creates a new Observable with this Subject as the source. You can do this\n * to create custom Observer-side logic of the Subject and conceal it from\n * code that uses the Observable.\n * @return {Observable} Observable that the Subject casts to\n */\n asObservable(): Observable {\n const observable: any = new Observable();\n observable.source = this;\n return observable;\n }\n}\n\n/**\n * @class AnonymousSubject\n */\nexport class AnonymousSubject extends Subject {\n constructor(\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n public destination?: Observer,\n source?: Observable\n ) {\n super();\n this.source = source;\n }\n\n next(value: T) {\n this.destination?.next?.(value);\n }\n\n error(err: any) {\n this.destination?.error?.(err);\n }\n\n complete() {\n this.destination?.complete?.();\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n return this.source?.subscribe(subscriber) ?? EMPTY_SUBSCRIPTION;\n }\n}\n", "import { Subject } from './Subject';\nimport { Subscriber } from './Subscriber';\nimport { Subscription } from './Subscription';\n\n/**\n * A variant of Subject that requires an initial value and emits its current\n * value whenever it is subscribed to.\n *\n * @class BehaviorSubject\n */\nexport class BehaviorSubject extends Subject {\n constructor(private _value: T) {\n super();\n }\n\n get value(): T {\n return this.getValue();\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n const subscription = super._subscribe(subscriber);\n !subscription.closed && subscriber.next(this._value);\n return subscription;\n }\n\n getValue(): T {\n const { hasError, thrownError, _value } = this;\n if (hasError) {\n throw thrownError;\n }\n this._throwIfClosed();\n return _value;\n }\n\n next(value: T): void {\n super.next((this._value = value));\n }\n}\n", "import { TimestampProvider } from '../types';\n\ninterface DateTimestampProvider extends TimestampProvider {\n delegate: TimestampProvider | undefined;\n}\n\nexport const dateTimestampProvider: DateTimestampProvider = {\n now() {\n // Use the variable rather than `this` so that the function can be called\n // without being bound to the provider.\n return (dateTimestampProvider.delegate || Date).now();\n },\n delegate: undefined,\n};\n", "import { Subject } from './Subject';\nimport { TimestampProvider } from './types';\nimport { Subscriber } from './Subscriber';\nimport { Subscription } from './Subscription';\nimport { dateTimestampProvider } from './scheduler/dateTimestampProvider';\n\n/**\n * A variant of {@link Subject} that \"replays\" old values to new subscribers by emitting them when they first subscribe.\n *\n * `ReplaySubject` has an internal buffer that will store a specified number of values that it has observed. Like `Subject`,\n * `ReplaySubject` \"observes\" values by having them passed to its `next` method. When it observes a value, it will store that\n * value for a time determined by the configuration of the `ReplaySubject`, as passed to its constructor.\n *\n * When a new subscriber subscribes to the `ReplaySubject` instance, it will synchronously emit all values in its buffer in\n * a First-In-First-Out (FIFO) manner. The `ReplaySubject` will also complete, if it has observed completion; and it will\n * error if it has observed an error.\n *\n * There are two main configuration items to be concerned with:\n *\n * 1. `bufferSize` - This will determine how many items are stored in the buffer, defaults to infinite.\n * 2. `windowTime` - The amount of time to hold a value in the buffer before removing it from the buffer.\n *\n * Both configurations may exist simultaneously. So if you would like to buffer a maximum of 3 values, as long as the values\n * are less than 2 seconds old, you could do so with a `new ReplaySubject(3, 2000)`.\n *\n * ### Differences with BehaviorSubject\n *\n * `BehaviorSubject` is similar to `new ReplaySubject(1)`, with a couple of exceptions:\n *\n * 1. `BehaviorSubject` comes \"primed\" with a single value upon construction.\n * 2. `ReplaySubject` will replay values, even after observing an error, where `BehaviorSubject` will not.\n *\n * @see {@link Subject}\n * @see {@link BehaviorSubject}\n * @see {@link shareReplay}\n */\nexport class ReplaySubject extends Subject {\n private _buffer: (T | number)[] = [];\n private _infiniteTimeWindow = true;\n\n /**\n * @param bufferSize The size of the buffer to replay on subscription\n * @param windowTime The amount of time the buffered items will stay buffered\n * @param timestampProvider An object with a `now()` method that provides the current timestamp. This is used to\n * calculate the amount of time something has been buffered.\n */\n constructor(\n private _bufferSize = Infinity,\n private _windowTime = Infinity,\n private _timestampProvider: TimestampProvider = dateTimestampProvider\n ) {\n super();\n this._infiniteTimeWindow = _windowTime === Infinity;\n this._bufferSize = Math.max(1, _bufferSize);\n this._windowTime = Math.max(1, _windowTime);\n }\n\n next(value: T): void {\n const { isStopped, _buffer, _infiniteTimeWindow, _timestampProvider, _windowTime } = this;\n if (!isStopped) {\n _buffer.push(value);\n !_infiniteTimeWindow && _buffer.push(_timestampProvider.now() + _windowTime);\n }\n this._trimBuffer();\n super.next(value);\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n this._throwIfClosed();\n this._trimBuffer();\n\n const subscription = this._innerSubscribe(subscriber);\n\n const { _infiniteTimeWindow, _buffer } = this;\n // We use a copy here, so reentrant code does not mutate our array while we're\n // emitting it to a new subscriber.\n const copy = _buffer.slice();\n for (let i = 0; i < copy.length && !subscriber.closed; i += _infiniteTimeWindow ? 1 : 2) {\n subscriber.next(copy[i] as T);\n }\n\n this._checkFinalizedStatuses(subscriber);\n\n return subscription;\n }\n\n private _trimBuffer() {\n const { _bufferSize, _timestampProvider, _buffer, _infiniteTimeWindow } = this;\n // If we don't have an infinite buffer size, and we're over the length,\n // use splice to truncate the old buffer values off. Note that we have to\n // double the size for instances where we're not using an infinite time window\n // because we're storing the values and the timestamps in the same array.\n const adjustedBufferSize = (_infiniteTimeWindow ? 1 : 2) * _bufferSize;\n _bufferSize < Infinity && adjustedBufferSize < _buffer.length && _buffer.splice(0, _buffer.length - adjustedBufferSize);\n\n // Now, if we're not in an infinite time window, remove all values where the time is\n // older than what is allowed.\n if (!_infiniteTimeWindow) {\n const now = _timestampProvider.now();\n let last = 0;\n // Search the array for the first timestamp that isn't expired and\n // truncate the buffer up to that point.\n for (let i = 1; i < _buffer.length && (_buffer[i] as number) <= now; i += 2) {\n last = i;\n }\n last && _buffer.splice(0, last + 1);\n }\n }\n}\n", "import { Scheduler } from '../Scheduler';\nimport { Subscription } from '../Subscription';\nimport { SchedulerAction } from '../types';\n\n/**\n * A unit of work to be executed in a `scheduler`. An action is typically\n * created from within a {@link SchedulerLike} and an RxJS user does not need to concern\n * themselves about creating and manipulating an Action.\n *\n * ```ts\n * class Action extends Subscription {\n * new (scheduler: Scheduler, work: (state?: T) => void);\n * schedule(state?: T, delay: number = 0): Subscription;\n * }\n * ```\n *\n * @class Action\n */\nexport class Action extends Subscription {\n constructor(scheduler: Scheduler, work: (this: SchedulerAction, state?: T) => void) {\n super();\n }\n /**\n * Schedules this action on its parent {@link SchedulerLike} for execution. May be passed\n * some context object, `state`. May happen at some point in the future,\n * according to the `delay` parameter, if specified.\n * @param {T} [state] Some contextual data that the `work` function uses when\n * called by the Scheduler.\n * @param {number} [delay] Time to wait before executing the work, where the\n * time unit is implicit and defined by the Scheduler.\n * @return {void}\n */\n public schedule(state?: T, delay: number = 0): Subscription {\n return this;\n }\n}\n", "import type { TimerHandle } from './timerHandle';\ntype SetIntervalFunction = (handler: () => void, timeout?: number, ...args: any[]) => TimerHandle;\ntype ClearIntervalFunction = (handle: TimerHandle) => void;\n\ninterface IntervalProvider {\n setInterval: SetIntervalFunction;\n clearInterval: ClearIntervalFunction;\n delegate:\n | {\n setInterval: SetIntervalFunction;\n clearInterval: ClearIntervalFunction;\n }\n | undefined;\n}\n\nexport const intervalProvider: IntervalProvider = {\n // When accessing the delegate, use the variable rather than `this` so that\n // the functions can be called without being bound to the provider.\n setInterval(handler: () => void, timeout?: number, ...args) {\n const { delegate } = intervalProvider;\n if (delegate?.setInterval) {\n return delegate.setInterval(handler, timeout, ...args);\n }\n return setInterval(handler, timeout, ...args);\n },\n clearInterval(handle) {\n const { delegate } = intervalProvider;\n return (delegate?.clearInterval || clearInterval)(handle as any);\n },\n delegate: undefined,\n};\n", "import { Action } from './Action';\nimport { SchedulerAction } from '../types';\nimport { Subscription } from '../Subscription';\nimport { AsyncScheduler } from './AsyncScheduler';\nimport { intervalProvider } from './intervalProvider';\nimport { arrRemove } from '../util/arrRemove';\nimport { TimerHandle } from './timerHandle';\n\nexport class AsyncAction extends Action {\n public id: TimerHandle | undefined;\n public state?: T;\n // @ts-ignore: Property has no initializer and is not definitely assigned\n public delay: number;\n protected pending: boolean = false;\n\n constructor(protected scheduler: AsyncScheduler, protected work: (this: SchedulerAction, state?: T) => void) {\n super(scheduler, work);\n }\n\n public schedule(state?: T, delay: number = 0): Subscription {\n if (this.closed) {\n return this;\n }\n\n // Always replace the current state with the new state.\n this.state = state;\n\n const id = this.id;\n const scheduler = this.scheduler;\n\n //\n // Important implementation note:\n //\n // Actions only execute once by default, unless rescheduled from within the\n // scheduled callback. This allows us to implement single and repeat\n // actions via the same code path, without adding API surface area, as well\n // as mimic traditional recursion but across asynchronous boundaries.\n //\n // However, JS runtimes and timers distinguish between intervals achieved by\n // serial `setTimeout` calls vs. a single `setInterval` call. An interval of\n // serial `setTimeout` calls can be individually delayed, which delays\n // scheduling the next `setTimeout`, and so on. `setInterval` attempts to\n // guarantee the interval callback will be invoked more precisely to the\n // interval period, regardless of load.\n //\n // Therefore, we use `setInterval` to schedule single and repeat actions.\n // If the action reschedules itself with the same delay, the interval is not\n // canceled. If the action doesn't reschedule, or reschedules with a\n // different delay, the interval will be canceled after scheduled callback\n // execution.\n //\n if (id != null) {\n this.id = this.recycleAsyncId(scheduler, id, delay);\n }\n\n // Set the pending flag indicating that this action has been scheduled, or\n // has recursively rescheduled itself.\n this.pending = true;\n\n this.delay = delay;\n // If this action has already an async Id, don't request a new one.\n this.id = this.id ?? this.requestAsyncId(scheduler, this.id, delay);\n\n return this;\n }\n\n protected requestAsyncId(scheduler: AsyncScheduler, _id?: TimerHandle, delay: number = 0): TimerHandle {\n return intervalProvider.setInterval(scheduler.flush.bind(scheduler, this), delay);\n }\n\n protected recycleAsyncId(_scheduler: AsyncScheduler, id?: TimerHandle, delay: number | null = 0): TimerHandle | undefined {\n // If this action is rescheduled with the same delay time, don't clear the interval id.\n if (delay != null && this.delay === delay && this.pending === false) {\n return id;\n }\n // Otherwise, if the action's delay time is different from the current delay,\n // or the action has been rescheduled before it's executed, clear the interval id\n if (id != null) {\n intervalProvider.clearInterval(id);\n }\n\n return undefined;\n }\n\n /**\n * Immediately executes this action and the `work` it contains.\n * @return {any}\n */\n public execute(state: T, delay: number): any {\n if (this.closed) {\n return new Error('executing a cancelled action');\n }\n\n this.pending = false;\n const error = this._execute(state, delay);\n if (error) {\n return error;\n } else if (this.pending === false && this.id != null) {\n // Dequeue if the action didn't reschedule itself. Don't call\n // unsubscribe(), because the action could reschedule later.\n // For example:\n // ```\n // scheduler.schedule(function doWork(counter) {\n // /* ... I'm a busy worker bee ... */\n // var originalAction = this;\n // /* wait 100ms before rescheduling the action */\n // setTimeout(function () {\n // originalAction.schedule(counter + 1);\n // }, 100);\n // }, 1000);\n // ```\n this.id = this.recycleAsyncId(this.scheduler, this.id, null);\n }\n }\n\n protected _execute(state: T, _delay: number): any {\n let errored: boolean = false;\n let errorValue: any;\n try {\n this.work(state);\n } catch (e) {\n errored = true;\n // HACK: Since code elsewhere is relying on the \"truthiness\" of the\n // return here, we can't have it return \"\" or 0 or false.\n // TODO: Clean this up when we refactor schedulers mid-version-8 or so.\n errorValue = e ? e : new Error('Scheduled action threw falsy error');\n }\n if (errored) {\n this.unsubscribe();\n return errorValue;\n }\n }\n\n unsubscribe() {\n if (!this.closed) {\n const { id, scheduler } = this;\n const { actions } = scheduler;\n\n this.work = this.state = this.scheduler = null!;\n this.pending = false;\n\n arrRemove(actions, this);\n if (id != null) {\n this.id = this.recycleAsyncId(scheduler, id, null);\n }\n\n this.delay = null!;\n super.unsubscribe();\n }\n }\n}\n", "import { Action } from './scheduler/Action';\nimport { Subscription } from './Subscription';\nimport { SchedulerLike, SchedulerAction } from './types';\nimport { dateTimestampProvider } from './scheduler/dateTimestampProvider';\n\n/**\n * An execution context and a data structure to order tasks and schedule their\n * execution. Provides a notion of (potentially virtual) time, through the\n * `now()` getter method.\n *\n * Each unit of work in a Scheduler is called an `Action`.\n *\n * ```ts\n * class Scheduler {\n * now(): number;\n * schedule(work, delay?, state?): Subscription;\n * }\n * ```\n *\n * @class Scheduler\n * @deprecated Scheduler is an internal implementation detail of RxJS, and\n * should not be used directly. Rather, create your own class and implement\n * {@link SchedulerLike}. Will be made internal in v8.\n */\nexport class Scheduler implements SchedulerLike {\n public static now: () => number = dateTimestampProvider.now;\n\n constructor(private schedulerActionCtor: typeof Action, now: () => number = Scheduler.now) {\n this.now = now;\n }\n\n /**\n * A getter method that returns a number representing the current time\n * (at the time this function was called) according to the scheduler's own\n * internal clock.\n * @return {number} A number that represents the current time. May or may not\n * have a relation to wall-clock time. May or may not refer to a time unit\n * (e.g. milliseconds).\n */\n public now: () => number;\n\n /**\n * Schedules a function, `work`, for execution. May happen at some point in\n * the future, according to the `delay` parameter, if specified. May be passed\n * some context object, `state`, which will be passed to the `work` function.\n *\n * The given arguments will be processed an stored as an Action object in a\n * queue of actions.\n *\n * @param {function(state: ?T): ?Subscription} work A function representing a\n * task, or some unit of work to be executed by the Scheduler.\n * @param {number} [delay] Time to wait before executing the work, where the\n * time unit is implicit and defined by the Scheduler itself.\n * @param {T} [state] Some contextual data that the `work` function uses when\n * called by the Scheduler.\n * @return {Subscription} A subscription in order to be able to unsubscribe\n * the scheduled work.\n */\n public schedule(work: (this: SchedulerAction, state?: T) => void, delay: number = 0, state?: T): Subscription {\n return new this.schedulerActionCtor(this, work).schedule(state, delay);\n }\n}\n", "import { Scheduler } from '../Scheduler';\nimport { Action } from './Action';\nimport { AsyncAction } from './AsyncAction';\nimport { TimerHandle } from './timerHandle';\n\nexport class AsyncScheduler extends Scheduler {\n public actions: Array> = [];\n /**\n * A flag to indicate whether the Scheduler is currently executing a batch of\n * queued actions.\n * @type {boolean}\n * @internal\n */\n public _active: boolean = false;\n /**\n * An internal ID used to track the latest asynchronous task such as those\n * coming from `setTimeout`, `setInterval`, `requestAnimationFrame`, and\n * others.\n * @type {any}\n * @internal\n */\n public _scheduled: TimerHandle | undefined;\n\n constructor(SchedulerAction: typeof Action, now: () => number = Scheduler.now) {\n super(SchedulerAction, now);\n }\n\n public flush(action: AsyncAction): void {\n const { actions } = this;\n\n if (this._active) {\n actions.push(action);\n return;\n }\n\n let error: any;\n this._active = true;\n\n do {\n if ((error = action.execute(action.state, action.delay))) {\n break;\n }\n } while ((action = actions.shift()!)); // exhaust the scheduler queue\n\n this._active = false;\n\n if (error) {\n while ((action = actions.shift()!)) {\n action.unsubscribe();\n }\n throw error;\n }\n }\n}\n", "import { AsyncAction } from './AsyncAction';\nimport { AsyncScheduler } from './AsyncScheduler';\n\n/**\n *\n * Async Scheduler\n *\n * Schedule task as if you used setTimeout(task, duration)\n *\n * `async` scheduler schedules tasks asynchronously, by putting them on the JavaScript\n * event loop queue. It is best used to delay tasks in time or to schedule tasks repeating\n * in intervals.\n *\n * If you just want to \"defer\" task, that is to perform it right after currently\n * executing synchronous code ends (commonly achieved by `setTimeout(deferredTask, 0)`),\n * better choice will be the {@link asapScheduler} scheduler.\n *\n * ## Examples\n * Use async scheduler to delay task\n * ```ts\n * import { asyncScheduler } from 'rxjs';\n *\n * const task = () => console.log('it works!');\n *\n * asyncScheduler.schedule(task, 2000);\n *\n * // After 2 seconds logs:\n * // \"it works!\"\n * ```\n *\n * Use async scheduler to repeat task in intervals\n * ```ts\n * import { asyncScheduler } from 'rxjs';\n *\n * function task(state) {\n * console.log(state);\n * this.schedule(state + 1, 1000); // `this` references currently executing Action,\n * // which we reschedule with new state and delay\n * }\n *\n * asyncScheduler.schedule(task, 3000, 0);\n *\n * // Logs:\n * // 0 after 3s\n * // 1 after 4s\n * // 2 after 5s\n * // 3 after 6s\n * ```\n */\n\nexport const asyncScheduler = new AsyncScheduler(AsyncAction);\n\n/**\n * @deprecated Renamed to {@link asyncScheduler}. Will be removed in v8.\n */\nexport const async = asyncScheduler;\n", "import { AsyncAction } from './AsyncAction';\nimport { Subscription } from '../Subscription';\nimport { QueueScheduler } from './QueueScheduler';\nimport { SchedulerAction } from '../types';\nimport { TimerHandle } from './timerHandle';\n\nexport class QueueAction extends AsyncAction {\n constructor(protected scheduler: QueueScheduler, protected work: (this: SchedulerAction, state?: T) => void) {\n super(scheduler, work);\n }\n\n public schedule(state?: T, delay: number = 0): Subscription {\n if (delay > 0) {\n return super.schedule(state, delay);\n }\n this.delay = delay;\n this.state = state;\n this.scheduler.flush(this);\n return this;\n }\n\n public execute(state: T, delay: number): any {\n return delay > 0 || this.closed ? super.execute(state, delay) : this._execute(state, delay);\n }\n\n protected requestAsyncId(scheduler: QueueScheduler, id?: TimerHandle, delay: number = 0): TimerHandle {\n // If delay exists and is greater than 0, or if the delay is null (the\n // action wasn't rescheduled) but was originally scheduled as an async\n // action, then recycle as an async action.\n\n if ((delay != null && delay > 0) || (delay == null && this.delay > 0)) {\n return super.requestAsyncId(scheduler, id, delay);\n }\n\n // Otherwise flush the scheduler starting with this action.\n scheduler.flush(this);\n\n // HACK: In the past, this was returning `void`. However, `void` isn't a valid\n // `TimerHandle`, and generally the return value here isn't really used. So the\n // compromise is to return `0` which is both \"falsy\" and a valid `TimerHandle`,\n // as opposed to refactoring every other instanceo of `requestAsyncId`.\n return 0;\n }\n}\n", "import { AsyncScheduler } from './AsyncScheduler';\n\nexport class QueueScheduler extends AsyncScheduler {\n}\n", "import { QueueAction } from './QueueAction';\nimport { QueueScheduler } from './QueueScheduler';\n\n/**\n *\n * Queue Scheduler\n *\n * Put every next task on a queue, instead of executing it immediately\n *\n * `queue` scheduler, when used with delay, behaves the same as {@link asyncScheduler} scheduler.\n *\n * When used without delay, it schedules given task synchronously - executes it right when\n * it is scheduled. However when called recursively, that is when inside the scheduled task,\n * another task is scheduled with queue scheduler, instead of executing immediately as well,\n * that task will be put on a queue and wait for current one to finish.\n *\n * This means that when you execute task with `queue` scheduler, you are sure it will end\n * before any other task scheduled with that scheduler will start.\n *\n * ## Examples\n * Schedule recursively first, then do something\n * ```ts\n * import { queueScheduler } from 'rxjs';\n *\n * queueScheduler.schedule(() => {\n * queueScheduler.schedule(() => console.log('second')); // will not happen now, but will be put on a queue\n *\n * console.log('first');\n * });\n *\n * // Logs:\n * // \"first\"\n * // \"second\"\n * ```\n *\n * Reschedule itself recursively\n * ```ts\n * import { queueScheduler } from 'rxjs';\n *\n * queueScheduler.schedule(function(state) {\n * if (state !== 0) {\n * console.log('before', state);\n * this.schedule(state - 1); // `this` references currently executing Action,\n * // which we reschedule with new state\n * console.log('after', state);\n * }\n * }, 0, 3);\n *\n * // In scheduler that runs recursively, you would expect:\n * // \"before\", 3\n * // \"before\", 2\n * // \"before\", 1\n * // \"after\", 1\n * // \"after\", 2\n * // \"after\", 3\n *\n * // But with queue it logs:\n * // \"before\", 3\n * // \"after\", 3\n * // \"before\", 2\n * // \"after\", 2\n * // \"before\", 1\n * // \"after\", 1\n * ```\n */\n\nexport const queueScheduler = new QueueScheduler(QueueAction);\n\n/**\n * @deprecated Renamed to {@link queueScheduler}. Will be removed in v8.\n */\nexport const queue = queueScheduler;\n", "import { AsyncAction } from './AsyncAction';\nimport { AnimationFrameScheduler } from './AnimationFrameScheduler';\nimport { SchedulerAction } from '../types';\nimport { animationFrameProvider } from './animationFrameProvider';\nimport { TimerHandle } from './timerHandle';\n\nexport class AnimationFrameAction extends AsyncAction {\n constructor(protected scheduler: AnimationFrameScheduler, protected work: (this: SchedulerAction, state?: T) => void) {\n super(scheduler, work);\n }\n\n protected requestAsyncId(scheduler: AnimationFrameScheduler, id?: TimerHandle, delay: number = 0): TimerHandle {\n // If delay is greater than 0, request as an async action.\n if (delay !== null && delay > 0) {\n return super.requestAsyncId(scheduler, id, delay);\n }\n // Push the action to the end of the scheduler queue.\n scheduler.actions.push(this);\n // If an animation frame has already been requested, don't request another\n // one. If an animation frame hasn't been requested yet, request one. Return\n // the current animation frame request id.\n return scheduler._scheduled || (scheduler._scheduled = animationFrameProvider.requestAnimationFrame(() => scheduler.flush(undefined)));\n }\n\n protected recycleAsyncId(scheduler: AnimationFrameScheduler, id?: TimerHandle, delay: number = 0): TimerHandle | undefined {\n // If delay exists and is greater than 0, or if the delay is null (the\n // action wasn't rescheduled) but was originally scheduled as an async\n // action, then recycle as an async action.\n if (delay != null ? delay > 0 : this.delay > 0) {\n return super.recycleAsyncId(scheduler, id, delay);\n }\n // If the scheduler queue has no remaining actions with the same async id,\n // cancel the requested animation frame and set the scheduled flag to\n // undefined so the next AnimationFrameAction will request its own.\n const { actions } = scheduler;\n if (id != null && actions[actions.length - 1]?.id !== id) {\n animationFrameProvider.cancelAnimationFrame(id as number);\n scheduler._scheduled = undefined;\n }\n // Return undefined so the action knows to request a new async id if it's rescheduled.\n return undefined;\n }\n}\n", "import { AsyncAction } from './AsyncAction';\nimport { AsyncScheduler } from './AsyncScheduler';\n\nexport class AnimationFrameScheduler extends AsyncScheduler {\n public flush(action?: AsyncAction): void {\n this._active = true;\n // The async id that effects a call to flush is stored in _scheduled.\n // Before executing an action, it's necessary to check the action's async\n // id to determine whether it's supposed to be executed in the current\n // flush.\n // Previous implementations of this method used a count to determine this,\n // but that was unsound, as actions that are unsubscribed - i.e. cancelled -\n // are removed from the actions array and that can shift actions that are\n // scheduled to be executed in a subsequent flush into positions at which\n // they are executed within the current flush.\n const flushId = this._scheduled;\n this._scheduled = undefined;\n\n const { actions } = this;\n let error: any;\n action = action || actions.shift()!;\n\n do {\n if ((error = action.execute(action.state, action.delay))) {\n break;\n }\n } while ((action = actions[0]) && action.id === flushId && actions.shift());\n\n this._active = false;\n\n if (error) {\n while ((action = actions[0]) && action.id === flushId && actions.shift()) {\n action.unsubscribe();\n }\n throw error;\n }\n }\n}\n", "import { AnimationFrameAction } from './AnimationFrameAction';\nimport { AnimationFrameScheduler } from './AnimationFrameScheduler';\n\n/**\n *\n * Animation Frame Scheduler\n *\n * Perform task when `window.requestAnimationFrame` would fire\n *\n * When `animationFrame` scheduler is used with delay, it will fall back to {@link asyncScheduler} scheduler\n * behaviour.\n *\n * Without delay, `animationFrame` scheduler can be used to create smooth browser animations.\n * It makes sure scheduled task will happen just before next browser content repaint,\n * thus performing animations as efficiently as possible.\n *\n * ## Example\n * Schedule div height animation\n * ```ts\n * // html:
\n * import { animationFrameScheduler } from 'rxjs';\n *\n * const div = document.querySelector('div');\n *\n * animationFrameScheduler.schedule(function(height) {\n * div.style.height = height + \"px\";\n *\n * this.schedule(height + 1); // `this` references currently executing Action,\n * // which we reschedule with new state\n * }, 0, 0);\n *\n * // You will see a div element growing in height\n * ```\n */\n\nexport const animationFrameScheduler = new AnimationFrameScheduler(AnimationFrameAction);\n\n/**\n * @deprecated Renamed to {@link animationFrameScheduler}. Will be removed in v8.\n */\nexport const animationFrame = animationFrameScheduler;\n", "import { Observable } from '../Observable';\nimport { SchedulerLike } from '../types';\n\n/**\n * A simple Observable that emits no items to the Observer and immediately\n * emits a complete notification.\n *\n * Just emits 'complete', and nothing else.\n *\n * ![](empty.png)\n *\n * A simple Observable that only emits the complete notification. It can be used\n * for composing with other Observables, such as in a {@link mergeMap}.\n *\n * ## Examples\n *\n * Log complete notification\n *\n * ```ts\n * import { EMPTY } from 'rxjs';\n *\n * EMPTY.subscribe({\n * next: () => console.log('Next'),\n * complete: () => console.log('Complete!')\n * });\n *\n * // Outputs\n * // Complete!\n * ```\n *\n * Emit the number 7, then complete\n *\n * ```ts\n * import { EMPTY, startWith } from 'rxjs';\n *\n * const result = EMPTY.pipe(startWith(7));\n * result.subscribe(x => console.log(x));\n *\n * // Outputs\n * // 7\n * ```\n *\n * Map and flatten only odd numbers to the sequence `'a'`, `'b'`, `'c'`\n *\n * ```ts\n * import { interval, mergeMap, of, EMPTY } from 'rxjs';\n *\n * const interval$ = interval(1000);\n * const result = interval$.pipe(\n * mergeMap(x => x % 2 === 1 ? of('a', 'b', 'c') : EMPTY),\n * );\n * result.subscribe(x => console.log(x));\n *\n * // Results in the following to the console:\n * // x is equal to the count on the interval, e.g. (0, 1, 2, 3, ...)\n * // x will occur every 1000ms\n * // if x % 2 is equal to 1, print a, b, c (each on its own)\n * // if x % 2 is not equal to 1, nothing will be output\n * ```\n *\n * @see {@link Observable}\n * @see {@link NEVER}\n * @see {@link of}\n * @see {@link throwError}\n */\nexport const EMPTY = new Observable((subscriber) => subscriber.complete());\n\n/**\n * @param scheduler A {@link SchedulerLike} to use for scheduling\n * the emission of the complete notification.\n * @deprecated Replaced with the {@link EMPTY} constant or {@link scheduled} (e.g. `scheduled([], scheduler)`). Will be removed in v8.\n */\nexport function empty(scheduler?: SchedulerLike) {\n return scheduler ? emptyScheduled(scheduler) : EMPTY;\n}\n\nfunction emptyScheduled(scheduler: SchedulerLike) {\n return new Observable((subscriber) => scheduler.schedule(() => subscriber.complete()));\n}\n", "import { SchedulerLike } from '../types';\nimport { isFunction } from './isFunction';\n\nexport function isScheduler(value: any): value is SchedulerLike {\n return value && isFunction(value.schedule);\n}\n", "import { SchedulerLike } from '../types';\nimport { isFunction } from './isFunction';\nimport { isScheduler } from './isScheduler';\n\nfunction last(arr: T[]): T | undefined {\n return arr[arr.length - 1];\n}\n\nexport function popResultSelector(args: any[]): ((...args: unknown[]) => unknown) | undefined {\n return isFunction(last(args)) ? args.pop() : undefined;\n}\n\nexport function popScheduler(args: any[]): SchedulerLike | undefined {\n return isScheduler(last(args)) ? args.pop() : undefined;\n}\n\nexport function popNumber(args: any[], defaultValue: number): number {\n return typeof last(args) === 'number' ? args.pop()! : defaultValue;\n}\n", "export const isArrayLike = ((x: any): x is ArrayLike => x && typeof x.length === 'number' && typeof x !== 'function');", "import { isFunction } from \"./isFunction\";\n\n/**\n * Tests to see if the object is \"thennable\".\n * @param value the object to test\n */\nexport function isPromise(value: any): value is PromiseLike {\n return isFunction(value?.then);\n}\n", "import { InteropObservable } from '../types';\nimport { observable as Symbol_observable } from '../symbol/observable';\nimport { isFunction } from './isFunction';\n\n/** Identifies an input as being Observable (but not necessary an Rx Observable) */\nexport function isInteropObservable(input: any): input is InteropObservable {\n return isFunction(input[Symbol_observable]);\n}\n", "import { isFunction } from './isFunction';\n\nexport function isAsyncIterable(obj: any): obj is AsyncIterable {\n return Symbol.asyncIterator && isFunction(obj?.[Symbol.asyncIterator]);\n}\n", "/**\n * Creates the TypeError to throw if an invalid object is passed to `from` or `scheduled`.\n * @param input The object that was passed.\n */\nexport function createInvalidObservableTypeError(input: any) {\n // TODO: We should create error codes that can be looked up, so this can be less verbose.\n return new TypeError(\n `You provided ${\n input !== null && typeof input === 'object' ? 'an invalid object' : `'${input}'`\n } where a stream was expected. You can provide an Observable, Promise, ReadableStream, Array, AsyncIterable, or Iterable.`\n );\n}\n", "export function getSymbolIterator(): symbol {\n if (typeof Symbol !== 'function' || !Symbol.iterator) {\n return '@@iterator' as any;\n }\n\n return Symbol.iterator;\n}\n\nexport const iterator = getSymbolIterator();\n", "import { iterator as Symbol_iterator } from '../symbol/iterator';\nimport { isFunction } from './isFunction';\n\n/** Identifies an input as being an Iterable */\nexport function isIterable(input: any): input is Iterable {\n return isFunction(input?.[Symbol_iterator]);\n}\n", "import { ReadableStreamLike } from '../types';\nimport { isFunction } from './isFunction';\n\nexport async function* readableStreamLikeToAsyncGenerator(readableStream: ReadableStreamLike): AsyncGenerator {\n const reader = readableStream.getReader();\n try {\n while (true) {\n const { value, done } = await reader.read();\n if (done) {\n return;\n }\n yield value!;\n }\n } finally {\n reader.releaseLock();\n }\n}\n\nexport function isReadableStreamLike(obj: any): obj is ReadableStreamLike {\n // We don't want to use instanceof checks because they would return\n // false for instances from another Realm, like an