composer.core.types#

Reference for common types used throughout our library.

TODO: This attributes list is incomplete.

composer.core.types.Model#

Alias for torch.nn.Module.

Type: Module

composer.core.types.ModelParameters#

Type alias for model parameters used to initialize optimizers.

Type: Iterable[Tensor] | Iterable[Dict[str, Tensor]]

composer.core.types.Tensors#

Commonly used to represent e.g. a set of inputs, where it is unclear whether each input has its own tensor, or if all the inputs are concatenated in a single tensor.

Type: Tensor | Tuple[Tensor, …] | List[Tensor]

composer.core.types.Batch#

Union type covering the most common representations of batches. A batch of data can be represented in several formats, depending on the application.

Type: BatchPair | BatchDict | Tensor

composer.core.types.BatchPair#

Commonly used in computer vision tasks. The object is assumed to contain exactly two elements, where the first represents inputs and the second represents targets.

Type: Tuple[Tensors, Tensors] | List[Tensor]

composer.core.types.BatchDict#

Commonly used in natural language processing tasks.

Type: Dict[str, Tensor]

composer.core.types.Metrics#

Union type covering common formats for representing metrics.

Type: Metric | MetricCollection

composer.core.types.Optimizer[source]#

Alias for torch.optim.Optimizer

Type: Optimizer

composer.core.types.Optimizers#

Union type for indeterminate amounts of optimizers.

Type: Optimizer | List[Optimizer] | Tuple[Optimizer, …]

composer.core.types.Scheduler#

Alias for torch.optim.lr_scheduler._LRScheduler

Type: Optimizer

composer.core.types.Schedulers#

Union type for indeterminate amounts of schedulers.

Type: Scheduler | List[Scheduler] | Tuple[Scheduler, …]

composer.core.types.Scaler#

Alias for torch.cuda.amp.grad_scaler.GradScaler.

Type: torch.cuda.amp.grad_scaler.GradScaler

composer.core.types.JSON#

JSON Data

Type: str | float | int | None | List[’JSON’] | Dict[str, ’JSON’]

Functions

`as_batch_dict`	Casts a `Batch` as a `BatchDict`.
`as_batch_pair`	Casts a `Batch` as a `BatchPair`.

Classes

`Algorithm`	Base class for algorithms.
`DataLoader`	Protocol for custom DataLoaders compatible with `torch.utils.data.DataLoader`.
`DataSpec`	Specifications for operating and training on data.
`Evaluator`	Wrapper for a dataloader to include metrics that apply to a specific dataset.
`Event`	Enum to represent events in the training loop.
`Logger`	Logger routes metrics to the `LoggerCallback`.
`MemoryFormat`	An enumeration.
`Metric`	Base class for all metrics present in the Metrics API.
`MetricCollection`	MetricCollection class can be used to chain metrics that have the same call pattern into one single class.
`Module`	Base class for all neural network modules.
`Optimizer`	Base class for all optimizers.
`Precision`	Enum class for the numerical precision to be used by the model.
`Protocol`	Base class for protocol classes.
`GradScaler`	composer.core.types.torch.cuda.amp.grad_scaler.GradScaler
`_LRScheduler`	composer.core.types.torch.optim.lr_scheduler._LRScheduler
`Serializable`	Interface for serialization; used by checkpointing.
`State`	The state of the trainer.
`StringEnum`	Base class for Enums containing string values.
`Tensor`	composer.core.types.torch.Tensor
`TypeVar`	Type variable.