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SequentialReadingService

class torchdata.dataloader2.SequentialReadingService(*reading_services)
checkpoint() bytes

ReadingService serializes the internal states. Called in DataLoader2.state_dict.

finalize() None

ReadingService cleans up internal states and fully shuts down the service. Called in DataLoader2’s shutdown and __del__.

finalize_iteration() None

ReadingService ends service after an epoch is finished. Called when the iterator of DataLoader2 is depleted.

initialize(datapipe: Union[IterDataPipe, MapDataPipe]) Union[IterDataPipe, MapDataPipe]

ReadingService takes a DataPipe graph, adapts it into a new DataPipe graph based on the custom need. Called once in creating DataLoader2 iterator at first time. Prior to calling this method, the ReadingService object must be picklable.

Parameters:

datapipe – Original DataPipe graph.

Returns:

An adapted or a new DataPipe graph.

initialize_iteration(seed_generator: SeedGenerator, iter_reset_fn: Optional[Callable[[Union[IterDataPipe, MapDataPipe]], Union[IterDataPipe, MapDataPipe]]] = None) Optional[Callable[[Union[IterDataPipe, MapDataPipe]], Union[IterDataPipe, MapDataPipe]]]

ReadingService spins up service for an epoch. Called at the beginning of every time getting DataLoader2 iterator.

Parameters:
  • seed_generator – SeedGenerator object created and managed by DataLoader2. As the single source of randomness, it will govern the determinism for all of random operations with the graph of DataPipes.

  • iter_reset_fn – Optional reset function from the prior ReadingServcie when SequentialReadingService chains multiple ReadingServices

Returns:

A new iter_reset_fn to be used by subseqeuent ReadingService

Example

MultiProcessingReadingService starts setting worker seeds per process and prefetching items from the graph.

restore(datapipe, serialized_state: bytes) Union[IterDataPipe, MapDataPipe]

ReadingService adapts DataPipe graph based on the serialized state. Called once in creating DataLoader2 iterator at first time. Counterpart of initialize, which adapt DataPipe graph from scratch.

Parameters:
  • datapipe – original DataPipe graph before adapted by ReadingService

  • serialized_state – The serialized state of internal state used to restore the state of the adapted DataPipe graph.

Returns:

Adapted DataPipe generated from the serialized state.

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