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.. automodule:: torchdata.stateful_dataloader
StatefulDataLoader is a drop-in replacement for torch.utils.data.DataLoader which offers state_dict / load_state_dict methods for handling mid-epoch checkpointing which operate on the previous/next iterator requested from the dataloader (resp.).
By default, the state includes the number of batches yielded and uses this to naively fast-forward the sampler (map-style) or the dataset (iterable-style). However if the sampler and/or dataset include state_dict / load_state_dict methods, then it will call them during its own state_dict / load_state_dict calls. Under the hood, :class:`StatefulDataLoader` handles aggregation and distribution of state across multiprocess workers (but not across ranks).
.. autoclass:: StatefulDataLoader
:members: