Introduce PyTorch DataPipes #173
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This pull request has been linked to Shortcut Story #19597: Investigate iterable-style DataPipes for Pytorch. |
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| schema.kind is not TensorKind.DENSE for schema in schemas | ||
| ): | ||
| raise NotImplementedError("https://github.com/pytorch/pytorch/issues/20248") | ||
| datapipe_for_key_range = partial(_get_datapipe, schemas) |
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Comments & docstrings added at a93e675
This was referenced Aug 19, 2022
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This PR introduces torchdata, a PyTorch library of common modular data loading primitives for easily constructing flexible and performant data pipelines, as opposed to a custom monolithic
IterableDatasetsubclass.Currently the main practical benefit is related to shuffling:
_iter_shuffledfunction with the Shuffler datapipe.In the future we might consider exposing the composed
IterDataPipein addition to (or instead of) theDataLoader, so that for example the user can apply a mapping datapipe before passing it to theDataLoader.