Updating dataset code to avoid creating multiple iterators from a DataPipe #1708
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NivekT
commented
May 10, 2022
| cache_decompressed_dp = cache_decompressed_dp.end_caching(mode="wb", same_filepath_fn=True) | ||
| cache_decompressed_dp_1, cache_decompressed_dp_2 = cache_decompressed_dp.fork(num_instances=2) |
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The recommended pattern is to use fork when you need the same DataPipe for multiple usages later.
| @@ -125,7 +125,7 @@ | |||
| # avoid additional conditional imports. | |||
| def _filter_clean_cache(cache_decompressed_dp, full_filepath, uncleaned_filename): | |||
| cache_inner_decompressed_dp = cache_decompressed_dp.on_disk_cache(filepath_fn=lambda x: full_filepath) | |||
| cache_inner_decompressed_dp = FileOpener(cache_inner_decompressed_dp, mode="b").load_from_tar() | |||
| cache_inner_decompressed_dp = cache_inner_decompressed_dp.open_files(mode="b").load_from_tar() | |||
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FYI, we recently added .open_files as the functional form of FileOpener
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We will be introducing a change in
torch/torchdatato prevent users from creating multiple iterators from a single DataPipe. In order to not break anything when it lands, this PR update certain DataPipe use cases to avoid creating multiple iterators from a DataPipe. This should not impact any functionality.Let me know if there are usages of DataPipes outside of
torchtext/datasets.