Avoid using skip() in hf_datasets #835
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This was referenced Feb 12, 2025
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| if isinstance(self._data, Dataset) and self._sample_idx == len(self._data): | ||
| return iter([]) | ||
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| return iter(self._data.skip(self._sample_idx)) |
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two questions:
- The wrong behavior is not captured by unit test https://github.com/pytorch/torchtitan/blob/main/tests/unit_tests/test_dataset_checkpointing.py. Is it because the error only happens in distributed environment, on some rank but not others?
- Does skip fail for both map-style datasets (
c4_test) and IterableDatasets (c4)? Asking because from my PR uniformly use skip for both (map-style) Dataset and IterableDataset #521 I recallskipfor IterableDataset is a "new" feature.
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I am working on testing loss issue(whether still happens) and whether difference between datasets c4/c4_test right now.
unit_test would be the next PR after fix.
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- It only happens in distributed environment and on certain ranks only.
- I could not reproduce this with
c4_test.
I don't know the detail of the root cause though.
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I would not land this PR but I verified all ranks output the expected sample even after resuming from checkpoints, @mori360 would work on loss parity with unittest verifcation.
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We found out that skip() may not behave as expected. This is a workaround solution while we are investiging the root cause. ghstack-source-id: 412810bc4a83de39df3fdfe62bc249d80c7deb19 Pull Request resolved: #835
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Stack from ghstack (oldest at bottom):
We found out that skip() may not behave as expected. This is a workaround solution while we are investiging the root cause.