Improve error message and reduce validation in autocast test #7547
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Signed-off-by: Masahiro Tanaka <[email protected]>
Signed-off-by: Masahiro Tanaka <[email protected]>
stas00
reviewed
Sep 4, 2025
Signed-off-by: Masahiro Tanaka <[email protected]>
Signed-off-by: Masahiro Tanaka <[email protected]>
stas00
reviewed
Sep 5, 2025
Flakes342
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to Flakes342/DeepSpeed
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this pull request
Sep 9, 2025
…edai#7547) This PR improves error logging and relaxes loss value checks in the autocast test. Previously, the test displayed error messages and mismatched loss values on all ranks, even if the mismatch only occurred on some ranks. This was confusing, since logs from other ranks could appear correct. This PR changes the behavior so that error messages are shown only on the ranks where the mismatch occurs. Additionally, this PR skips loss value validation for `test_lower_precision_model`, where we intentionally use a different communication dtype from the baseline (standard PyTorch autocast). --------- Signed-off-by: Masahiro Tanaka <[email protected]> Co-authored-by: Stas Bekman <[email protected]> Signed-off-by: Flakes342 <[email protected]>
mauryaavinash95
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to DataStates/DeepSpeed
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this pull request
Oct 4, 2025
…edai#7547) This PR improves error logging and relaxes loss value checks in the autocast test. Previously, the test displayed error messages and mismatched loss values on all ranks, even if the mismatch only occurred on some ranks. This was confusing, since logs from other ranks could appear correct. This PR changes the behavior so that error messages are shown only on the ranks where the mismatch occurs. Additionally, this PR skips loss value validation for `test_lower_precision_model`, where we intentionally use a different communication dtype from the baseline (standard PyTorch autocast). --------- Signed-off-by: Masahiro Tanaka <[email protected]> Co-authored-by: Stas Bekman <[email protected]>
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This PR improves error logging and relaxes loss value checks in the autocast test.
Previously, the test displayed error messages and mismatched loss values on all ranks, even if the mismatch only occurred on some ranks. This was confusing, since logs from other ranks could appear correct. This PR changes the behavior so that error messages are shown only on the ranks where the mismatch occurs.
Additionally, this PR skips loss value validation for
test_lower_precision_model, where we intentionally use a different communication dtype from the baseline (standard PyTorch autocast).