Intel GPU: specify the tolerance for torchbench models #125213
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/125213
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (1 Unrelated Failure)As of commit 000d2cf with merge base 8320b77 ( FLAKY - The following job failed but was likely due to flakiness present on trunk:
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We encountered some model accuracy failures as the tolerance is critical. In general, we align with CUDA practice. This PR intends to adjust the tolerance for Torchbench models for training mode on Intel GPU devices and aligns with CUDA. Pull Request resolved: pytorch#125213 Approved by: https://github.com/desertfire
andoorve
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We encountered some model accuracy failures as the tolerance is critical. In general, we align with CUDA practice. This PR intends to adjust the tolerance for Torchbench models for training mode on Intel GPU devices and aligns with CUDA. Pull Request resolved: pytorch#125213 Approved by: https://github.com/desertfire
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Summary: We encountered some model accuracy failures as the tolerance is critical. In general, we align with CUDA practice. This PR intends to adjust the tolerance for Torchbench models for training mode on Intel GPU devices and aligns with CUDA. X-link: pytorch/pytorch#125213 Approved by: https://github.com/desertfire Reviewed By: kit1980 Differential Revision: D56862220 fbshipit-source-id: a773ff0162da3bcac91834876c5ab0335c03ed53
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We encountered some model accuracy failures as the tolerance is critical. In general, we align with CUDA practice. This PR intends to adjust the tolerance for Torchbench models for training mode on Intel GPU devices and aligns with CUDA. Pull Request resolved: #125213 Approved by: https://github.com/desertfire
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We encountered some model accuracy failures as the tolerance is critical. In general, we align with CUDA practice. This PR intends to adjust the tolerance for Torchbench models for training mode on Intel GPU devices and aligns with CUDA.
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