8000 Flaky Dynamo test: TestAutograd.test_gradcheck_nondeterministic · Issue #145231 · pytorch/pytorch · GitHub
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Flaky Dynamo test: TestAutograd.test_gradcheck_nondeterministic #145231

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ya 8000 nboliang opened this issue Jan 21, 2025 · 0 comments
Open

Flaky Dynamo test: TestAutograd.test_gradcheck_nondeterministic #145231

yanboliang opened this issue Jan 21, 2025 · 0 comments
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module: autograd Related to torch.autograd, and the autograd engine in general module: testing Issues related to the torch.testing module (not tests) oncall: pt2 triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module

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yanboliang commented Jan 21, 2025 •
edited by pytorch-bot bot
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🐛 Describe the bug

Reproduce command:

PYTORCH_TEST_WITH_DYNAMO=1 python test/test_autograd.py TestAutograd.test_gradcheck_nondeterministic

This issue was discovered while I was working on #142830. The core problem is that this unit test produces different results on CI compared to running it locally. The test passes in the main branch, but if I remove the assertRaisesRegex assertion (#145205), the test still passes locally but fails on CI. I suspect that even though it currently passes on CI, it’s likely coincidental.

After making changes in #142830, this test began failing. However, I’ve been unable to reproduce the failure locally.

There is a similar flaky test marked at #127115.

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cc @ezyang @albanD @gqchen @pearu @nikitaved @soulitzer @Varal7 @xmfan @chauhang @penguinwu
@malfet malfet added module: autograd Related to torch.autograd, and the autograd engine in general module: testing Issues related to the torch.testing module (not tests) oncall: pt2 labels Jan 21, 2025
@eellison eellison added the triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module label Jan 21, 2025
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module: autograd Related to torch.autograd, and the autograd engine in general module: testing Issues related to the torch.testing module (not tests) oncall: pt2 triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module
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