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OpInfo: nn.functional.conv2d #63517
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OpInfo: nn.functional.conv2d #63517
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💊 CI failures summary and remediationsAs of commit 78287a1 (more details on the Dr. CI page): ✅ None of the CI failures appear to be your fault 💚
❄️ 1 failure tentatively classified as flakybut reruns have not yet been triggered to confirm:
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Gentle Ping @zou3519 |
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Gentle ping @zou3519 :) |
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Thanks for the ping and sorry for the delay! Will review later today |
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This looks great! I added some suggestions for more test cases. Because conv2d is one of PyTorch's most important ops (and also very complicated in terms of what it can call in the backend), we should try to add more test cases especially following existing test cases in common_nn.py
Codecov Report
@@ Coverage Diff @@
## master #63517 +/- ##
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+ Coverage 66.39% 66.48% +0.08%
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Files 725 725
Lines 93461 93473 +12
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+ Hits 62055 62141 +86
+ Misses 31406 31332 -74 |
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Some minor comments, but otherwise, this LGTM
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@zou3519 has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator. |
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Sorry, this appears to have broken trunk so I am reverting. |
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You can view the related failures here: https://hud.pytorch.org/commit/873255c6d95342d144e9d1b633c16410844b934e |
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This pull request has been reverted by ecfc784. |
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@kshitij12345 could you send a new PR for this please? The error message implies that the backward is non-deterministic, but I'm not sure if that is true (need to think about it for a little bit...) |
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Yes, convolution is deterministic so we want to add a |
Summary: Reland : #63517 Reference: #54261 Reference: pytorch/functorch#78 Pull Request resolved: #65233 Reviewed By: malfet Differential Revision: D31025538 Pulled By: zou3519 fbshipit-source-id: b1cd38c22f4cb8eedd3f958e02dd7410dcbb8d8d
Reference: #54261
Reference: pytorch/functorch#78
Mostly inspired from #62882