Relax cudnn conditions for channels-last convolutions #38904
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💊 CI failures summary and remediationsAs of commit 870b169 (more details on the Dr. CI page): 💚 💚 Looks good so far! There are no failures yet. 💚 💚 This comment was automatically generated by Dr. CI (expand for details).Follow this link to opt-out of these comments for your Pull Requests.Please report bugs/suggestions on the GitHub issue tracker or post in the (internal) Dr. CI Users group. This comment has been revised 34 times. |
ptrblck
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test/test_nn.py
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| self.assertEqual(out, ref_out, rtol=0.001, atol=0.001) | ||
| self.assertEqual(conv.weight.grad, ref_conv.weight.grad, rtol=0.001, atol=0.001) | ||
| self.assertEqual(conv.bias.grad, ref_conv.bias.grad, rtol=0.001, atol=0.001) | ||
| self.assertEqual(input.grad, ref_input.grad, rtol=0.001, atol=0.001) |
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Could we use the dtype_precisions from here for the check?
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@ngimel @VitalyFedyunin This should be ready for review. |
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@VitalyFedyunin merged this pull request in 17d3f74. |
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Follow up of #38044. Thanks @ptrblck, @mcarilli for the help on discussing the changes!
Could fix #37725 by skipping the depthwise-workload check introduced in #22302. This PR also relaxed dilated convolution for channels-last.
The testing script is https://gist.github.com/xwang233/82a707f69bb710cb612349280a2c5f41. About 387k conv arguments were tested and no cudnn exception was thrown.
cc @ngimel @VitalyFedyunin @ptrblck @mcarilli