Fill eigenvector with zeros if not required#10645
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I think it would be nice to have a test for this. |
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li-roy
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Should we consider adding python wrapper and just returning a single Tensor in the eigenvectors=False case? Other than that, lgtm.
| resv2 = torch.randn(3, 3) | ||
| cov = cov.cuda() | ||
| rese2 = torch.zeros(3).cuda() | ||
| resv2 = torch.randn(3, 3).cuda() |
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@pytorchbot retest this please |
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@pytorchbot retest this please |
Summary: Fix #10345, which only happens in CUDA case. * Instead of returning some random buffer, we fill it with zeros. * update torch.symeig doc. Pull Request resolved: pytorch/pytorch#10645 Reviewed By: soumith Differential Revision: D9395762 Pulled By: ailzhang fbshipit-source-id: 0f3ed9bb6a919a9c1a4b8eb45188f65a68bfa9ba
Summary: Fix pytorch#10345, which only happens in CUDA case. * Instead of returning some random buffer, we fill it with zeros. * update torch.symeig doc. Pull Request resolved: pytorch#10645 Reviewed By: soumith Differential Revision: D9395762 Pulled By: ailzhang fbshipit-source-id: 0f3ed9bb6a919a9c1a4b8eb45188f65a68bfa9ba
Summary: Fix pytorch#10345, which only happens in CUDA case. * Instead of returning some random buffer, we fill it with zeros. * update torch.symeig doc. Pull Request resolved: pytorch#10645 Reviewed By: soumith Differential Revision: D9395762 Pulled By: ailzhang fbshipit-source-id: 0f3ed9bb6a919a9c1a4b8eb45188f65a68bfa9ba
Fix #10345, which only happens in CUDA case.
Instead of returning some random buffer, we fill it with zeros.
update torch.symeig doc.