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pytorch/test
Kim Juhyeong 89c844db9b [torch.distributions] Implement positive-semidefinite constraint (#71375)
Summary:
While implementing https://github.com/pytorch/pytorch/issues/70275, I thought that it will be useful if there is a `torch.distributions.constraints` to check the positive-semidefiniteness of matrix random variables.
This PR implements it with `torch.linalg.eigvalsh`, different from `torch.distributions.constraints.positive_definite` implemented with `torch.linalg.cholesky_ex`.
Currently, `torch.linalg.cholesky_ex` returns only the order of the leading minor that is not positive-definite in symmetric matrices and we can't check positive semi-definiteness by the mechanism.
cc neerajprad

Pull Request resolved: https://github.com/pytorch/pytorch/pull/71375

Reviewed By: H-Huang

Differential Revision: D33663990

Pulled By: neerajprad

fbshipit-source-id: 02cefbb595a1da5e54a239d4f17b33c619416518
(cherry picked from commit 43eaea5bd861714f234e9efc1a7fb571631298f4)
2022-01-20 17:33:08 +00:00
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