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Quite a few things fail because some operations are not yet supported on MPS. They either raise a NotImplementedError, which we now catch, or they raise a warning, which is not so convenient to catch (still need to fix those cases). See pytorch/pytorch#141287 for the status of this on PyTorch side. Also, in some cases, we get small numerical errors that make the test fail. Lastly, some ConFIG tests seem to fail by a large margin. |
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A bit too much work required for this ATM because quite a lot of necessary operations are still not available on MPS. We should work again on that in ~1 or 2 years I think. Archiving the branch and cherry-picking 32aab4f. |
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There are three main goals with this PR:
device=...are properly tested throughout torchjd. Forgetting one of them is the most likely cause of error that would not be caught when testing only on CPU when developing new things. Since this is the same for MPS and cuda, it basically fixes half of the problem of not running the CI on GPU. (The other half is that some device-specific function could behave differently or not even exist on some device, which would make the tests fail if we run them on this device. We cannot test that without running on these device types.)