Update torch_patch.py

[S163669]

Removed the PositiveDefinite() function for the one from PyTorch to be used instead, as the way of checking was less precise than the one from PyTorch resulting in errors for certain cases.

More details can be found here on the Pyro forum:
https://forum.pyro.ai/t/positive-definiteness-error-due-to-import-of-pyro/4887/5

[fehiepsi]

Thanks @S163669!

[fehiepsi]

@S163669 Probably the test failing is due to this line. Could you try to see if changing it to

dist.MultivariateNormal(mu, scale_tril=scale_tril)

fixes the issues?

[S163669]

@fehiepsi It should be good now :)

[fehiepsi]

@S163669 could you merge the dev branch? It includes some fixes to make tests pass for the changes here.

[S163669]

@fehiepsi I just did :)

[fehiepsi]

@S163669 Looks like that the additional symmetric check of the upstream PositiveDefinite constraint is making GP tutorial failing. Could you add torch.set_default_tensor_type(torch.DoubleTensor) at the end of the first cell of that tutorial?

[review-notebook-app]

Check out this pull request on 

See visual diffs & provide feedback on Jupyter Notebooks.

---

Powered by ReviewNB

[S163669]

@fehiepsi Yes, it's done.

[fehiepsi]

Sorry, I didn't run the tutorial until the end to catch all errors. Could you update the cell 27 to

X = torch.from_numpy(
    df[df.columns[2:4]].values.astype("float64"),
)

We need to use float64 numpy array after setting DoubleTensor. Thanks!

[S163669]

No worries @fehiepsi . It is changed now!

[fehiepsi]

Thanks, @S163669!