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Hi Joakim, When training on 10shot, I am facing with warnings like the below:
WARNING batched routines are designed for small sizes. It might be better to use the Native/Hybrid classical routines if you want good performance.
I think this warning comes from the torch.linalg.cholesky(K_ss), when K_ss's largest size() > 2048.
May I know how you deal with this warning during training? Thanks in advance!
The text was updated successfully, but these errors were encountered:
Hey,
Unfortunately, we have no simple fix that removes the warning. It seems to stem from a package, magma, that is called by PyTorch.
Best regards, Joakim
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@ry-jojo You can do a for-loop instead. Not sure about the performance loss/gains.
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Hi Joakim,
When training on 10shot, I am facing with warnings like the below:
WARNING batched routines are designed for small sizes. It might be better to use the
Native/Hybrid classical routines if you want good performance.
I think this warning comes from the torch.linalg.cholesky(K_ss), when K_ss's largest size() > 2048.
May I know how you deal with this warning during training? Thanks in advance!
The text was updated successfully, but these errors were encountered: