Added linalg.eig, linalg.eigvals (#52491)
Summary:
This PR adds `torch.linalg.eig`, and `torch.linalg.eigvals` for NumPy compatibility.
MAGMA uses a hybrid CPU-GPU algorithm and doesn't have a GPU interface for the non-symmetric eigendecomposition. It means that it forces us to transfer inputs living in GPU memory to CPU first before calling MAGMA, and then transfer results from MAGMA to CPU. That is rather slow for smaller matrices and MAGMA is faster than CPU path only for matrices larger than 3000x3000.
Unfortunately, there is no cuSOLVER function for this operation.
Autograd support for `torch.linalg.eig` will be added in a follow-up PR.
Ref https://github.com/pytorch/pytorch/issues/42666
Pull Request resolved: https://github.com/pytorch/pytorch/pull/52491
Reviewed By: anjali411
Differential Revision: D27563616
Pulled By: mruberry
fbshipit-source-id: b42bb98afcd2ed7625d30bdd71cfc74a7ea57bb5
