Hi fellows,
I need to improve torch.symeig() 166 in the following directions and like to get hints on where to start and how to do these:

I need to make it more stable, like torch.svd(). I don’t know why svd function is more stable (maybe related to Issue #440 18).
I need to implement a batch version of it on GPU. That means the input will be of size (B x D x D) where B is the batch size.
I need to be able to implement top-k decomposition like scipy.linalg.eigh 18. For example, I should be compute only the top (dominant) eigenvalue and eigenvector.

Any hint about where to start is appreciated.