Computing gradients on sparse matrix eigensolves

Hi, does anyone have any suggestions for computing gradients on an eigensolve of a sparse matrix.

The lobpcg function does not support this, the documentation explicitly mentions that the backward method is not supported for sparse inputs (torch.lobpcg — PyTorch 2.0 documentation).

Thanks!