From my understanding, torch.norm when p=2 should give the spectral norm, i.e. largest singular value of a matrix:

```
A = torch.eye(2)
norm = torch.norm(A, p=2)
```

The singular values of `A`

are of course 1 and 1, and so the max s.v. should also be 1. But the returned value `norm`

is sqrt(2) which is the Frobenius norm.

I’ve also tried various values of `dim`

to no avail.

[**Update**: It looks like this is a high priority issue https://github.com/pytorch/pytorch/issues/24802 ]