Torch.norm when p=2 doesn't give largest singular value as expected

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 ]