Trouble running code with CovarianceMatrix(sqrt=True)

Merry Christmas @jankrepl

I am having trouble running code with:

```
cov_layer = CovarianceMatrix(sqrt=True)
...
covmat_sqrt = cov_layer(rets)
```

I was wondering if this would be an equivalent replacement?:

```
cov_layer = CovarianceMatrix(sqrt=False)
...
covmat_sqrt = torch.sqrt(cov_layer(rets))
```
------------------------------------------------------------------------------------------------------------------------

Just in case you were curious, the error I was getting with `CovarianceMatrix(sqrt=True):`

> rets has NAN
warnings.warn('rets has NAN')
....
Intel MKL ERROR: Parameter 4 was incorrect on entry to SLASCL.
....
/deepdow/layers/misc.py", line 162, in compute_sqrt
_, s, v = m.svd()
RuntimeError: svd_cuda: the updating process of SBDSDC did not converge (error: 16)

However, when I checked `rets` before passing into `cov_layer` with `assert torch.all(torch.isnan(rets))`, no assert error occured.

Start at deepdow/layers/misc.py around compute_sqrt (line 162) and inspect the CovarianceMatrix(sqrt=True) path using the provided rets example. Reproduce the NaN warning and CUDA SVD failure, then determine the supported behavior for this input and whether the proposed torch.sqrt replacement is valid. Done means a confirmed diagnosis with a regression test or clear usage guidance.

Written by the indexing model from the issue text.