For my task, I do not need to compute gradients. I am simply replacing `nn.L1Loss`

with a numpy function (`corrcoef`

) in my loss evaluation but I get the following error:

RuntimeError: Can’t call numpy() on Variable that requires grad. Use var.detach().numpy() instead.

I couldn’t figure out how exactly I should detach the graph (I tried `torch.Tensor.detach(np.corrcoef(x, y))`

but I still get the same error. I eventually wrapped everything using `with torch.no_grad`

as follow:

```
with torch.no_grad():
predFeats = self.forward(x)
targetFeats = self.forward(target)
loss = torch.from_numpy(np.corrcoef(predFeats.cpu().numpy().astype(np.float32), targetFeats.cpu().numpy().astype(np.float32))[1][1])
```

But this time I get the following error:

TypeError: expected np.ndarray (got numpy.float64)

I wonder, what am I doing wrong?