Hello,

I have a question about how autograd handles Nans,

```
a = torch.tensor([np.nan, 2])
param = torch.tensor([1.], requires_grad=True)
(a * param)[1].backward()
print(param.grad) # yields tensor([nan])
```

I was expecting it to return `tensor([2])`

since param grad is independent of the `a[0]`

Is this normal behavior ? Is there a way to force autograd to ignore `nan`

if the grad is independent of that value ?

Thank you for your answer.