The following code really confuses me , the `cond = n < beta`

is never true, However when I do backward pass input grad is `NaN`

, I believe this is because `0.5 * n**2 / beta`

, I would like to know how is this possible ? Thanks

```
>>> import torch
>>> torch.__version__
'1.8.0+cpu'
>>> input = torch.tensor([[-0.6205, 0.225],[-0.8916, 0.4492]], requires_grad = True)
>>> target = torch.tensor([[-0.6205, 0.225],[-0.8916, 0.4492]])
>>> beta = 0
>>> n = torch.abs(input - target)
#Since input == target so the cond is never true.
>>> cond = n < beta
>>> loss = torch.where(cond, 0.5 * n**2 / beta, n - 0.5 * beta)
>>> loss = loss.sum()
>>> loss.backward()
>>> input.grad
tensor([[nan, nan],
[nan, nan]])
```