Hello

Im wonder why NLLLoss doesn’t change when using [2,2] weights in example below?

There is really incomplete documentation related to details of calculations.

```
log_prob = torch.tensor([[0.1, 0.5],
[0.8, 0.8],
[0.8, 0.1]])
target = torch.tensor([0, 0, 1])
weight = torch.tensor([2.0, 2.0])
criterion = nn.NLLLoss()
criterion_weighted = nn.NLLLoss(weight=weight)
print('NLLLoss = {}'.format(criterion(log_prob, target)))
#NLLLoss = -0.3333333432674408
print('Weighted NLLLoss = {}'.format(criterion_weighted(log_prob, target)))
#Weighted NLLLoss = -0.3333333432674408
print('Manualy calculated weighted NLLLoss = {}'.format((-2*np.log(0.1) - 2*np.log(0.8) - 2*np.log(0.1)) / (3 * 4)))
Manualy calculated weighted NLLLoss = 0.8047189562170501
```

I guess there is some mistakes in my manual calculations. Any suggestion how can I calculate weighted NLLLoss manuall?