I’m comparing the results of NLLLoss and CrossEntropyLoss and I don’t understand why the loss for NLLLoss is negative compared to CrossEntropyLoss with the same inputs.

```
import torch.nn as nn
import torch
label = torch.tensor([3, 0, 1, 1, 4])
output = torch.tensor([[0.5073, 0.4838, 0.5053, 0.4839, 0.5183],
[0.5072, 0.4849, 0.4933, 0.4809, 0.5148],
[0.5020, 0.4836, 0.5021, 0.4829, 0.5162],
[0.5023, 0.4801, 0.4994, 0.4805, 0.5174],
[0.5024, 0.4899, 0.4932, 0.4835, 0.5148]])
criterion = nn.NLLLoss()
loss = criterion(output, label)
loss
tensor(-0.4939)
criterion = nn.CrossEntropyLoss()
loss = criterion(output, label)
loss
tensor(1.6128)
```