Should I use softmax as output when using cross entropy loss in pytorch?

Question

I have a problem with classifying fully connected deep neural net with 2 hidden layers for MNIST dataset in pytorch.

I want to use tanh

Answer 1

As stated in the torch.nn.CrossEntropyLoss() doc:

This criterion combines nn.LogSoftmax() and nn.NLLLoss() in one single class.

Therefore, you should not use softmax before.