Yeah that’s one way to get softmax output.
But there is problem.
I want to use this loss function.
criterion = nn.CrossEntropyLoss().cuda()
outputs = model(input)
softmax_output = probs(outputs)
loss = criterion(softmax_output , labels)  ?? 

Then the loss is like nn.Softmax(nn.logsoftmax(outputs)), right?
Because nn.CrossEntropyLoss() will apply logsoftmax itself.
What should I do?
Thank you.