of course, I added print in there to ensure everything correct
I just try to replace cross_entropy with nll_loss and refactor forward function, but why it returns another loss value (but still wrong value)
    def forward(self, x):
        x = self.model(x)

        return F.log_softmax(x)

I have similar implementation in Tensorflow, so I know how loss value drop if doing correctly