from documentation here : http://pytorch.org/docs/master/nn.html#torch.nn.LogSoftmax 330, log-softmax is defined as:
f(x)=log(softmax(x))

as I know, using log in probabilities will change the high-low value, so biggest value in softmax(x) will be the smallest value in log(softmax(x)).
Will it change the way Negative Log Likelihood compute loss when it implements it together in CrossEntropy?