Is -log_softmax the same as NLLLoss applied on log_softmax, and if so why is a separate function required ?
No, you won’t get the same result.
nn.NLLLoss calculates the loss value by reducing the log probability for each sample using the target index.
log_softmax will just calculate the log probabilities for the complete tensor in the specified dimension.
The reduction type can be specified and is the mean by default.
So in the default use case, nn.NLLLoss will return a single loss value, while the output tensor of log_softmax will have the same shape as the input tensor.
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