I noticed CrossEntropyLoss now has an ignore_index parameter, but I am not sure I understand what that means:
ignore_index (int, optional): Specifies a target value that is ignored
            and does not contribute to the input gradient. When size_average is
            True, the loss is averaged over non-ignored targets.

First of all, I know that CrossEntropyLoss takes a 1-dimensional array of targets:
Target: :math:`(N)` where each value is `0 <= targets[i] <= C-1`

So then I assume that ignore_index allows you to ignore one of the outputs in the loss calculation. I can imagine it’s useful to mask a whole bunch of outputs. Simply ignoring only one output node,what is the use-case of that?
I probably misunderstood what ignore_index does or when do people use it?