The documentation isn’t clear. Is y supposed to be a binary vector, i.e.
[0, 0, 1, 1]
for classes 2 and 3, or a vector of classes, i.e.
[2,3,0,0]
for classes 2 and 3?
For MultiLabelSoftMarginLoss it is clear, but for this one is isn’t.
Have you figured it out? I’m confused about it too.
I was searching the same stuff. To me, it seems the y should be something like:
for a task, each sample can have at most 3 labels:
[0,0,1] ---> y = [2,-1,-1]
[1,0,1] ---> y = [0, 2,-1]
[0,1,1] ---> y = [1, 2,-1]
y includes the index of the target labels, and padded with negative values if num of labels is less than 3(in this example).
Note: I haven’t tested this.
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