Thanks for helping, I’d be happy to.
Targets tensor size: [10000 x 1000] So the shape of each is (1000,) as a 1-hot vector.
I want to reduce the tensor to [10000 x 100] where the 1 is redistributed to the correct overlapping bin.
As probably the real question, are there any loss functions that consider proximity of classes within the loss? So if the correct target class is N in range [0, C-1], it could consider a classification of N-1 or N+1 partially correct?