I have a set of ID labels from 0…24 that encodes 19 classes and I want basically to have a 1 hot encoding of them: if I use :
target = torch.sparse.torch.eye(19).index_select(dim=0, index=target)
I get index out of range which I completely understand since some labels are 24 (but the number of total classes is 19), strange but the data set is built this way., and if I use:
targets=torch.nn.functional.one_hot(targets)
I get a tensor of 18 columns instead of 19, does anyone knows how to solve this?
even if I set nbr classes to 19 this still blocks due to the fact that some labels are 24  but refers to another lower class
Thanks in advance.