Hi @ptrblck,
I would be glad for your approach of stacking one-hot tensors to have the same dimension. For example. I have x1 = torch.randint(0, 2, size=(1, 3, 3)) ->
tensor([[[0, 1, 1],
[0, 1, 0],
[0, 1, 1]]])
and x2 = tensor([[[1, 0, 0],
[1, 0, 1],
[1, 0, 0]]])
I want to have x3 = tensor([[[1, 1, 1],
[1, 1, 1],
[1, 1, 1]]]).
And how can I have x2 using pytorch function?