Hi,
I think this is mostly expected, my understanding is that:

When you do tensor + array, then the sum op from pytorch is used and we do not support adding a numpy array to a Tensor, you should use torch.from_numpy() to get a Tensor first.
When you do array + tensor, then numpy’s sum op is used and they seem to be doing weird things when given a tensor: like moving it to cpu then returning another tensor? Not sure why though you would need to check numpy’s code.