Computes the element-wise logical XOR of the given input tensors. Zeros are treated as False and nonzeros are treated as True.
>>> torch.logical_xor(torch.tensor([True, False, True]), torch.tensor([True, False, False])) tensor([False, False, True]) >>> a = torch.tensor([0, 1, 10, 0], dtype=torch.int8) >>> b = torch.tensor([4, 0, 1, 0], dtype=torch.int8) >>> torch.logical_xor(a, b) tensor([ True, True, False, False]) >>> torch.logical_xor(a.double(), b.double()) tensor([ True, True, False, False]) >>> torch.logical_xor(a.double(), b) tensor([ True, True, False, False]) >>> torch.logical_xor(a, b, out=torch.empty(4, dtype=torch.bool)) tensor([ True, True, False, False])
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