mindspore.Tensor.logical_xor

Tensor.logical_xor(other) → Tensor[source]

Computes the "logical XOR" of two tensors element-wise.

\[out_{i} = self_{i} \oplus other_{i}\]

Note

self and other comply with the type conversion rules to make the data types consistent.
When the other is bool, it could only be a constant.

Parameters:: other (Union[Tensor, bool]) – A bool or a tensor whose data type can be implicitly converted to bool.
Returns:: Tensor, the shape is the same as the self and other after broadcasting, and the data type is bool.

Supported Platforms:: Ascend CPU

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor
>>> input = Tensor(np.array([True, False, True]), mindspore.bool)
>>> other = Tensor(np.array([True, True, False]), mindspore.bool)
>>> output = input.logical_xor(other)
>>> print(output)
[ False True True]
>>> x = Tensor(1, mindspore.bool)
>>> other = Tensor(0, mindspore.bool)
>>> output = input.logical_xor(other)
>>> print(output)
True