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mindspore.Tensor.logical_xor

Tensor.logical_xor(other) → Tensor

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

$$ou{t}_i=sel{f}_i\oplus othe{r}_i$$

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