mindspore.ops.logical_xor
- mindspore.ops.logical_xor(input, other)[source]
Computes the "logical XOR" of two tensors element-wise.
\[out_{i} = input_{i} \oplus other_{i}\]- Parameters
- Returns
Tensor, the shape is the same as the one after broadcasting, and the data type is bool.
- Raises
TypeError – If the dtype of input or other is not bool or can not be implicitly converted to bool.
ValueError – If the shape of two inputs cannot be broadcast.
- Supported Platforms:
Ascend
CPU
Examples
>>> import mindspore >>> import numpy as np >>> from mindspore import Tensor, ops >>> x = Tensor(np.array([True, False, True]), mindspore.bool_) >>> y = Tensor(np.array([True, True, False]), mindspore.bool_) >>> output = ops.logical_xor(x, y) >>> print(output) [False True True] >>> x = Tensor(1, mindspore.bool_) >>> y = Tensor(0, mindspore.bool_) >>> output = ops.logical_xor(x, y) >>> print(output) True >>> x = True >>> y = Tensor(0, mindspore.bool_) >>> output = ops.logical_xor(x, y) >>> print(output) True >>> x = True >>> y = Tensor(np.array([True, False]), mindspore.bool_) >>> output = ops.logical_xor(x, y) >>> print(output) [False True]