mindspore.numpy.logical_xor
- mindspore.numpy.logical_xor(x1, x2, dtype=None)[source]
Computes the truth value of x1 XOR x2, element-wise.
Note
Numpy arguments out, where, casting, order, subok, signature, and extobj are not supported.
- Parameters
x1 (Tensor) – Input tensor.
x2 (Tensor) – Input tensor. If
x1.shape != x2.shape
, they must be broadcastable to a common shape (which becomes the shape of the output).dtype (
mindspore.dtype
, optional) – defaults to None. Overrides the dtype of the output Tensor.
- Returns
Tensor or scalar. Boolean result of the logical AND operation applied to the elements of x1 and x2; the shape is determined by broadcasting. This is a scalar if both x1 and x2 are scalars.
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> import mindspore.numpy as np >>> x1 = np.array([True, False]) >>> x2 = np.array([False, False]) >>> output = np.logical_xor(x1, x2) >>> print(output) [True False]