mindspore.numpy.logical_and(x1, x2, dtype=None)[source]

Computes the truth value of x1 AND x2 element-wise.


Numpy arguments out, where, casting, order, subok, signature, and extobj are not supported.

  • 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.


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


>>> import mindspore.numpy as np
>>> x1 = np.array([True, False])
>>> x2 = np.array([False, False])
>>> output = np.logical_and(x1, x2)
>>> print(output)
[False False]