mindspore.mint.bitwise_and

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mindspore.mint.bitwise_and(input, other)[source]

Returns bitwise and of two tensors element-wise.

\[out_i = input_{i} \wedge other_{i}\]

Note

Args of input and other comply with the implicit type conversion rules to make the data types consistent. If they have different data types, the lower precision data type will be converted to the relatively highest precision data type.

Parameters

  • input (Tensor) – The input tensor.

  • other (Tensor, Number.number) – The input tensor or scalar. It has the same shape with input or its shape is able to broadcast with input.

Returns

Tensor, the shape is the same as the one after broadcasting, and the data type is same as input.

Supported Platforms:

Ascend

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor, mint
>>> input = Tensor(np.array([0, 0, 1, -1, 1, 1, 1]), mindspore.int16)
>>> other = Tensor(np.array([0, 1, 1, -1, -1, 2, 3]), mindspore.int16)
>>> output = mint.bitwise_and(input, other)
>>> print(output)
[ 0  0  1 -1  1  0  1]