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Specifications and Common Mistakes

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mindspore.ops.bitwise_and

mindspore.ops.bitwise_and(input, other)

Returns bitwise and of two tensors element-wise.

$$ou{t}_i=inpu{t}_i\wedge othe{r}_i$$

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 priority data type will be converted to the relatively highest priority data type.

Parameters

• input (Tensor) – The first input tensor with shape $(N,\ast )$ where $\ast$ means any number of additional dimensions.

• other (Tensor) – The second input tensor with the same dtype as input.

Returns

Tensor, has the same type as the input.

Raises

TypeError – If input or other is not a Tensor.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor, ops
>>> 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 = ops.bitwise_and(input, other)
>>> print(output)
[ 0  0  1 -1  1  0  1]