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Specifications and Common Mistakes

- Specifications and Common Mistakes:

- Misspellings or punctuation mistakes,incorrect formulas, abnormal display.

- Incorrect links, empty cells, or wrong formats.

- Chinese characters in English context.

- Minor inconsistencies between the UI and descriptions.

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- Incorrect version numbers, including software package names and version numbers on the UI.

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- Incorrect code.

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Problem description

Describe the bug so that we can quickly locate the problem.

mindspore.mint.bitwise_or

View Source On Gitee
mindspore.mint.bitwise_or(input, other)[source]

Returns bitwise or of two tensors element-wise.

outi=inputiotheri

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_or(input, other)
>>> print(output)
[ 0  1  1 -1 -1  3  3]