Document feedback

Question document fragment

When a question document fragment contains a formula, it is displayed as a space.

Submission type

issue

It's a little complicated...

I'd like to ask someone.

Please select the submission type

Problem type

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.

- Low writing fluency that does not affect understanding.

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

Usability

- Usability:

- Incorrect or missing key steps.

- Missing main function descriptions, keyword explanation, necessary prerequisites, or precautions.

- Ambiguous descriptions, unclear reference, or contradictory context.

- Unclear logic, such as missing classifications, items, and steps.

Correctness

- Correctness:

- Technical principles, function descriptions, supported platforms, parameter types, or exceptions inconsistent with that of software implementation.

- Incorrect schematic or architecture diagrams.

- Incorrect commands or command parameters.

- Incorrect code.

- Commands inconsistent with the functions.

- Wrong screenshots.

- Sample code running error, or running results inconsistent with the expectation.

Risk Warnings

- Risk Warnings:

- Lack of risk warnings for operations that may damage the system or important data.

Content Compliance

- Content Compliance:

- Contents that may violate applicable laws and regulations or geo-cultural context-sensitive words and expressions.

- Copyright infringement.

Please select the type of question

Problem description

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

Submit

Document feedback

mindspore.Tensor.logical_and

Tensor.logical_and(other) → Tensor

Computes the "logical AND" of two tensors element-wise.

$$ou{t}_i=sel{f}_i\wedge othe{r}_i$$

Note

• Inputs of self and other comply with the implicit type conversion rules to make the data types consistent.

• When the other is bool, it could only be a constant.

Inputs:

• other (Union[Tensor, bool]) - A bool or a tensor whose data type can be implicitly converted to bool.

Outputs:

Tensor, the shape is the same as that of self and other after broadcasting, and the data type is bool.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor
>>> x = Tensor(np.array([True, False, True]), mindspore.bool_)
>>> other = Tensor(np.array([True, True, False]), mindspore.bool_)
>>> output = x.logical_and(other)
>>> print(output)
[ True False False]
>>> x = Tensor(1, mindspore.bool_)
>>> other = Tensor(0, mindspore.bool_)
>>> output = x.logical_and(other)
>>> print(output)
False