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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.

- 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.

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Problem description

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

sponge.function.reduce_any

View Source On Gitee
sponge.function.reduce_any(x: Tensor, axis: Union[int, Tuple[int], List[int]] = ())[source]

Reduces a dimension of a tensor by the "logical OR" of all elements in the dimension, by default. And also can reduce a dimension of x along the axis. See mindspore.ops.ReduceAny for detailed information.

Parameters
  • x (Tensor[bool]) – The input tensor. The dtype of the tensor to be reduced is bool. (N,) where means, any number of additional dimensions, its rank should be less than 8.

  • axis (Union[int, tuple(int), list(int)]) – The dimensions to reduce. Default: (), reduce all dimensions. Only constant value is allowed. Must be in the range [-rank(x), rank(x)).

Outputs:

Tensor, the dtype is bool.

Supported Platforms:

Ascend GPU CPU