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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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mindspore.ops.isfinite

mindspore.ops.isfinite(x)

Determines which elements are finite for each position.

$$\begin{array}{r}ou{t}_i=\{\begin{array}{ll}& \text{ if }{x}_i=\text{Finite},True\\ & \text{ if }{x}_i\ne \text{Finite},False\end{array}\end{array}$$

Parameters

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

Returns

Tensor, has the same shape of input, and the dtype is bool.

Raises

TypeError – If x is not a Tensor.

Supported Platforms:

Ascend GPU CPU

Examples

>>> x = Tensor(np.array([np.log(-1), 1, np.log(0)]), mindspore.float32)
>>> output = ops.isfinite(x)
>>> print(output)
[False  True False]