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.

Document feedback

mindspore.ops.nan_to_num

mindspore.ops.nan_to_num(input, nan=0.0, posinf=None, neginf=None)[source]

Replace the NaN, positive infinity and negative infinity values in ‘input’ with the specified values in nan, posinf and neginf respectively.

Parameters

input (Tensor) – The shape of tensor is $(i n p u t_{1}, i n p u t_{2}, . . ., i n p u t_{R})$ . With float32 or float16 data type.
nan (float) – The replace value of ‘NaN’. Default value is 0.0.
posinf (float) – the value to replace positive infinity values with. Default: None, replacing positive infinity with the maximum value supported by the data type of input.
neginf (float) – the value to replace negative infinity values with. Default: None, replacing negative infinity with the minimum value supported by the data type of input.

Returns

Tensor, has the same shape and dtype as the input.

Raises

TypeError – If input is not a Tensor.
TypeError – If dtype of input is not float16 or float32.

Supported Platforms:: Ascend CPU

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor, ops
>>> input = Tensor(np.array([float('nan'), float('inf'), -float('inf'), 5.0]), mindspore.float32)
>>> output = ops.nan_to_num(input, 1.0, 2.0, 3.0)
>>> print(output)
[1.  2.  3.  5.0]