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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.

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- 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

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

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mindspore.ops.nan_to_num

mindspore.ops.nan_to_num(input, nan=None, 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.

Warning

For Ascend, it is only supported on Atlas A2 Training Series Products. This is an experimental API that is subject to change or deletion.

Parameters

input (Tensor) – The shape of tensor is $(i n p u t_{1}, i n p u t_{2}, . . ., i n p u t_{R})$ .
nan (number, optional) – The replace value of NaN. Default value is None.
posinf (number, optional) – 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 (number, optional) – 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.

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]