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.mint.nn.functional.log_softmax

mindspore.mint.nn.functional.log_softmax(input, dim=None, *, dtype=None)

Applies the Log Softmax function to the input tensor on the specified axis. Supposes a slice in the given axis, $x$ for each element $x_i$, the Log Softmax function is shown as follows:

$$\text{output}(x_i)=\log \left(\frac{\exp (x_i)}{\sum _{j=0}^{N-1}\exp (x_j)}\right),$$

where $N$ is the length of the Tensor.

Parameters

• input (Tensor) – The input Tensor.

• dim (int, optional) – The axis to perform the Log softmax operation. Default: None .

Keyword Arguments

dtype (mindspore.dtype, optional) – The desired dtype of returned Tensor. If not set to None, the input Tensor will be cast to dtype before the operation is performed. This is useful for preventing overflows. If set to None, stay the same as original Tensor. Default: None .

Returns

Tensor, with the same shape as the input.

Raises

• TypeError – If dim is not an int.

• ValueError – If dim is not in range [-len(input.shape), len(input.shape)).

Supported Platforms:

Ascend

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor, mint
>>> logits = Tensor(np.array([1, 2, 3, 4, 5]), mindspore.float32)
>>> output = mint.nn.functional.log_softmax(logits, dim=-1)
>>> print(output)
[-4.4519143 -3.4519143 -2.4519143 -1.4519144 -0.4519144]