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.nn.AdaptiveMaxPool1d

class mindspore.nn.AdaptiveMaxPool1d(output_size)

Applies a 1D adaptive maximum pooling over an input Tensor which can be regarded as a composition of 1D input planes.

Typically, the input is of shape $(N_{in},C_{in},L_{in})$, AdaptiveMaxPool1d outputs regional maximum in the $L_{in}$-dimension. The output is of shape $(N_{in},C_{in},L_{out})$, where $L_{out}$ is defined by output_size.

Note

$L_{in}$ must be divisible by output_size.

Parameters

output_size (int) – the target output size $L_{out}$.

Inputs:

• x (Tensor) - Tensor of shape $(N,C_{in},L_{in})$, with float16 or float32 data type.

Outputs:

Tensor of shape $(N,C_{in},L_{out})$, has the same type as x.

Raises

• TypeError – If x is neither float16 nor float32.

• TypeError – If output_size is not an int.

• ValueError – If output_size is less than 1.

• ValueError – If the last dimension of x is smaller than output_size.

• ValueError – If the last dimension of x is not divisible by output_size.

• ValueError – If length of shape of x is not equal to 3.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore as ms
>>> import numpy as np
>>> pool = ms.nn.AdaptiveMaxPool1d(output_size=3)
>>> x = ms.Tensor(np.random.randint(0, 10, [1, 3, 6]), ms.float32)
>>> output = pool(x)
>>> result = output.shape
>>> print(result)
(1, 3, 3)