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.AdaptiveMaxPool3d

class mindspore.nn.AdaptiveMaxPool3d(output_size, return_indices=False)

Applies a 3D adaptive max pooling over an input signal composed of several input planes.

The output is of size $(D,H,W)$, for any input size. The number of output features is equal to the number of input planes.

Parameters

• output_size (Union[int, tuple]) – The target output size is $(D,H,W)$. ouput_size can be a tuple with 3 elements, or a single D for $(D,D,D)$. $D$, $H$ and $W$ can be int or None which means the output size is the same as that of the input.

• return_indices (bool) – If return_indices is True, the indices of max value would be output. Default: False.

Inputs:

• x (Tensor) - Tensor, has shape of $(C,D,H,W)$ or $(N,C,D,H,W)$ . The suppoerted dtypes are int8, int16, int32, int64, uint8, uint16, uint32, uint64, float16, float32 and float64 data type.

Outputs:

• y (Tensor) - Tensor, has the same number of dims and data type as the x .

• argmax (Tensor) - Tensor, the indices of the maximum values along with the outputs, has the same shape as y and a dtype of int32. Return this only when return_indices is True.

Raises

• TypeError – If x is not a Tensor.

• ValueError – If the dimensions number of x is not 4 or 5.

• TypeError – If dtype of x is not int8, int16, int32, int64, uint8, uint16, uint32, uint64, float16, float32 or float64.

• ValueError – If output_size is neither an int nor a tuple with shape (3,).

Supported Platforms:

GPU CPU

Examples

>>> x = Tensor(np.arange(0,36).reshape((1, 3, 3, 4)).astype(np.float32))
>>> output_size = (1, 1, 2)
>>> net = nn.AdaptiveMaxPool3d(output_size, True)
>>> output = net(x)
>>> print(output[0].asnumpy())
[[[[33. 35.]]]]
>>> print(output[1].asnumpy())
[[[[33 35]]]]