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.

PR

Just a small problem.

I can fix it online!

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.ops.transpose

mindspore.ops.transpose(input, input_perm)

Permutes the dimensions of the input tensor according to input permutation.

For a 1-D array this has no effect, as a transposed vector is simply the same vector. To convert a 1-D array into a 2D column vector please refer to mindspore.ops.expand_dims(). For a 2-D array, this is a standard matrix transpose. For an n-D array, if axes are given, their order indicates how the axes are permuted (see Examples). If axes are not provided and a.shape is $(i[0],i[1],...i[n-2],i[n-1])$, then a.transpose().shape is $(i[n-1],i[n-2],...i[1],i[0])$.

Note

On GPU and CPU, if the value of input_perm is negative, its actual value is input_perm[i] + rank(input). Negative value of input_perm is not supported on Ascend.

Parameters

• input (Tensor) – The shape of tensor is $(x_1,x_2,...,x_R)$.

• input_perm (tuple[int]) – The permutation to be converted. The elements in input_perm are composed of the indexes of each dimension of input. The length of input_perm and the shape of input must be the same. Only constant value is allowed. Must be in the range [-rank(input), rank(input)).

Returns

Tensor, the type of output tensor is the same as input and the shape of output tensor is decided by the shape of input and the value of input_perm.

Raises

• TypeError – If input_perm is not a tuple.

• ValueError – If length of shape of input is not equal to length of shape of input_perm.

• ValueError – If the same element exists in input_perm.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor, ops
>>> input = Tensor(np.array([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]]), mindspore.float32)
>>> input_perm = (0, 2, 1)
>>> output = ops.transpose(input, input_perm)
>>> print(output)
[[[ 1.  4.]
  [ 2.  5.]
  [ 3.  6.]]
 [[ 7. 10.]
  [ 8. 11.]
  [ 9. 12.]]]