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.

mindspore.mint.tile

View Source On Gitee
mindspore.mint.tile(input, dims)[source]

Creates a new tensor by repeating the elements in the input tensor dims times.

The i'th dimension of output tensor has input.shape[i] * dims[i] elements, and the values of input are repeated dims[i] times along the i'th dimension.

Note

  • On Ascend, the number of dims should not exceed 8, and currently does not support scenarios where more than 4 dimensions are repeated simultaneously.

  • If input.dim = d, then the shape of their corresponding positions can be multiplied, and the shape of Outputs is (x1y1,x2y2,...,xSyS).

  • If input.dim < d, prepend 1 to the shape of input until their lengths are consistent. Such as set the shape of input as (1,...,x1,x2,...,xS), then the shape of their corresponding positions can be multiplied, and the shape of Outputs is (1y1,...,xRyR,xSyS).

  • If input.dim > d, prepend 1 to dims until their lengths are consistent. Such as set the dims as (1,...,y1,y2,...,yS), then the shape of their corresponding positions can be multiplied, and the shape of Outputs is (x11,...,xRyR,xSyS).

Parameters
  • input (Tensor) – The input tensor.

  • dims (tuple[int]) – The specified number of repetitions in each dimension.

Returns

Tensor

Supported Platforms:

Ascend

Examples

>>> import mindspore
>>> input = mindspore.tensor([[1, 2], [3, 4]])
>>> mindspore.mint.tile(input, (2, 3))
Tensor(shape=[4, 6], dtype=Int64, value=
[[1, 2, 1, 2, 1, 2],
 [3, 4, 3, 4, 3, 4],
 [1, 2, 1, 2, 1, 2],
 [3, 4, 3, 4, 3, 4]])
>>> mindspore.mint.tile(input, (2, 3, 2))
Tensor(shape=[2, 6, 4], dtype=Int64, value=
[[[1, 2, 1, 2],
  [3, 4, 3, 4],
  [1, 2, 1, 2],
  [3, 4, 3, 4],
  [1, 2, 1, 2],
  [3, 4, 3, 4]],
 [[1, 2, 1, 2],
  [3, 4, 3, 4],
  [1, 2, 1, 2],
  [3, 4, 3, 4],
  [1, 2, 1, 2],
  [3, 4, 3, 4]]])