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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

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- Unclear logic, such as missing classifications, items, and steps.

Correctness

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- Technical principles, function descriptions, supported platforms, parameter types, or exceptions inconsistent with that of software implementation.

- Incorrect schematic or architecture diagrams.

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- Incorrect code.

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- Sample code running error, or running results inconsistent with the expectation.

Risk Warnings

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Problem description

Describe the bug so that we can quickly locate the problem.

mindspore.ops.Reshape

View Source On Gitee
class mindspore.ops.Reshape[source]

Rearranges the input Tensor based on the given shape.

Refer to mindspore.ops.reshape() for more details.

Inputs:
  • input_x (Tensor) - The shape of tensor is (x1,x2,...,xR).

  • input_shape (tuple[int]) - The input tuple is constructed by multiple integers, i.e., (y1,y2,...,yS).

Outputs:

Tensor, the shape of tensor is (y1,y2,...,yS).

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor, ops
>>> input_x = Tensor(np.array([[-0.1, 0.3, 3.6], [0.4, 0.5, -3.2]]), mindspore.float32)
>>> reshape = ops.Reshape()
>>> output = reshape(input_x, (3, 2))
>>> print(output)
[[-0.1  0.3]
 [ 3.6  0.4]
 [ 0.5 -3.2]]