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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.

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- Incorrect version numbers, including software package names and version numbers on the UI.

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- Risk Warnings:

- Lack of risk warnings for operations that may damage the system or important data.

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

mindspore.ops.slice

View Source On Gitee
mindspore.ops.slice(input_x, begin, size)[source]

Slice a tensor in the specified shape.

Note

begin is zero-based and size is one-based.

If size[i] is -1, all remaining elements in dimension i are included in the slice. This is equivalent to setting size[i]=input_x.shape(i)begin[i].

Parameters
  • input_x (Tensor) – The input tensor.

  • begin (Union[tuple, list]) – The beginning of the slice which represents the offset in each dimension.

  • size (Union[tuple, list]) – The size of the slice.

Returns

Tensor

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore
>>> data = mindspore.tensor([[[1, 1, 1], [2, 2, 2]],
...                         [[3, 3, 3], [4, 4, 4]],
...                         [[5, 5, 5], [6, 6, 6]]], mindspore.int32)
>>> output = mindspore.ops.slice(data, (1, 0, 0), (1, 1, 3))
>>> print(output)
[[[3 3 3]]]
>>> output = mindspore.ops.slice(data, (1, 0, 0), (1, 1, 2))
>>> print(output)
[[[3 3]]]
>>> output = mindspore.ops.slice(data, (1, 0, 0), (1, 1, 1))
>>> print(output)
[[[3]]]
>>> output = mindspore.ops.slice(data, (1, 1, 0), (1, 1, 3))
>>> print(output)
[[[4 4 4]]]
>>> output = mindspore.ops.slice(data, (1, 0, 1), (1, 1, 2))
>>> print(output)
[[[3 3]]]