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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.

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- Minor inconsistencies between the UI and descriptions.

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mindspore.ops.Squeeze

class mindspore.ops.Squeeze(axis=())

Returns a tensor with the same data type but dimensions of 1 are removed based on axis.

If axis is specified, it will remove the dimensions of size 1 in the given axis. It axis is None, it will remove all the dimensions of size 1.

Note

The dimension index starts at 0 and must be in the range [-input.ndim, input.ndim).

Parameters

axis (Union[int, tuple(int)]) – Specifies the dimension indexes of shape to be removed, which will remove all the dimensions that are equal to 1. If specified, it must be int32 or int64. Default: (), an empty tuple.

Inputs:

• input_x (Tensor) - The shape of tensor is $(x_1,x_2,...,x_R)$.

Outputs:

Tensor, the shape of tensor is $(x_1,x_2,...,x_S)$.

Raises

• TypeError – If axis is neither an int nor tuple.

• TypeError – If axis is a tuple whose elements are not all int.

• ValueError – If the corresponding dimension of the specified axis does not equal to 1.

Supported Platforms:

Ascend GPU CPU

Examples

>>> input_x = Tensor(np.ones(shape=[3, 2, 1]), mindspore.float32)
>>> squeeze = ops.Squeeze(2)
>>> output = squeeze(input_x)
>>> print(output)
[[1. 1.]
 [1. 1.]
 [1. 1.]]