mindspore.ops.unsqueeze

mindspore.ops.unsqueeze(input, dim)[source]

Adds an additional dimension to input at the given dim.

Parameters

input (Tensor) – The shape of tensor is $(n_{1}, n_{2}, . . ., n_{R})$ .
dim (int) – Specifies the dimension index at which to expand the shape of input. The value of dim must be in the range [-input.ndim-1, input.ndim]. Only constant value is allowed.

Returns

Tensor, the shape of tensor is $(1, n_{1}, n_{2}, . . ., n_{R})$ if the value of dim is 0. It has the same data type as input.

Raises

TypeError – If dim is not an int.
ValueError – If dim is not in the valid range $[- i n p u t . n d i m - 1, i n p u t . n d i m]$ .

Supported Platforms:: Ascend GPU CPU

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor, ops
>>> input_tensor = Tensor(np.array([[2, 2], [2, 2]]), mindspore.float32)
>>> output = ops.unsqueeze(input_tensor, dim=0)
>>> print(output)
[[[2. 2.]
  [2. 2.]]]