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Specifications and Common Mistakes

- Specifications and Common Mistakes:

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mindspore.ops.expand_dims

mindspore.ops.expand_dims(input_x, axis)

Adds an additional dimension to input_x at the given axis, the dimension of input_x should be greater than or equal to 1.

Note

If the specified axis is a negative number, the index is counted backward from the end and starts at 1.

Parameters

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

• axis (int) – Specifies the dimension index at which to expand the shape of input_x. The value of axis must be in the range [-input_x.ndim-1, input_x.ndim]. Only constant value is allowed.

Returns

Tensor, the shape of tensor is $(1,x_1,x_2,...,x_R)$ if the value of axis is 0. It has the same data type as input_x.

Raises

• TypeError – If axis is not an int.

• ValueError – If axis is not in the valid range $[-a.ndim-1,a.ndim]$.

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.expand_dims(input_tensor, 0)
>>> print(output)
[[[2. 2.]
  [2. 2.]]]