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Specifications and Common Mistakes

- Specifications and Common Mistakes:

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mindspore.mint.stack

mindspore.mint.stack(tensors, dim=0)

Stacks a list of tensors in specified dim.

Stacks the list of input tensors with the same rank R, output is a tensor of rank (R+1).

Given input tensors of shape $(x_1,x_2,...,x_R)$. Set the number of input tensors as N. If $dim\ge 0$, the shape of the output tensor is $(x_1,x_2,...,x_{dim},N,x_{dim+1},...,x_R)$.

Parameters

• tensors (Union[tuple, list]) – A Tuple or list of Tensor objects with the same shape and type.

• dim (int, optional) – Dimension to stack. The range is [-(R+1), R+1). Default: 0 .

Returns

Tensor. A stacked Tensor with the same type as tensors.

Raises

• TypeError – If the data types of elements in tensors are not the same.

• ValueError – If dim is out of the range [-(R+1), R+1); or if the shapes of elements in tensors are not the same.

Supported Platforms:

Ascend

Examples

>>> import mindspore
>>> from mindspore import Tensor, mint
>>> import numpy as np
>>> data1 = Tensor(np.array([0, 1]).astype(np.float32))
>>> data2 = Tensor(np.array([2, 3]).astype(np.float32))
>>> output = mint.stack([data1, data2], 0)
>>> print(output)
[[0. 1.]
 [2. 3.]]