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Specifications and Common Mistakes

- Specifications and Common Mistakes:

- Misspellings or punctuation mistakes,incorrect formulas, abnormal display.

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mindspore.mint.unbind

mindspore.mint.unbind(input, dim=0)

Unbind a tensor dimension in specified axis.

Given a tensor of shape $(n_1,n_2,...,n_R)$ and unbinding it in the specified dim, multiple tensors with shape $(n_1,n_2,...,n_{dim},n_{dim+2},...,n_R)$ are returned.

Warning

This is an experimental API that is subject to change or deletion.

Parameters

• input (Tensor) – The input tensor to unbind, with a shape of $(n_1,n_2,...,n_R)$. The rank of the tensor must be greater than 0.

• dim (int, optional) – Dimension along which to unbind. The range is [-R, R). Default: 0 .

Returns

A tuple of tensors, the shape of each objects is the same.

Raises

• TypeError – If input is not a Tensor.

• TypeError – If dim is not an int.

• ValueError – If dim is out of the range [-R, R).

Supported Platforms:

Ascend

Examples

>>> import numpy as np
>>> from mindspore import Tensor, mint
>>> input = Tensor(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]))
>>> output = mint.unbind(input, dim=0)
>>> print(output)
(Tensor(shape=[3], dtype=Int64, value=[1, 2, 3]), Tensor(shape=[3], dtype=Int64, value=[4, 5, 6]),
Tensor(shape=[3], dtype=Int64, value=[7, 8, 9]))