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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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mindspore.mint.nn.functional.one_hot

View Source On Gitee
mindspore.mint.nn.functional.one_hot(tensor, num_classes=- 1)[source]

Computes a one-hot tensor.

The locations represented by tensor in tensor take value 1, while all other locations take value 0.

Parameters

  • tensor (Tensor) – A tensor of indices. Tensor of shape (X0,…,Xn). Data type must be int32 or int64. Dimension cannot be greater than 7.

  • num_classes (int, optional) – A scalar defining the depth of the one-hot dimension, default: -1.

Returns

Tensor, one-hot tensor.

Raises

  • TypeError – If num_classes is not an int.

  • TypeError – If dtype of tensor is not int32 or int64.

  • ValueError – If num_classes is less than -1.

Supported Platforms:

Ascend

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor, mint
>>> tensor = Tensor(np.array([0, 1, 2]), mindspore.int32)
>>> num_classes = 3
>>> output = mint.nn.functional.one_hot(tensor, num_classes)
>>> print(output)
[[1 0 0]
 [0 1 0]
 [0 0 1]]