Document feedback

Question document fragment

When a question document fragment contains a formula, it is displayed as a space.

Submission type

issue

It's a little complicated...

I'd like to ask someone.

PR

Just a small problem.

I can fix it online!

Please select the submission type

Problem type

Specifications and Common Mistakes

- Specifications and Common Mistakes:

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

- Incorrect links, empty cells, or wrong formats.

- Chinese characters in English context.

- Minor inconsistencies between the UI and descriptions.

- Low writing fluency that does not affect understanding.

- Incorrect version numbers, including software package names and version numbers on the UI.

Usability

- Usability:

- Incorrect or missing key steps.

- Missing main function descriptions, keyword explanation, necessary prerequisites, or precautions.

- Ambiguous descriptions, unclear reference, or contradictory context.

- Unclear logic, such as missing classifications, items, and steps.

Correctness

- Correctness:

- Technical principles, function descriptions, supported platforms, parameter types, or exceptions inconsistent with that of software implementation.

- Incorrect schematic or architecture diagrams.

- Incorrect commands or command parameters.

- Incorrect code.

- Commands inconsistent with the functions.

- Wrong screenshots.

- Sample code running error, or running results inconsistent with the expectation.

Risk Warnings

- Risk Warnings:

- Lack of risk warnings for operations that may damage the system or important data.

Content Compliance

- Content Compliance:

- Contents that may violate applicable laws and regulations or geo-cultural context-sensitive words and expressions.

- Copyright infringement.

Please select the type of question

Problem description

Describe the bug so that we can quickly locate the problem.

Submit

Document feedback

mindspore.dataset.transforms.OneHot

class mindspore.dataset.transforms.OneHot(num_classes, smoothing_rate=0.0)

Apply One-Hot encoding to the input labels.

For a 1-D input of shape $(\ast )$, an output of shape $(\ast ,nu{m}_{c}lasses)$ will be returned, where the elements with index values equal to the input values will be set to 1, and the rest will be set to 0. If a label smoothing rate is specified, the element values are further smoothed to enhance generalization.

Parameters

• num_classes (int) – Total number of classes. Must be greater than the maximum value of the input labels.

• smoothing_rate (float, optional) – The amount of label smoothing. Must be between [0.0, 1.0]. Default: 0.0, no label smoothing.

Raises

• TypeError – If num_classes is not of type int.

• TypeError – If smoothing_rate is not of type float.

• ValueError – If smoothing_rate is not in range of [0.0, 1.0].

• RuntimeError – If input label is not of type int.

• RuntimeError – If the dimension of the input label is not 1.

Supported Platforms:

CPU

Examples

>>> import mindspore.dataset as ds
>>> import mindspore.dataset.transforms as transforms
>>>
>>> mnist_dataset_dir = "/path/to/mnist_dataset_directory"
>>> mnist_dataset = ds.MnistDataset(dataset_dir=mnist_dataset_dir)
>>>
>>> # Assume that dataset has 10 classes, thus the label ranges from 0 to 9
>>> onehot_op = transforms.OneHot(num_classes=10)
>>> mnist_dataset = mnist_dataset.map(operations=onehot_op, input_columns=["label"])