mindspore.dataset.transforms.OneHot
- class mindspore.dataset.transforms.OneHot(num_classes, smoothing_rate=0.0)[source]
Tensor operation to apply one hot encoding.
- Parameters
- Raises
TypeError – num_classes is not of type int.
TypeError – smoothing_rate is not of type float or int.
ValueError – smoothing_rate is not in range [0.0, 1.0].
RuntimeError – Input tensor is not of type int.
RuntimeError – Input tensor is not a 1-D tensor.
- Supported Platforms:
CPU
Examples
>>> # 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"])