mindspore.dataset.transforms.py_transforms.OneHotOp

class mindspore.dataset.transforms.py_transforms.OneHotOp(num_classes, smoothing_rate=0.0)[source]

Apply one hot encoding transformation to the input label, make label be more smoothing and continuous.

Parameters

num_classes (int) – Number of classes of objects in dataset. Value must be larger than 0.
smoothing_rate (float, optional) – Adjustable hyperparameter for label smoothing level. (Default=0.0 means no smoothing is applied.)

Examples

>>> import mindspore.dataset.transforms as py_transforms
>>>
>>> transforms_list = [py_transforms.OneHotOp(num_classes=10, smoothing_rate=0.1)]
>>> transform = py_transforms.Compose(transforms_list)
>>> data1 = data1.map(input_columns=["label"], operations=transform())