def _transform(self, input: Any, params: Dict[str, Any]) -> Any:
if type(input) is features.Label:
num_categories = self.num_categories
if num_categories == -1 and input.categories is not None:
num_categories = len(input.categories)
output = F.label_to_one_hot(input, num_categories=num_categories)
return features.OneHotLabel(output, categories=input.categories)
else:
return input
def make_one_hot_label(*args, **kwargs):
label = make_label(*args, **kwargs)
return features.OneHotLabel(one_hot(label,
num_classes=len(label.categories)),
categories=label.categories)