|
- # Copyright 2019 Huawei Technologies Co., Ltd
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- # ==============================================================================
-
- """
- This module py_transforms is implemented basing on python. It provides common
- operations including OneHotOp.
- """
-
- from .validators import check_one_hot_op
- from .vision import py_transforms_util as util
-
-
- class OneHotOp:
- """
- Apply one hot encoding transformation to the input label, make label be more smoothing and continuous.
-
- Args:
- num_classes (int): Num class of object in dataset, type is int and value over 0.
- smoothing_rate (float): The adjustable Hyper parameter decides the label smoothing level , 0.0 means not do it.
- """
-
- @check_one_hot_op
- def __init__(self, num_classes, smoothing_rate=0.0):
- self.num_classes = num_classes
- self.smoothing_rate = smoothing_rate
-
- def __call__(self, label):
- """
- Call method.
-
- Args:
- label (numpy.ndarray): label to be applied label smoothing.
-
- Returns:
- label (numpy.ndarray), label after being Smoothed.
- """
- return util.one_hot_encoding(label, self.num_classes, self.smoothing_rate)
|
