# 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
[docs]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)