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# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. | |
# | |
# 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. | |
from __future__ import absolute_import | |
from __future__ import division | |
from __future__ import print_function | |
from __future__ import unicode_literals | |
import paddle | |
class L1Decay(object): | |
""" | |
L1 Weight Decay Regularization, which encourages the weights to be sparse. | |
Args: | |
factor(float): regularization coeff. Default:0.0. | |
""" | |
def __init__(self, factor=0.0): | |
super(L1Decay, self).__init__() | |
self.coeff = factor | |
def __call__(self): | |
reg = paddle.regularizer.L1Decay(self.coeff) | |
return reg | |
class L2Decay(object): | |
""" | |
L2 Weight Decay Regularization, which helps to prevent the model over-fitting. | |
Args: | |
factor(float): regularization coeff. Default:0.0. | |
""" | |
def __init__(self, factor=0.0): | |
super(L2Decay, self).__init__() | |
self.coeff = float(factor) | |
def __call__(self): | |
return self.coeff |