37 lines
1.2 KiB
Python
37 lines
1.2 KiB
Python
|
#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
|
||
|
|
import paddle.fluid as fluid
|
||
|
|
|
||
|
|
|
||
|
|
def AdamDecay(params, parameter_list=None):
|
||
|
|
"""
|
||
|
|
define optimizer function
|
||
|
|
args:
|
||
|
|
params(dict): the super parameters
|
||
|
|
parameter_list (list): list of Variable names to update to minimize loss
|
||
|
|
return:
|
||
|
|
"""
|
||
|
|
base_lr = params['base_lr']
|
||
|
|
beta1 = params['beta1']
|
||
|
|
beta2 = params['beta2']
|
||
|
|
optimizer = fluid.optimizer.Adam(
|
||
|
|
learning_rate=base_lr,
|
||
|
|
beta1=beta1,
|
||
|
|
beta2=beta2,
|
||
|
|
parameter_list=parameter_list)
|
||
|
|
return optimizer
|