54 lines
1.9 KiB
Python
54 lines
1.9 KiB
Python
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#copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
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#
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#Licensed under the Apache License, Version 2.0 (the "License");
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#you may not use this file except in compliance with the License.
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#You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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#Unless required by applicable law or agreed to in writing, software
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#distributed under the License is distributed on an "AS IS" BASIS,
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#WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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#See the License for the specific language governing permissions and
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#limitations under the License.
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import paddle.fluid.optimizer as pfopt
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import paddle.fluid.regularizer as pfreg
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__all__ = ['OptimizerBuilder']
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class OptimizerBuilder(object):
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"""
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Build optimizer with fluid api in fluid.layers.optimizer,
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such as fluid.layers.optimizer.Momentum()
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https://www.paddlepaddle.org.cn/documentation/docs/zh/api_cn/optimizer_cn.html
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https://www.paddlepaddle.org.cn/documentation/docs/zh/api_cn/regularizer_cn.html
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Args:
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function(str): optimizer name of learning rate
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params(dict): parameters used for init the class
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regularizer (dict): parameters used for create regularization
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"""
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def __init__(self,
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function='Momentum',
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params={'momentum': 0.9},
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regularizer=None):
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self.function = function
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self.params = params
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# create regularizer
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if regularizer is not None:
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reg_func = regularizer['function'] + 'Decay'
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reg_factor = regularizer['factor']
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reg = getattr(pfreg, reg_func)(reg_factor)
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self.params['regularization'] = reg
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def __call__(self, learning_rate):
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opt = getattr(pfopt, self.function)
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return opt(learning_rate=learning_rate, **self.params)
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