57 lines
1.9 KiB
Python
Executable File
57 lines
1.9 KiB
Python
Executable File
#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 as fluid
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from paddle.fluid.regularizer import L2Decay
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from ppocr.utils.utility import initial_logger
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logger = initial_logger()
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def AdamDecay(params, parameter_list=None):
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"""
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define optimizer function
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args:
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params(dict): the super parameters
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parameter_list (list): list of Variable names to update to minimize loss
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return:
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"""
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base_lr = params['base_lr']
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beta1 = params['beta1']
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beta2 = params['beta2']
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l2_decay = params.get("l2_decay", 0.0)
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if 'decay' in params:
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params = params['decay']
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decay_mode = params['function']
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step_each_epoch = params['step_each_epoch']
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total_epoch = params['total_epoch']
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if decay_mode == "cosine_decay":
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base_lr = fluid.layers.cosine_decay(
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learning_rate=base_lr,
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step_each_epoch=step_each_epoch,
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epochs=total_epoch)
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else:
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logger.info("Only support Cosine decay currently")
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optimizer = fluid.optimizer.Adam(
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learning_rate=base_lr,
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beta1=beta1,
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beta2=beta2,
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regularization=L2Decay(regularization_coeff=l2_decay),
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parameter_list=parameter_list)
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return optimizer
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