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46 lines
1.5 KiB
46 lines
1.5 KiB
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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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 paddle.optimizer.lr import LRScheduler
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class CyclicLRScheduler(LRScheduler):
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def __init__(self,
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base_lr: float=1e-8,
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max_lr: float=1e-3,
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step_size: int=10000):
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super(CyclicLRScheduler, self).__init__()
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self.current_step = -1
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self.base_lr = base_lr
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self.max_lr = max_lr
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self.step_size = step_size
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def step(self):
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if not hasattr(self, 'current_step'):
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return
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self.current_step += 1
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if self.current_step >= 2 * self.step_size:
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self.current_step %= 2 * self.step_size
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self.last_lr = self.get_lr()
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def get_lr(self):
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p = self.current_step / (2 * self.step_size) # Proportion in one cycle.
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if p < 0.5: # Increase
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return self.base_lr + p / 0.5 * (self.max_lr - self.base_lr)
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else: # Decrease
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return self.max_lr - (p / 0.5 - 1) * (self.max_lr - self.base_lr)
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