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