learning_rate_scheduler.py 2.0 KB
Newer Older
M
minqiyang 已提交
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
# Copyright (c) 2016 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 __future__ import print_function

from .. import unique_name

M
minqiyang 已提交
19
__all__ = ['PiecewiseDecay']
M
minqiyang 已提交
20 21 22 23 24 25 26


class LearningRateDecay(object):
    """
    Base class of learning rate decay
    """

M
minqiyang 已提交
27 28 29
    def __init__(self, begin=0, step=1, dtype='float32'):
        self.step_num = begin
        self.step_size = step
M
minqiyang 已提交
30 31 32 33 34 35
        self.dtype = dtype

    def __call__(self):
        lr = self.step()
        if isinstance(lr, float):
            lr = self._create_lr_var(lr)
M
minqiyang 已提交
36
        self.step_num += self.step_size
M
minqiyang 已提交
37 38
        return lr

M
minqiyang 已提交
39 40
    def create_lr_var(self, lr):
        from .. import layers
M
minqiyang 已提交
41 42 43 44 45 46
        lr = layers.create_global_var(
            name=unique_name.generate("learning_rate"),
            shape=[1],
            value=float(lr),
            dtype=self.dtype,
            persistable=True)
M
minqiyang 已提交
47
        return lr
M
minqiyang 已提交
48 49 50 51 52

    def step(self):
        raise NotImplementedError()


M
minqiyang 已提交
53 54 55
class PiecewiseDecay(LearningRateDecay):
    def __init__(self, boundaries, values, begin, step=1, dtype='float32'):
        super(PiecewiseDecay, self).__init__(begin, step, dtype)
M
minqiyang 已提交
56 57 58 59 60 61 62 63
        self.boundaries = boundaries
        self.values = values

        self.vars = []
        for value in values:
            self.vars.append(self.create_lr_var(value))

    def step(self):
M
minqiyang 已提交
64 65
        for i in range(len(self.boundaries)):
            if self.step_num < self.boundaries[i]:
M
minqiyang 已提交
66
                return self.vars[i]
M
minqiyang 已提交
67
        return self.vars[len(self.values) - 1]