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150 lines
5.2 KiB
150 lines
5.2 KiB
# Copyright (c) 2016 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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import unittest
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import math
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import copy
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import paddle.fluid.framework as framework
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import paddle.fluid as fluid
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import paddle.fluid.layers as layers
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import paddle.fluid.learning_rate_decay as lr_decay
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def exponential_decay(learning_rate,
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global_step,
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decay_steps,
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decay_rate,
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staircase=False):
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exponent = float(global_step) / float(decay_steps)
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if staircase:
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exponent = math.floor(exponent)
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return learning_rate * decay_rate**exponent
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def natural_exp_decay(learning_rate,
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global_step,
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decay_steps,
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decay_rate,
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staircase=False):
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exponent = float(global_step) / float(decay_steps)
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if staircase:
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exponent = math.floor(exponent)
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return learning_rate * math.exp(-1 * decay_rate * exponent)
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def inverse_time_decay(learning_rate,
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global_step,
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decay_steps,
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decay_rate,
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staircase=False):
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temp = float(global_step) / float(decay_steps)
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if staircase:
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temp = math.floor(temp)
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return learning_rate / (1 + decay_rate * temp)
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def polynomial_decay(learning_rate,
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global_step,
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decay_steps,
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end_learning_rate=0.0001,
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power=1.0,
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cycle=False):
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if cycle:
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div = math.ceil(global_step / float(decay_steps))
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if div == 0:
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div = 1
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decay_steps = decay_steps * div
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else:
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global_step = min(global_step, decay_steps)
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return (learning_rate - end_learning_rate) * \
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((1 - float(global_step) / float(decay_steps)) ** power) + end_learning_rate
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def piecewise_decay(global_step, boundaries, values):
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assert len(boundaries) + 1 == len(values)
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for i in range(len(boundaries)):
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if global_step < boundaries[i]:
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return values[i]
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return values[len(values) - 1]
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class TestLearningRateDecay(unittest.TestCase):
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def check_decay(self, python_decay_fn, fluid_decay_fn, kwargs):
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global_step = layers.create_global_var(
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shape=[1], value=0.0, dtype='float32', persistable=True)
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decayed_lr = fluid_decay_fn(global_step=global_step, **kwargs)
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layers.increment(global_step, 1.0)
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place = fluid.CPUPlace()
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exe = fluid.Executor(place)
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exe.run(fluid.default_startup_program())
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for step in range(10):
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step_val, lr_val = exe.run(fluid.default_main_program(),
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feed=[],
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fetch_list=[global_step, decayed_lr])
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python_decayed_lr = python_decay_fn(global_step=step, **kwargs)
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self.assertAlmostEqual(python_decayed_lr, lr_val[0])
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def test_decay(self):
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common_kwargs_true = {
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"learning_rate": 1.0,
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"decay_steps": 5,
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"decay_rate": 0.5,
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"staircase": True
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}
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common_kwargs_false = copy.deepcopy(common_kwargs_true)
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common_kwargs_false["staircase"] = False
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decay_fns = [
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(exponential_decay, lr_decay.exponential_decay, common_kwargs_true),
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(exponential_decay, lr_decay.exponential_decay,
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common_kwargs_false),
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(natural_exp_decay, lr_decay.natural_exp_decay, common_kwargs_true),
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(natural_exp_decay, lr_decay.natural_exp_decay,
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common_kwargs_false),
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(inverse_time_decay, lr_decay.inverse_time_decay,
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common_kwargs_true),
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(inverse_time_decay, lr_decay.inverse_time_decay,
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common_kwargs_false),
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(polynomial_decay, lr_decay.polynomial_decay, {
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"learning_rate": 1.0,
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"decay_steps": 5,
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"cycle": True
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}),
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(polynomial_decay, lr_decay.polynomial_decay, {
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"learning_rate": 1.0,
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"decay_steps": 5,
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"cycle": False
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}),
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(piecewise_decay, lr_decay.piecewise_decay, {
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"boundaries": [3, 6, 9],
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"values": [0.1, 0.2, 0.3, 0.4]
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}),
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]
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for py_decay_fn, fluid_decay_fn, kwargs in decay_fns:
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print("decay_fn=" + py_decay_fn.__name__ + " kwargs=" + str(kwargs))
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main_program = framework.Program()
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startup_program = framework.Program()
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with framework.program_guard(main_program, startup_program):
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self.check_decay(py_decay_fn, fluid_decay_fn, kwargs)
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if __name__ == '__main__':
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unittest.main()
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