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111 lines
3.9 KiB
111 lines
3.9 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 paddle.v2.fluid.framework as framework
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import paddle.v2.fluid as fluid
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import paddle.v2.fluid.layers as layers
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import paddle.v2.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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class TestLearningRateDecay(unittest.TestCase):
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def check_decay(self, python_decay_fn, fluid_decay_fn, staircase):
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init_lr = 1.0
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decay_steps = 5
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decay_rate = 0.5
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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(
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learning_rate=init_lr,
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global_step=global_step,
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decay_steps=decay_steps,
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decay_rate=decay_rate,
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staircase=staircase)
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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(
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learning_rate=init_lr,
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global_step=step,
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decay_steps=decay_steps,
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decay_rate=decay_rate,
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staircase=staircase)
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self.assertAlmostEqual(python_decayed_lr, lr_val[0])
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def test_decay(self):
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decay_fns = [
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(exponential_decay, lr_decay.exponential_decay, True),
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(exponential_decay, lr_decay.exponential_decay, False),
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(natural_exp_decay, lr_decay.natural_exp_decay, True),
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(natural_exp_decay, lr_decay.natural_exp_decay, False),
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(inverse_time_decay, lr_decay.inverse_time_decay, True),
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(inverse_time_decay, lr_decay.inverse_time_decay, False),
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]
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for py_decay_fn, fluid_decay_fn, staircase in decay_fns:
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print("decay_fn=" + str(py_decay_fn) + " staircase=" + str(
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staircase))
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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, staircase)
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if __name__ == '__main__':
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unittest.main()
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