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utils_test.py
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# Copyright 2021 Google Research. 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.
# ==============================================================================
"""Tests for utils."""
import tensorflow as tf
import utils
class UtilsTest(tf.test.TestCase):
def test_constant_lr(self):
constant_schedule = utils.WarmupLearningRateSchedule(
1.0, lr_decay_type='constant', warmup_epochs=None)
lr = constant_schedule(10)
self.assertAllClose(lr, 1.0)
def test_linear_lr(self):
linear_schedule = utils.WarmupLearningRateSchedule(
1.0, total_steps=10, lr_decay_type='linear', warmup_epochs=None)
lr = linear_schedule(0)
self.assertAllClose(lr, 1.0)
lr = linear_schedule(5)
self.assertAllClose(lr, 0.5)
lr = linear_schedule(10)
self.assertAllClose(lr, 0.0)
def test_cosine_lr(self):
cosine_schedule = utils.WarmupLearningRateSchedule(
1.0, total_steps=10, lr_decay_type='cosine', warmup_epochs=None)
lr = cosine_schedule(4)
self.assertAllClose(lr, 0.654508)
lr = cosine_schedule(5)
self.assertAllClose(lr, 0.5)
lr = cosine_schedule(6)
self.assertAllClose(lr, 0.345491)
def test_exponential_lr(self):
exponential_schedule = utils.WarmupLearningRateSchedule(
1.0,
total_steps=100,
steps_per_epoch=10,
decay_epochs=2,
decay_factor=0.5,
lr_decay_type='exponential',
warmup_epochs=None)
lr = exponential_schedule(5)
self.assertAllClose(lr, 1.0)
lr = exponential_schedule(25)
self.assertAllClose(lr, 0.5)
lr = exponential_schedule(70)
self.assertAllClose(lr, 0.125)
def test_warmup(self):
warmup_schedule = utils.WarmupLearningRateSchedule(
1.0,
total_steps=100,
steps_per_epoch=10,
warmup_epochs=2,
lr_decay_type='constant')
lr = warmup_schedule(5)
self.assertAllClose(lr, 0.25)
lr = warmup_schedule(35)
self.assertAllClose(lr, 1.0)
if __name__ == '__main__':
tf.test.main()