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# Copyright 2023 The TensorFlow 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.
"""Tests for optimization_config.py."""
import tensorflow as tf, tf_keras
from official.modeling.optimization.configs import learning_rate_config as lr_cfg
from official.modeling.optimization.configs import optimization_config
from official.modeling.optimization.configs import optimizer_config as opt_cfg
class OptimizerConfigTest(tf.test.TestCase):
def test_no_optimizer(self):
optimizer = optimization_config.OptimizationConfig({}).optimizer.get()
self.assertIsNone(optimizer)
def test_no_lr_schedule(self):
lr = optimization_config.OptimizationConfig({}).learning_rate.get()
self.assertIsNone(lr)
def test_no_warmup_schedule(self):
warmup = optimization_config.OptimizationConfig({}).warmup.get()
self.assertIsNone(warmup)
def test_config(self):
opt_config = optimization_config.OptimizationConfig({
'optimizer': {
'type': 'sgd',
'sgd': {} # default config
},
'learning_rate': {
'type': 'polynomial',
'polynomial': {}
},
'warmup': {
'type': 'linear'
}
})
self.assertEqual(opt_config.optimizer.get(), opt_cfg.SGDConfig())
self.assertEqual(opt_config.learning_rate.get(),
lr_cfg.PolynomialLrConfig())
self.assertEqual(opt_config.warmup.get(), lr_cfg.LinearWarmupConfig())
if __name__ == '__main__':
tf.test.main()
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