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# Copyright 2019 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 optimizer_builder."""
import unittest
import tensorflow.compat.v1 as tf
from google.protobuf import text_format
from object_detection.builders import optimizer_builder
from object_detection.protos import optimizer_pb2
from object_detection.utils import tf_version
@unittest.skipIf(tf_version.is_tf1(), 'Skipping TF2.X only test.')
class OptimizerBuilderV2Test(tf.test.TestCase):
"""Test building optimizers in V2 mode."""
def testBuildRMSPropOptimizer(self):
optimizer_text_proto = """
rms_prop_optimizer: {
learning_rate: {
exponential_decay_learning_rate {
initial_learning_rate: 0.004
decay_steps: 800720
decay_factor: 0.95
}
}
momentum_optimizer_value: 0.9
decay: 0.9
epsilon: 1.0
}
use_moving_average: false
"""
optimizer_proto = optimizer_pb2.Optimizer()
text_format.Merge(optimizer_text_proto, optimizer_proto)
optimizer, _ = optimizer_builder.build(optimizer_proto)
self.assertIsInstance(optimizer, tf.keras.optimizers.RMSprop)
def testBuildMomentumOptimizer(self):
optimizer_text_proto = """
momentum_optimizer: {
learning_rate: {
constant_learning_rate {
learning_rate: 0.001
}
}
momentum_optimizer_value: 0.99
}
use_moving_average: false
"""
optimizer_proto = optimizer_pb2.Optimizer()
text_format.Merge(optimizer_text_proto, optimizer_proto)
optimizer, _ = optimizer_builder.build(optimizer_proto)
self.assertIsInstance(optimizer, tf.keras.optimizers.SGD)
def testBuildAdamOptimizer(self):
optimizer_text_proto = """
adam_optimizer: {
learning_rate: {
constant_learning_rate {
learning_rate: 0.002
}
}
}
use_moving_average: false
"""
optimizer_proto = optimizer_pb2.Optimizer()
text_format.Merge(optimizer_text_proto, optimizer_proto)
optimizer, _ = optimizer_builder.build(optimizer_proto)
self.assertIsInstance(optimizer, tf.keras.optimizers.Adam)
def testMovingAverageOptimizerUnsupported(self):
optimizer_text_proto = """
adam_optimizer: {
learning_rate: {
constant_learning_rate {
learning_rate: 0.002
}
}
}
use_moving_average: True
"""
optimizer_proto = optimizer_pb2.Optimizer()
text_format.Merge(optimizer_text_proto, optimizer_proto)
with self.assertRaises(ValueError):
optimizer_builder.build(optimizer_proto)
if __name__ == '__main__':
tf.enable_v2_behavior()
tf.test.main()
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