59 lines
2.1 KiB
Python
59 lines
2.1 KiB
Python
# Copyright 2020 The TensorFlow 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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#,============================================================================
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"""Tests for `get_config` backwards compatibility."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from tensorflow.python.keras import keras_parameterized
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from tensorflow.python.keras.engine import sequential
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from tensorflow.python.keras.engine import training
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from tensorflow.python.keras.tests import get_config_samples
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from tensorflow.python.platform import test
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@keras_parameterized.run_all_keras_modes
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class TestGetConfigBackwardsCompatible(keras_parameterized.TestCase):
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def test_functional_dnn(self):
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model = training.Model.from_config(get_config_samples.FUNCTIONAL_DNN)
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self.assertLen(model.layers, 3)
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def test_functional_cnn(self):
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model = training.Model.from_config(get_config_samples.FUNCTIONAL_CNN)
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self.assertLen(model.layers, 4)
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def test_functional_lstm(self):
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model = training.Model.from_config(get_config_samples.FUNCTIONAL_LSTM)
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self.assertLen(model.layers, 3)
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def test_sequential_dnn(self):
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model = sequential.Sequential.from_config(get_config_samples.SEQUENTIAL_DNN)
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self.assertLen(model.layers, 2)
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def test_sequential_cnn(self):
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model = sequential.Sequential.from_config(get_config_samples.SEQUENTIAL_CNN)
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self.assertLen(model.layers, 3)
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def test_sequential_lstm(self):
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model = sequential.Sequential.from_config(
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get_config_samples.SEQUENTIAL_LSTM)
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self.assertLen(model.layers, 2)
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if __name__ == '__main__':
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test.main()
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