68 lines
2.5 KiB
Python
68 lines
2.5 KiB
Python
# Copyright 2018 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 serialization functions."""
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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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import json
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from tensorflow.python.framework import constant_op
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from tensorflow.python.framework import test_util
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from tensorflow.python.keras.engine import input_layer
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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.layers import core
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from tensorflow.python.platform import test
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from tensorflow.python.util import serialization
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class SerializationTests(test.TestCase):
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def test_serialize_dense(self):
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dense = core.Dense(3)
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dense(constant_op.constant([[4.]]))
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round_trip = json.loads(json.dumps(
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dense, default=serialization.get_json_type))
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self.assertEqual(3, round_trip["config"]["units"])
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@test_util.run_in_graph_and_eager_modes
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def test_serialize_sequential(self):
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model = sequential.Sequential()
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model.add(core.Dense(4))
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model.add(core.Dense(5))
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model(constant_op.constant([[1.]]))
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sequential_round_trip = json.loads(
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json.dumps(model, default=serialization.get_json_type))
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self.assertEqual(
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# Note that `config['layers'][0]` will be an InputLayer in V2
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# (but not in V1)
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5, sequential_round_trip["config"]["layers"][-1]["config"]["units"])
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@test_util.run_in_graph_and_eager_modes
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def test_serialize_model(self):
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x = input_layer.Input(shape=[3])
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y = core.Dense(10)(x)
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model = training.Model(x, y)
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model(constant_op.constant([[1., 1., 1.]]))
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model_round_trip = json.loads(
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json.dumps(model, default=serialization.get_json_type))
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self.assertEqual(
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10, model_round_trip["config"]["layers"][1]["config"]["units"])
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if __name__ == "__main__":
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test.main()
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