f618ab4955
- assertEquals -> assertEqual - assertRaisesRegexp -> assertRegexpMatches - assertRegexpMatches -> assertRegex PiperOrigin-RevId: 319118081 Change-Id: Ieb457128522920ab55d6b69a7f244ab798a7d689
116 lines
4.1 KiB
Python
116 lines
4.1 KiB
Python
# Copyright 2019 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 feature_column and DenseFeatures serialization."""
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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.feature_column import feature_column_v2 as fc
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from tensorflow.python.feature_column import serialization
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from tensorflow.python.platform import test
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class FeatureColumnSerializationTest(test.TestCase):
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"""Tests for serialization, deserialization helpers."""
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def test_serialize_non_feature_column(self):
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class NotAFeatureColumn(object):
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pass
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with self.assertRaisesRegex(ValueError, 'is not a FeatureColumn'):
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serialization.serialize_feature_column(NotAFeatureColumn())
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def test_deserialize_invalid_config(self):
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with self.assertRaisesRegex(ValueError, 'Improper config format: {}'):
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serialization.deserialize_feature_column({})
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def test_deserialize_config_missing_key(self):
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config_missing_key = {
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'config': {
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# Dtype is missing and should cause a failure.
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# 'dtype': 'int32',
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'default_value': None,
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'key': 'a',
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'normalizer_fn': None,
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'shape': (2,)
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},
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'class_name': 'NumericColumn'
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}
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with self.assertRaisesRegex(ValueError,
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'Invalid config:.*expected keys.*dtype'):
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serialization.deserialize_feature_column(config_missing_key)
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def test_deserialize_invalid_class(self):
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with self.assertRaisesRegex(
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ValueError, 'Unknown feature_column_v2: NotExistingFeatureColumnClass'):
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serialization.deserialize_feature_column({
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'class_name': 'NotExistingFeatureColumnClass',
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'config': {}
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})
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def test_deserialization_deduping(self):
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price = fc.numeric_column('price')
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bucketized_price = fc.bucketized_column(price, boundaries=[0, 1])
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configs = serialization.serialize_feature_columns([price, bucketized_price])
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deserialized_feature_columns = serialization.deserialize_feature_columns(
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configs)
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self.assertLen(deserialized_feature_columns, 2)
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new_price = deserialized_feature_columns[0]
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new_bucketized_price = deserialized_feature_columns[1]
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# Ensure these are not the original objects:
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self.assertIsNot(price, new_price)
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self.assertIsNot(bucketized_price, new_bucketized_price)
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# But they are equivalent:
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self.assertEqual(price, new_price)
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self.assertEqual(bucketized_price, new_bucketized_price)
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# Check that deduping worked:
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self.assertIs(new_bucketized_price.source_column, new_price)
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def deserialization_custom_objects(self):
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# Note that custom_objects is also tested extensively above per class, this
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# test ensures that the public wrappers also handle it correctly.
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def _custom_fn(input_tensor):
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return input_tensor + 42.
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price = fc.numeric_column('price', normalizer_fn=_custom_fn)
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configs = serialization.serialize_feature_columns([price])
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deserialized_feature_columns = serialization.deserialize_feature_columns(
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configs)
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self.assertLen(deserialized_feature_columns, 1)
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new_price = deserialized_feature_columns[0]
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# Ensure these are not the original objects:
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self.assertIsNot(price, new_price)
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# But they are equivalent:
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self.assertEqual(price, new_price)
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# Check that normalizer_fn points to the correct function.
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self.assertIs(new_price.normalizer_fn, _custom_fn)
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if __name__ == '__main__':
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test.main()
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