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Diffstat (limited to 'tensorflow/contrib/feature_column/python/feature_column/sequence_feature_column_integration_test.py')
| -rw-r--r-- | tensorflow/contrib/feature_column/python/feature_column/sequence_feature_column_integration_test.py | 280 |
1 files changed, 280 insertions, 0 deletions
diff --git a/tensorflow/contrib/feature_column/python/feature_column/sequence_feature_column_integration_test.py b/tensorflow/contrib/feature_column/python/feature_column/sequence_feature_column_integration_test.py new file mode 100644 index 0000000000..d8ca363627 --- /dev/null +++ b/tensorflow/contrib/feature_column/python/feature_column/sequence_feature_column_integration_test.py @@ -0,0 +1,280 @@ +# Copyright 2018 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. +# ============================================================================== +"""Integration test for sequence feature columns with SequenceExamples.""" + +from __future__ import absolute_import +from __future__ import division +from __future__ import print_function + +import string +import tempfile + +from google.protobuf import text_format + +from tensorflow.contrib.feature_column.python.feature_column import sequence_feature_column as sfc +from tensorflow.core.example import example_pb2 +from tensorflow.core.example import feature_pb2 +from tensorflow.python.data.ops import dataset_ops +from tensorflow.python.feature_column import feature_column as fc +from tensorflow.python.keras.layers import recurrent +from tensorflow.python.ops import parsing_ops +from tensorflow.python.ops import variables +from tensorflow.python.platform import test +from tensorflow.python.util import compat + + +class SequenceFeatureColumnIntegrationTest(test.TestCase): + + def _make_sequence_example(self): + example = example_pb2.SequenceExample() + example.context.feature['int_ctx'].int64_list.value.extend([5]) + example.context.feature['float_ctx'].float_list.value.extend([123.6]) + for val in range(0, 10, 2): + feat = feature_pb2.Feature() + feat.int64_list.value.extend([val] * val) + example.feature_lists.feature_list['int_list'].feature.extend([feat]) + for val in range(1, 11, 2): + feat = feature_pb2.Feature() + feat.bytes_list.value.extend([compat.as_bytes(str(val))] * val) + example.feature_lists.feature_list['str_list'].feature.extend([feat]) + + return example + + def _build_feature_columns(self): + col = fc.categorical_column_with_identity( + 'int_ctx', num_buckets=100) + ctx_cols = [ + fc.embedding_column(col, dimension=10), + fc.numeric_column('float_ctx')] + + identity_col = sfc.sequence_categorical_column_with_identity( + 'int_list', num_buckets=10) + bucket_col = sfc.sequence_categorical_column_with_hash_bucket( + 'bytes_list', hash_bucket_size=100) + seq_cols = [ + fc.embedding_column(identity_col, dimension=10), + fc.embedding_column(bucket_col, dimension=20)] + + return ctx_cols, seq_cols + + def test_sequence_example_into_input_layer(self): + examples = [_make_sequence_example().SerializeToString()] * 100 + ctx_cols, seq_cols = self._build_feature_columns() + + def _parse_example(example): + ctx, seq = parsing_ops.parse_single_sequence_example( + example, + context_features=fc.make_parse_example_spec(ctx_cols), + sequence_features=fc.make_parse_example_spec(seq_cols)) + ctx.update(seq) + return ctx + + ds = dataset_ops.Dataset.from_tensor_slices(examples) + ds = ds.map(_parse_example) + ds = ds.batch(20) + + # Test on a single batch + features = ds.make_one_shot_iterator().get_next() + + # Tile the context features across the sequence features + seq_layer, _ = sfc.sequence_input_layer(features, seq_cols) + ctx_layer = fc.input_layer(features, ctx_cols) + input_layer = sfc.concatenate_context_input(ctx_layer, seq_layer) + + rnn_layer = recurrent.RNN(recurrent.SimpleRNNCell(10)) + output = rnn_layer(input_layer) + + with self.cached_session() as sess: + sess.run(variables.global_variables_initializer()) + features_r = sess.run(features) + self.assertAllEqual(features_r['int_list'].dense_shape, [20, 3, 6]) + + output_r = sess.run(output) + self.assertAllEqual(output_r.shape, [20, 10]) + + +class SequenceExampleParsingTest(test.TestCase): + + def test_seq_ex_in_sequence_categorical_column_with_identity(self): + self._test_parsed_sequence_example( + 'int_list', sfc.sequence_categorical_column_with_identity, + 10, [3, 6], [2, 4, 6]) + + def test_seq_ex_in_sequence_categorical_column_with_hash_bucket(self): + self._test_parsed_sequence_example( + 'bytes_list', sfc.sequence_categorical_column_with_hash_bucket, + 10, [3, 4], [compat.as_bytes(x) for x in 'acg']) + + def test_seq_ex_in_sequence_categorical_column_with_vocabulary_list(self): + self._test_parsed_sequence_example( + 'bytes_list', sfc.sequence_categorical_column_with_vocabulary_list, + list(string.ascii_lowercase), [3, 4], + [compat.as_bytes(x) for x in 'acg']) + + def test_seq_ex_in_sequence_categorical_column_with_vocabulary_file(self): + _, fname = tempfile.mkstemp() + with open(fname, 'w') as f: + f.write(string.ascii_lowercase) + self._test_parsed_sequence_example( + 'bytes_list', sfc.sequence_categorical_column_with_vocabulary_file, + fname, [3, 4], [compat.as_bytes(x) for x in 'acg']) + + def _test_parsed_sequence_example( + self, col_name, col_fn, col_arg, shape, values): + """Helper function to check that each FeatureColumn parses correctly. + + Args: + col_name: string, name to give to the feature column. Should match + the name that the column will parse out of the features dict. + col_fn: function used to create the feature column. For example, + sequence_numeric_column. + col_arg: second arg that the target feature column is expecting. + shape: the expected dense_shape of the feature after parsing into + a SparseTensor. + values: the expected values at index [0, 2, 6] of the feature + after parsing into a SparseTensor. + """ + example = _make_sequence_example() + columns = [ + fc.categorical_column_with_identity('int_ctx', num_buckets=100), + fc.numeric_column('float_ctx'), + col_fn(col_name, col_arg) + ] + context, seq_features = parsing_ops.parse_single_sequence_example( + example.SerializeToString(), + context_features=fc.make_parse_example_spec(columns[:2]), + sequence_features=fc.make_parse_example_spec(columns[2:])) + + with self.cached_session() as sess: + ctx_result, seq_result = sess.run([context, seq_features]) + self.assertEqual(list(seq_result[col_name].dense_shape), shape) + self.assertEqual( + list(seq_result[col_name].values[[0, 2, 6]]), values) + self.assertEqual(list(ctx_result['int_ctx'].dense_shape), [1]) + self.assertEqual(ctx_result['int_ctx'].values[0], 5) + self.assertEqual(list(ctx_result['float_ctx'].shape), [1]) + self.assertAlmostEqual(ctx_result['float_ctx'][0], 123.6, places=1) + + +_SEQ_EX_PROTO = """ +context { + feature { + key: "float_ctx" + value { + float_list { + value: 123.6 + } + } + } + feature { + key: "int_ctx" + value { + int64_list { + value: 5 + } + } + } +} +feature_lists { + feature_list { + key: "bytes_list" + value { + feature { + bytes_list { + value: "a" + } + } + feature { + bytes_list { + value: "b" + value: "c" + } + } + feature { + bytes_list { + value: "d" + value: "e" + value: "f" + value: "g" + } + } + } + } + feature_list { + key: "float_list" + value { + feature { + float_list { + value: 1.0 + } + } + feature { + float_list { + value: 3.0 + value: 3.0 + value: 3.0 + } + } + feature { + float_list { + value: 5.0 + value: 5.0 + value: 5.0 + value: 5.0 + value: 5.0 + } + } + } + } + feature_list { + key: "int_list" + value { + feature { + int64_list { + value: 2 + value: 2 + } + } + feature { + int64_list { + value: 4 + value: 4 + value: 4 + value: 4 + } + } + feature { + int64_list { + value: 6 + value: 6 + value: 6 + value: 6 + value: 6 + value: 6 + } + } + } + } +} +""" + + +def _make_sequence_example(): + example = example_pb2.SequenceExample() + return text_format.Parse(_SEQ_EX_PROTO, example) + + +if __name__ == '__main__': + test.main() |