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| # 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. | |
| # ============================================================================== | |
| """Utility methods for accessing and operating on test data.""" | |
| from __future__ import absolute_import | |
| from __future__ import division | |
| from __future__ import print_function | |
| import os | |
| from absl import flags | |
| import tensorflow as tf | |
| from google.protobuf import text_format | |
| import input as seq2species_input | |
| from protos import seq2label_pb2 | |
| FLAGS = flags.FLAGS | |
| # Target names included in the example inputs. | |
| TEST_TARGETS = ['test_target_1', 'test_target_2'] | |
| def _as_bytes_feature(in_string): | |
| """Converts the given string to a tf.train.BytesList feature. | |
| Args: | |
| in_string: string to be converted to BytesList Feature. | |
| Returns: | |
| The TF BytesList Feature representing the given string. | |
| """ | |
| return tf.train.Feature(bytes_list=tf.train.BytesList(value=[in_string])) | |
| def create_tmp_train_file(num_examples, | |
| read_len, | |
| characters=seq2species_input.DNA_BASES, | |
| name='test.tfrecord'): | |
| """Write a test TFRecord of input examples to temporary test directory. | |
| The generated input examples are test tf.train.Example protos, each comprised | |
| of a toy sequence of length read_len and non-meaningful labels for targets in | |
| TEST_TARGETS. | |
| Args: | |
| num_examples: int; number of examples to write to test input file. | |
| read_len: int; length of test read sequences. | |
| characters: string; set of characters from which to construct test reads. | |
| Defaults to canonical DNA bases. | |
| name: string; filename for the test input file. | |
| Returns: | |
| Full path to the generated temporary test input file. | |
| """ | |
| tmp_path = os.path.join(FLAGS.test_tmpdir, name) | |
| with tf.python_io.TFRecordWriter(tmp_path) as writer: | |
| for i in xrange(num_examples): | |
| char = characters[i % len(characters)] | |
| features_dict = {'sequence': _as_bytes_feature(char * read_len)} | |
| for target_name in TEST_TARGETS: | |
| nonsense_label = _as_bytes_feature(str(i)) | |
| features_dict[target_name] = nonsense_label | |
| tf_features = tf.train.Features(feature=features_dict) | |
| example = tf.train.Example(features=tf_features) | |
| writer.write(example.SerializeToString()) | |
| return tmp_path | |
| def create_tmp_metadata(num_examples, read_len): | |
| """Write a test Seq2LabelDatasetInfo test proto to temporary test directory. | |
| Args: | |
| num_examples: int; number of example labels to write into test metadata. | |
| read_len: int; length of test read sequences. | |
| Returns: | |
| Full path to the generated temporary test file containing the | |
| Seq2LabelDatasetInfo text proto. | |
| """ | |
| dataset_info = seq2label_pb2.Seq2LabelDatasetInfo( | |
| read_length=read_len, | |
| num_examples=num_examples, | |
| read_stride=1, | |
| dataset_path='test.tfrecord') | |
| for target in TEST_TARGETS: | |
| dataset_info.labels.add( | |
| name=target, values=[str(i) for i in xrange(num_examples)]) | |
| tmp_path = os.path.join(FLAGS.test_tmpdir, 'test.pbtxt') | |
| with tf.gfile.GFile(tmp_path, 'w') as f: | |
| f.write(text_format.MessageToString(dataset_info)) | |
| return tmp_path | |