# Copyright 2023 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. """File writer functions for dataset preparation, infra validation, and unit tests.""" import io from typing import Optional, Sequence, Union import tensorflow as tf, tf_keras def write_small_dataset(examples: Sequence[Union[tf.train.Example, tf.train.SequenceExample]], output_path: str, file_type: str = 'tfrecord') -> None: """Writes `examples` to a file at `output_path` with type `file_type`. CAVEAT: This function is not recommended for writing large datasets, since it will loop through `examples` and perform write operation sequentially. Args: examples: List of tf.train.Example or tf.train.SequenceExample. output_path: Output path for the dataset. file_type: A string indicating the file format, could be: 'tfrecord', 'tfrecords', 'tfrecord_compressed', 'tfrecords_gzip', 'riegeli'. The string is case insensitive. """ file_type = file_type.lower() if file_type == 'tfrecord' or file_type == 'tfrecords': _write_tfrecord(examples, output_path) elif file_type == 'tfrecord_compressed' or file_type == 'tfrecords_gzip': _write_tfrecord(examples, output_path, tf.io.TFRecordOptions(compression_type='GZIP')) elif file_type == 'riegeli': _write_riegeli(examples, output_path) else: raise ValueError(f'Unknown file_type: {file_type}') def _write_tfrecord(examples: Sequence[Union[tf.train.Example, tf.train.SequenceExample]], output_path: str, options: Optional[tf.io.TFRecordOptions] = None) -> None: """Writes `examples` to a TFRecord file at `output_path`. Args: examples: A list of tf.train.Example. output_path: Output path for the dataset. options: Options used for manipulating TFRecord files. """ with tf.io.TFRecordWriter(output_path, options) as writer: for example in examples: writer.write(example.SerializeToString()) def _write_riegeli(examples: Sequence[Union[tf.train.Example, tf.train.SequenceExample]], output_path: str) -> None: """Writes `examples` to a Riegeli file at `output_path`. Args: examples: A list of tf.train.Example. output_path: Output path for the dataset. """ with io.FileIO(output_path, 'wb') as fileio: import riegeli # pylint: disable=g-import-not-at-top with riegeli.RecordWriter(fileio) as writer: writer.write_messages(examples)