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# Copyright 2017 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.
# ==============================================================================
"""Generate a synthetic dataset."""
import os
import numpy as np
from six.moves import xrange
import tensorflow as tf
import synthetic_model
FLAGS = tf.app.flags.FLAGS
tf.app.flags.DEFINE_string(
'dataset_dir', None,
"""Directory where to write the dataset and the configs.""")
tf.app.flags.DEFINE_integer(
'count', 1000,
"""Number of samples to generate.""")
def int64_feature(values):
"""Returns a TF-Feature of int64s.
Args:
values: A scalar or list of values.
Returns:
A TF-Feature.
"""
if not isinstance(values, (tuple, list)):
values = [values]
return tf.train.Feature(int64_list=tf.train.Int64List(value=values))
def float_feature(values):
"""Returns a TF-Feature of floats.
Args:
values: A scalar of list of values.
Returns:
A TF-Feature.
"""
if not isinstance(values, (tuple, list)):
values = [values]
return tf.train.Feature(float_list=tf.train.FloatList(value=values))
def AddToTFRecord(code, tfrecord_writer):
example = tf.train.Example(features=tf.train.Features(feature={
'code_shape': int64_feature(code.shape),
'code': float_feature(code.flatten().tolist()),
}))
tfrecord_writer.write(example.SerializeToString())
def GenerateDataset(filename, count, code_shape):
with tf.python_io.TFRecordWriter(filename) as tfrecord_writer:
for _ in xrange(count):
code = synthetic_model.GenerateSingleCode(code_shape)
# Convert {0,1} codes to {-1,+1} codes.
code = 2.0 * code - 1.0
AddToTFRecord(code, tfrecord_writer)
def main(argv=None): # pylint: disable=unused-argument
GenerateDataset(os.path.join(FLAGS.dataset_dir + '/synthetic_dataset'),
FLAGS.count,
[35, 48, 8])
if __name__ == '__main__':
tf.app.run()
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