def load_pipeline_proto(filename):
"""Load pipeline proto file.
Args:
filename: path to the pipeline proto file.
Returns:
pipeline_proto: an instance of pipeline_pb2.Pipeline
"""
def _revise_name(filename, offset):
filename, postfix = filename.split('.record.')
filename = '{}.record.{}'.format(filename,
(int(postfix) + offset) % 10)
return filename
pipeline_proto = pipeline_pb2.Pipeline()
with open(filename, 'r') as fp:
text_format.Merge(fp.read(), pipeline_proto)
if FLAGS.number_of_steps > 0:
pipeline_proto.train_config.number_of_steps = FLAGS.number_of_steps
pipeline_proto.eval_config.number_of_steps = FLAGS.number_of_steps
pipeline_proto.example_reader.batch_size = 1
pipeline_proto.example_reader.num_epochs = 1
if FLAGS.split > -1:
for _ in xrange(4):
del pipeline_proto.example_reader.input_path[-1]
n_files = len(pipeline_proto.example_reader.input_path)
for i in xrange(n_files):
pipeline_proto.example_reader.input_path[i] = _revise_name(
pipeline_proto.example_reader.input_path[i], FLAGS.split + 8)
return pipeline_proto
def _load_pipeline_proto(filename):
"""Loads pipeline proto from file.
Args:
filename: Path to the pipeline config file.
Returns:
An instance of pipeline_pb2.Pipeline.
"""
with tf.io.gfile.GFile(filename, 'r') as fp:
return text_format.Merge(fp.read(), pipeline_pb2.Pipeline())
def load_pipeline_proto(filename):
"""Loads pipeline proto file.
Args:
filename: path to the pipeline proto file.
Returns:
pipeline_proto: an instance of pipeline_pb2.Pipeline
"""
pipeline_proto = pipeline_pb2.Pipeline()
with open(filename, 'r') as fp:
text_format.Merge(fp.read(), pipeline_proto)
if FLAGS.number_of_steps > 0:
pipeline_proto.train_config.number_of_steps = FLAGS.number_of_steps
pipeline_proto.eval_config.number_of_steps = FLAGS.number_of_steps
return pipeline_proto
