def get_configs_from_pipeline_file():
"""Reads training configuration from a os_pipeline_pb2.CoLocTrainEvalPipelineConfig.
Reads training config from file specified by pipeline_config_path flag.
Returns:
model_config: attention_model_pb2.CoLocDetectionModel
train_config: train_pb2.TrainConfig
input_config: coloc_input_reader_pb2.CoLocInputReader
"""
pipeline_config = attention_pipeline_pb2.AttentionTrainEvalPipelineConfig()
with tf.gfile.GFile(FLAGS.pipeline_config_path, 'r') as f:
text_format.Merge(f.read(), pipeline_config)
model_config = pipeline_config.model
train_config = pipeline_config.train_config
input_config = pipeline_config.train_input_reader
return model_config, train_config, input_config
def get_configs_from_pipeline_file():
"""Reads evaluation configuration from a pipeline_pb2.TrainEvalPipelineConfig.
Reads evaluation config from file specified by pipeline_config_path flag.
Returns:
model_config: a model_pb2.DetectionModel
eval_config: a eval_pb2.EvalConfig
input_config: a input_reader_pb2.InputReader
"""
pipeline_config = attention_pipeline_pb2.AttentionTrainEvalPipelineConfig()
with tf.gfile.GFile(FLAGS.pipeline_config_path, 'r') as f:
text_format.Merge(f.read(), pipeline_config)
model_config = pipeline_config.model
if FLAGS.eval_training_data:
eval_config = pipeline_config.train_config
else:
eval_config = pipeline_config.eval_config
input_config = pipeline_config.eval_input_reader
return model_config, eval_config, input_config
def read_pipeline_config(config_path):
pipeline_config = attention_pipeline_pb2.AttentionTrainEvalPipelineConfig()
assert os.path.exists(config_path), 'Config file does not exist'
with open(config_path, 'r') as f:
text_format.Merge(f.read(), pipeline_config)
return pipeline_config