def create_configs_from_pipeline_proto(pipeline_config):
  """Creates a configs dictionary from pipeline_pb2.TrainEvalPipelineConfig.

  Args:
    pipeline_config: pipeline_pb2.TrainEvalPipelineConfig proto object.

  Returns:
    Dictionary of configuration objects. Keys are `model`, `train_config`,
      `train_input_config`, `eval_config`, `eval_input_configs`. Value are
      the corresponding config objects or list of config objects (only for
      eval_input_configs).
  """
  configs = {}
  configs["model"] = pipeline_config.model
  configs["train_config"] = pipeline_config.train_config
  configs["train_input_config"] = pipeline_config.train_input_reader
  configs["eval_config"] = pipeline_config.eval_config
  configs["eval_input_configs"] = pipeline_config.eval_input_reader
  # Keeps eval_input_config only for backwards compatibility. All clients should
  # read eval_input_configs instead.
  if configs["eval_input_configs"]:
    configs["eval_input_config"] = configs["eval_input_configs"][0]
  if pipeline_config.HasField("graph_rewriter"):
    configs["graph_rewriter_config"] = pipeline_config.graph_rewriter

  return configs
Creates a configs dictionary from pipeline_pb2.TrainEvalPipelineConfig.

  Args:
    pipeline_config: pipeline_pb2.TrainEvalPipelineConfig proto object.

  Returns:
    Dictionary of configuration objects. Keys are `model`, `train_config`,
      `train_input_config`, `eval_config`, `eval_input_configs`. Value are
      the corresponding config objects or list of config objects (only for
      eval_input_configs).
  
inference_api/src/main/object_detection/utils/config_util.py