code: def train(config_path: str, cl_arguments: Iterable[str], output_root: str) -> None:
      
      config = None
  
      try:
          config_path = find_config(config_path)
          config = load_config(config_file=config_path, additional_args=cl_arguments)
          validate_config(config)
          logging.debug('\tLoaded config: %s', config)
      except Exception as ex:  # pylint: disable=broad-except
          fallback('Loading config failed', ex)
  
      run(config=config, output_root=output_root)
docs: Load config and start the training.
  
      :param config_path: path to configuration file
      :param cl_arguments: additional command line arguments which will update the configuration
      :param output_root: output root in which the training directory will be created