code: def get_trainer(train_fn_name):
      """Get the corresponding trainer function.
  
      The returned train function has the following API:
      ```
        train_state, train_summary, eval_summary = train_fn(
          rng, model_cls, dataset, config, workdir, summary_writer)
      ```
      Where the train_state is a checkpointable state of training and train_summary,
      and eval_summary are python dictionary that contains metrics.
  
      Args:
        train_fn_name: str; Name of the train_fn_name, e.g.
          'classification_trainer'.
  
      Returns:
        The train function.
      Raises:
        ValueError if train_fn_name is unrecognized.
      """
      if train_fn_name not in ALL_TRAINERS.keys():
          raise ValueError(
              "Unrecognized trainer: {}".format(train_fn_name)
          )
      return ALL_TRAINERS[train_fn_name]
  
label_desc: Use image node_id 1 for calling a global function with example usage: get_trainer(train_fn_name) and returns: ALL_TRAINERS