code: def begin_task_train(
      task_config: dict, experiment_name: str, recorder_name: str = None
  ) -> Recorder:
      """
      Begin task training to start a recorder and save the task config.
  
      Args:
          task_config (dict): the config of a task
          experiment_name (str): the name of experiment
          recorder_name (str): the given name will be the recorder name. None for using rid.
  
      Returns:
          Recorder: the model recorder
      """
      with R.start(
          experiment_name=experiment_name, recorder_name=recorder_name
      ):
          _log_task_info(task_config)
          return R.get_recorder()
  
imports: import socket
  from typing import Callable, List, Optional
  from tqdm.auto import tqdm
  from qlib.config import C
  from qlib.data.dataset import Dataset
  from qlib.data.dataset.weight import Reweighter
  from qlib.log import get_module_logger
  from qlib.model.base import Model
  from qlib.utils import auto_filter_kwargs, fill_placeholder, flatten_dict, init_instance_by_config
  from qlib.utils.paral import call_in_subproc
  from qlib.workflow import R
  from qlib.workflow.recorder import Recorder
  from qlib.workflow.task.manage import TaskManager, run_task
label_desc: Use image node_id 3 for calling a global function with example usage: begin_task_train(task_config, experiment_name, recorder_name) and returns: R