code: def make_exp_dir(
      root_path: str,
      job_name: str,
      create: Optional[bool] = True,
  ):
      """
      Creates the exp dir of format e.g.,: root_path/2022_01_01/job_name_12_00_00/
      This function is to better organize the training runs. It is recommended to call this
      function and pass the returned "exp_dir" to "MultiModalPredictor.fit(save_path=exp_dir)".
  
      Parameters
      ----------
      root_path
          The basic path where to create saving directories for training runs.
      job_name
          The job names to name training runs.
      create
          Whether to make the directory.
  
      Returns
      -------
      The formatted directory path.
      """
      tz = pytz.timezone("US/Pacific")
      ct = datetime.datetime.now(tz=tz)
      date_stamp = ct.strftime("%Y_%m_%d")
      time_stamp = ct.strftime("%H_%M_%S")
  
      # Group logs by day first
      exp_dir = os.path.join(root_path, date_stamp)
  
      # Then, group by run_name and hour + min + sec to avoid duplicates
      exp_dir = os.path.join(exp_dir, "_".join([job_name, time_stamp]))
  
      if create:
          os.makedirs(exp_dir, mode=0o777, exist_ok=False)
  
      return exp_dir
  
file_path: autogluon/multimodal/src/autogluon/multimodal/utils/log.py
imports: import datetime
  import logging
  import os
  from contextlib import contextmanager
  from typing import Dict, List, Optional, Tuple, Union
  import pytz
  import torch
  from autogluon.common.utils.system_info import get_ag_system_info
label_desc: Use image node_id 1 for calling a global function with example usage: make_exp_dir(root_path, job_name, create) and returns: exp_dir