code: def main():
      """
      Call train.py as a new process and pass command arguments
      """
      parser = argparse.ArgumentParser()
      parser.add_argument(
          "--script",
          type=str,
          help="Target training script to distibute.",
      )
      parser.add_argument(
          "--continue_path",
          type=str,
          help='Training output folder to continue training. Use to continue a training. If it is used, "config_path" is ignored.',
          default="",
          required="--config_path" not in sys.argv,
      )
      parser.add_argument(
          "--restore_path",
          type=str,
          help="Model file to be restored. Use to finetune a model.",
          default="",
      )
      parser.add_argument(
          "--config_path",
          type=str,
          help="Path to config file for training.",
          required="--continue_path" not in sys.argv,
      )
      args = parser.parse_args()
  
      num_gpus = torch.cuda.device_count()
      group_id = time.strftime("%Y_%m_%d-%H%M%S")
  
      # set arguments for train.py
      folder_path = pathlib.Path(__file__).parent.absolute()
      command = [os.path.join(folder_path, args.script)]
      command.append("--continue_path={}".format(args.continue_path))
      command.append("--restore_path={}".format(args.restore_path))
      command.append("--config_path={}".format(args.config_path))
      command.append("--group_id=group_{}".format(group_id))
      command.append("")
  
      # run processes
      processes = []
      for i in range(num_gpus):
          my_env = os.environ.copy()
          my_env["PYTHON_EGG_CACHE"] = "/tmp/tmp{}".format(i)
          command[-1] = "--rank={}".format(i)
          stdout = None if i == 0 else open(os.devnull, "w")
          p = subprocess.Popen(
              ["python3"] + command, stdout=stdout, env=my_env
          )
          processes.append(p)
          print(command)
  
      for p in processes:
          p.wait()
  
imports: import os
  import sys
  import pathlib
  import time
  import subprocess
  import argparse
  import torch
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types