code: def main():
      args = parse_args()
  
      # set PyTorch distributed related environmental variables
      current_env = os.environ.copy()
      current_env["WORLD_SIZE"] = str(args.world_size)
  
      processes = []
  
      # Use random file so multiple jobs can be run simultaneously
      INIT_METHOD = "file:///tmp/crypten-rendezvous-{}".format(
          uuid.uuid1()
      )
  
      for rank in range(0, args.world_size):
          # each process's rank
          current_env["RANK"] = str(rank)
          current_env["RENDEZVOUS"] = INIT_METHOD
  
          # spawn the processes
          cmd = [args.training_script] + args.training_script_args
  
          process = subprocess.Popen(cmd, env=current_env)
          processes.append(process)
  
      for process in processes:
          process.wait()
          if process.returncode != 0:
              raise subprocess.CalledProcessError(
                  returncode=process.returncode, cmd=process.args
              )
  
imports: import os
  import subprocess
  import uuid
  from argparse import ArgumentParser, REMAINDER
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types