code: def launch_and_eval(opt, port):
      """
      Perform a fork() to many processes.
      """
      # Launch multiple subprocesses
      spawncontext = torch.multiprocessing.start_processes(
          multiprocess_eval,
          # need to give rank offset as 1 to cover the fact that the main
          # process is rank 0, but that spawn() doesn't let you control rank
          args=(opt, port, 1),
          nprocs=opt["distributed_world_size"]
          - 1,  # main proc will also run loop
          join=False,
          start_method="spawn",  # never fork, or will cause hangs with chunkteacher
      )
  
      try:
          retval = multiprocess_eval(0, opt, port)
          spawncontext.join()
          return retval
      except KeyboardInterrupt:
          # tell the subprocesses to stop too
          for p in spawncontext.processes:
              if p.is_alive():
                  os.kill(p.pid, signal.SIGINT)
          raise
  
file_path: ParlAI/parlai/scripts/multiprocessing_eval.py
imports: import torch
  import os
  import signal
  import parlai.scripts.eval_model
  import parlai.utils.distributed
  import parlai.utils.fsdp
  from parlai.core.script import ParlaiScript, register_script
label_desc: Use image node_id 2 for calling a global function with example usage: launch_and_eval(opt, port) and returns: retval