code: def parse_args():
      """
      Helper function parsing the command line options
      @retval ArgumentParser
      """
      parser = ArgumentParser(
          description="PyTorch distributed training launch "
          "helper utilty that will spawn up "
          "multiple distributed processes"
      )
  
      # Optional arguments for the launch helper
      parser.add_argument(
          "--nnodes",
          type=int,
          default=1,
          help="The number of nodes to use for distributed " "training",
      )
      parser.add_argument(
          "--node_rank",
          type=int,
          default=0,
          help="The rank of the node for multi-node distributed "
          "training",
      )
      parser.add_argument(
          "--nproc_per_node",
          type=int,
          default=1,
          help="The number of processes to launch on each node, "
          "for GPU training, this is recommended to be set "
          "to the number of GPUs in your system so that "
          "each process can be bound to a single GPU.",
      )
      parser.add_argument(
          "--master_addr",
          default="127.0.0.1",
          type=str,
          help="Master node (rank 0)'s address, should be either "
          "the IP address or the hostname of node 0, for "
          "single node multi-proc training, the "
          "--master_addr can simply be 127.0.0.1",
      )
      parser.add_argument(
          "--master_port",
          default=29500,
          type=int,
          help="Master node (rank 0)'s free port that needs to "
          "be used for communciation during distributed "
          "training",
      )
  
      # positional
      parser.add_argument(
          "training_script",
          type=str,
          help="The full path to the single GPU training "
          "program/script to be launched in parallel, "
          "followed by all the arguments for the "
          "training script",
      )
  
      # rest from the training program
      parser.add_argument("training_script_args", nargs=REMAINDER)
      return parser.parse_args()
  
file_path: DALI/docs/examples/use_cases/pytorch/efficientnet/multiproc.py
imports: import sys
  import subprocess
  import os
  import socket
  import time
  from argparse import ArgumentParser, REMAINDER
  import torch
label_desc: Use image node_id 1 for calling a global function with example usage: parse_args() and returns: parser