code: def main():
      import argparse
  
      parser = argparse.ArgumentParser(
          description="Megatron Checkpoint Utility Arguments",
          allow_abbrev=False,
          conflict_handler="resolve",
      )
  
      parser.add_argument(
          "--model-type",
          type=str,
          required=True,
          choices=["GPT", "BERT"],
          help="Type of the model",
      )
      parser.add_argument(
          "--loader",
          type=str,
          default="megatron",
          help="Module name to load checkpoint, should be on python path",
      )
      parser.add_argument(
          "--saver",
          type=str,
          default="megatron",
          help="Module name to save checkpoint, shdoul be on python path",
      )
      parser.add_argument(
          "--load-dir",
          type=str,
          required=True,
          help="Directory to load model checkpoint from",
      )
      parser.add_argument(
          "--save-dir",
          type=str,
          required=True,
          help="Directory to save model checkpoint to",
      )
      parser.add_argument(
          "--max-queue-size",
          type=int,
          default=50,
          help="Maximum number of tensors in the queue",
      )
      parser.add_argument(
          "--no-checking",
          action="store_false",
          help="Do not perform checking on the name and ordering of weights",
          dest="checking",
      )
  
      known_args, _ = parser.parse_known_args()
      loader = load_plugin("loader", known_args.loader)
      saver = load_plugin("saver", known_args.saver)
  
      loader.add_arguments(parser)
      saver.add_arguments(parser)
  
      args = parser.parse_args()
  
      queue = mp.Queue(maxsize=args.max_queue_size)
  
      print("Starting saver...")
      saver_proc = mp.Process(
          target=saver.save_checkpoint, args=(queue, args)
      )
      saver_proc.start()
  
      print("Starting loader...")
      loader.load_checkpoint(queue, args)
  
      print("Waiting for saver to complete...")
      saver_proc.join()
  
imports: import argparse
  import importlib
  import torch.multiprocessing
  import os
  import sys
label_desc: Use image node_id 2 for calling a global function with example usage: main() without return types