code: def cli_main(modify_parser=None):
      parser = options.get_training_parser()
      args = options.parse_args_and_arch(
          parser, modify_parser=modify_parser
      )
      if args.profile:
          with torch.cuda.profiler.profile():
              with torch.autograd.profiler.emit_nvtx():
                  distributed_utils.call_main(args, main)
      else:
          distributed_utils.call_main(args, main)
  
imports: import argparse
  import logging
  import math
  import os
  import random
  import sys
  import numpy
  import torch
  from fairseq import checkpoint_utils, distributed_utils, options, quantization_utils, tasks, utils
  from fairseq.data import iterators
  from fairseq.logging import meters, metrics, progress_bar
  from fairseq.model_parallel.megatron_trainer import MegatronTrainer
  from .ls_fs_gcq_trainer import LSTrainer
label_desc: Use image node_id 8 for calling a global function with example usage: cli_main(modify_parser) without return types