code: def get_args(tmpdir, config_dict):
      parser = argparse.ArgumentParser()
      parser.add_argument("--local_rank", type=int, default=0)
      parser.add_argument("--zero", type=int, default=0)
      args = parser.parse_args()  # args=''
  
      config_dict["zero_optimization"]["stage"] = args.zero
      print(
          'config_dict["zero_optimization"]',
          config_dict["zero_optimization"],
      )
      config_path = create_config_from_dict(tmpdir, config_dict)
  
      args.deepspeed_config = config_path
      return args
  
file_path: H2O/h2o_flexgen/benchmark/third_party/DeepSpeed/tests/small_model_debugging/test_model.py
imports: import os
  import json
  import argparse
  import torch
  import deepspeed
  from torch.utils.data.distributed import DistributedSampler
  import deepspeed.comm
label_desc: Use image node_id 3 for calling a global function with example usage: get_args(tmpdir, config_dict) and returns: args