code: def gen_config(ni, config, configs):
      if ni >= len(param_names):
          configs.append(config.copy())
          return
      pname = param_names[ni]
      plist = grid_list[pname]
      for p in plist:
          config.append(p)
          gen_config(ni + 1, config, configs)
          config.pop()
  
file_path: AutoGL/test/nas/bench_mp.py
imports: import torch.multiprocessing
  from queue import Queue
  import time
  import random
  import os
  import pandas
label_desc: Use image node_id 2 for calling a global function with example usage: gen_config(ni, config, configs) without return types