code: def extract_result():
      result_dict = AutoVivification()
      speed_dict = AutoVivification()
      logs_list = glob.glob(os.path.join(args.log_dir, "*/workerlog.0"))
      for l in logs_list:
          extract_info_from_file(l, result_dict, speed_dict)
  
      # compute speedup
      compute_speedup(result_dict, speed_dict)
  
      # print result
      pp.pprint(result_dict)
  
      # write to file as JSON format
      os.makedirs(args.output_dir, exist_ok=True)
      result_file_name = os.path.join(
          args.output_dir, "arcface_paddle_result.json"
      )
      print("Saving result to {}".format(result_file_name))
      with open(result_file_name, "w") as f:
          json.dump(result_dict, f)
  
file_path: insightface/recognition/arcface_paddle/tools/extract_perf_logs.py
imports: import os
  import re
  import sys
  import glob
  import json
  import argparse
  import pprint
  import numpy
label_desc: Use image node_id 5 for calling a global function with example usage: extract_result() without return types