code: def print_json_pep_format(results):
      # print the AI-PEP format json string for each model
      for group_name, group_val in results.items():
          for model_name, run_time in group_val.items():
              # Output for AI-PEP
              num_iters = len(run_time["info"])
              info = run_time["info"].tolist()
              for i in range(num_iters):
                  print(
                      "Caffe2Observer "
                      + json.dumps(
                          {
                              "type": "NET",
                              "metric": group_name + "-" + model_name,
                              "unit": "ms",
                              "value": str(info[i]),
                          }
                      )
                  )
  
imports: import argparse
  import copy
  import gc
  import json
  import sys
  import time
  from collections import namedtuple
  import torch
  from torch.autograd.profiler import record_function
  from .fuser import set_fuser
  from .runner import get_nn_runners
label_desc: Use image node_id 8 for calling a global function with example usage: print_json_pep_format(results) without return types