code: def get_cover_info():
      for model_path in track(
          model_paths, description="Collecting sets..."
      ):
          if not model_path[-1].isdigit():
              continue
          eval_json_path = os.path.join(
              LLM_HOME_PATH, model_path, "eval_results.json"
          )
          if not os.path.exists(eval_json_path):
              continue
          with open(eval_json_path, "r") as f:
              res = json.load(f)["eval"]
              for task_id, v in res.items():
                  for i_code, (status, res_list) in enumerate(
                      v["base"]
                  ):
                      if status == "success":
                          continue
                      code_id = hash(v["files"][i_code])
                      for i_test, res in enumerate(res_list):
                          test_id = f"base_{i_test}"
                          if res == False:
                              cover_info[task_id].setdefault(
                                  test_id, []
                              ).append(code_id)
                  for i_code, (status, res_list) in enumerate(
                      v["plus"]
                  ):
                      if status == "success":
                          continue
                      code_id = hash(v["files"][i_code])
                      for i_test, res in enumerate(res_list):
                          test_id = f"plus_{i_test}"
                          if res == False:
                              cover_info[task_id].setdefault(
                                  test_id, []
                              ).append(code_id)
  
imports: import json
  import os
  from rich.progress import track
  from evalplus.data import get_human_eval_plus, get_human_eval_plus_inputs
label_desc: Use image node_id 1 for calling a global function with example usage: get_cover_info() without return types