code: def agg_dict_list(dict_list):
      """Aggregate a list of dictionaries: mean + std
      Args:
          dict_list: list of dictionaries.
  
      """
      dict_agg = {"epoch": dict_list[0]["epoch"]}
      for key in dict_list[0]:
          if key != "epoch":
              value = np.array([dict[key] for dict in dict_list])
              dict_agg[key] = np.mean(value).round(cfg.round)
              dict_agg["{}_std".format(key)] = np.std(value).round(
                  cfg.round
              )
      return dict_agg
  
file_path: pytorch_geometric/torch_geometric/graphgym/utils/agg_runs.py
imports: import logging
  import os
  import os.path
  import numpy
  from torch_geometric.graphgym.config import cfg
  from torch_geometric.graphgym.utils.io import dict_list_to_json, dict_list_to_tb, dict_to_json, json_to_dict_list, makedirs_rm_exist, string_to_python
label_desc: Use image node_id 4 for calling a global function with example usage: agg_dict_list(dict_list) and returns: dict_agg