code: def print_config(config):
      print("**************** MODEL CONFIGURATION ****************")
      for key in sorted(config.keys()):
          val = config[key]
          keystr = "{}".format(key) + (" " * (24 - len(key)))
          print("{} -->   {}".format(keystr, val))
      print("**************** MODEL CONFIGURATION ****************")
  
imports: import os
  import pickle
  from collections import OrderedDict
  import numpy
  import torch
  import torch.nn
  import yaml
  from scipy import sparse
  from sklearn import preprocessing
  from graph4nlp.pytorch.data.data import GraphData
label_desc: Use image node_id 2 for calling a global function with example usage: print_config(config) without return types