code: def print_statistics(statistics, function_name):
      print(f"(E) | {function_name}:", end=" ")
      for i, key in enumerate(statistics.keys()):
          mean = statistics[key]["mean"]
          std = statistics[key]["std"]
          print(f"{key}={mean:.4f}+-{std:.4f}", end="")
          if i != len(statistics.keys()) - 1:
              print(",", end=" ")
          else:
              print()
  
file_path: dgl/examples/pytorch/grace/eval.py
imports: import functools
  import numpy
  from sklearn.linear_model import LogisticRegression
  from sklearn.metrics import f1_score
  from sklearn.model_selection import GridSearchCV, train_test_split
  from sklearn.multiclass import OneVsRestClassifier
  from sklearn.preprocessing import normalize, OneHotEncoder
label_desc: Use image node_id 3 for calling a global function with example usage: print_statistics(statistics, function_name) without return types