code: def test_one_user(x):
      # user u's ratings for user u
      rating = x[0]
      # uid
      u = x[1]
      # user u's items in the training set
      try:
          training_items = data_generator.train_items[u]
      except Exception:
          training_items = []
      # user u's items in the test set
      user_pos_test = data_generator.test_set[u]
  
      all_items = set(range(ITEM_NUM))
  
      test_items = list(all_items - set(training_items))
  
      if args.test_flag == "part":
          r, auc = ranklist_by_heapq(
              user_pos_test, test_items, rating, Ks
          )
      else:
          r, auc = ranklist_by_sorted(
              user_pos_test, test_items, rating, Ks
          )
  
      return get_performance(user_pos_test, r, auc, Ks)
  
file_path: dgl/examples/pytorch/NGCF/NGCF/utility/batch_test.py
imports: import heapq
  import multiprocessing
  import utility.metrics
  from utility.load_data import *
  from utility.parser import parse_args
label_desc: Use image node_id 5 for calling a global function with example usage: test_one_user(x) and returns: get_performance