code: def check_test_split(test, data_dict, splitname):
      """find testing data in data_dict"""
  
      train_idx = []
      data = list(data_dict.keys())
      count = 0
      space = {}
      idx_space = {}
      for key in data:
          idx, start, end = key.split("-")
          idx_space[idx] = idx_space.get(idx, []) + [
              [str(start), str(end)]
          ]
          space[idx] = space.get(idx, []) + [[float(start), float(end)]]
  
      for key in test:
          idx, start, end = key.split("-")
          start, end = float(start), float(end)
          for list_idx, time in enumerate(space[idx]):
              if abs(start - time[0]) < 3 and abs(end - time[1]) < 3:
                  count += 1
                  time1, time2 = idx_space.get(idx)[list_idx]
                  data_dict[(f"{idx}-{time1}-{time2}")][
                      "split"
                  ] = splitname
                  break
  
      print(f"=> Test set = {count}/{len(test)}")
  
imports: import argparse
  import collections
  import itertools
  import os
  import random
  import re
  import sys
label_desc: Use image node_id 15 for calling a global function with example usage: check_test_split(test, data_dict, splitname) without return types