code: def speed_test(corpus_path, vocab_size, algorithms, n_threads):
      train_res = {}
      infer_res = {}
      for algorithm in algorithms:
          time_train = check_train(
              algorithm, vocab_size, corpus_path, n_threads
          )
          time_infer = check_inference_file(
              algorithm, corpus_path, n_threads
          )
  
          train_res[algorithm] = time_train
          infer_res[algorithm] = time_infer
  
      return train_res, infer_res
  
imports: import argparse
  import os
  from pathlib import Path
  from time import time
  from tabulate import tabulate
  from tokenizers import pre_tokenizers
  from tokenizers import Tokenizer
  from tokenizers.models import BPE
  from tokenizers.trainers import BpeTrainer
label_desc: Use image node_id 6 for calling a global function with example usage: speed_test(corpus_path, vocab_size, algorithms, n_threads) and returns: train_res,  infer_res