code: def main(
      kenlm_bin_path: str,
      ngram_bin_path: str,
      arpa_a: str,
      alpha: float,
      arpa_b: str,
      beta: float,
      out_path: str,
      test_file: str,
      symbols: str,
      nemo_model_file: str,
      force: bool,
  ) -> None:
      """
      Entry point function for merging ARPA format language models, testing perplexity, creating symbol list,
      and making ARPA and Kenlm models.
  
      Args:
      - kenlm_bin_path (str): The path to the Kenlm binary.
      - arpa_a (str): The path to the first ARPA format language model.
      - alpha (float): The weight given to the first language model during merging.
      - arpa_b (str): The path to the second ARPA format language model.
      - beta (float): The weight given to the second language model during merging.
      - out_path (str): The path where the output files will be saved.
      - test_file (str): The path to the file on which perplexity needs to be calculated.
      - symbols (str): The path to the file where symbol list for the tokenizer model will be saved.
      - nemo_model_file (str): The path to the NeMo model file.
      - force (bool): If True, overwrite existing files, otherwise skip the operations.
  
      Returns:
      - None
      """
      nm = NgramMerge(ngram_bin_path)
      mod_c, arpa_c = nm.merge(
          arpa_a, alpha, arpa_b, beta, out_path, force
      )
  
      if test_file and nemo_model_file:
          if not symbols:
              symbols = os.path.join(
                  out_path, os.path.split(nemo_model_file)[1] + ".syms"
              )
              make_symbol_list(nemo_model_file, symbols, force)
          for test_f in test_file.split(","):
              test_p = nm.test_perplexity(
                  mod_c, symbols, test_f, nemo_model_file, out_path
              )
              logging.info(
                  "Perplexity summary " + test_f + " : " + test_p
              )
  
      logging.info("Making ARPA and Kenlm model " + arpa_c)
      out = nm.make_arpa(mod_c, arpa_c, force)
      if out:
          logging.info("\n" + str(out) + "\n")
  
      out = make_kenlm(kenlm_bin_path, arpa_c, force)
      if out:
          logging.info("\n" + str(out) + "\n")
  
imports: import argparse
  import os
  import subprocess
  import sys
  from typing import Tuple
  import kenlm_utils
  import torch
  import nemo.collections.asr
  from nemo.collections.asr.modules.rnnt import RNNTDecoder
  from nemo.collections.asr.parts.submodules.ctc_beam_decoding import DEFAULT_TOKEN_OFFSET
  from nemo.utils import logging
label_desc: Use image node_id 4 for calling a global function with example usage: main(kenlm_bin_path, ngram_bin_path, arpa_a, alpha, arpa_b, beta, out_path, test_file, symbols, nemo_model_file, force) without return types