docstr: Merge two ARPA n-gram language models using the ngrammerge command-line tool and output the result in ARPA format.
  
  Args:
      arpa_a (str): Path to the first input ARPA file.
      alpha (float): Interpolation weight for the first model.
      arpa_b (str): Path to the second input ARPA file.
      beta (float): Interpolation weight for the second model.
      arpa_c (str): Path to the output ARPA file.
      force (bool): Whether to overwrite existing output files.
  
  Returns:
      str: Path to the output ARPA file in mod format.
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code: def ngrammerge(
      self,
      arpa_a: str,
      alpha: float,
      arpa_b: str,
      beta: float,
      arpa_c: str,
      force: bool,
  ) -> str:
      """
      Merge two ARPA n-gram language models using the ngrammerge command-line tool and output the result in ARPA format.
  
      Args:
          arpa_a (str): Path to the first input ARPA file.
          alpha (float): Interpolation weight for the first model.
          arpa_b (str): Path to the second input ARPA file.
          beta (float): Interpolation weight for the second model.
          arpa_c (str): Path to the output ARPA file.
          force (bool): Whether to overwrite existing output files.
  
      Returns:
          str: Path to the output ARPA file in mod format.
      """
      mod_a = arpa_a + ".mod"
      mod_b = arpa_b + ".mod"
      mod_c = arpa_c + ".mod"
      if os.path.isfile(mod_c) and not force:
          logging.info("File " + mod_c + " exists. Skipping.")
      else:
          sh_args = [
              os.path.join(self.ngram_bin_path, "ngrammerge"),
              "--alpha=" + str(alpha),
              "--beta=" + str(beta),
              "--normalize",
              # "--use_smoothing",
              mod_a,
              mod_b,
              mod_c,
          ]
          logging.info(
              "\n"
              + str(
                  subprocess.run(
                      sh_args,
                      capture_output=False,
                      text=True,
                      stdout=sys.stdout,
                      stderr=sys.stderr,
                  )
              )
              + "\n",
          )
      return mod_c
  
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 2 for calling the NgramMerge obj's underlying member method code with example usage: obj.ngrammerge(arpa_a, alpha, arpa_b, beta, arpa_c, force) and returns: mod_c