code: def add_asr_eval_argument(parser):
      parser.add_argument(
          "--kspmodel", default=None, help="sentence piece model"
      )
      parser.add_argument(
          "--wfstlm",
          default=None,
          help="wfstlm on dictonary output units",
      )
      parser.add_argument(
          "--rnnt_decoding_type",
          default="greedy",
          help="wfstlm on dictonary\
  output units",
      )
      try:
          parser.add_argument(
              "--lm-weight",
              "--lm_weight",
              type=float,
              default=0.2,
              help="weight for lm while interpolating with neural score",
          )
      except:
          pass
      parser.add_argument(
          "--rnnt_len_penalty",
          default=-0.5,
          help="rnnt length penalty on word level",
      )
      parser.add_argument(
          "--w2l-decoder",
          choices=["viterbi", "kenlm", "fairseqlm"],
          help="use a w2l decoder",
      )
      parser.add_argument("--lexicon", help="lexicon for w2l decoder")
      parser.add_argument(
          "--unit-lm", action="store_true", help="if using a unit lm"
      )
      parser.add_argument(
          "--kenlm-model", "--lm-model", help="lm model for w2l decoder"
      )
      parser.add_argument("--beam-threshold", type=float, default=25.0)
      parser.add_argument("--beam-size-token", type=float, default=100)
      parser.add_argument("--word-score", type=float, default=1.0)
      parser.add_argument("--unk-weight", type=float, default=-math.inf)
      parser.add_argument("--sil-weight", type=float, default=0.0)
      parser.add_argument(
          "--dump-emissions",
          type=str,
          default=None,
          help="if present, dumps emissions into this file and exits",
      )
      parser.add_argument(
          "--dump-features",
          type=str,
          default=None,
          help="if present, dumps features into this file and exits",
      )
      parser.add_argument(
          "--load-emissions",
          type=str,
          default=None,
          help="if present, loads emissions from this file",
      )
      return parser
  
imports: import ast
  import logging
  import math
  import os
  import sys
  import editdistance
  import numpy
  import torch
  from fairseq import checkpoint_utils, options, progress_bar, tasks, utils
  from fairseq.data.data_utils import post_process
  from fairseq.logging.meters import StopwatchMeter, TimeMeter
label_desc: Use image node_id 1 for calling a global function with example usage: add_asr_eval_argument(parser) and returns: parser