code: def _parse_args():
      parser = argparse.ArgumentParser(
          description=__doc__,
          formatter_class=argparse.RawTextHelpFormatter,
      )
      parser.add_argument(
          "--librispeech_path",
          type=str,
          help="folder where LibriSpeech is stored",
      )
      parser.add_argument(
          "--split",
          type=str,
          help="LibriSpeech dataset split",
          choices=[
              "dev-clean",
              "dev-other",
              "test-clean",
              "test-other",
          ],
          default="test-other",
      )
      parser.add_argument(
          "--model",
          type=str,
          default="WAV2VEC2_ASR_BASE_960H",
          help="pretrained Wav2Vec2 model from torchaudio.pipelines",
      )
      parser.add_argument(
          "--nbest",
          type=int,
          default=1,
          help="number of best hypotheses to return",
      )
      parser.add_argument(
          "--beam-size",
          type=int,
          default=500,
          help="beam size for determining number of hypotheses to store",
      )
      parser.add_argument(
          "--beam-size-token",
          type=Optional[int],
          default=None,
          help="number of tokens to consider at each beam search step",
      )
      parser.add_argument(
          "--beam-threshold",
          type=int,
          default=50,
          help="beam threshold for pruning hypotheses",
      )
      parser.add_argument(
          "--lm-weight",
          type=float,
          default=1.74,
          help="languge model weight",
      )
      parser.add_argument(
          "--word-score",
          type=float,
          default=0.52,
          help="word insertion score",
      )
      parser.add_argument(
          "--unk_score",
          type=float,
          default=float("-inf"),
          help="unknown word insertion score",
      )
      parser.add_argument(
          "--sil_score",
          type=float,
          default=0,
          help="silence insertion score",
      )
      parser.add_argument(
          "--debug",
          action="store_true",
          help="whether to use debug level for logging",
      )
      return parser.parse_args()
  
file_path: audio/examples/asr/librispeech_ctc_decoder/inference.py
imports: import argparse
  import logging
  from typing import Optional
  import torch
  import torchaudio
  from torchaudio.models.decoder import ctc_decoder, download_pretrained_files
label_desc: Use image node_id 2 for calling a global function with example usage: _parse_args() and returns: parser