code: def _parse_args():
      parser = argparse.ArgumentParser(
          description=__doc__,
      )
      parser.add_argument(
          "--model-file",
          required=True,
          help="Path to the input pretrained weight file.",
      )
      parser.add_argument(
          "--dict-dir",
          help=(
              "Path to the directory in which `dict.ltr.txt` file is found. "
              "Required only when the model is finetuned."
          ),
      )
      parser.add_argument(
          "--output-path",
          help="Path to the directory, where the TorchScript-ed pipelines are saved.",
      )
      parser.add_argument(
          "--test-file",
          help="Path to a test audio file.",
      )
      parser.add_argument(
          "--debug",
          action="store_true",
          help=(
              "When enabled, individual components are separately tested "
              "for the numerical compatibility and TorchScript compatibility."
          ),
      )
      parser.add_argument(
          "--quantize",
          action="store_true",
          help="Apply quantization to model.",
      )
      parser.add_argument(
          "--optimize-for-mobile",
          action="store_true",
          help="Apply optmization for mobile.",
      )
      return parser.parse_args()
  
imports: import argparse
  import logging
  import os
  from typing import Tuple
  import fairseq
  import torch
  import torchaudio
  from greedy_decoder import Decoder
  from torch.utils.mobile_optimizer import optimize_for_mobile
  from torchaudio.models.wav2vec2.utils.import_fairseq import import_fairseq_model
label_desc: Use image node_id 1 for calling a global function with example usage: _parse_args() and returns: parser