code: def get_parser():
      parser = argparse.ArgumentParser(description="GSLM U2S tool")
      parser.add_argument(
          "--feature_type",
          type=str,
          choices=["logmel", "hubert", "w2v2", "cpc"],
          default=None,
          required=True,
          help="Acoustic feature type",
      )
      parser.add_argument(
          "--acoustic_model_path",
          type=str,
          help="Pretrained acoustic model checkpoint",
      )
      parser.add_argument(
          "--layer", type=int, help="Layer of acoustic model"
      )
      parser.add_argument(
          "--kmeans_model_path",
          type=str,
          required=True,
          help="K-means model file path to use for inference",
      )
      parser.add_argument(
          "--tts_model_path",
          type=str,
          help="TTS model file path to use for inference",
      )
      parser.add_argument(
          "--code_dict_path",
          type=str,
          help="Code dict file path to use for inference",
      )
      parser.add_argument(
          "--waveglow_path",
          type=str,
          help="Waveglow (vocoder) model file path to use for inference",
      )
      parser.add_argument("--max_decoder_steps", type=int, default=2000)
      parser.add_argument(
          "--denoiser_strength", type=float, default=0.1
      )
      return parser
  
file_path: fairseq/examples/textless_nlp/gslm/tools/resynthesize_speech.py
imports: import argparse
  import gc
  import logging
  import os
  import joblib
  import soundfile
  import torch
  from examples.textless_nlp.gslm.speech2unit.pretrained.utils import get_feature_reader
  from examples.textless_nlp.gslm.unit2speech.tts_data import TacotronInputDataset
  from examples.textless_nlp.gslm.unit2speech.utils import load_tacotron, load_waveglow, synthesize_audio
label_desc: Use image node_id 2 for calling a global function with example usage: get_parser() and returns: parser