code: def main():
      parser = argparse.ArgumentParser()
  
      parser.add_argument(
          "--model_name",
          type=str,
          default="arijitx/wav2vec2-xls-r-300m-bengali",
          help="wav2vec model name",
      )
      parser.add_argument(
          "--wav_dir",
          type=str,
          default="./wavs",
          help="directory containing wavs",
      )
      parser.add_argument(
          "--text_file",
          type=str,
          default="script.txt",
          help="file containing text",
      )
      parser.add_argument(
          "--input_wavs_sr",
          type=int,
          default=16000,
          help="sampling rate of input audios",
      )
      parser.add_argument(
          "--output_dir",
          type=str,
          default="./out_alignment",
          help="output directory containing the alignment files",
      )
      parser.add_argument("--cuda", action="store_true")
  
      args = parser.parse_args()
  
      aligner = Wav2Vec2Aligner(
          args.model_name, args.input_wavs_sr, args.cuda
      )
      aligner.align_data(args.wav_dir, args.text_file, args.output_dir)
  
file_path: transformers/examples/research_projects/wav2vec2/alignment.py
imports: import argparse
  import os
  from dataclasses import dataclass
  import torch
  import torchaudio
  from tqdm import tqdm
  from transformers import AutoConfig, AutoModelForCTC, AutoProcessor
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types