code: def main():
      args = get_args()
  
      # Check file paths from arguments
      if not os.path.exists(args.model):
          print("Could not find model checkpoint file: ", args.model)
      if not os.path.exists(args.manifest):
          print("Could not find data manifest file: ", args.manifest)
      if os.path.exists(args.out):
          print("Output file already exists: ", args.out)
          overwrite = input("Is it okay to overwrite it? (Y/N): ")
          if overwrite.lower() != "y":
              print("Not overwriting output file, quitting.")
              quit()
      if not os.path.exists(args.heteronyms):
          print("Could not find heteronyms list: ", args.heteronyms)
  
      # Read heteronyms list, one per line
      heteronyms = set()
      with open(args.heteronyms, "r") as f_het:
          for line in f_het:
              heteronyms.add(line.strip().lower())
  
      # Load model
      print("Restoring Aligner model from checkpoint...")
      device = torch.device(
          "cuda" if torch.cuda.is_available() else "cpu"
      )
      aligner = AlignerModel.restore_from(
          args.model, map_location=device
      )
  
      # Disambiguation
      print("Beginning disambiguation...")
      device = torch.device(
          "cuda:0" if torch.cuda.is_available() else "cpu"
      )
      disambiguate_dataset(
          aligner,
          args.manifest,
          args.out,
          args.sr,
          heteronyms,
          args.confidence,
          device,
          args.verbose,
      )
  
file_path: NeMo/examples/tts/aligner_heteronym_disambiguation.py
imports: import argparse
  import json
  import os
  import re
  import librosa
  import soundfile
  import torch
  from nemo.collections.tts.models import AlignerModel
  from nemo.collections.tts.parts.utils.tts_dataset_utils import general_padding
label_desc: Use image node_id 5 for calling a global function with example usage: main() without return types