code: def get_args():
      """Retrieve arguments for disambiguation."""
      parser = argparse.ArgumentParser(
          "G2P disambiguation using Aligner input embedding distances."
      )
      # TODO(jocelynh): Make this required=False with default download from NGC once ckpt uploaded
      parser.add_argument(
          "--model",
          required=True,
          type=str,
          help="Path to Aligner model checkpoint (.nemo file).",
      )
      parser.add_argument(
          "--manifest",
          required=True,
          type=str,
          help="Path to data manifest. Each entry should contain the path to the audio file as well as the text in graphemes.",
      )
      parser.add_argument(
          "--out",
          required=True,
          type=str,
          help="Path to output file where disambiguations will be written.",
      )
      parser.add_argument(
          "--sr",
          required=False,
          default=22050,
          type=int,
          help="Target sample rate to load the dataset. Should match what the model was trained on.",
      )
      parser.add_argument(
          "--heteronyms",
          required=False,
          type=str,
          default="../../scripts/tts_dataset_files/heteronyms-052722",
          help="Heteronyms file to specify which words should be disambiguated. All others will use default pron.",
      )
      parser.add_argument(
          "--confidence",
          required=False,
          type=float,
          default=0.0,
          help="Confidence threshold to keep a disambiguation.",
      )
      parser.add_argument(
          "--verbose",
          action="store_true",
          help="If set to True, logs scores for each disambiguated word in disambiguation_logs.txt.",
      )
      args = parser.parse_args()
      return args
  
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 1 for calling a global function with example usage: get_args() and returns: args