code: def get_args():
      parser = argparse.ArgumentParser(
          formatter_class=argparse.ArgumentDefaultsHelpFormatter,
          description="Download Thorsten Müller's neutral voice dataset and create manifests with predefined split. "
          "Thorsten Müller published two neural voice datasets, 21.02 and 22.10, where 22.10 provides better "
          "audio quality. Please choose one of the two for your TTS models. Details about the dataset are "
          "in https://github.com/thorstenMueller/Thorsten-Voice.",
      )
      parser.add_argument(
          "--data-root",
          required=True,
          type=Path,
          help="where the resulting dataset will reside.",
      )
      parser.add_argument(
          "--manifests-root",
          required=True,
          type=Path,
          help="where the manifests files will reside.",
      )
      parser.add_argument(
          "--data-version",
          default="22_10",
          choices=["21_02", "22_10"],
          type=str,
      )
      parser.add_argument("--min-duration", default=0.1, type=float)
      parser.add_argument(
          "--max-duration", default=float("inf"), type=float
      )
      parser.add_argument("--val-size", default=100, type=int)
      parser.add_argument("--test-size", default=100, type=int)
      parser.add_argument(
          "--num-workers",
          default=-1,
          type=int,
          help="Specify the max number of concurrent Python worker processes. "
          "If -1 all CPUs are used. If 1 no parallel computing is used.",
      )
      parser.add_argument(
          "--normalize-text",
          default=False,
          action="store_true",
          help="Normalize original text and add a new entry 'normalized_text' to .json file if True.",
      )
      parser.add_argument(
          "--seed-for-ds-split",
          default=100,
          type=float,
          help="Seed for deterministic split of train/dev/test, NVIDIA's default is 100.",
      )
      args = parser.parse_args()
      return args
  
file_path: NeMo/scripts/dataset_processing/tts/thorsten_neutral/get_data.py
imports: import argparse
  import json
  import random
  import shutil
  import subprocess
  import urllib.request
  from pathlib import Path
  from joblib import Parallel, delayed
  from tqdm import tqdm
  from nemo.utils import logging
label_desc: Use image node_id 1 for calling a global function with example usage: get_args() and returns: args