code: def __process_data(
      dataset_url: str, dataset_path: Path, manifest_output_path: Path
  ):
      os.makedirs(dataset_path, exist_ok=True)
      tar_file_path = os.path.join(
          dataset_path, os.path.basename(dataset_url)
      )
      if not os.path.exists(tar_file_path):
          wget.download(dataset_url, tar_file_path)
      extract_file(tar_file_path, str(dataset_path))
      wav_path = dataset_path / "converted_wav/"
      extracted_dir = Path(tar_file_path).stem.replace(".tar", "")
      flac_path = dataset_path / (extracted_dir + "/wav/")
      __process_flac_audio(flac_path, wav_path)
  
      audio_files = [
          os.path.join(os.path.abspath(wav_path), file)
          for file in os.listdir(str(wav_path))
      ]
      rttm_files = glob.glob(
          str(dataset_path / (extracted_dir + "/TextGrid/*.rttm"))
      )
      rttm_files = [os.path.abspath(file) for file in rttm_files]
  
      audio_list = dataset_path / "audio_files.txt"
      rttm_list = dataset_path / "rttm_files.txt"
      with open(audio_list, "w") as f:
          f.write("\n".join(audio_files))
      with open(rttm_list, "w") as f:
          f.write("\n".join(rttm_files))
      create_manifest(
          str(audio_list),
          manifest_output_path,
          rttm_path=str(rttm_list),
      )
  
file_path: NeMo/scripts/dataset_processing/speaker_tasks/get_aishell_diarization_data.py
imports: import argparse
  import glob
  import logging
  import os
  import tarfile
  from pathlib import Path
  import wget
  from sox import Transformer
  from nemo.collections.asr.parts.utils.manifest_utils import create_manifest
label_desc: Use image node_id 2 for calling a global function with example usage: __process_data(dataset_url, dataset_path, manifest_output_path) without return types