code: def QuantizedVCTK_092(
      speech_encoder: Callable,
      root: Union[str, pathlib.Path],
      mic_id: Optional[str] = "mic2",
      download: bool = False,
      url: Optional[
          str
      ] = "https://datashare.is.ed.ac.uk/bitstream/handle/10283/3443/VCTK-Corpus-0.92.zip",
      audio_ext=".flac",
      device: Optional[str] = None,
  ):
      dataset = VCTK_092(root, mic_id, download, url, audio_ext)
      return QuantizeDataset(
          dataset,
          speech_encoder,
          device,
          speaker_extractor=default_speaker_vctk,
      )
  
imports: from typing import Callable, Union, Optional, Any, Dict, List
  import pathlib
  import torch
  import logging
  from torchaudio.datasets import LIBRISPEECH, LJSPEECH, COMMONVOICE, VCTK_092, YESNO
  from torch.utils.data import Dataset
  from textless.data.speech_encoder import SpeechEncoder
  from textless.data.collater_utils import collate_tensors
label_desc: Use image node_id 6 for calling a global function with example usage: QuantizedVCTK_092(speech_encoder, root, mic_id, download, url, audio_ext, device) and returns: QuantizeDataset