code: def QuantizedYesNo(
      speech_encoder: Callable,
      root: Union[str, pathlib.Path],
      url: str = "http://www.openslr.org/resources/1/waves_yesno.tar.gz",
      folder_in_archive: str = "waves_yesno",
      download: bool = False,
      device: Optional[str] = None,
  ):
      dataset = YESNO(root, url, folder_in_archive, download)
      return QuantizeDataset(
          dataset, speech_encoder, device, speaker_extractor=no_speaker
      )
  
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 8 for calling a global function with example usage: QuantizedYesNo(speech_encoder, root, url, folder_in_archive, download, device) and returns: QuantizeDataset