code: def QuantizedLjSpeech(
      speech_encoder: Callable,
      root: Union[str, pathlib.Path],
      url: str = "https://data.keithito.com/data/speech/LJSpeech-1.1.tar.bz2",
      folder_in_archive: str = "wavs",
      download: bool = False,
      device: Optional[str] = None,
  ):
      dataset = LJSPEECH(root, url, folder_in_archive, download)
      return QuantizeDataset(dataset, speech_encoder, device)
  
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 3 for calling a global function with example usage: QuantizedLjSpeech(speech_encoder, root, url, folder_in_archive, download, device) and returns: QuantizeDataset