class_docstr: *MUSDB_HQ* :cite:`MUSDB18HQ` dataset.
  
  Args:
      root (str or Path): Root directory where the dataset's top level directory is found
      subset (str): Subset of the dataset to use. Options: [``"train"``, ``"test"``].
      sources (List[str] or None, optional): Sources extract data from.
          List can contain the following options: [``"bass"``, ``"drums"``, ``"other"``, ``"mixture"``, ``"vocals"``].
          If ``None``, dataset consists of tracks except mixture.
          (default: ``None``)
      split (str or None, optional): Whether to split training set into train and validation set.
          If ``None``, no splitting occurs. If ``train`` or ``validation``, returns respective set.
          (default: ``None``)
      download (bool, optional): Whether to download the dataset if it is not found at root path.
          (default: ``False``)
code: def _load_sample(self, n: int) -> Tuple[torch.Tensor, int, int, str]:
      name = self.names[n]
      wavs = []
      num_frames = None
      for source in self.sources:
          track = self._get_track(name, source)
          wav, sr = torchaudio.load(str(track))
          if sr != _SAMPLE_RATE:
              raise ValueError(
                  f"expected sample rate {_SAMPLE_RATE}, but got {sr}"
              )
          if num_frames is None:
              num_frames = wav.shape[-1]
          else:
              if wav.shape[-1] != num_frames:
                  raise ValueError(
                      "num_frames do not match across sources"
                  )
          wavs.append(wav)
  
      stacked = torch.stack(wavs)
  
      return stacked, _SAMPLE_RATE, num_frames, name
  
file_path: audio/src/torchaudio/datasets/musdb_hq.py
imports: import os
  from pathlib import Path
  from typing import List, Optional, Tuple, Union
  import torch
  import torchaudio
  from torch.utils.data import Dataset
  from torchaudio._internal import download_url_to_file
  from torchaudio.datasets.utils import _extract_zip
label_desc: Use image node_id 3 for calling the MUSDB_HQ obj's underlying member method code with example usage: obj._load_sample(n) and returns: stacked,  _SAMPLE_RATE,  num_frames,  name