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``)
docstr: Load the n-th sample from the dataset.
  
  Args:
      n (int): The index of the sample to be loaded
  Returns:
      Tuple of the following items;
  
      Tensor:
          Waveform
      int:
          Sample rate
      int:
          Num frames
      str:
          Track name
docstr_tok: ["Load","the","n-th","sample","from","the","dataset",".","Args",":","n","(","int",")",":","The","index","of","the","sample","to","be","loaded","Returns",":","Tuple","of","the","following","items",";","Tensor",":","Waveform","int",":","Sample","rate","int",":","Num","frames","str",":","Track","name"]
code: def __getitem__(self, n: int) -> Tuple[torch.Tensor, int, int, str]:
      """Load the n-th sample from the dataset.
  
      Args:
          n (int): The index of the sample to be loaded
      Returns:
          Tuple of the following items;
  
          Tensor:
              Waveform
          int:
              Sample rate
          int:
              Num frames
          str:
              Track name
      """
      return self._load_sample(n)
  
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 5 for calling the MUSDB_HQ obj's underlying member method code with example usage: obj.__getitem__(n) and returns: self