class_docstr: *YesNo* :cite:`YesNo` dataset.
  
  Args:
      root (str or Path): Path to the directory where the dataset is found or downloaded.
      url (str, optional): The URL to download the dataset from.
          (default: ``"http://www.openslr.org/resources/1/waves_yesno.tar.gz"``)
      folder_in_archive (str, optional):
          The top-level directory of the dataset. (default: ``"waves_yesno"``)
      download (bool, optional):
          Whether to download the dataset if it is not found at root path. (default: ``False``).
class_docstr_tok: ["*","YesNo","*",":","cite",":","`","YesNo","`","dataset",".","Args",":","root","(","str","or","Path",")",":","Path","to","the","directory","where","the","dataset","is","found","or","downloaded",".","url","(","str",",","optional",")",":","The","URL","to","download","the","dataset","from",".","(","default",":","``","``","http",":","\/\/www.openslr.org\/resources\/1\/waves_yesno.tar.gz","''","``",")","folder_in_archive","(","str",",","optional",")",":","The","top-level","directory","of","the","dataset",".","(","default",":","``","``","waves_yesno","''","``",")","download","(","bool",",","optional",")",":","Whether","to","download","the","dataset","if","it","is","not","found","at","root","path",".","(","default",":","``","False","``",")","."]
code: def _load_item(self, fileid: str, path: str):
      labels = [int(c) for c in fileid.split("_")]
      file_audio = os.path.join(path, fileid + ".wav")
      waveform, sample_rate = torchaudio.load(file_audio)
      return waveform, sample_rate, labels
  
file_path: audio/src/torchaudio/datasets/yesno.py
imports: import os
  from pathlib import Path
  from typing import List, Tuple, Union
  import torchaudio
  from torch import Tensor
  from torch.utils.data import Dataset
  from torchaudio._internal import download_url_to_file
  from torchaudio.datasets.utils import _extract_tar
label_desc: Use image node_id 3 for calling the YESNO obj's underlying member method code with example usage: obj._load_item(fileid, path) and returns: waveform,  sample_rate,  labels