class_docstr: *Fluent Speech Commands* :cite:`fluent` dataset
  
  Args:
      root (str of Path): Path to the directory where the dataset is found.
      subset (str, optional): subset of the dataset to use.
          Options: [``"train"``, ``"valid"``, ``"test"``].
          (Default: ``"train"``)
class_docstr_tok: ["*","Fluent","Speech","Commands","*",":","cite",":","`","fluent","`","dataset","Args",":","root","(","str","of","Path",")",":","Path","to","the","directory","where","the","dataset","is","found",".","subset","(","str",",","optional",")",":","subset","of","the","dataset","to","use",".","Options",":","[","``","``","train","''","``",",","``","``","valid","''","``",",","``","``","test","''","``","]",".","(","Default",":","``","``","train","''","``",")"]
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
      str:
          File name
      int:
          Speaker ID
      str:
          Transcription
      str:
          Action
      str:
          Object
      str:
          Location
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","str",":","File","name","int",":","Speaker","ID","str",":","Transcription","str",":","Action","str",":","Object","str",":","Location"]
code: def __getitem__(
      self, n: int
  ) -> Tuple[Tensor, int, str, int, str, str, str, 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
          str:
              File name
          int:
              Speaker ID
          str:
              Transcription
          str:
              Action
          str:
              Object
          str:
              Location
      """
      metadata = self.get_metadata(n)
      waveform = _load_waveform(self._path, metadata[0], metadata[1])
      return (waveform,) + metadata[1:]
  
file_path: audio/src/torchaudio/datasets/fluentcommands.py
imports: import csv
  import os
  from pathlib import Path
  from typing import Tuple, Union
  from torch import Tensor
  from torch.utils.data import Dataset
  from torchaudio.datasets.utils import _load_waveform
label_desc: Use image node_id 4 for calling the FluentSpeechCommands obj's underlying member method code with example usage: obj.__getitem__(n) and returns: unknown