class_docstr: *IEMOCAP* :cite:`iemocap` dataset.
  
  Args:
      root (str or Path): Root directory where the dataset's top level directory is found
      sessions (Tuple[int]): Tuple of sessions (1-5) to use. (Default: ``(1, 2, 3, 4, 5)``)
      utterance_type (str or None, optional): Which type(s) of utterances to include in the dataset.
          Options: ("scripted", "improvised", ``None``). If ``None``, both scripted and improvised
          data are used.
code: def __len__(self):
      return len(self.data)
  
file_path: audio/src/torchaudio/datasets/iemocap.py
imports: import os
  import re
  from pathlib import Path
  from typing import Optional, 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 IEMOCAP obj's underlying member method code with example usage: obj.__len__() and returns: len