class_docstr: Pytorch Dataset class for ESPNet.
  
  Examples:
      >>> dataset = IterableESPnetDataset([('wav.scp', 'input', 'sound'),
      ...                                  ('token_int', 'output', 'text_int')],
      ...                                )
      >>> for uid, data in dataset:
      ...     data
      {'input': per_utt_array, 'output': per_utt_array}
class_docstr_tok: ["Pytorch","Dataset","class","for","ESPNet",".","Examples",":",">",">",">","dataset","=","IterableESPnetDataset","(","[","(","'wav.scp","'",",","'input","'",",","'sound","'",")",",","...","(","'token_int","'",",","'output","'",",","'text_int","'",")","]",",","...",")",">",">",">","for","uid",",","data","in","dataset",":","...","data","{","'input","'",":","per_utt_array",",","'output","'",":","per_utt_array","}"]
code: def names(self) -> Tuple[str, ...]:
      return tuple(self.debug_info)
  
file_path: espnet/espnet2/train/iterable_dataset.py
imports: import copy
  from io import StringIO
  from pathlib import Path
  from typing import Callable, Collection, Dict, Iterator, Tuple, Union
  import kaldiio
  import numpy
  import soundfile
  import torch
  from torch.utils.data.dataset import IterableDataset
  from typeguard import check_argument_types
  from espnet2.train.dataset import ESPnetDataset
label_desc: Use image node_id 3 for calling the IterableESPnetDataset obj's underlying member method code with example usage: obj.names() and returns: tuple