class_docstr: Text-to-Text Iterable Dataset for hybrid ASR-TTS models
  Only part necessary for current process should be loaded and stored
class_docstr_tok: ["Text-to-Text","Iterable","Dataset","for","hybrid","ASR-TTS","models","Only","part","necessary","for","current","process","should","be","loaded","and","stored"]
code: def __init__(
      self,
      manifest_filepath: Union[AnyPath, List[AnyPath]],
      speakers_filepath: Union[AnyPath, List[AnyPath]],
      asr_tokenizer: TokenizerSpec,
      asr_use_start_end_token: bool,
      tts_parser: Callable,
      tts_text_pad_id: int,
      tts_text_normalizer: "Normalizer",
      tts_text_normalizer_call_kwargs: Dict,
      min_words: int = 1,
      max_words: int = 1_000_000,
      tokenizer_workers: int = 1,
      num_parts: int = 1,
      current_part_index: int = 0,
  ):
      super().__init__(
          manifest_filepath=manifest_filepath,
          speakers_filepath=speakers_filepath,
          asr_tokenizer=asr_tokenizer,
          asr_use_start_end_token=asr_use_start_end_token,
          tts_parser=tts_parser,
          tts_text_pad_id=tts_text_pad_id,
          tts_text_normalizer=tts_text_normalizer,
          tts_text_normalizer_call_kwargs=tts_text_normalizer_call_kwargs,
          min_words=min_words,
          max_words=max_words,
          tokenizer_workers=tokenizer_workers,
          num_parts=num_parts,
          current_part_index=current_part_index,
      )
  
imports: from __future__ import annotations
  import concurrent.futures
  import copy
  import gc
  import json
  import math
  import random
  from pathlib import Path
  from typing import Any, Callable, Dict, Iterable, List, NamedTuple, Optional, Set, Union
  import numpy
  import torch
  import torch.utils.data
  from torch.nn.utils.rnn import pad_sequence
  from tqdm.auto import tqdm
  from nemo.collections.asr.data.audio_to_text import _speech_collate_fn
  from nemo.collections.common.tokenizers import TokenizerSpec
  from nemo.core.classes import Dataset, IterableDataset
  from nemo.utils import logging
label_desc: Use image node_id 1 to create a new TextToTextIterableDataset object from inherited base classes: TextToTextDatasetBase, IterableDataset with example: obj = TextToTextIterableDataset(manifest_filepath, speakers_filepath, asr_tokenizer, asr_use_start_end_token, tts_parser, tts_text_pad_id, tts_text_normalizer, tts_text_normalizer_call_kwargs, min_words, max_words, tokenizer_workers, num_parts, current_part_index)