docstr: Test iterable text-to-text dataset with ASR and TTS tokenizers with normalized text
docstr_tok: ["Test","iterable","text-to-text","dataset","with","ASR","and","TTS","tokenizers","with","normalized","text"]
code: def test_text_to_text_iterable_dataset(
      self,
      textonly_manifest_path,
      tokenizer_workers,
      speakers_path,
      asr_tokenizer,
      tts_tokenizer,
      tts_normalizer,
      set_multiprocessing_method,
  ):
      """
      Test iterable text-to-text dataset with ASR and TTS tokenizers with normalized text
      """
      dataset = TextToTextIterableDataset(
          manifest_filepath=textonly_manifest_path,
          speakers_filepath=speakers_path,
          asr_tokenizer=asr_tokenizer,
          asr_use_start_end_token=False,
          tts_parser=tts_tokenizer,
          tts_text_pad_id=0,
          tts_text_normalizer=tts_normalizer,
          tts_text_normalizer_call_kwargs=dict(),
          tokenizer_workers=tokenizer_workers,
      )
      assert len(dataset) == 2
      item = next(iter(dataset))
      assert isinstance(item, TextToTextItem)
  
imports: import json
  import multiprocessing
  import os
  from dataclasses import dataclass, field
  from pathlib import Path
  import pytest
  from hydra.utils import instantiate
  from omegaconf import OmegaConf
  from nemo.collections.asr.data.text_to_text import TextToTextDataset, TextToTextItem, TextToTextIterableDataset
  from nemo.collections.common import tokenizers
label_desc: Use image node_id 3 for calling the TestTextToTextDataset obj's underlying member method code with example usage: obj.test_text_to_text_iterable_dataset(textonly_manifest_path, tokenizer_workers, speakers_path, asr_tokenizer, tts_tokenizer, tts_normalizer, set_multiprocessing_method) without return types