class_docstr: T5-based grapheme-to-phoneme model.
code: def setup_multiple_validation_data(
      self, val_data_config: Union[DictConfig, Dict] = None
  ):
      if (
          not val_data_config
          or val_data_config.manifest_filepath is None
      ):
          self._validation_dl = None
          return
      return super().setup_multiple_validation_data(val_data_config)
  
imports: from dataclasses import dataclass
  from typing import Any, Dict, List, Optional, Union
  import torch
  from hydra.utils import instantiate
  from omegaconf import DictConfig, OmegaConf
  from pytorch_lightning import Trainer
  from transformers import AutoTokenizer, T5ForConditionalGeneration
  from nemo.collections.asr.metrics.wer import word_error_rate
  from nemo.collections.tts.g2p.data.t5 import T5G2PDataset
  from nemo.collections.tts.models.base import G2PModel
  from nemo.core.classes.common import PretrainedModelInfo, typecheck
  from nemo.core.neural_types import LabelsType, LossType, MaskType, NeuralType, TokenIndex
  from nemo.utils import logging
label_desc: Use image node_id 18 for calling the T5G2PModel obj's underlying member method code with example usage: obj.setup_multiple_validation_data(val_data_config) and returns: super