class_docstr: Tacotron 2 Model that is used to generate mel spectrograms from text
code: def setup_validation_data(self, cfg):
      self._validation_dl = self.__setup_dataloader_from_config(
          cfg, shuffle_should_be=False, name="validation"
      )
  
imports: import contextlib
  from dataclasses import dataclass, field
  from typing import Any, Dict, List, Optional
  import torch
  from hydra.utils import instantiate
  from omegaconf import MISSING, DictConfig, OmegaConf, open_dict
  from omegaconf.errors import ConfigAttributeError
  from pytorch_lightning.loggers import TensorBoardLogger, WandbLogger
  from torch import nn
  from nemo.collections.common.parts.preprocessing import parsers
  from nemo.collections.tts.losses.tacotron2loss import Tacotron2Loss
  from nemo.collections.tts.models.base import SpectrogramGenerator
  from nemo.collections.tts.parts.utils.helpers import g2p_backward_compatible_support, get_mask_from_lengths, tacotron2_log_to_tb_func, tacotron2_log_to_wandb_func
  from nemo.core.classes.common import PretrainedModelInfo, typecheck
  from nemo.core.neural_types.elements import AudioSignal, EmbeddedTextType, LengthsType, LogitsType, MelSpectrogramType, SequenceToSequenceAlignmentType
  from nemo.core.neural_types.neural_type import NeuralType
  from nemo.utils import logging, model_utils
label_desc: Use image node_id 15 for calling the Tacotron2Model obj's underlying member method code with example usage: obj.setup_validation_data(cfg) without return types