code: def batch_dict(self, batch_data):
      if len(batch_data) < 14:
          spk_id = (
              torch.tensor([0] * (batch_data[3]).size(0))
              .cuda()
              .to(self.device)
          )
          v_m = batch_data[9]
          p_v = batch_data[10]
      else:
          spk_id = batch_data[13]
          v_m = batch_data[9]
          p_v = batch_data[10]
      batch_data_dict = {
          "audio": batch_data[0],
          "audio_lens": batch_data[1],
          "text": batch_data[2],
          "text_lens": batch_data[3],
          "log_mel": batch_data[4],
          "log_mel_lens": batch_data[5],
          "align_prior_matrix": batch_data[6],
          "pitch": batch_data[7],
          "pitch_lens": batch_data[8],
          "voiced_mask": v_m,
          "p_voiced": p_v,
          "energy": batch_data[11],
          "energy_lens": batch_data[12],
          "speaker_id": spk_id,
      }
      return batch_data_dict
  
imports: import contextlib
  import torch
  from hydra.utils import instantiate
  from omegaconf import DictConfig, OmegaConf
  from pytorch_lightning import Trainer
  from pytorch_lightning.loggers import TensorBoardLogger
  from nemo.collections.common.tokenizers.text_to_speech.tts_tokenizers import BaseTokenizer
  from nemo.collections.tts.losses.radttsloss import AttentionBinarizationLoss, RADTTSLoss
  from nemo.collections.tts.models.base import SpectrogramGenerator
  from nemo.collections.tts.parts.utils.helpers import batch_from_ragged, g2p_backward_compatible_support, plot_alignment_to_numpy, regulate_len, sample_tts_input
  from nemo.core.classes import Exportable
  from nemo.core.classes.common import typecheck
  from nemo.core.neural_types.elements import Index, MelSpectrogramType, RegressionValuesType, TokenDurationType, TokenIndex
  from nemo.core.neural_types.neural_type import NeuralType
  from nemo.core.optim.radam import RAdam
  from nemo.utils import logging
  from nemo.utils.decorators import experimental
label_desc: Use image node_id 2 for calling the RadTTSModel obj's underlying member method code with example usage: obj.batch_dict(batch_data) and returns: batch_data_dict