code: def input_example(self, max_batch=1, max_dim=400):
      par = next(self.model.parameters())
      inputs = sample_tts_input(
          self.export_config,
          par.device,
          max_batch=max_batch,
          max_dim=max_dim,
      )
      speaker = inputs.pop("speaker")
      inp = inputs["text"]
      pad_id = self.tokenizer.pad
      inp[inp == pad_id] = pad_id - 1 if pad_id > 0 else pad_id + 1
  
      inputs.update(
          {
              "speaker_id": speaker,
              "speaker_id_text": speaker,
              "speaker_id_attributes": speaker,
          }
      )
      new_inputs = {
          "text": inp,
          "batch_lengths": inputs["batch_lengths"],
          "speaker_id": speaker,
          "speaker_id_text": speaker,
          "speaker_id_attributes": speaker,
          "pitch": inputs["pitch"],
          "pace": inputs["pace"],
          "volume": inputs["volume"],
      }
  
      return (new_inputs,)
  
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 21 for calling the RadTTSModel obj's underlying member method code with example usage: obj.input_example(max_batch, max_dim) and returns: new_inputs