code: def generate_dummy_inputs():
      chars_seq = torch.randint(0, 24, (8, 128)).long().to(device)
      chars_seq_lengths = (
          torch.randint(100, 128, (8,)).long().to(device)
      )
      chars_seq_lengths = torch.sort(
          chars_seq_lengths, descending=True
      )[0]
      mel_spec = torch.rand(8, 30, c.audio["num_mels"]).to(device)
      mel_postnet_spec = torch.rand(8, 30, c.audio["num_mels"]).to(
          device
      )
      mel_lengths = torch.randint(20, 30, (8,)).long().to(device)
      stop_targets = torch.zeros(8, 30, 1).float().to(device)
      speaker_ids = torch.randint(0, 5, (8,)).long().to(device)
  
      chars_seq = tf.convert_to_tensor(chars_seq.cpu().numpy())
      chars_seq_lengths = tf.convert_to_tensor(
          chars_seq_lengths.cpu().numpy()
      )
      mel_spec = tf.convert_to_tensor(mel_spec.cpu().numpy())
      return (
          chars_seq,
          chars_seq_lengths,
          mel_spec,
          mel_postnet_spec,
          mel_lengths,
          stop_targets,
          speaker_ids,
      )
  
file_path: TTS/tests/test_tacotron2_tf_model.py
imports: import os
  import unittest
  import numpy
  import tensorflow
  import torch
  from tests import get_tests_input_path
  from TTS.tts.tf.models.tacotron2 import Tacotron2
  from TTS.tts.tf.utils.tflite import convert_tacotron2_to_tflite, load_tflite_model
  from TTS.utils.io import load_config
label_desc: Use image node_id 1 for calling the TacotronTFTrainTest obj's underlying member method code with example usage: obj.generate_dummy_inputs() and returns: chars_seq,  chars_seq_lengths,  mel_spec,  mel_postnet_spec,  mel_lengths,  stop_targets,  speaker_ids