code: def test_transition_model(self):
      model = self._get_transition_model()
      (
          input_dummy,
          input_lengths,
          mel_spec,
          mel_lengths,
      ) = self._get_embedded_input()
      prev_t_log_scaled_alph = torch.randn(
          input_dummy.shape[0], input_lengths.max()
      ).to(device)
      transition_vector = torch.randn(input_lengths.max()).to(device)
      out = model(
          prev_t_log_scaled_alph, transition_vector, input_lengths
      )
      self.assertEqual(
          out.shape, (input_dummy.shape[0], input_lengths.max())
      )
  
imports: import os
  import random
  import unittest
  from copy import deepcopy
  import torch
  from tests import get_tests_output_path
  from TTS.tts.configs.overflow_config import OverflowConfig
  from TTS.tts.layers.overflow.common_layers import Encoder, Outputnet, OverflowUtils
  from TTS.tts.layers.overflow.decoder import Decoder
  from TTS.tts.layers.overflow.neural_hmm import EmissionModel, NeuralHMM, TransitionModel
  from TTS.tts.models.overflow import Overflow
  from TTS.tts.utils.helpers import sequence_mask
  from TTS.utils.audio import AudioProcessor
label_desc: Use image node_id 13 for calling the TestNeuralHMM obj's underlying member method code with example usage: obj.test_transition_model() without return types