code: def test_forward_algorithm_variables(self):
      model = self._get_neural_hmm()
      (
          input_dummy,
          input_lengths,
          mel_spec,
          mel_lengths,
      ) = self._get_embedded_input()
  
      (
          log_c,
          log_alpha_scaled,
          transition_matrix,
          _,
      ) = model._initialize_forward_algorithm_variables(  # pylint: disable=protected-access
          mel_spec, input_dummy.shape[1] * config_global.state_per_phone
      )
  
      self.assertEqual(
          log_c.shape, (mel_spec.shape[0], mel_spec.shape[1])
      )
      self.assertEqual(
          log_alpha_scaled.shape,
          (
              mel_spec.shape[0],
              mel_spec.shape[1],
              input_dummy.shape[1] * config_global.state_per_phone,
          ),
      )
      self.assertEqual(
          transition_matrix.shape,
          (
              mel_spec.shape[0],
              mel_spec.shape[1],
              input_dummy.shape[1] * config_global.state_per_phone,
          ),
      )
  
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 9 for calling the TestNeuralHMM obj's underlying member method code with example usage: obj.test_forward_algorithm_variables() without return types