code: def test_inference(self):
      model = self._get_neural_hmm()
      (
          input_dummy,
          input_lengths,
          mel_spec,
          mel_lengths,
      ) = self._get_embedded_input()
      for temp in [0.334, 0.667, 1.0]:
          outputs = model.inference(
              input_dummy,
              input_lengths,
              temp,
              config_global.max_sampling_time,
              config_global.duration_threshold,
          )
          self.assertEqual(
              outputs["hmm_outputs"].shape[-1],
              outputs["input_parameters"][0][0][0].shape[-1],
          )
          self.assertEqual(
              outputs["output_parameters"][0][0][0].shape[-1],
              outputs["input_parameters"][0][0][0].shape[-1],
          )
          self.assertEqual(
              len(outputs["alignments"]), input_dummy.shape[0]
          )
  
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 11 for calling the TestNeuralHMM obj's underlying member method code with example usage: obj.test_inference() without return types