code: def _test_inference_with_MAS(self, batch_size):
      (
          input_dummy,
          input_lengths,
          mel_spec,
          mel_lengths,
          speaker_ids,
      ) = self._create_inputs(batch_size)
      # create model
      config = GlowTTSConfig(num_chars=32)
      model = GlowTTS(config).to(device)
      model.eval()
      # inference encoder and decoder with MAS
      y = model.inference_with_MAS(
          input_dummy, input_lengths, mel_spec, mel_lengths
      )
      y2 = model.decoder_inference(mel_spec, mel_lengths)
      assert (
          y2["model_outputs"].shape == y["model_outputs"].shape
      ), "Difference between the shapes of the glowTTS inference with MAS ({}) and the inference using only the decoder ({}) !!".format(
          y["model_outputs"].shape, y2["model_outputs"].shape
      )
  
imports: import copy
  import os
  import unittest
  import torch
  from torch import optim
  from trainer.logging.tensorboard_logger import TensorboardLogger
  from tests import get_tests_data_path, get_tests_input_path, get_tests_output_path
  from TTS.tts.configs.glow_tts_config import GlowTTSConfig
  from TTS.tts.layers.losses import GlowTTSLoss
  from TTS.tts.models.glow_tts import GlowTTS
  from TTS.tts.utils.speakers import SpeakerManager
  from TTS.utils.audio import AudioProcessor
label_desc: Use image node_id 19 for calling the TestGlowTTS obj's underlying member method code with example usage: obj._test_inference_with_MAS(batch_size) without return types