code: def test_train_eval_log(self):
      batch_size = BATCH_SIZE
      (
          input_dummy,
          input_lengths,
          mel_spec,
          mel_lengths,
          _,
      ) = self._create_inputs(batch_size)
      batch = {}
      batch["text_input"] = input_dummy
      batch["text_lengths"] = input_lengths
      batch["mel_lengths"] = mel_lengths
      batch["mel_input"] = mel_spec
      batch["d_vectors"] = None
      batch["speaker_ids"] = None
      config = GlowTTSConfig(num_chars=32)
      model = GlowTTS.init_from_config(config, verbose=False).to(device)
      model.run_data_dep_init = False
      model.train()
      logger = TensorboardLogger(
          log_dir=os.path.join(
              get_tests_output_path(), "dummy_glow_tts_logs"
          ),
          model_name="glow_tts_test_train_log",
      )
      criterion = model.get_criterion()
      outputs, _ = model.train_step(batch, criterion)
      model.train_log(batch, outputs, logger, None, 1)
      model.eval_log(batch, outputs, logger, None, 1)
      logger.finish()
  
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 22 for calling the TestGlowTTS obj's underlying member method code with example usage: obj.test_train_eval_log() without return types