code: def test_train_eval_log(self):
      batch_size = 2
      config = VitsConfig(
          model_args=VitsArgs(num_chars=32, spec_segment_size=10)
      )
      model = Vits.init_from_config(config, verbose=False).to(device)
      model.run_data_dep_init = False
      model.train()
      batch = self._create_batch(config, batch_size)
      logger = TensorboardLogger(
          log_dir=os.path.join(
              get_tests_output_path(), "dummy_vits_logs"
          ),
          model_name="vits_test_train_log",
      )
      criterion = model.get_criterion()
      criterion = [criterion[0].to(device), criterion[1].to(device)]
      outputs = [None] * 2
      outputs[0], _ = model.train_step(batch, criterion, 0)
      outputs[1], _ = model.train_step(batch, criterion, 1)
      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 trainer.logging.tensorboard_logger import TensorboardLogger
  from tests import assertHasAttr, assertHasNotAttr, get_tests_data_path, get_tests_input_path, get_tests_output_path
  from TTS.config import load_config
  from TTS.encoder.utils.generic_utils import setup_encoder_model
  from TTS.tts.configs.vits_config import VitsConfig
  from TTS.tts.models.vits import Vits, VitsArgs, VitsAudioConfig, amp_to_db, db_to_amp, load_audio, spec_to_mel, wav_to_mel, wav_to_spec
  from TTS.tts.utils.speakers import SpeakerManager
label_desc: Use image node_id 24 for calling the TestVits obj's underlying member method code with example usage: obj.test_train_eval_log() without return types