code: def _check_inference_outputs(
      self, config, outputs, input_dummy, batch_size=1
  ):
      feat_len = outputs["z"].shape[2]
      self.assertEqual(
          outputs["model_outputs"].shape[:2], (batch_size, 1)
      )  # we don't know the channel dimension
      self.assertEqual(
          outputs["alignments"].shape,
          (batch_size, input_dummy.shape[1], feat_len),
      )
      self.assertEqual(
          outputs["z"].shape,
          (batch_size, config.model_args.hidden_channels, feat_len),
      )
      self.assertEqual(
          outputs["z_p"].shape,
          (batch_size, config.model_args.hidden_channels, feat_len),
      )
      self.assertEqual(
          outputs["m_p"].shape,
          (batch_size, config.model_args.hidden_channels, feat_len),
      )
      self.assertEqual(
          outputs["logs_p"].shape,
          (batch_size, config.model_args.hidden_channels, feat_len),
      )
  
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 14 for calling the TestVits obj's underlying member method code with example usage: obj._check_inference_outputs(config, outputs, input_dummy, batch_size) without return types