code: def _create_inputs(self, config, batch_size=2):
      input_dummy = (
          torch.randint(0, 24, (batch_size, 128)).long().to(device)
      )
      input_lengths = (
          torch.randint(100, 129, (batch_size,)).long().to(device)
      )
      input_lengths[-1] = 128
      spec = torch.rand(
          batch_size, config.audio["fft_size"] // 2 + 1, 30
      ).to(device)
      mel = torch.rand(batch_size, config.audio["num_mels"], 30).to(
          device
      )
      spec_lengths = (
          torch.randint(20, 30, (batch_size,)).long().to(device)
      )
      spec_lengths[-1] = spec.size(2)
      waveform = torch.rand(
          batch_size, 1, spec.size(2) * config.audio["hop_length"]
      ).to(device)
      return (
          input_dummy,
          input_lengths,
          mel,
          spec,
          spec_lengths,
          waveform,
      )
  
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 7 for calling the TestVits obj's underlying member method code with example usage: obj._create_inputs(config, batch_size) and returns: input_dummy,  input_lengths,  mel,  spec,  spec_lengths,  waveform