code: def test_d_vector_forward(self):
      batch_size = 2
      args = VitsArgs(
          spec_segment_size=10,
          num_chars=32,
          use_d_vector_file=True,
          d_vector_dim=256,
          d_vector_file=[
              os.path.join(get_tests_data_path(), "dummy_speakers.json")
          ],
      )
      config = VitsConfig(model_args=args)
      model = Vits.init_from_config(config, verbose=False).to(device)
      model.train()
      (
          input_dummy,
          input_lengths,
          _,
          spec,
          spec_lengths,
          waveform,
      ) = self._create_inputs(config, batch_size=batch_size)
      d_vectors = torch.randn(batch_size, 256).to(device)
      output_dict = model.forward(
          input_dummy,
          input_lengths,
          spec,
          spec_lengths,
          waveform,
          aux_input={"d_vectors": d_vectors},
      )
      self._check_forward_outputs(config, output_dict)
  
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 11 for calling the TestVits obj's underlying member method code with example usage: obj.test_d_vector_forward() without return types