code: def create_and_check_model_forward(self, config, inputs_dict):
      model = VitsModel(config=config).to(torch_device).eval()
  
      input_ids = inputs_dict["input_ids"]
      attention_mask = inputs_dict["attention_mask"]
  
      result = model(input_ids, attention_mask=attention_mask)
      self.parent.assertEqual(
          (self.batch_size, 624), result.waveform.shape
      )
  
imports: import copy
  import os
  import tempfile
  import unittest
  from typing import Dict, List, Tuple
  import numpy
  from transformers import PretrainedConfig, VitsConfig
  from transformers.testing_utils import is_flaky, is_torch_available, require_torch, require_torch_multi_gpu, slow, torch_device
  from transformers.trainer_utils import set_seed
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, global_rng, ids_tensor, random_attention_mask
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 5 for calling the VitsModelTester obj's underlying member method code with example usage: obj.create_and_check_model_forward(config, inputs_dict) without return types