code: def prepare_config_and_inputs(self):
      vit_model_tester = ViTModelTester(self)
      bert_model_tester = BertModelTester(self)
      vision_config_and_inputs = (
          vit_model_tester.prepare_config_and_inputs()
      )
      text_config_and_inputs = (
          bert_model_tester.prepare_config_and_inputs()
      )
  
      vision_config, pixel_values, _ = vision_config_and_inputs
  
      (
          text_config,
          input_ids,
          token_type_ids,
          input_mask,
          sequence_labels,
          token_labels,
          choice_labels,
      ) = text_config_and_inputs
  
      return {
          "text_config": text_config,
          "vision_config": vision_config,
          "pixel_values": pixel_values,
          "attention_mask": input_mask,
          "text_config": text_config,
          "input_ids": input_ids,
          "text_token_type_ids": token_type_ids,
          "text_sequence_labels": sequence_labels,
          "text_token_labels": token_labels,
          "text_choice_labels": choice_labels,
      }
  
imports: import collections
  import tempfile
  import unittest
  import numpy
  from transformers.testing_utils import is_pt_flax_cross_test, require_torch, require_vision, slow, torch_device
  from transformers.utils import is_flax_available, is_torch_available, is_vision_available
  from ...test_modeling_common import floats_tensor, ids_tensor, random_attention_mask
  from ..bert.test_modeling_bert import BertModelTester
  from ..clip.test_modeling_clip import CLIPVisionModelTester
  from ..deit.test_modeling_deit import DeiTModelTester
  from ..roberta.test_modeling_roberta import RobertaModelTester
  from ..vit.test_modeling_vit import ViTModelTester
label_desc: Use image node_id 3 for calling the ViTBertModelTest obj's underlying member method code with example usage: obj.prepare_config_and_inputs() and returns: dict