code: def prepare_config_and_inputs(self):
      vit_model_tester = TFDeiTModelTester(self)
      bert_model_tester = TFRobertaModelTester(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,
          "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: from __future__ import annotations
  import collections
  import tempfile
  import unittest
  import numpy
  from transformers.testing_utils import require_tf, require_vision, slow
  from transformers.utils import is_tf_available, is_vision_available
  from ...test_modeling_tf_common import floats_tensor, ids_tensor, random_attention_mask
  from ..bert.test_modeling_tf_bert import TFBertModelTester
  from ..clip.test_modeling_tf_clip import TFCLIPVisionModelTester
  from ..deit.test_modeling_tf_deit import TFDeiTModelTester
  from ..roberta.test_modeling_tf_roberta import TFRobertaModelTester
  from ..vit.test_modeling_tf_vit import TFViTModelTester
label_desc: Use image node_id 4 for calling the TFDeiTRobertaModelTest obj's underlying member method code with example usage: obj.prepare_config_and_inputs() and returns: dict