code: def prepare_config_and_inputs(self):
      model_tester_encoder = FlaxBertModelTester(self, batch_size=13)
      model_tester_decoder = FlaxGPT2ModelTester(self, batch_size=13)
      encoder_config_and_inputs = (
          model_tester_encoder.prepare_config_and_inputs()
      )
      decoder_config_and_inputs = (
          model_tester_decoder.prepare_config_and_inputs_for_decoder()
      )
      (
          config,
          input_ids,
          token_type_ids,
          attention_mask,
      ) = encoder_config_and_inputs
      (
          decoder_config,
          decoder_input_ids,
          decoder_attention_mask,
          encoder_hidden_states,
          encoder_attention_mask,
      ) = decoder_config_and_inputs
  
      # make sure that cross attention layers are added
      decoder_config.add_cross_attention = True
      return {
          "config": config,
          "input_ids": input_ids,
          "attention_mask": attention_mask,
          "decoder_config": decoder_config,
          "decoder_input_ids": decoder_input_ids,
          "decoder_attention_mask": decoder_attention_mask,
          "encoder_hidden_states": encoder_hidden_states,
      }
  
imports: import tempfile
  import unittest
  import numpy
  from transformers import is_flax_available, is_torch_available
  from transformers.testing_utils import is_pt_flax_cross_test, require_flax, slow, torch_device
  from ...test_modeling_flax_common import ids_tensor
  from ..bart.test_modeling_flax_bart import FlaxBartStandaloneDecoderModelTester
  from ..bert.test_modeling_flax_bert import FlaxBertModelTester
  from ..gpt2.test_modeling_flax_gpt2 import FlaxGPT2ModelTester
label_desc: Use image node_id 2 for calling the FlaxGPT2EncoderDecoderModelTest obj's underlying member method code with example usage: obj.prepare_config_and_inputs() and returns: dict