code: def check_encoder_decoder_model_from_pretrained(
      self,
      config,
      input_ids,
      attention_mask,
      encoder_hidden_states,
      decoder_config,
      decoder_input_ids,
      decoder_attention_mask,
      return_dict,
      **kwargs,
  ):
      encoder_model, decoder_model = self.get_encoder_decoder_model(
          config, decoder_config
      )
      kwargs = {
          "encoder_model": encoder_model,
          "decoder_model": decoder_model,
          "return_dict": return_dict,
      }
      enc_dec_model = (
          FlaxEncoderDecoderModel.from_encoder_decoder_pretrained(
              **kwargs
          )
      )
      outputs_encoder_decoder = enc_dec_model(
          input_ids=input_ids,
          decoder_input_ids=decoder_input_ids,
          attention_mask=attention_mask,
          decoder_attention_mask=decoder_attention_mask,
          return_dict=True,
      )
  
      self.assertEqual(
          outputs_encoder_decoder["logits"].shape,
          (decoder_input_ids.shape + (decoder_config.vocab_size,)),
      )
      self.assertEqual(
          outputs_encoder_decoder["encoder_last_hidden_state"].shape,
          (input_ids.shape + (config.hidden_size,)),
      )
  
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 5 for calling the FlaxEncoderDecoderMixin obj's underlying member method code with example usage: obj.check_encoder_decoder_model_from_pretrained(config, input_ids, attention_mask, encoder_hidden_states, decoder_config, decoder_input_ids, decoder_attention_mask, return_dict) without return types