code: def check_encoder_decoder_model_from_encoder_decoder_pretrained(
      self,
      config,
      inputs,
      attention_mask,
      encoder_hidden_states,
      decoder_config,
      decoder_input_ids,
      decoder_attention_mask,
      **kwargs,
  ):
      encoder_model, decoder_model = self.get_encoder_decoder_model(
          config, decoder_config
      )
      # assert that loading encoder and decoder models from configs has been correctly executed
      self.assertEqual(
          config.add_adapter, encoder_model.config.add_adapter
      )
      self.assertEqual(
          decoder_config.use_cache, decoder_model.config.use_cache
      )
  
      with tempfile.TemporaryDirectory() as enc_tmpdir:
          with tempfile.TemporaryDirectory() as dec_tmpdir:
              encoder_model.save_pretrained(enc_tmpdir)
              decoder_model.save_pretrained(dec_tmpdir)
              # load a model from pretrained encoder and decoder checkpoints, setting one encoder and one decoder kwarg opposite to that specified in their respective configs
              enc_dec_model = FlaxSpeechEncoderDecoderModel.from_encoder_decoder_pretrained(
                  encoder_pretrained_model_name_or_path=enc_tmpdir,
                  decoder_pretrained_model_name_or_path=dec_tmpdir,
                  encoder_add_adapter=not config.add_adapter,
                  decoder_use_cache=not decoder_config.use_cache,
              )
  
      # assert that setting encoder and decoder kwargs opposite to those in the configs has correctly been applied
      self.assertNotEqual(
          config.add_adapter, enc_dec_model.config.encoder.add_adapter
      )
      self.assertNotEqual(
          decoder_config.use_cache,
          enc_dec_model.config.decoder.use_cache,
      )
  
      outputs_encoder_decoder = enc_dec_model(
          inputs=inputs,
          attention_mask=attention_mask,
          decoder_input_ids=decoder_input_ids,
          decoder_attention_mask=decoder_attention_mask,
          output_hidden_states=True,
          return_dict=True,
      )
  
      self.assertEqual(
          outputs_encoder_decoder["logits"].shape,
          (decoder_input_ids.shape + (decoder_config.vocab_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 floats_tensor, ids_tensor, random_attention_mask
  from ..bart.test_modeling_flax_bart import FlaxBartStandaloneDecoderModelTester
  from ..bert.test_modeling_flax_bert import FlaxBertModelTester
  from ..gpt2.test_modeling_flax_gpt2 import FlaxGPT2ModelTester
  from ..wav2vec2.test_modeling_flax_wav2vec2 import FlaxWav2Vec2ModelTester
label_desc: Use image node_id 8 for calling the FlaxEncoderDecoderMixin obj's underlying member method code with example usage: obj.check_encoder_decoder_model_from_encoder_decoder_pretrained(config, inputs, attention_mask, encoder_hidden_states, decoder_config, decoder_input_ids, decoder_attention_mask) without return types