code: def test_real_model_save_load_from_pretrained(self):
      model_2 = self.get_pretrained_model()
      input_ids = ids_tensor([13, 5], model_2.config.encoder.vocab_size)
      decoder_input_ids = ids_tensor(
          [13, 1], model_2.config.encoder.vocab_size
      )
      attention_mask = ids_tensor([13, 5], vocab_size=2)
  
      outputs = model_2(
          input_ids=input_ids,
          decoder_input_ids=decoder_input_ids,
          attention_mask=attention_mask,
      )
      out_2 = np.array(outputs[0])
      out_2[np.isnan(out_2)] = 0
  
      with tempfile.TemporaryDirectory() as tmp_dirname:
          model_2.save_pretrained(tmp_dirname)
          model_1 = FlaxEncoderDecoderModel.from_pretrained(tmp_dirname)
  
          after_outputs = model_1(
              input_ids=input_ids,
              decoder_input_ids=decoder_input_ids,
              attention_mask=attention_mask,
          )
          out_1 = np.array(after_outputs[0])
          out_1[np.isnan(out_1)] = 0
          max_diff = np.amax(np.abs(out_1 - out_2))
          self.assertLessEqual(max_diff, 1e-5)
  
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 22 for calling the FlaxEncoderDecoderMixin obj's underlying member method code with example usage: obj.test_real_model_save_load_from_pretrained() without return types