code: def test_translation_en_to_de(self):
      tok = T5Tokenizer.from_pretrained("t5-base")
      model = self.model
  
      task_specific_config = getattr(
          model.config, "task_specific_params", {}
      )
      translation_config = task_specific_config.get(
          "translation_en_to_de", {}
      )
      self.model.config.update(translation_config)
  
      original_input = '"Luigi often said to me that he never wanted the brothers to end up in court", she wrote.'
      expected_translation = '"Luigi sagte mir oft, dass er nie wollte, dass die Brüder am Gericht sitzen", schrieb sie.'
  
      input_ids = tok.encode(
          model.config.prefix + original_input, return_tensors="tf"
      )
  
      output = model.generate(
          input_ids=input_ids,
          num_beams=4,
          length_penalty=2.0,
          max_length=50,
          no_repeat_ngram_size=3,
          do_sample=False,
          early_stopping=True,
      )
      translation = tok.decode(
          output[0],
          skip_special_tokens=True,
          clean_up_tokenization_spaces=False,
      )
  
      self.assertEqual(translation, expected_translation)
  
imports: from __future__ import annotations
  import unittest
  from transformers import T5Config, is_tf_available
  from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
  from transformers.utils import cached_property
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 6 for calling the TFT5ModelIntegrationTests obj's underlying member method code with example usage: obj.test_translation_en_to_de() without return types