code: def test_model_for_encoder_decoder_lm(self):
      for model_name in TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
          config = AutoConfig.from_pretrained(model_name)
          self.assertIsNotNone(config)
          self.assertIsInstance(config, T5Config)
  
          model = TFAutoModelForSeq2SeqLM.from_pretrained(
              model_name, from_pt=True
          )
          model, loading_info = TFAutoModelForSeq2SeqLM.from_pretrained(
              model_name, output_loading_info=True, from_pt=True
          )
          self.assertIsNotNone(model)
          self.assertIsInstance(model, TFT5ForConditionalGeneration)
  
          model = AutoModelForSeq2SeqLM.from_pretrained(
              model_name, from_tf=True
          )
          model, loading_info = AutoModelForSeq2SeqLM.from_pretrained(
              model_name, output_loading_info=True, from_tf=True
          )
          self.assertIsNotNone(model)
          self.assertIsInstance(model, T5ForConditionalGeneration)
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/tests/models/auto/test_modeling_tf_pytorch.py
imports: import unittest
  from transformers import is_tf_available, is_torch_available
  from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
label_desc: Use image node_id 6 for calling the TFPTAutoModelTest obj's underlying member method code with example usage: obj.test_model_for_encoder_decoder_lm() without return types