code: def test_new_model_registration(self):
      try:
          AutoConfig.register("new-model", NewModelConfig)
  
          auto_classes = [
              TFAutoModel,
              TFAutoModelForCausalLM,
              TFAutoModelForMaskedLM,
              TFAutoModelForPreTraining,
              TFAutoModelForQuestionAnswering,
              TFAutoModelForSequenceClassification,
              TFAutoModelForTokenClassification,
          ]
  
          for auto_class in auto_classes:
              with self.subTest(auto_class.__name__):
                  # Wrong config class will raise an error
                  with self.assertRaises(ValueError):
                      auto_class.register(BertConfig, TFNewModel)
                  auto_class.register(NewModelConfig, TFNewModel)
                  # Trying to register something existing in the Transformers library will raise an error
                  with self.assertRaises(ValueError):
                      auto_class.register(BertConfig, TFBertModel)
  
                  # Now that the config is registered, it can be used as any other config with the auto-API
                  tiny_config = BertModelTester(self).get_config()
                  config = NewModelConfig(**tiny_config.to_dict())
                  model = auto_class.from_config(config)
                  self.assertIsInstance(model, TFNewModel)
  
                  with tempfile.TemporaryDirectory() as tmp_dir:
                      model.save_pretrained(tmp_dir)
                      new_model = auto_class.from_pretrained(tmp_dir)
                      self.assertIsInstance(new_model, TFNewModel)
  
      finally:
          if "new-model" in CONFIG_MAPPING._extra_content:
              del CONFIG_MAPPING._extra_content["new-model"]
          for mapping in (
              TF_MODEL_MAPPING,
              TF_MODEL_FOR_PRETRAINING_MAPPING,
              TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING,
              TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
              TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING,
              TF_MODEL_FOR_CAUSAL_LM_MAPPING,
              TF_MODEL_FOR_MASKED_LM_MAPPING,
          ):
              if NewModelConfig in mapping._extra_content:
                  del mapping._extra_content[NewModelConfig]
  
imports: import copy
  import tempfile
  import unittest
  from transformers import CONFIG_MAPPING, AutoConfig, BertConfig, GPT2Config, T5Config, TapasConfig, is_tf_available
  from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, RequestCounter, require_tensorflow_probability, require_tf, slow
  from ..bert.test_modeling_bert import BertModelTester
label_desc: Use image node_id 13 for calling the TFAutoModelTest obj's underlying member method code with example usage: obj.test_new_model_registration() without return types