code: def test_model_for_causal_lm(self):
      for model_name in TF_GPT2_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
          config = AutoConfig.from_pretrained(model_name)
          self.assertIsNotNone(config)
          self.assertIsInstance(config, GPT2Config)
  
          model = TFAutoModelForCausalLM.from_pretrained(
              model_name, from_pt=True
          )
          model, loading_info = TFAutoModelForCausalLM.from_pretrained(
              model_name, output_loading_info=True, from_pt=True
          )
          self.assertIsNotNone(model)
          self.assertIsInstance(model, TFGPT2LMHeadModel)
  
          model = AutoModelForCausalLM.from_pretrained(
              model_name, from_tf=True
          )
          model, loading_info = AutoModelForCausalLM.from_pretrained(
              model_name, output_loading_info=True, from_tf=True
          )
          self.assertIsNotNone(model)
          self.assertIsInstance(model, GPT2LMHeadModel)
  
file_path: transformers/tests/models/auto/test_modeling_tf_pytorch.py
imports: from __future__ import annotations
  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 3 for calling the TFPTAutoModelTest obj's underlying member method code with example usage: obj.test_model_for_causal_lm() without return types