code: def create_and_check_lm_head_model(
      self,
      config,
      input_ids,
      input_mask,
      head_mask,
      token_type_ids,
      *args,
  ):
      model = GPT2LMHeadModel(config)
      model.to(torch_device)
      model.eval()
  
      result = model(
          input_ids, token_type_ids=token_type_ids, labels=input_ids
      )
      self.parent.assertEqual(result.loss.shape, ())
      self.parent.assertEqual(
          result.logits.shape,
          (self.batch_size, self.seq_length, self.vocab_size),
      )
  
imports: import datetime
  import gc
  import math
  import unittest
  from transformers import GPT2Config, is_torch_available
  from transformers.testing_utils import backend_empty_cache, require_torch, slow, torch_device
  from ...generation.test_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 11 for calling the GPT2ModelTester obj's underlying member method code with example usage: obj.create_and_check_lm_head_model(config, input_ids, input_mask, head_mask, token_type_ids) without return types