code: def create_and_check_xglm_model(
      self, config, input_ids, input_mask, head_mask, *args
  ):
      model = XGLMModel(config=config)
      model.to(torch_device)
      model.eval()
  
      result = model(input_ids, head_mask=head_mask)
      result = model(input_ids)
  
      self.parent.assertEqual(
          result.last_hidden_state.shape,
          (self.batch_size, self.seq_length, self.hidden_size),
      )
      self.parent.assertEqual(
          len(result.past_key_values), config.num_hidden_layers
      )
  
imports: import datetime
  import math
  import unittest
  from transformers import XGLMConfig, is_torch_available
  from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
  from ...generation.test_generation_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
label_desc: Use image node_id 6 for calling the XGLMModelTester obj's underlying member method code with example usage: obj.create_and_check_xglm_model(config, input_ids, input_mask, head_mask) without return types