code: def create_and_check_imagegpt_for_image_classification(
      self,
      config,
      pixel_values,
      input_mask,
      head_mask,
      token_type_ids,
      mc_token_ids,
      sequence_labels,
      *args,
  ):
      config.num_labels = self.num_labels
      model = ImageGPTForImageClassification(config)
      model.to(torch_device)
      model.eval()
      result = model(
          pixel_values,
          attention_mask=input_mask,
          token_type_ids=token_type_ids,
          labels=sequence_labels,
      )
      self.parent.assertEqual(
          result.logits.shape, (self.batch_size, self.num_labels)
      )
  
imports: import copy
  import inspect
  import os
  import tempfile
  import unittest
  from transformers import ImageGPTConfig
  from transformers.testing_utils import require_torch, require_vision, slow, torch_device
  from transformers.utils import cached_property, is_torch_available, is_vision_available
  from ...generation.test_generation_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, _config_zero_init, floats_tensor, ids_tensor, random_attention_mask
label_desc: Use image node_id 9 for calling the ImageGPTModelTester obj's underlying member method code with example usage: obj.create_and_check_imagegpt_for_image_classification(config, pixel_values, input_mask, head_mask, token_type_ids, mc_token_ids, sequence_labels) without return types