code: def create_and_check_distilbert_for_sequence_classification(
      self,
      config,
      input_ids,
      input_mask,
      sequence_labels,
      token_labels,
      choice_labels,
  ):
      config.num_labels = self.num_labels
      model = DistilBertForSequenceClassification(config)
      model.to(torch_device)
      model.eval()
      result = model(
          input_ids, attention_mask=input_mask, labels=sequence_labels
      )
      self.parent.assertEqual(
          result.logits.shape, (self.batch_size, self.num_labels)
      )
  
imports: import os
  import tempfile
  import unittest
  from transformers import DistilBertConfig, is_torch_available
  from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
label_desc: Use image node_id 7 for calling the DistilBertModelTester obj's underlying member method code with example usage: obj.create_and_check_distilbert_for_sequence_classification(config, input_ids, input_mask, sequence_labels, token_labels, choice_labels) without return types