class_docstr: You can also import this e.g, from .test_modeling_funnel import FunnelModelTester
code: def create_and_check_for_token_classification(
      self,
      config,
      input_ids,
      token_type_ids,
      input_mask,
      sequence_labels,
      token_labels,
      choice_labels,
  ):
      config.num_labels = self.num_labels
      model = TFFunnelForTokenClassification(config=config)
      inputs = {
          "input_ids": input_ids,
          "attention_mask": input_mask,
          "token_type_ids": token_type_ids,
      }
      result = model(inputs)
      self.parent.assertEqual(
          result.logits.shape,
          (self.batch_size, self.seq_length, self.num_labels),
      )
  
imports: import unittest
  from transformers import FunnelConfig, is_tf_available
  from transformers.testing_utils import require_tf, tooslow
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
label_desc: Use image node_id 9 for calling the TFFunnelModelTester obj's underlying member method code with example usage: obj.create_and_check_for_token_classification(config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels) without return types