code: def create_and_check_flaubert_sequence_classif(
      self,
      config,
      input_ids,
      token_type_ids,
      input_lengths,
      sequence_labels,
      token_labels,
      is_impossible_labels,
      choice_labels,
      input_mask,
  ):
      model = TFFlaubertForSequenceClassification(config)
  
      inputs = {"input_ids": input_ids, "lengths": input_lengths}
  
      result = model(inputs)
  
      self.parent.assertEqual(
          result.logits.shape,
          (self.batch_size, self.type_sequence_label_size),
      )
  
imports: from __future__ import annotations
  import unittest
  from transformers import is_tf_available
  from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 6 for calling the TFFlaubertModelTester obj's underlying member method code with example usage: obj.create_and_check_flaubert_sequence_classif(config, input_ids, token_type_ids, input_lengths, sequence_labels, token_labels, is_impossible_labels, choice_labels, input_mask) without return types