code: def create_and_check_xlnet_for_multiple_choice(
      self,
      config,
      input_ids_1,
      input_ids_2,
      input_ids_q,
      perm_mask,
      input_mask,
      target_mapping,
      segment_ids,
      lm_labels,
      sequence_labels,
      is_impossible_labels,
  ):
      config.num_choices = self.num_choices
      model = TFXLNetForMultipleChoice(config=config)
      multiple_choice_inputs_ids = tf.tile(
          tf.expand_dims(input_ids_1, 1), (1, self.num_choices, 1)
      )
      multiple_choice_input_mask = tf.tile(
          tf.expand_dims(input_mask, 1), (1, self.num_choices, 1)
      )
      multiple_choice_token_type_ids = tf.tile(
          tf.expand_dims(segment_ids, 1), (1, self.num_choices, 1)
      )
      inputs = {
          "input_ids": multiple_choice_inputs_ids,
          "attention_mask": multiple_choice_input_mask,
          "token_type_ids": multiple_choice_token_type_ids,
      }
      result = model(inputs)
  
      self.parent.assertEqual(
          result.logits.shape, (self.batch_size, self.num_choices)
      )
      self.parent.assertListEqual(
          [mem.shape for mem in result.mems],
          [
              (
                  self.seq_length,
                  self.batch_size * self.num_choices,
                  self.hidden_size,
              )
          ]
          * self.num_hidden_layers,
      )
  
imports: from __future__ import annotations
  import inspect
  import random
  import unittest
  from transformers import XLNetConfig, is_tf_available
  from transformers.testing_utils import require_tf, 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 9 for calling the TFXLNetModelTester obj's underlying member method code with example usage: obj.create_and_check_xlnet_for_multiple_choice(config, input_ids_1, input_ids_2, input_ids_q, perm_mask, input_mask, target_mapping, segment_ids, lm_labels, sequence_labels, is_impossible_labels) without return types