code: def prepare_config_and_inputs(self):
      input_ids = ids_tensor(
          [self.batch_size, self.seq_length], self.vocab_size
      )
  
      input_mask = None
      if self.use_input_mask:
          input_mask = random_attention_mask(
              [self.batch_size, self.seq_length]
          )
  
      token_type_ids = None
      if self.use_token_type_ids:
          token_type_ids = ids_tensor(
              [self.batch_size, self.seq_length], self.type_vocab_size
          )
  
      mc_token_ids = None
      if self.use_mc_token_ids:
          mc_token_ids = ids_tensor(
              [self.batch_size, self.num_choices], self.seq_length
          )
  
      sequence_labels = None
      token_labels = None
      choice_labels = None
      if self.use_labels:
          sequence_labels = ids_tensor(
              [self.batch_size], self.type_sequence_label_size
          )
          token_labels = ids_tensor(
              [self.batch_size, self.seq_length], self.num_labels
          )
          choice_labels = ids_tensor(
              [self.batch_size], self.num_choices
          )
  
      config = CTRLConfig(
          vocab_size=self.vocab_size,
          n_embd=self.hidden_size,
          n_layer=self.num_hidden_layers,
          n_head=self.num_attention_heads,
          dff=self.intermediate_size,
          # hidden_act=self.hidden_act,
          # hidden_dropout_prob=self.hidden_dropout_prob,
          # attention_probs_dropout_prob=self.attention_probs_dropout_prob,
          n_positions=self.max_position_embeddings,
          # type_vocab_size=self.type_vocab_size,
          # initializer_range=self.initializer_range,
          pad_token_id=self.pad_token_id,
      )
  
      head_mask = ids_tensor(
          [self.num_hidden_layers, self.num_attention_heads], 2
      )
  
      return (
          config,
          input_ids,
          input_mask,
          head_mask,
          token_type_ids,
          mc_token_ids,
          sequence_labels,
          token_labels,
          choice_labels,
      )
  
imports: from __future__ import annotations
  import unittest
  from transformers import CTRLConfig, 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 2 for calling the TFCTRLModelTester obj's underlying member method code with example usage: obj.prepare_config_and_inputs() and returns: config,  input_ids,  input_mask,  head_mask,  token_type_ids,  mc_token_ids,  sequence_labels,  token_labels,  choice_labels