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]
          )
  
      if self.use_labels:
          token_labels = ids_tensor(
              [self.batch_size, self.seq_length], self.vocab_size
          )
  
      config = self.get_config()
  
      return config, input_ids, input_mask, token_labels
  
imports: import unittest
  from transformers import BertGenerationConfig, is_torch_available
  from transformers.testing_utils import require_torch, slow, torch_device
  from ...generation.test_generation_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
label_desc: Use image node_id 2 for calling the BertGenerationEncoderTester obj's underlying member method code with example usage: obj.prepare_config_and_inputs() and returns: config,  input_ids,  input_mask,  token_labels