code: def prepare_config_and_inputs_for_decoder(self):
      (
          config,
          input_ids,
          token_type_ids,
          input_mask,
          sequence_labels,
          token_labels,
          choice_labels,
      ) = self.prepare_config_and_inputs()
  
      config.is_decoder = True
      encoder_hidden_states = floats_tensor(
          [self.batch_size, self.seq_length, self.hidden_size]
      )
      encoder_attention_mask = ids_tensor(
          [self.batch_size, self.seq_length], vocab_size=2
      )
  
      return (
          config,
          input_ids,
          token_type_ids,
          input_mask,
          sequence_labels,
          token_labels,
          choice_labels,
          encoder_hidden_states,
          encoder_attention_mask,
      )
  
imports: import os
  import tempfile
  import unittest
  from transformers import ErnieConfig, is_torch_available
  from transformers.models.auto import get_values
  from transformers.testing_utils import require_torch, require_torch_accelerator, slow, torch_device
  from ...generation.test_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 4 for calling the ErnieModelTester obj's underlying member method code with example usage: obj.prepare_config_and_inputs_for_decoder() and returns: config,  input_ids,  token_type_ids,  input_mask,  sequence_labels,  token_labels,  choice_labels,  encoder_hidden_states,  encoder_attention_mask