code: def prepare_config_and_inputs_for_decoder(self):
      config_and_inputs = self.prepare_config_and_inputs()
      (
          config,
          input_ids,
          token_type_ids,
          attention_mask,
      ) = 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,
          encoder_hidden_states,
          encoder_attention_mask,
      )
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/tests/models/roberta/test_modeling_flax_roberta.py
imports: import unittest
  import numpy
  from transformers import RobertaConfig, is_flax_available
  from transformers.testing_utils import require_flax, slow
  from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
label_desc: Use image node_id 4 for calling the FlaxRobertaModelTester obj's underlying member method code with example usage: obj.prepare_config_and_inputs_for_decoder() and returns: config,  input_ids,  token_type_ids,  encoder_hidden_states,  encoder_attention_mask