code: def prepare_config_and_inputs_for_decoder(self):
      (
          config,
          input_ids,
          attention_mask,
          lm_labels,
      ) = self.prepare_config_and_inputs()
  
      encoder_hidden_states = floats_tensor(
          [self.batch_size, self.decoder_seq_length, self.hidden_size]
      )
      encoder_attention_mask = ids_tensor(
          [self.batch_size, self.decoder_seq_length], vocab_size=2
      )
  
      return (
          config,
          input_ids,
          attention_mask,
          encoder_hidden_states,
          encoder_attention_mask,
          lm_labels,
      )
  
imports: import copy
  import tempfile
  import unittest
  import timeout_decorator
  from transformers import MvpConfig, is_torch_available
  from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
  from transformers.utils import cached_property
  from ...generation.test_generation_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor
label_desc: Use image node_id 3 for calling the MvpStandaloneDecoderModelTester obj's underlying member method code with example usage: obj.prepare_config_and_inputs_for_decoder() and returns: config,  input_ids,  attention_mask,  encoder_hidden_states,  encoder_attention_mask,  lm_labels