code: def check_decoder_model_past_large_inputs(self, config, inputs_dict):
      model = TFMBartModel(config=config).get_decoder()
      input_ids = inputs_dict["input_ids"]
  
      input_ids = input_ids[:1, :]
      attention_mask = inputs_dict["attention_mask"][:1, :]
      head_mask = inputs_dict["head_mask"]
      self.batch_size = 1
  
      # first forward pass
      outputs = model(
          input_ids,
          attention_mask=attention_mask,
          head_mask=head_mask,
          use_cache=True,
      )
  
      output, past_key_values = outputs.to_tuple()
      past_key_values = past_key_values[1]
  
imports: import tempfile
  import unittest
  from transformers import AutoTokenizer, MBartConfig, is_tf_available
  from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow, tooslow
  from transformers.utils import cached_property
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
label_desc: Use image node_id 3 for calling the TFMBartModelTester obj's underlying member method code with example usage: obj.check_decoder_model_past_large_inputs(config, inputs_dict) without return types