code: def create_and_check_gptj_model_past_large_inputs(
      self,
      config,
      input_ids,
      input_mask,
      head_mask,
      token_type_ids,
      *args,
  ):
      model = TFGPTJModel(config=config)
  
      input_ids = input_ids[:1, :]
      input_mask = input_mask[:1, :]
      token_type_ids = token_type_ids[:1, :]
      self.batch_size = 1
  
      # first forward pass
      outputs = model(
          input_ids,
          attention_mask=input_mask,
          token_type_ids=token_type_ids,
          use_cache=True,
      )
  
      output, past = outputs.to_tuple()
  
      # create hypothetical next token and extent to next_input_ids
      next_tokens = ids_tensor((self.batch_size, 3), config.vocab_size)
      next_attn_mask = ids_tensor((self.batch_size, 3), 2)
      next_token_types = ids_tensor(
          (self.batch_size, 3), self.type_vocab_size
      )
  
      # append to next input_ids and token_type_ids
      next_input_ids = tf.concat([input_ids, next_tokens], axis=-1)
      next_attention_mask = tf.concat(
          [input_mask, next_attn_mask], axis=-1
      )
      next_token_type_ids = tf.concat(
          [token_type_ids, next_token_types], axis=-1
      )
  
      output_from_no_past = model(
          next_input_ids,
          token_type_ids=next_token_type_ids,
          attention_mask=next_attention_mask,
      )["last_hidden_state"]
      output_from_past = model(
          next_tokens,
          token_type_ids=next_token_types,
          attention_mask=next_attention_mask,
          past=past,
      )["last_hidden_state"]
      self.parent.assertTrue(
          output_from_past.shape[1] == next_tokens.shape[1]
      )
  
      # select random slice
      random_slice_idx = int(
          ids_tensor((1,), shape_list(output_from_past)[-1])
      )
      output_from_no_past_slice = output_from_no_past[
          :, -3:, random_slice_idx
      ]
      output_from_past_slice = output_from_past[:, :, random_slice_idx]
  
      # test that outputs are equal for slice
      tf.debugging.assert_near(
          output_from_past_slice, output_from_no_past_slice, rtol=1e-3
      )
  
imports: import unittest
  from transformers import AutoTokenizer, GPTJConfig, is_tf_available
  from transformers.testing_utils import require_tf, slow, tooslow
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
  from ...utils.test_modeling_tf_core import TFCoreModelTesterMixin
label_desc: Use image node_id 6 for calling the TFGPTJModelTester obj's underlying member method code with example usage: obj.create_and_check_gptj_model_past_large_inputs(config, input_ids, input_mask, head_mask, token_type_ids) without return types