code: def create_and_check_bloom_model_past(
      self, config, input_ids, input_mask, *args
  ):
      model = BloomModel(config=config)
  
      model.to(torch_device)
      model.eval()
  
      # first forward pass
      outputs = model(
          input_ids,
          attention_mask=torch.ones_like(input_ids),
          use_cache=True,
      )
      outputs_use_cache_conf = model(
          input_ids, attention_mask=torch.ones_like(input_ids)
      )
      outputs_no_past = model(
          input_ids,
          use_cache=False,
          attention_mask=torch.ones_like(input_ids),
      )
  
      self.parent.assertTrue(
          len(outputs) == len(outputs_use_cache_conf)
      )
      self.parent.assertTrue(len(outputs) == len(outputs_no_past) + 1)
  
      past = outputs["past_key_values"]
  
      # create hypothetical next token and extent to next_input_ids
      next_tokens = ids_tensor((self.batch_size, 1), config.vocab_size)
  
      # append to next input_ids and token_type_ids
      next_input_ids = torch.cat([input_ids, next_tokens], dim=-1)
  
      output_from_no_past = model(next_input_ids)["last_hidden_state"]
      output_from_past = model(next_tokens, past_key_values=past)[
          "last_hidden_state"
      ]
  
      # select random slice
      random_slice_idx = ids_tensor(
          (1,), output_from_past.shape[-1]
      ).item()
      output_from_no_past_slice = output_from_no_past[
          :, -1, random_slice_idx
      ].detach()
      output_from_past_slice = output_from_past[
          :, 0, random_slice_idx
      ].detach()
  
      # test that outputs are equal for slice
      self.parent.assertTrue(
          torch.allclose(
              output_from_past_slice,
              output_from_no_past_slice,
              atol=1e-3,
          )
      )
  
imports: import math
  import unittest
  from transformers import BloomConfig, is_torch_available
  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, ids_tensor, random_attention_mask
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 6 for calling the BloomModelTester obj's underlying member method code with example usage: obj.create_and_check_bloom_model_past(config, input_ids, input_mask) without return types