code: def test_determinism(self):
      for model_class in self.all_model_classes:
          (
              config,
              inputs_dict,
          ) = self.model_tester.prepare_config_and_inputs_for_model_class(
              model_class
          )
  
          model = model_class(config)
          model.to(torch_device)
          model.eval()
          with torch.no_grad():
              inputs_dict = self._prepare_for_class(
                  inputs_dict, model_class
              )
              first = model(**inputs_dict)[0]
              second = model(**inputs_dict)[0]
  
          if (
              model_class.__name__
              == "PerceiverForMultimodalAutoencoding"
          ):
              # model outputs a dictionary with logits per modality, let's verify each modality
              for modality in first.keys():
                  out_1 = first[modality].cpu().numpy()
                  out_2 = second[modality].cpu().numpy()
                  out_1 = out_1[~np.isnan(out_1)]
                  out_2 = out_2[~np.isnan(out_2)]
                  max_diff = np.amax(np.abs(out_1 - out_2))
                  self.assertLessEqual(max_diff, 1e-5)
          else:
              out_1 = first.cpu().numpy()
              out_2 = second.cpu().numpy()
              out_1 = out_1[~np.isnan(out_1)]
              out_2 = out_2[~np.isnan(out_2)]
              max_diff = np.amax(np.abs(out_1 - out_2))
              self.assertLessEqual(max_diff, 1e-5)
  
imports: import copy
  import inspect
  import math
  import tempfile
  import unittest
  import warnings
  from typing import Dict, List, Tuple
  import numpy
  from datasets import load_dataset
  from transformers import PerceiverConfig
  from transformers.models.auto import get_values
  from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
  from transformers.utils import is_torch_available, is_vision_available
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
label_desc: Use image node_id 12 for calling the PerceiverModelTest obj's underlying member method code with example usage: obj.test_determinism() without return types