code: def test_uniter_for_pretraining(self):
      self.model_for_pretraining.eval()
      self.model_for_pretraining = self.model_for_pretraining.to(
          get_current_device()
      )
      sample_list = self._get_sample_list()
      sample_list["tasks"] = "wra"
  
      sample_list.dataset_name = "vqa2"
      sample_list.dataset_type = "test"
      with torch.no_grad():
          model_output = self.model_for_pretraining(sample_list)
  
      self.assertTrue("losses" in model_output)
      self.assertTrue("wra_loss" in model_output["losses"])
  
imports: import gc
  import unittest
  import tests.test_utils
  import torch
  from mmf.common.sample import SampleList
  from mmf.models.uniter import UNITERForClassification, UNITERForPretraining, UNITERImageEmbeddings, UNITERModelBase
  from mmf.utils.build import build_model
  from mmf.utils.configuration import Configuration
  from mmf.utils.env import setup_imports, teardown_imports
  from mmf.utils.general import get_current_device
  from omegaconf import OmegaConf
label_desc: Use image node_id 5 for calling the TestUniterModel obj's underlying member method code with example usage: obj.test_uniter_for_pretraining() without return types