code: def test_uniter_for_classification(self):
      heads = {"test": {"type": "mlp", "num_labels": 3129}}
      tasks = "test"
      losses = {"test": "logit_bce"}
      model = UNITERForClassification(
          head_configs=heads, loss_configs=losses, tasks=tasks
      )
  
      model.eval()
      model = model.to(get_current_device())
      sample_list = self._get_sample_list()
  
      with torch.no_grad():
          model_output = model(sample_list)
  
      self.assertTrue("losses" in model_output)
      self.assertTrue("test/test/logit_bce" 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 2 for calling the TestUniterWithHeads obj's underlying member method code with example usage: obj.test_uniter_for_classification() without return types