code: def test_forward(self) -> None:
      pos_scores = torch.tensor(
          [0.8181, 0.5700, 0.3506], requires_grad=True
      )
      neg_scores = torch.tensor(
          [
              [0.4437, 0.6573, 0.9986, 0.2548, 0.0998],
              [0.6175, 0.4061, 0.4582, 0.5382, 0.3126],
              [0.9869, 0.2028, 0.1667, 0.0044, 0.9934],
          ],
          requires_grad=True,
      )
      loss_fn = RankingLossFunction(margin=1.0)
      loss = loss_fn(pos_scores, neg_scores, None)
      self.assertTensorEqual(loss, torch.tensor(13.4475))
      loss.backward()
      self.assertTrue((pos_scores.grad != 0).any())
      self.assertTrue((neg_scores.grad != 0).any())
  
imports: from unittest import main, TestCase
  import torch
  from torchbiggraph.losses import LogisticLossFunction, RankingLossFunction, SoftmaxLossFunction
label_desc: Use image node_id 1 for calling the TestRankingLossFunction obj's underlying member method code with example usage: obj.test_forward() without return types