def METHOD_NAME(self):
    alpha, beta, base = 0.1, 40, 0.5
    loss_func = MultiSimilarityLoss(alpha=alpha, beta=beta, base=base)
    for dtype in TEST_DTYPES:
        embedding_angles = [0]
        embeddings = torch.tensor(
            [angle_to_coord(a) for a in embedding_angles],
            requires_grad=True,
            dtype=dtype,
        ).to(
            TEST_DEVICE
        )  # 2D embeddings
        labels = torch.LongTensor([0])
        loss = loss_func(embeddings, labels)
        loss.backward()
        self.assertEqual(loss, 0)