def METHOD_NAME(self):
    temperature = 0.1
    for loss_class in [NTXentLoss, SupConLoss]:
        loss_funcA = loss_class(temperature)
        loss_funcB = loss_class(temperature, distance=LpDistance())
        for dtype in TEST_DTYPES:
            for loss_func in [loss_funcA, loss_funcB]:
                embedding_angles = [0, 20, 40, 60, 80]
                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, 0, 1, 1, 2])
                loss = loss_func(embeddings, labels)
                loss.backward()