7634391b070859dc1c11b092fde754dbc7911d4a,test/test_losses.py,TestDepthSmoothnessLoss,test_smoke,#TestDepthSmoothnessLoss#Any#Any#,237

Before Change

        depth = torch.rand(data_shape).to(device)

        criterion = kornia.losses.InverseDepthSmoothnessLoss()
        loss = criterion(depth, image)

    // TODO: implement me
    def test_1(self, device):
        pass

After Change

class TestDiceLoss:
    def test_smoke(self, device, dtype):
        num_classes = 3
        logits = torch.rand(2, num_classes, 3, 2, device=device, dtype=dtype)
        labels = torch.rand(2, 3, 2) * num_classes
        labels = labels.to(device).long()

        criterion = kornia.losses.DiceLoss()
        assert criterion(logits, labels) is not None

Instances