6ee3f1b0d2a6ebadc9e2f664354594342ab0805d,kornia/augmentation/augmentation.py,RandomSolarize,__init__,#RandomSolarize#Any#Any#Any#Any#Any#,944

Before Change

        super(RandomSolarize, self).__init__(p=p, return_transform=return_transform, same_on_batch=same_on_batch)

        thresholds = \
            cast(torch.Tensor, thresholds) if isinstance(thresholds, torch.Tensor) else torch.tensor(thresholds)
        self.thresholds = _range_bound(thresholds, "thresholds", center=0.5, bounds=(0., 1.))

        additions = \
            cast(torch.Tensor, additions) if isinstance(additions, torch.Tensor) else torch.tensor(additions)
        self.additions = _range_bound(additions, "additions", bounds=(-0.5, 0.5))

After Change

        sharpness = cast(torch.Tensor, sharpness) if isinstance(sharpness, torch.Tensor) else torch.tensor(sharpness)
        if sharpness.dim() == 0:
            self.sharpness = torch.tensor([0, sharpness], dtype=torch.float32)
        elif sharpness.dim() == 1 and sharpness.size(0) == 2:
            self.sharpness = torch.tensor([sharpness[0], sharpness[1]], dtype=torch.float32)
        else:
            raise ValueError(f""sharpness" must be a scalar or a length 2 tensor. Got {sharpness}.")

    def __repr__(self) -> str:

Instances