6ee3f1b0d2a6ebadc9e2f664354594342ab0805d,kornia/augmentation/augmentation.py,RandomSharpness,__init__,#RandomSharpness#Any#Any#Any#Any#,1077

Before 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}.")

After Change

    def generate_parameters(self, batch_shape: torch.Size) -> Dict[str, torch.Tensor]:
        return dict()

    def compute_transformation(self, input: torch.Tensor, params: Dict[str, torch.Tensor]) -> torch.Tensor:
        return F.compute_hflip_transformation(input)

    def apply_transform(self, input: torch.Tensor, params: Dict[str, torch.Tensor]) -> torch.Tensor:

Instances