66a3e3cb31ddc9214c47a54411d58a31f1ab9ea7,kornia/augmentation/augmentation.py,RandomAffine,forward,#RandomAffine#Any#Any#,344

Before Change

        if params is None:
            height, width = self.infer_image_shape(input)
            batch_size: int = self.infer_batch_size(input)
            self.set_params(batch_size, height, width, self.degrees, self.translate, self.scale, self.shear)
        return super().forward(input, self._params)


class CenterCrop(AugmentationBase):

After Change

        return pg.random_affine_gen(
            batch_size, height, width, self.degrees, self.translate, self.scale, self.shear, same_on_batch)

    def forward(self, input: UnionType, params: Optional[Dict[str, torch.Tensor]] = None) -> UnionType:  // type: ignore
        if params is None:
            height, width = self.infer_image_shape(input)
            batch_size: int = self.infer_batch_size(input)
            self._params = self.get_params(batch_size, height, width)
        else:
            self._params = params
        return super().forward(input, self._params)


class CenterCrop(AugmentationBase):

Instances