520e8fb57b890a7249334d9e90c9ad209d0b849f,modules.py,retina,extract_patch,#retina#Any#Any#Any#,73

Before Change

                    (0, 0), (size//2+1, size//2+1),
                    (size//2+1, size//2+1), (0, 0),
                ]
                p = p.numpy()
                p = np.pad(p, pad_dims, mode="constant")
                p = torch.from_numpy(p)

                // add correction factor
                from_x += (size//2+1)

After Change

            // pad tensor in case exceeds
            if self.exceeds(from_x, to_x, from_y, to_y, T):
                pad_dims = (
                    size//2+1, size//2+1,
                    size//2+1, size//2+1,
                    0, 0,
                    0, 0,
                )
                im = F.pad(im, pad_dims, "constant", 0)

                // add correction factor
                from_x += (size//2+1)
                to_x += (size//2+1)

Instances