def forward(self, depth_src: Tensor, patch_dst: Tensor) -> Tensor:
        """Warp a tensor from destination frame to reference given the depth in the reference frame.

        Args:
            depth_src: the depth in the reference frame. The tensor must have a shape :math:`(B, 1, H, W)`.
            patch_dst: the patch in the destination frame. The tensor must have a shape :math:`(B, C, H, W)`.

        Return:
            the warped patch from destination frame to reference.

        Shape:
            - Output: :math:`(N, C, H, W)` where C = number of channels.

        Example:
            >>> # pinholes camera models
            >>> pinhole_dst = PinholeCamera(torch.randn(1, 4, 4), torch.randn(1, 4, 4),
            ... torch.tensor([32]), torch.tensor([32]))
            >>> pinhole_src = PinholeCamera(torch.randn(1, 4, 4), torch.randn(1, 4, 4),
            ... torch.tensor([32]), torch.tensor([32]))
            >>> # create the depth warper, compute the projection matrix
            >>> warper = DepthWarper(pinhole_dst, 32, 32)
            >>> _ = warper.compute_projection_matrix(pinhole_src)
            >>> # warp the destination frame to reference by depth
            >>> depth_src = torch.ones(1, 1, 32, 32)  # Nx1xHxW
            >>> image_dst = torch.rand(1, 3, 32, 32)  # NxCxHxW
            >>> image_src = warper(depth_src, image_dst)  # NxCxHxW

        """
        return kornia_ops.map_coordinates(
            patch_dst,
            self.warp_grid(depth_src),
            mode=self.mode,
            padding_mode=self.padding_mode,
            align_corners=self.align_corners,
        )
Warp a tensor from destination frame to reference given the depth in the reference frame.

        Args:
            depth_src: the depth in the reference frame. The tensor must have a shape :math:`(B, 1, H, W)`.
            patch_dst: the patch in the destination frame. The tensor must have a shape :math:`(B, C, H, W)`.

        Return:
            the warped patch from destination frame to reference.

        Shape:
            - Output: :math:`(N, C, H, W)` where C = number of channels.

        Example:
            >>> # pinholes camera models
            >>> pinhole_dst = PinholeCamera(torch.randn(1, 4, 4), torch.randn(1, 4, 4),
            ... torch.tensor([32]), torch.tensor([32]))
            >>> pinhole_src = PinholeCamera(torch.randn(1, 4, 4), torch.randn(1, 4, 4),
            ... torch.tensor([32]), torch.tensor([32]))
            >>> # create the depth warper, compute the projection matrix
            >>> warper = DepthWarper(pinhole_dst, 32, 32)
            >>> _ = warper.compute_projection_matrix(pinhole_src)
            >>> # warp the destination frame to reference by depth
            >>> depth_src = torch.ones(1, 1, 32, 32)  # Nx1xHxW
            >>> image_dst = torch.rand(1, 3, 32, 32)  # NxCxHxW
            >>> image_src = warper(depth_src, image_dst)  # NxCxHxW

        
kornia/geometry/depth.py