code: def compute_appfeature(self, xyz_sampled):
      coordinate_plane = (
          torch.stack(
              (
                  xyz_sampled[..., self.matMode[0]],
                  xyz_sampled[..., self.matMode[1]],
                  xyz_sampled[..., self.matMode[2]],
              )
          )
          .detach()
          .view(3, -1, 1, 2)
      )
      coordinate_line = torch.stack(
          (
              xyz_sampled[..., self.vecMode[0]],
              xyz_sampled[..., self.vecMode[1]],
              xyz_sampled[..., self.vecMode[2]],
          )
      )
      coordinate_line = (
          torch.stack(
              (torch.zeros_like(coordinate_line), coordinate_line),
              dim=-1,
          )
          .detach()
          .view(3, -1, 1, 2)
      )
      plane_coef_point, line_coef_point = [], []
      for idx_plane in range(len(self.app_plane)):
          plane_coef_point.append(
              F.grid_sample(
                  self.app_plane[idx_plane]
                  * self.app_plane_mask[idx_plane],
                  coordinate_plane[[idx_plane]],
                  align_corners=True,
              ).view(-1, *xyz_sampled.shape[:1])
          )
          line_coef_point.append(
              F.grid_sample(
                  self.app_line[idx_plane]
                  * self.app_line_mask[idx_plane],
                  coordinate_line[[idx_plane]],
                  align_corners=True,
              ).view(-1, *xyz_sampled.shape[:1])
          )
      plane_coef_point, line_coef_point = torch.cat(
          plane_coef_point
      ), torch.cat(line_coef_point)
      return self.basis_mat((plane_coef_point * line_coef_point).T)
  
file_path: slimmerf/models/tensoRF.py
imports: from .tensorBase import *
label_desc: Use image node_id 14 for calling the TensorVMSplit obj's underlying member method code with example usage: obj.compute_appfeature(xyz_sampled) and returns: self