code: def upsample_volume_grid(self, res_target, device):
      self.app_plane, self.app_line = self.up_sampling_VM(
          self.app_plane, self.app_line, res_target
      )
      self.density_plane, self.density_line = self.up_sampling_VM(
          self.density_plane, self.density_line, res_target
      )
      for i in range(len(self.vecMode)):
          d_mask_size = self.density_line_mask[i].size()
          a_mask_size = self.app_line_mask[i].size()
          d_dim = self.density_line[i].size()
          a_dim = self.app_line[i].size()
          self.density_line_mask[i] = self.rank_mask(
              self.current_rank[0],
              d_mask_size[1],
              d_dim[2],
              d_dim[3],
              device,
          )
          self.app_line_mask[i] = self.rank_mask(
              self.current_rank[1],
              a_mask_size[1],
              a_dim[2],
              a_dim[3],
              device,
          )
      for i in range(len(self.matMode)):
          d_mask_size = self.density_plane_mask[i].size()
          a_mask_size = self.app_plane_mask[i].size()
          d_dim = self.density_plane[i].size()
          a_dim = self.app_plane[i].size()
          self.density_plane_mask[i] = self.rank_mask(
              self.current_rank[0],
              d_mask_size[1],
              d_dim[2],
              d_dim[3],
              device,
          )
          self.app_plane_mask[i] = self.rank_mask(
              self.current_rank[1],
              a_mask_size[1],
              a_dim[2],
              d_dim[3],
              device,
          )
      self.update_stepSize(res_target)
      print(f"upsamping to {res_target}")
  
file_path: slimmerf/models/tensoRF.py
imports: from .tensorBase import *
label_desc: Use image node_id 16 for calling the TensorVMSplit obj's underlying member method code with example usage: obj.upsample_volume_grid(res_target, device) without return types