(self, mask)
| 402 | return optimizable_tensors |
| 403 | |
| 404 | def prune_points(self, mask): |
| 405 | valid_points_mask = ~mask |
| 406 | optimizable_tensors = self._prune_optimizer(valid_points_mask) |
| 407 | |
| 408 | self._xyz = optimizable_tensors["xyz"] |
| 409 | self._features_dc = optimizable_tensors["f_dc"] |
| 410 | self._features_rest = optimizable_tensors["f_rest"] |
| 411 | self._opacity = optimizable_tensors["opacity"] |
| 412 | self._scaling = optimizable_tensors["scaling"] |
| 413 | self._rotation = optimizable_tensors["rotation"] |
| 414 | |
| 415 | self.xyz_gradient_accum = self.xyz_gradient_accum[valid_points_mask] |
| 416 | |
| 417 | self.denom = self.denom[valid_points_mask] |
| 418 | self.max_radii2D = self.max_radii2D[valid_points_mask] |
| 419 | |
| 420 | if self.gaussian_dim == 4: |
| 421 | self._t = optimizable_tensors['t'] |
| 422 | self._scaling_t = optimizable_tensors['scaling_t'] |
| 423 | if self.rot_4d: |
| 424 | self._rotation_r = optimizable_tensors['rotation_r'] |
| 425 | self.t_gradient_accum = self.t_gradient_accum[valid_points_mask] |
| 426 | |
| 427 | def cat_tensors_to_optimizer(self, tensors_dict): |
| 428 | optimizable_tensors = {} |
no test coverage detected