(self)
| 311 | |
| 312 | @property |
| 313 | def grad(self): |
| 314 | size = self.size() |
| 315 | if not self.is_contiguous(): |
| 316 | size = torch.Size((size[1], size[0])) |
| 317 | out = Matrix(size, |
| 318 | self.data.grad, |
| 319 | self.row_indices, |
| 320 | self.column_indices, |
| 321 | self.offsets, |
| 322 | self.column_indices_t, |
| 323 | self.offsets_t, |
| 324 | self.block_offsets_t) |
| 325 | return out if self.is_contiguous() else out.t() |
| 326 | |
| 327 | @torch.no_grad() |
| 328 | def _expand_for_blocking(idxs, blocking): |
no test coverage detected