(self, param_state_pairs, optim_state)
| 460 | t.set(ndarray, place) |
| 461 | |
| 462 | def load(self, param_state_pairs, optim_state): |
| 463 | if self._executor is None: |
| 464 | executor = base.Executor(base.CPUPlace())._default_executor |
| 465 | else: |
| 466 | executor = self._executor._default_executor |
| 467 | |
| 468 | paddle.base.libpaddle.pir.create_loaded_parameter( |
| 469 | [param for param, state in param_state_pairs], |
| 470 | global_scope(), |
| 471 | executor, |
| 472 | ) |
| 473 | for param, state in param_state_pairs: |
| 474 | self._set_var(param.name, state) |
| 475 | |
| 476 | # restore optimizer states |
| 477 | # FIXME what if a different optimizer is used? |
| 478 | if not self.model._optimizer or not optim_state: |
| 479 | return |
| 480 | self._load_optimizer(optim_state, executor) |
| 481 | |
| 482 | def _load_optimizer(self, state, executor): |
| 483 | prog = self._progs.get('train', None) |
nothing calls this directly
no test coverage detected