Launch training.
(self)
| 91 | return self._iter |
| 92 | |
| 93 | def run(self) -> torch.nn.Module: |
| 94 | """Launch training.""" |
| 95 | self.runner.call_hook('before_train') |
| 96 | |
| 97 | while self._epoch < self._max_epochs and not self.stop_training: |
| 98 | self.run_epoch() |
| 99 | |
| 100 | self._decide_current_val_interval() |
| 101 | if (self.runner.val_loop is not None |
| 102 | and self._epoch >= self.val_begin |
| 103 | and (self._epoch % self.val_interval == 0 |
| 104 | or self._epoch == self._max_epochs)): |
| 105 | self.runner.val_loop.run() |
| 106 | |
| 107 | self.runner.call_hook('after_train') |
| 108 | return self.runner.model |
| 109 | |
| 110 | def run_epoch(self) -> None: |
| 111 | """Iterate one epoch.""" |
nothing calls this directly
no test coverage detected