Args: start_iter, max_iter (int): See docs above
(self, start_iter: int, max_iter: int)
| 116 | self._hooks.extend(hooks) |
| 117 | |
| 118 | def train(self, start_iter: int, max_iter: int): |
| 119 | """ |
| 120 | Args: |
| 121 | start_iter, max_iter (int): See docs above |
| 122 | """ |
| 123 | logger = logging.getLogger(__name__) |
| 124 | logger.info("Starting training from iteration {}".format(start_iter)) |
| 125 | |
| 126 | self.iter = self.start_iter = start_iter |
| 127 | self.max_iter = max_iter |
| 128 | |
| 129 | with EventStorage(start_iter) as self.storage: |
| 130 | try: |
| 131 | self.before_train() |
| 132 | for self.iter in range(start_iter, max_iter): |
| 133 | self.before_step() |
| 134 | self.run_step() |
| 135 | self.after_step() |
| 136 | # self.iter == max_iter can be used by `after_train` to |
| 137 | # tell whether the training successfully finished or failed |
| 138 | # due to exceptions. |
| 139 | self.iter += 1 |
| 140 | except Exception: |
| 141 | logger.exception("Exception during training:") |
| 142 | raise |
| 143 | finally: |
| 144 | self.after_train() |
| 145 | |
| 146 | def before_train(self): |
| 147 | for h in self._hooks: |