Args: start_iter, max_iter (int): See docs above
(self, start_iter: int, max_iter: int)
| 137 | self._hooks.extend(hooks) |
| 138 | |
| 139 | def train(self, start_iter: int, max_iter: int): |
| 140 | """ |
| 141 | Args: |
| 142 | start_iter, max_iter (int): See docs above |
| 143 | """ |
| 144 | logger = logging.getLogger(__name__) |
| 145 | logger.info("Starting training from iteration {}".format(start_iter)) |
| 146 | |
| 147 | self.iter = self.start_iter = start_iter |
| 148 | self.max_iter = max_iter |
| 149 | |
| 150 | with EventStorage(start_iter) as self.storage: |
| 151 | try: |
| 152 | self.before_train() |
| 153 | for self.iter in range(start_iter, max_iter): |
| 154 | self.before_step() |
| 155 | self.run_step() |
| 156 | self.after_step() |
| 157 | # self.iter == max_iter can be used by `after_train` to |
| 158 | # tell whether the training successfully finished or failed |
| 159 | # due to exceptions. |
| 160 | self.iter += 1 |
| 161 | except Exception: |
| 162 | logger.exception("Exception during training:") |
| 163 | raise |
| 164 | finally: |
| 165 | self.after_train() |
| 166 | |
| 167 | def before_train(self): |
| 168 | for h in self._hooks: |