Returns the state of the scheduler as a :class:`dict`. It contains an entry for every variable in self.__dict__ which is not the optimizer. The learning rate lambda functions will only be saved if they are callable objects and not if they are functions or lambdas.
(self)
| 261 | super(LambdaLR, self).__init__(optimizer, last_epoch) |
| 262 | |
| 263 | def state_dict(self): |
| 264 | """Returns the state of the scheduler as a :class:`dict`. |
| 265 | |
| 266 | It contains an entry for every variable in self.__dict__ which |
| 267 | is not the optimizer. |
| 268 | The learning rate lambda functions will only be saved if they are callable objects |
| 269 | and not if they are functions or lambdas. |
| 270 | """ |
| 271 | |
| 272 | warnings.warn(SAVE_STATE_WARNING, UserWarning) |
| 273 | state_dict = {key: value for key, value in self.__dict__.items() if key not in ('optimizer', 'lr_lambdas')} |
| 274 | state_dict['lr_lambdas'] = [None] * len(self.lr_lambdas) |
| 275 | |
| 276 | for idx, fn in enumerate(self.lr_lambdas): |
| 277 | if not isinstance(fn, types.FunctionType): |
| 278 | state_dict['lr_lambdas'][idx] = fn.__dict__.copy() |
| 279 | |
| 280 | return state_dict |
| 281 | |
| 282 | def load_state_dict(self, state_dict): |
| 283 | """Loads the schedulers state. |
no outgoing calls
no test coverage detected