| class TrainerCallback:
|
| def __init__(self) -> None:
|
| self.callbacks_on_init_start = []
|
| self.callbacks_on_init_end = []
|
| self.callbacks_on_epoch_start = []
|
| self.callbacks_on_epoch_end = []
|
| self.callbacks_on_train_step_start = []
|
| self.callbacks_on_train_step_end = []
|
| self.callbacks_on_keyboard_interrupt = []
|
|
|
| def on_init_start(self, trainer) -> None:
|
| if hasattr(trainer.model, "module"):
|
| if hasattr(trainer.model.module, "on_init_start"):
|
| trainer.model.module.on_init_start(trainer)
|
| else:
|
| if hasattr(trainer.model, "on_init_start"):
|
| trainer.model.on_init_start(trainer)
|
|
|
| if hasattr(trainer.criterion, "on_init_start"):
|
| trainer.criterion.on_init_start(trainer)
|
|
|
| if hasattr(trainer.optimizer, "on_init_start"):
|
| trainer.optimizer.on_init_start(trainer)
|
|
|
| if self.callbacks_on_init_start:
|
| for callback in self.callbacks_on_init_start:
|
| callback(trainer)
|
|
|
| def on_init_end(self, trainer) -> None:
|
| if hasattr(trainer.model, "module"):
|
| if hasattr(trainer.model.module, "on_init_end"):
|
| trainer.model.module.on_init_end(trainer)
|
| else:
|
| if hasattr(trainer.model, "on_init_end"):
|
| trainer.model.on_init_end(trainer)
|
|
|
| if hasattr(trainer.criterion, "on_init_end"):
|
| trainer.criterion.on_init_end(trainer)
|
|
|
| if hasattr(trainer.optimizer, "on_init_end"):
|
| trainer.optimizer.on_init_end(trainer)
|
|
|
| if self.callbacks_on_init_end:
|
| for callback in self.callbacks_on_init_start:
|
| callback(trainer)
|
|
|
| def on_epoch_start(self, trainer) -> None:
|
| if hasattr(trainer.model, "module"):
|
| if hasattr(trainer.model.module, "on_epoch_start"):
|
| trainer.model.module.on_epoch_start(trainer)
|
| else:
|
| if hasattr(trainer.model, "on_epoch_start"):
|
| trainer.model.on_epoch_start(trainer)
|
|
|
| if hasattr(trainer.criterion, "on_epoch_start"):
|
| trainer.criterion.on_epoch_start(trainer)
|
|
|
| if hasattr(trainer.optimizer, "on_epoch_start"):
|
| trainer.optimizer.on_epoch_start(trainer)
|
|
|
| if self.callbacks_on_epoch_start:
|
| for callback in self.callbacks_on_epoch_start:
|
| callback(trainer)
|
|
|
| def on_epoch_end(self, trainer) -> None:
|
| if hasattr(trainer.model, "module"):
|
| if hasattr(trainer.model.module, "on_epoch_end"):
|
| trainer.model.module.on_epoch_end(trainer)
|
| else:
|
| if hasattr(trainer.model, "on_epoch_end"):
|
| trainer.model.on_epoch_end(trainer)
|
|
|
| if hasattr(trainer.criterion, "on_epoch_end"):
|
| trainer.criterion.on_epoch_end(trainer)
|
|
|
| if hasattr(trainer.optimizer, "on_epoch_end"):
|
| trainer.optimizer.on_epoch_end(trainer)
|
|
|
| if self.callbacks_on_epoch_end:
|
| for callback in self.callbacks_on_epoch_end:
|
| callback(trainer)
|
|
|
| @staticmethod
|
| def before_backward_pass(trainer, loss_dict) -> None:
|
| if hasattr(trainer.model, "module"):
|
| if hasattr(trainer.model.module, "before_backward_pass"):
|
| trainer.model.module.before_backward_pass(loss_dict, trainer.optimizer)
|
| else:
|
| if hasattr(trainer.model, "before_backward_pass"):
|
| trainer.model.before_backward_pass(loss_dict, trainer.optimizer)
|
|
|
| @staticmethod
|
| def before_gradient_clipping(trainer) -> None:
|
| if hasattr(trainer.model, "module"):
|
| if hasattr(trainer.model.module, "before_gradient_clipping"):
|
| trainer.model.module.before_gradient_clipping()
|
| else:
|
| if hasattr(trainer.model, "before_gradient_clipping"):
|
| trainer.model.before_gradient_clipping()
|
|
|
| def on_train_step_start(self, trainer) -> None:
|
| if hasattr(trainer.model, "module"):
|
| if hasattr(trainer.model.module, "on_train_step_start"):
|
| trainer.model.module.on_train_step_start(trainer)
|
| else:
|
| if hasattr(trainer.model, "on_train_step_start"):
|
| trainer.model.on_train_step_start(trainer)
|
|
|
| if hasattr(trainer.criterion, "on_train_step_start"):
|
| trainer.criterion.on_train_step_start(trainer)
|
|
|
| if hasattr(trainer.optimizer, "on_train_step_start"):
|
| trainer.optimizer.on_train_step_start(trainer)
|
|
|
| if self.callbacks_on_train_step_start:
|
| for callback in self.callbacks_on_train_step_start:
|
| callback(trainer)
|
|
|
| def on_train_step_end(self, trainer) -> None:
|
| if hasattr(trainer.model, "module"):
|
| if hasattr(trainer.model.module, "on_train_step_end"):
|
| trainer.model.module.on_train_step_end(trainer)
|
| else:
|
| if hasattr(trainer.model, "on_train_step_end"):
|
| trainer.model.on_train_step_end(trainer)
|
|
|
| if hasattr(trainer.criterion, "on_train_step_end"):
|
| trainer.criterion.on_train_step_end(trainer)
|
|
|
| if hasattr(trainer.optimizer, "on_train_step_end"):
|
| trainer.optimizer.on_train_step_end(trainer)
|
|
|
| if self.callbacks_on_train_step_end:
|
| for callback in self.callbacks_on_train_step_end:
|
| callback(trainer)
|
|
|
| def on_keyboard_interrupt(self, trainer) -> None:
|
| if hasattr(trainer.model, "module"):
|
| if hasattr(trainer.model.module, "on_keyboard_interrupt"):
|
| trainer.model.module.on_keyboard_interrupt(trainer)
|
| else:
|
| if hasattr(trainer.model, "on_keyboard_interrupt"):
|
| trainer.model.on_keyboard_interrupt(trainer)
|
|
|
| if hasattr(trainer.criterion, "on_keyboard_interrupt"):
|
| trainer.criterion.on_keyboard_interrupt(trainer)
|
|
|
| if hasattr(trainer.optimizer, "on_keyboard_interrupt"):
|
| trainer.optimizer.on_keyboard_interrupt(trainer)
|
|
|
| if self.callbacks_on_keyboard_interrupt:
|
| for callback in self.callbacks_on_keyboard_interrupt:
|
| callback(trainer)
|
|
|
