avalanche.training.ICaRLLossPlugin

class avalanche.training.ICaRLLossPlugin[source]

Similar to the Knowledge Distillation Loss. Works as follows: The target is constructed by taking the one-hot vector target for the current sample and assigning to the position corresponding to the past classes the output of the old model on the current sample. Doesn’t work if classes observed in previous experiences might be observed again in future training experiences.

__init__()[source]

Methods

__init__()

after_backward(strategy, **kwargs)

Called after criterion.backward() by the BaseStrategy.

after_eval(strategy, **kwargs)

Called after eval by the BaseStrategy.

after_eval_dataset_adaptation(strategy, **kwargs)

Called after eval_dataset_adaptation by the BaseStrategy.

after_eval_exp(strategy, **kwargs)

Called after eval_exp by the BaseStrategy.

after_eval_forward(strategy, **kwargs)

Called after model.forward() by the BaseStrategy.

after_eval_iteration(strategy, **kwargs)

Called after the end of an iteration by the BaseStrategy.

after_forward(strategy, **kwargs)

Called after model.forward() by the BaseStrategy.

after_train_dataset_adaptation(strategy, ...)

Called after train_dataset_adapatation by the BaseStrategy.

after_training(strategy, **kwargs)

Called after train by the BaseStrategy.

after_training_epoch(strategy, **kwargs)

Called after train_epoch by the BaseStrategy.

after_training_exp(strategy, **kwargs)

Called after train_exp by the BaseStrategy.

after_training_iteration(strategy, **kwargs)

Called after the end of a training iteration by the BaseStrategy.

after_update(strategy, **kwargs)

Called after optimizer.update() by the BaseStrategy.

before_backward(strategy, **kwargs)

Called before criterion.backward() by the BaseStrategy.

before_eval(strategy, **kwargs)

Called before eval by the BaseStrategy.

before_eval_dataset_adaptation(strategy, ...)

Called before eval_dataset_adaptation by the BaseStrategy.

before_eval_exp(strategy, **kwargs)

Called before eval_exp by the BaseStrategy.

before_eval_forward(strategy, **kwargs)

Called before model.forward() by the BaseStrategy.

before_eval_iteration(strategy, **kwargs)

Called before the start of a training iteration by the BaseStrategy.

before_forward(strategy, **kwargs)

Called before model.forward() by the BaseStrategy.

before_train_dataset_adaptation(strategy, ...)

Called before train_dataset_adapatation by the BaseStrategy.

before_training(strategy, **kwargs)

Called before train by the BaseStrategy.

before_training_epoch(strategy, **kwargs)

Called before train_epoch by the BaseStrategy.

before_training_exp(strategy, **kwargs)

Called before train_exp by the BaseStrategy.

before_training_iteration(strategy, **kwargs)

Called before the start of a training iteration by the BaseStrategy.

before_update(strategy, **kwargs)

Called before optimizer.update() by the BaseStrategy.