avalanche.evaluation.metrics.StreamBWT

class avalanche.evaluation.metrics.StreamBWT

The StreamBWT metric, emitting the average BWT across all experiences encountered during training.

This plugin metric, computed over all observed experiences during training, is the average over the difference between the last accuracy result obtained on an experience and the accuracy result obtained when first training on that experience.

This metric is computed during the eval phase only.

__init__()

Creates an instance of the StreamForgetting metric.

Methods

__init__()	Creates an instance of the StreamForgetting metric.
after_backward(strategy)	Called after criterion.backward() by the BaseStrategy.
after_eval(strategy)	Called after eval by the BaseStrategy.
after_eval_dataset_adaptation(strategy)	Called after eval_dataset_adaptation by the BaseStrategy.
after_eval_exp(strategy)	Called after eval_exp by the BaseStrategy.
after_eval_forward(strategy)	Called after model.forward() by the BaseStrategy.
after_eval_iteration(strategy)	Called after the end of an iteration by the BaseStrategy.
after_forward(strategy)	Called after model.forward() by the BaseStrategy.
after_train_dataset_adaptation(strategy)	Called after train_dataset_adapatation by the BaseStrategy.
after_training(strategy)	Called after train by the BaseStrategy.
after_training_epoch(strategy)	Called after train_epoch by the BaseStrategy.
after_training_exp(strategy)	Called after train_exp by the BaseStrategy.
after_training_iteration(strategy)	Called after the end of a training iteration by the BaseStrategy.
after_update(strategy)	Called after optimizer.update() by the BaseStrategy.
before_backward(strategy)	Called before criterion.backward() by the BaseStrategy.
before_eval(strategy)	Called before eval by the BaseStrategy.
before_eval_dataset_adaptation(strategy)	Called before eval_dataset_adaptation by the BaseStrategy.
before_eval_exp(strategy)	Called before eval_exp by the BaseStrategy.
before_eval_forward(strategy)	Called before model.forward() by the BaseStrategy.
before_eval_iteration(strategy)	Called before the start of a training iteration by the BaseStrategy.
before_forward(strategy)	Called before model.forward() by the BaseStrategy.
before_train_dataset_adaptation(strategy)	Called before train_dataset_adapatation by the BaseStrategy.
before_training(strategy)	Called before train by the BaseStrategy.
before_training_epoch(strategy)	Called before train_epoch by the BaseStrategy.
before_training_exp(strategy)	Called before train_exp by the BaseStrategy.
before_training_iteration(strategy)	Called before the start of a training iteration by the BaseStrategy.
before_update(strategy)	Called before optimizer.update() by the BaseStrategy.
exp_result([k])	Result for experience defined by a key.
exp_update(k, v[, initial])	Update forgetting metric.
metric_result(strategy)
metric_update(strategy)
reset()	Resets the forgetting metrics.
reset_last()	Resets the last metric value.
result([k])	The average forgetting over all experience.
update(k, v[, initial])	Update forgetting metric.

Attributes