avalanche.evaluation.metrics.ExperienceForgetting

class avalanche.evaluation.metrics.ExperienceForgetting

The ExperienceForgetting metric, describing the accuracy loss detected for a certain experience.

This plugin metric, computed separately for each experience, is the difference between the accuracy result obtained after first training on a experience and the accuracy result obtained on the same experience at the end of successive experiences.

This metric is computed during the eval phase only.

__init__()

Creates an instance of the ExperienceForgetting metric.

Methods

__init__()	Creates an instance of the ExperienceForgetting metric.
after_backward(strategy)
after_eval(strategy)
after_eval_dataset_adaptation(strategy)
after_eval_exp(strategy)
after_eval_forward(strategy)
after_eval_iteration(strategy)
after_forward(strategy)
after_train_dataset_adaptation(strategy)
after_training(strategy)
after_training_epoch(strategy)
after_training_exp(strategy)
after_training_iteration(strategy)
after_update(strategy)
before_backward(strategy)
before_eval(strategy)
before_eval_dataset_adaptation(strategy)
before_eval_exp(strategy)
before_eval_forward(strategy)
before_eval_iteration(strategy)
before_forward(strategy)
before_train_dataset_adaptation(strategy)
before_training(strategy)
before_training_epoch(strategy)
before_training_exp(strategy)
before_training_iteration(strategy)
before_update(strategy)
metric_result(strategy)
metric_update(strategy)
reset()	Resets the metric.
reset_last()	Resets the last metric value.
result()	Forgetting for all experiences.
result_key(k)	Forgetting for an experience defined by its key.
update(k, v[, initial])	Update forgetting metric.

Attributes

forgetting	The general metric to compute forgetting
eval_exp_id	The current evaluation experience id
train_exp_id	The last encountered training experience id