avalanche.evaluation.metrics.StreamForgetting

class avalanche.evaluation.metrics.StreamForgetting[source]

The StreamForgetting metric, describing the average evaluation accuracy loss detected over all experiences observed during training.

This plugin metric, computed over all observed experiences during training, is the average over 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__()[source]

Creates an instance of the StreamForgetting metric.

Methods

__init__()

Creates an instance of the StreamForgetting 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)

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