avalanche.evaluation.metric_definitions.GenericPluginMetric

class avalanche.evaluation.metric_definitions.GenericPluginMetric(metric, reset_at='experience', emit_at='experience', mode='eval')[source]

This class provides a generic implementation of a Plugin Metric. The user can subclass this class to easily implement custom plugin metrics.

__init__(metric, reset_at='experience', emit_at='experience', mode='eval')[source]

Creates an instance of a plugin metric.

Child classes can safely invoke this (super) constructor as the first experience.

Methods

__init__(metric[, reset_at, emit_at, mode])

Creates an instance of a plugin 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)

reset(strategy)

Resets the metric internal state.

result(strategy)

Obtains the value of the metric.

update(strategy)