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)