avalanche.evaluation.metrics.RunningEpochTopkAccuracy

class avalanche.evaluation.metrics.RunningEpochTopkAccuracy(top_k)

The average top-k accuracy across all minibatches up to the current epoch iteration. This plugin metric only works at training time.

At each iteration, this metric logs the top-k accuracy averaged over all patterns seen so far in the current epoch. The metric resets its state after each training epoch.

__init__(top_k)

Creates an instance of the RunningEpochTopkAccuracy metric.

Methods

__init__(top_k)	Creates an instance of the RunningEpochTopkAccuracy 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)