avalanche.evaluation.metrics.RunningEpochTopkAccuracy

class avalanche.evaluation.metrics.RunningEpochTopkAccuracy(top_k)[source]

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)[source]

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)