avalanche.evaluation.metrics.MinibatchClassAccuracy

class avalanche.evaluation.metrics.MinibatchClassAccuracy(classes=None)

The minibatch plugin class accuracy metric. This metric only works at training time.

This metric computes the average accuracy over patterns from a single minibatch. It reports the result after each iteration.

If a more coarse-grained logging is needed, consider using EpochClassAccuracy instead.

__init__(classes=None)

Creates an instance of the MinibatchClassAccuracy metric.

Methods

__init__([classes])	Creates an instance of the MinibatchClassAccuracy 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)
metric_value_name(m_value)
reset()	Resets the metric internal state.
result()	Obtains the value of the metric.
update(strategy)