icarl# Classes class models.icarl.ICarl(backbone, loss, args, transform)[source]# Bases: ContinualModel COMPATIBILITY: List[str] = ['class-il', 'task-il']# NAME: str = 'icarl'# begin_task(dataset)[source]# static binary_cross_entropy(pred, y)[source]# compute_class_means()[source]# Computes a vector representing mean features for each class. end_task(dataset)[source]# forward(x)[source]# get_loss(inputs, labels, task_idx, logits)[source]# Computes the loss tensor. Parameters: inputs (Tensor) – the images to be fed to the network labels (Tensor) – the ground-truth labels task_idx (int) – the task index logits (Tensor) – the logits of the old network Returns: the differentiable loss value Return type: Tensor static get_parser()[source]# Return type: ArgumentParser observe(inputs, labels, not_aug_inputs, logits=None, epoch=None)[source]#