avalanche.training.templates.BaseTemplate

class avalanche.training.templates.BaseTemplate(model: Module, device='cpu', plugins: Optional[List[BasePlugin]] = None)

Base class for continual learning skeletons.

Training loop The training loop is organized as follows:

train
    train_exp  # for each experience

Evaluation loop The evaluation loop is organized as follows:

eval
    eval_exp  # for each experience

__init__(model: Module, device='cpu', plugins: Optional[List[BasePlugin]] = None)

Init.

Methods

__init__(model[, device, plugins])	Init.
eval(exp_list, **kwargs)	Evaluate the current model on a series of experiences and returns the last recorded value for each metric.
train(experiences[, eval_streams])	Training loop.

Attributes

is_eval	True if the strategy is in evaluation mode.
model	PyTorch model.
device	PyTorch device where the model will be allocated.
plugins	List of `SupervisedPlugin`s. .
experience	Current experience.
is_training	True if the strategy is in training mode.
current_eval_stream	Current evaluation stream.