<reponame>aishikhar/avalanche<gh_stars>1-10
"""
The :py:mod:`training` module provides a generic continual learning training
class (:py:class:`BaseStrategy`) and implementations of the most common
CL strategies. These are provided either as standalone strategies in
:py:mod:`training.strategies` or as plugins (:py:mod:`training.plugins`) that
can be easily combined with your own strategy.
"""
from avalanche.evaluation.metrics import accuracy_metrics, loss_metrics
from avalanche.logging import InteractiveLogger
from .plugins import EvaluationPlugin


default_logger = EvaluationPlugin(
    accuracy_metrics(minibatch=False, epoch=True, experience=True, stream=True),
    loss_metrics(minibatch=False, epoch=True, experience=True, stream=True),
    loggers=[InteractiveLogger()])

"""
The :py:mod:`training` module provides a generic continual learning training
class (:py:class:`BaseStrategy`) and implementations of the most common
CL strategies. These are provided either as standalone strategies in
:py:mod:`training.strategies` or as plugins (:py:mod:`training.plugins`) that
can be easily combined with your own strategy.
"""
from avalanche.evaluation.metrics import accuracy_metrics, loss_metrics
from avalanche.logging import InteractiveLogger
from .plugins import EvaluationPlugin


default_logger = EvaluationPlugin(
    accuracy_metrics(minibatch=False, epoch=True, experience=True, stream=True),
    loss_metrics(minibatch=False, epoch=True, experience=True, stream=True),
    loggers=[InteractiveLogger()])
The :py:mod:`training` module provides a generic continual learning training class (:py:class:`BaseStrategy`) and implementations of the most common CL strategies. These are provided either as standalone strategies in :py:mod:`training.strategies` or as plugins (:py:mod:`training.plugins`) that can be easily combined with your own strategy.