Training

Baselines and Strategies Code Examples

Avalanche offers significant support for training (with templates, strategies and plug-ins). Here you can find a list of examples related to the training and some strategies available in Avalanche (each strategy reproduces original paper results in the CL-Baselines repository:

• Joint-Training: this example shows how to take a stream of experiences and train simultaneously on all of them. This is useful to implement the "offline" or "multi-task" upper bound.

• AR1 strategy: t_his is a simple example on how to use the AR1 strategy._

• Cumulative Strategy: h_ow to define your own cumulative strategy based on the different Data Loaders made available in Avalanche._

• Early Stopping: this example shows how to use early stopping to dynamically stop the training procedure when the model converged instead of training for a fixed number of epochs.

• Object Detection: this example shows how to run object detection/segmentation tasks.

• Object Detection with Elvis: this example shows how to run object detection/segmentation tasks with a toy benchmark based on the LVIS dataset.

• Object Detection Training: set of examples showing how you can use Avalanche for distributed training of object detector.

• Ex-Model Continual Learning: this example shows how to create a stream of pre-trained model from which to learn.

• Generative Replay: this is a simple example on how to implement generative replay in Avalanche.

• Online Naive: example to run a naive strategy in an online setting.

• Continual Sequence Classification: sequence classification example using torchaudio and Speech Commands.