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.
- CoPE Strategy: this is a simple example on how to use the CoPE plugin. It's an example in the online data incremental setting, where both learning and evaluation is completely task-agnostic.
- Cumulative Strategy: how 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 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.
- Continual Sequence Classification: sequence classification example using torchaudio and Speech Commands.