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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.
​Replay strategy: simple example on the usage of replay in Avalanche.
​AR1 strategy: this is a simple example on how to use the AR1 strategy.
​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. 
​Deep SLDA: this is a simple example on how to use the Deep SLDA strategy.
​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.
​EWC on MNIST: this example tests EWC on Split MNIST and Permuted MNIST.
​LWF on MNIST: this example tests LWF on Permuted MNIST.
​GEM and A-GEM on MNIST: this example shows how to use GEM and A-GEM strategies on MNIST.
​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.
​iCARL strategy: simple example to show how to use the iCARL strategy.
​LaMAML strategy: example on how to use a meta continual learning in Avalanche.
​RWalk strategy: example of the RWalk strategy usage.
​Online Naive: example to run a naive strategy in an online setting.
​Synaptic Intelligence: this is a simple example on how to use the Synaptic Intelligence Plugin.
​Continual Sequence Classification: sequence classification example using torchaudio and Speech Commands.
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