From 12f37f8786b0e80ab40cd733afa57884ae7c03ad Mon Sep 17 00:00:00 2001 From: Antonio Carta Date: Fri, 17 Nov 2023 13:19:53 +0100 Subject: [PATCH] Update training.md --- docs/gitbook/examples/training.md | 10 ---------- 1 file changed, 10 deletions(-) diff --git a/docs/gitbook/examples/training.md b/docs/gitbook/examples/training.md index 275ae191a..1c0e2dc3e 100644 --- a/docs/gitbook/examples/training.md +++ b/docs/gitbook/examples/training.md @@ -7,23 +7,13 @@ description: 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](https://github.com/ContinualAI/continual-learning-baselines) repository: * [Joint-Training](../../../examples/joint\_training.py): _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](../../../examples/replay.py)_: simple example on the usage of replay in Avalanche._ * [AR1 strategy](../../../examples/ar1.py): t_his is a simple example on how to use the AR1 strategy._ -* [CoPE Strategy](../../../examples/cope.py): _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](../../../examples/dataloader.py): h_ow to define your own cumulative strategy based on the different Data Loaders made available in Avalanche._ -* [Deep SLDA](../../../examples/deep\_slda.py)_: this is a simple example on how to use the Deep SLDA strategy._ * [Early Stopping](../../../examples/all\_mnist\_early\_stopping.py): _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](../../../examples/detection.py): _this example shows how to run object detection/segmentation tasks._ * [Object Detection with Elvis](../../../examples/detection\_lvis.py)_: this example shows how to run object detection/segmentation tasks with a_ _toy benchmark based on the LVIS dataset._ * [Object Detection Training](https://github.com/ContinualAI/avalanche/tree/master/examples/tvdetection): _set of examples showing how you can use Avalanche for distributed training of object detector._ -* [EWC on MNIST](../../../examples/ewc\_mnist.py)_: this example tests EWC on Split MNIST and Permuted MNIST._ -* [LWF on MNIST](../../../examples/lfl\_mnist.py)_: this example tests LWF on Permuted MNIST._ -* [GEM and A-GEM on MNIST](../../../examples/gem\_agem\_mnist.py)_: this example shows how to use GEM and A-GEM strategies on MNIST._ * [Ex-Model Continual Learning](../../../examples/ex\_model\_cl.py)_: this example shows how to create a stream of pre-trained model from which to learn._ * [Generative Replay](../../../examples/generative\_replay\_MNIST\_generator.py)_: this is a simple example on how to implement generative replay in Avalanche._ -* [iCARL strategy](../../../examples/icarl.py): _simple example to show how to use the iCARL strategy._ -* [LaMAML strategy](../../../examples/lamaml\_cifar100.py)_: example on how to use a meta continual learning in Avalanche._ -* [RWalk strategy](../../../examples/rwalk\_mnist.py): _example of the RWalk strategy usage._ * [Online Naive](https://github.com/ContinualAI/avalanche/blob/6dbabb2ab787a53b59b9cbcb245ad500e984f671/examples/online\_naive.py): _example to run a naive strategy in an online setting._ -* [Synaptic Intelligence](../../../examples/synaptic\_intelligence.py): _this is a simple example on how to use the Synaptic Intelligence Plugin._ * [Continual Sequence Classification](../../../examples/continual\_sequence\_classification.py): _sequence classification example using torchaudio and Speech Commands._