Adversarial Training Box

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This Adversarial Training Box package simplifies your experiment pipeline for training neural networks using adversarial training. The entire package os class-based and can be easily extended with new training methods. The training progress can be logged via Weights & Biases

Installation

• clone the repository locally
• create new environment conda create -n adversarial-training-box python=3.10
• activate the environment conda activate adversarial-training-box
• change into verona directory cd adversarial_training_box
• install dependencies pip install -r requirements.txt
• install package locally (editable install for development) pip install -e .

Available Training Techniques

• Standard training
• FGSM
• PGD

Tutorial

Example Scripts

There are a few example scripts in the example scripts folder to see, how one can do an HPO and adversarial training for different networks and datasets.

Testing

The package was tested on the following datasets: MNIST, CIFAR-10 and GTSRB