Shypd.aiThe largest open index of AI toolsAdversarial-Attacks-PyTorch is an open-source PyTorch library that provides adversarial attacks to generate adversarial examples. It offers a PyTorch-like interface, simplifying the implementation of these attacks for model robustness testing.
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Adversarial-Attacks-PyTorch, also known as Torchattacks, is a comprehensive PyTorch library designed for generating adversarial examples to test the robustness of deep learning models. It provides a PyTorch-like interface, making it intuitive for developers and researchers already familiar with PyTorch to implement various adversarial attacks. The library supports a wide array of attacks, including FGSM, PGD, CW, AutoAttack, and many more, covering different distance measures like Linf, L2, L1, and L0. It also includes features for targeted attacks, saving/loading adversarial images, and managing model training modes during attacks. The tool emphasizes ease of use and performance, often outperforming other libraries in speed for certain attacks.
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