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Foolbox: Fast adversarial attacks to benchmark the robustness of machine learning models in PyTorch, TensorFlow, and JAX. Foolbox 3 is built on top of EagerPy and runs natively in PyTorch, TensorFlow, and JAX. Foolbox provides a large collection of state-of-the-art gradient-based and decision-based adversarial attacks. Catch bugs before running your code thanks to extensive type annotations in Foolbox. Foolbox is a Python library that lets you easily run adversarial attacks against machine learning models like deep neural networks. It is built on top of EagerPy and works natively with models in PyTorch, TensorFlow, and JAX.
Features
- Native Performance
- State-of-the-art attacks
- Documentation available
- Type Checking
- Foolbox 3 is built on top of EagerPy and runs natively in PyTorch, TensorFlow, and JAX and comes with real batch support
- Foolbox provides a large collection of state-of-the-art gradient-based and decision-based adversarial attacks
- Catch bugs before running your code thanks to extensive type annotations in Foolbox
Project Samples
Categories
Machine LearningLicense
MIT LicenseFollow Foolbox
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