PyArmour
Zero-configuration adversarial robustness testing for ML models using pytest.
Installation
pip install pyarmour
Quick Start
Decorator Usage
import pytest
from pyarmour import adversarial_test
@adversarial_test(model, attacks=["fgsm", "pgd"], epsilons=[0.03, 0.1])
def test_my_model(model, x, y):
assert model(x).argmax() == y
CLI Usage
pyarmour run --model-path model.pth --data-path test_data/ --output report.html
Features
- Zero-configuration adversarial testing via pytest
- Pure NumPy implementation - no framework dependencies
- Built-in attacks: FGSM, PGD, DeepFool
- Visual diagnostics for vision models
- Text diff reports for NLP models
Documentation
Full documentation available at pyarmour.readthedocs.io
1 maintainer
Metadata
1 maintainer
Release files for pyarmour 0.1.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pyarmour-0.1.3.tar.gz | 19.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pyarmour-0.1.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 39.5 kB
Release files / pyarmour-0.1.3.tar.gz
| Download URL | pyarmour-0.1.3.tar.gz |
|---|---|
| Size | 19.4 kB |
| Tags | Source |
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Release files / pyarmour-0.1.3-py3-none-any.whl
| Download URL | pyarmour-0.1.3-py3-none-any.whl |
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| Size | 20.1 kB |
| Tags | Python 3 |
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