Adversarial-Machine-Learnin.../examples/pseudocode.py
2024-05-11 21:39:29 -04:00

22 lines
593 B
Python

model = Net()
accuracies = {}
for filter_name in filters:
for epsilon in epsilons:
for strength in range(5):
correct = 0
total = 0
for data, target in dataset:
atk_data = fgsm_attack(data, epsilon)
filt_data = filtered(atk_data, filter_name, strength)
prediction = model(filt_data)
total += 1
if prediction == target:
correct += 1
accuracies[filter_name][epsilon][strength] = correct/total
save_json("results.json", accuracies)