fgsm.py

import numpy as np

from cleverhans.torch.attacks.fast_gradient_method import fast_gradient_method

eps = 0.1

# load image
url = "http://images.cocodataset.org/val2017/000000039769.jpg"
image = Image.open(requests.get(url, stream=True).raw)
x = feature_extractor(image, return_tensors="pt").pixel_values

# fast gradient sign method
x_fgm = fast_gradient_method(
    lambda x: model(x).logits, # maps normalized image to model logits
    x, # original image we want to modify
    eps, # max size of the perturbation
    np.inf #l-infinite distance to measure the perturbation
)

# print results
new_image = inverse_feature_extractor(x_fgm)
print('Predicted class: ', image2class(new_image))
new_image