def test_channels(self):
x = np.arange(9).reshape(1, 1, 3, 3)
preprocess = SpatialSmoothing(channel_index=1)
smooth_x = preprocess(x)
new_x = np.arange(9).reshape(1, 3, 3, 1)
preprocess = SpatialSmoothing()
new_smooth_x = preprocess(new_x)
self.assertTrue((smooth_x[0, 0] == new_smooth_x[0, :, :, 0]).all())
def test_channels(self):
x = np.arange(9).reshape(1, 1, 3, 3)
preprocess = SpatialSmoothing(channel_index=1)
x_smooth, _ = preprocess(x)
x_new = np.arange(9).reshape(1, 3, 3, 1)
preprocess = SpatialSmoothing()
x_new_smooth, _ = preprocess(x_new)
self.assertTrue((x_smooth[0, 0] == x_new_smooth[0, :, :, 0]).all())
def test_failure(self):
x = np.arange(10).reshape(5, 2)
preprocess = SpatialSmoothing(channel_index=1)
with self.assertRaises(ValueError) as context:
preprocess(x)
self.assertIn('Feature vectors detected.', str(context.exception))
def test_ones(self):
m, n = 10, 2
x = np.ones((1, m, n, 3))
# Start to test
for window_size in range(1, 20):
preprocess = SpatialSmoothing(window_size=window_size)
smoothed_x, _ = preprocess(x)
self.assertTrue((smoothed_x == 1).all())
def test_ones(self):
m, n = 10, 2
x = np.ones((1, m, n, 3))
# Start to test
for window_size in range(1, 20):
with self.subTest("Sliding window size = {}".format(window_size)):
preprocess = SpatialSmoothing()
smoothed_x = preprocess(x, window_size)
self.assertTrue((smoothed_x == 1).all())
def defenses(model, X, adv_X, FS=False, SS=False, targeted=False):
if FS:
fs = FeatureSqueezing(bit_depth=1)(adv_X, clip_values=(-1, 1))
succ_rate, _ = evaluate(model, X, fs, targeted=targeted)
print("\nAfter FS %s success rate: %.2f%%" %
(targeted, succ_rate * 100))
if SS:
ss = SpatialSmoothing(channel_index=1,
window_size=20)(adv_X, clip_values=(-1, 1))
succ_rate, _ = evaluate(model, X, ss, targeted=targeted)
print("\nAfter SS %s success rate: %.2f%%" %
(targeted, succ_rate * 100))
return 0
def test_fix(self):
x = np.array([[[[0.1], [0.2], [0.3]], [[0.7], [0.8], [0.9]],
[[0.4], [0.5], [0.6]]]]).astype(np.float32)
# Start to test
preprocess = SpatialSmoothing(window_size=3)
x_smooth, _ = preprocess(x)
self.assertTrue(
(x_smooth == np.array([[[[0.2], [0.3], [0.3]], [[0.4], [0.5],
[0.6]],
[[0.5], [0.6],
[0.6]]]]).astype(np.float32)).all())
preprocess = SpatialSmoothing(window_size=1)
x_smooth, _ = preprocess(x)
self.assertTrue((x_smooth == x).all())
preprocess = SpatialSmoothing(window_size=2)
x_smooth, _ = preprocess(x)
self.assertTrue(
(x_smooth == np.array([[[[0.1], [0.2], [0.3]], [[0.7], [0.7],
[0.8]],
[[0.7], [0.7],
[0.8]]]]).astype(np.float32)).all())
def test_fix(self):
x = np.array([[[[1], [2], [3]], [[7], [8], [9]], [[4], [5], [6]]]])
# Start to test
preprocess = SpatialSmoothing()
smooth_x = preprocess(x, window_size=3)
self.assertTrue((smooth_x == np.array([[[[2], [3], [3]], [[4], [5],
[6]],
[[5], [6], [6]]]])).all())
smooth_x = preprocess(x, window_size=1)
self.assertTrue((smooth_x == x).all())
smooth_x = preprocess(x, window_size=2)
self.assertTrue((smooth_x == np.array([[[[1], [2], [3]], [[7], [7],
[8]],
[[7], [7], [8]]]])).all())