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Beat Buesser
committed
Update ElasticNet unit tests
Signed-off-by: Beat Buesser <[email protected]>
1 parent f48c045 commit 4bf9c3f

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1 file changed

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‎tests/attacks/test_elastic_net.py‎

Lines changed: 91 additions & 84 deletions
Original file line numberDiff line numberDiff line change
@@ -108,28 +108,28 @@ def test_4_tensorflow_mnist(self):
108108
x_test_adv = ead.generate(self.x_test_mnist, **params)
109109
expected_x_test_adv = np.asarray(
110110
[
111-
0.45704955,
112-
0.43627003,
113-
0.57238287,
111+
0.45284095,
112+
0.43225235,
113+
0.577448,
114114
1.0,
115-
0.11541145,
116-
0.12619308,
117-
0.48318917,
118-
0.3457903,
119-
0.17863746,
120-
0.09060935,
115+
0.16554962,
116+
0.3587564,
117+
0.19202651,
118+
0.04293771,
121119
0.0,
122-
0.00963121,
120+
0.25811037,
123121
0.0,
124-
0.04749763,
125-
0.4058206,
126-
0.17860745,
122+
0.0290696,
127123
0.0,
128-
0.9153206,
129-
0.84564775,
130-
0.20603634,
131-
0.10586322,
132-
0.00947509,
124+
0.136172,
125+
0.6153389,
126+
0.12244645,
127+
0.0,
128+
0.7586619,
129+
0.8366919,
130+
0.22206311,
131+
0.12455986,
132+
0.02862802,
133133
0.0,
134134
0.0,
135135
0.0,
@@ -138,6 +138,7 @@ def test_4_tensorflow_mnist(self):
138138
0.0,
139139
]
140140
)
141+
print(x_test_adv[0, 14, :, 0])
141142
np.testing.assert_array_almost_equal(x_test_adv[0, 14, :, 0], expected_x_test_adv, decimal=6)
142143
self.assertLessEqual(np.amax(x_test_adv), 1.0)
143144
self.assertGreaterEqual(np.amin(x_test_adv), 0.0)
@@ -213,28 +214,28 @@ def test_4_tensorflow_mnist(self):
213214
x_test_adv = ead_wob.generate(self.x_test_mnist, **params)
214215
expected_x_test_adv = np.asarray(
215216
[
216-
0.3287169,
217-
0.31374657,
218-
0.42853343,
219-
0.8994576,
220-
0.19850709,
221-
0.11997936,
222-
0.5622535,
223-
0.43854535,
224-
0.19387433,
225-
0.12516324,
226-
0.0,
227-
0.10933565,
228-
0.02162433,
229-
0.07120894,
230-
0.95224255,
231-
0.3072921,
232-
0.48966524,
217+
0.32568744,
218+
0.31085464,
219+
0.43235543,
233220
1.0,
234-
0.3814998,
235-
0.15782641,
236-
0.52283823,
237-
0.12852049,
221+
0.2433605,
222+
0.3411813,
223+
0.49469775,
224+
0.2603619,
225+
0.0,
226+
0.35584357,
227+
0.0,
228+
0.2046029,
229+
0.0,
230+
0.08249304,
231+
1.0,
232+
0.35813788,
233+
0.62945133,
234+
1.0,
235+
0.32154015,
236+
0.3497113,
237+
0.7613426,
238+
0.36533928,
238239
0.0,
239240
0.0,
240241
0.0,
@@ -243,6 +244,7 @@ def test_4_tensorflow_mnist(self):
243244
0.0,
244245
]
245246
)
247+
print(x_test_adv[0, 14, :, 0])
246248
np.testing.assert_array_almost_equal(x_test_adv[0, 14, :, 0], expected_x_test_adv, decimal=6)
247249
self.assertLessEqual(np.amax(x_test_adv), 1.0)
248250
self.assertGreaterEqual(np.amin(x_test_adv), 0.0)
@@ -296,34 +298,34 @@ def test_9a_keras_mnist(self):
296298
x_test_adv = ead.generate(self.x_test_mnist, y=y_target)
297299
expected_x_test_adv = np.asarray(
298300
[
299-
0.0,
300-
0.0,
301-
0.0,
302-
0.0,
303-
0.0,
304-
0.0,
305-
0.0,
306-
0.0,
307-
0.0,
308-
0.0,
309-
0.00183569,
310-
0.0,
311-
0.0,
312-
0.49765405,
313-
1.0,
314-
0.6467149,
315-
0.0033755,
316-
0.0052456,
317-
0.0,
318-
0.01104407,
319-
0.00495547,
320-
0.02747423,
321-
0.0,
322-
0.0,
323-
0.0,
324-
0.0,
325-
0.0,
326-
0.0,
301+
0.0000000e00,
302+
0.0000000e00,
303+
0.0000000e00,
304+
0.0000000e00,
305+
0.0000000e00,
306+
0.0000000e00,
307+
0.0000000e00,
308+
0.0000000e00,
309+
0.0000000e00,
310+
7.8193319e-04,
311+
5.5843666e-03,
312+
0.0000000e00,
313+
0.0000000e00,
314+
4.9869284e-01,
315+
1.0000000e00,
316+
6.4663666e-01,
317+
3.4855194e-03,
318+
3.5087438e-03,
319+
0.0000000e00,
320+
9.8862723e-03,
321+
3.8835173e-03,
322+
3.0151173e-02,
323+
0.0000000e00,
324+
0.0000000e00,
325+
0.0000000e00,
326+
0.0000000e00,
327+
0.0000000e00,
328+
0.0000000e00,
327329
]
328330
)
329331
np.testing.assert_array_almost_equal(x_test_adv[2, 14, :, 0], expected_x_test_adv, decimal=6)
@@ -371,28 +373,28 @@ def test_6_pytorch_mnist(self):
371373
x_test_adv = ead.generate(x_test, **params)
372374
expected_x_test_adv = np.asarray(
373375
[
374-
0.01678124,
376+
0.01758931,
375377
0.0,
376378
0.0,
377379
0.0,
378380
0.0,
379381
0.0,
380382
0.0,
381383
0.0,
382-
0.00665895,
384+
0.00698278,
383385
0.0,
384-
0.11374763,
385-
0.36250514,
386-
0.5472948,
387-
0.9308808,
386+
0.11318438,
387+
0.36223832,
388+
0.54720753,
389+
0.93125045,
388390
1.0,
389-
0.99920374,
390-
0.86274165,
391-
0.6346757,
392-
0.5597227,
393-
0.24191494,
391+
0.9999359,
392+
0.8638486,
393+
0.6354147,
394+
0.5600332,
395+
0.24081531,
394396
0.25882354,
395-
0.0091916,
397+
0.00899846,
396398
0.0,
397399
0.0,
398400
0.0,
@@ -401,6 +403,7 @@ def test_6_pytorch_mnist(self):
401403
0.0,
402404
]
403405
)
406+
print(x_test_adv[2, 0, :, 14])
404407
np.testing.assert_array_almost_equal(x_test_adv[2, 0, :, 14], expected_x_test_adv, decimal=6)
405408
self.assertLessEqual(np.amax(x_test_adv), 1.0)
406409
self.assertGreaterEqual(np.amin(x_test_adv), 0.0)
@@ -429,7 +432,7 @@ def test_8_keras_iris_clipped(self):
429432
classifier = get_tabular_classifier_kr()
430433
attack = ElasticNet(classifier, targeted=False, max_iter=10, verbose=False)
431434
x_test_adv = attack.generate(self.x_test_iris)
432-
expected_x_test_adv = np.asarray([0.860373, 0.455002, 0.654925, 0.240258])
435+
expected_x_test_adv = np.asarray([0.8670352, 0.4624909, 0.6453267, 0.23096858])
433436
np.testing.assert_array_almost_equal(x_test_adv[0, :], expected_x_test_adv, decimal=6)
434437
self.assertLessEqual(np.amax(x_test_adv), 1.0)
435438
self.assertGreaterEqual(np.amin(x_test_adv), 0.0)
@@ -498,7 +501,7 @@ def test_9_keras_iris_unbounded(self):
498501
classifier = KerasClassifier(model=classifier._model, use_logits=False, channels_first=True)
499502
attack = ElasticNet(classifier, targeted=False, max_iter=10, verbose=False)
500503
x_test_adv = attack.generate(self.x_test_iris)
501-
expected_x_test_adv = np.asarray([0.860373, 0.455002, 0.654925, 0.240258])
504+
expected_x_test_adv = np.asarray([0.8670352, 0.4624909, 0.6453267, 0.23096858])
502505
np.testing.assert_array_almost_equal(x_test_adv[0, :], expected_x_test_adv, decimal=6)
503506
predictions_adv = np.argmax(classifier.predict(x_test_adv), axis=1)
504507
np.testing.assert_array_equal(
@@ -564,8 +567,10 @@ def test_3_tensorflow_iris(self):
564567
# Test untargeted attack
565568
attack = ElasticNet(classifier, targeted=False, max_iter=10, verbose=False)
566569
x_test_adv = attack.generate(self.x_test_iris)
567-
expected_x_test_adv = np.asarray([0.852286, 0.434626, 0.703376, 0.293738])
570+
expected_x_test_adv = np.asarray([0.84810126, 0.43320203, 0.70404345, 0.29160658])
571+
print(x_test_adv[0, :])
568572
np.testing.assert_array_almost_equal(x_test_adv[0, :], expected_x_test_adv, decimal=6)
573+
print(np.amax(x_test_adv))
569574
self.assertLessEqual(np.amax(x_test_adv), 1.0)
570575
self.assertGreaterEqual(np.amin(x_test_adv), 0.0)
571576

@@ -629,7 +634,8 @@ def test_3_tensorflow_iris(self):
629634
targets = random_targets(self.y_test_iris, nb_classes=3)
630635
attack = ElasticNet(classifier, targeted=True, max_iter=10, verbose=False)
631636
x_test_adv = attack.generate(self.x_test_iris, **{"y": targets})
632-
expected_x_test_adv = np.asarray([0.892806, 0.531875, 0.501707, 0.059951])
637+
expected_x_test_adv = np.asarray([0.88713187, 0.5239736, 0.49900988, 0.05677444])
638+
print(x_test_adv[0, :])
633639
np.testing.assert_array_almost_equal(x_test_adv[0, :], expected_x_test_adv, decimal=6)
634640
self.assertLessEqual(np.amax(x_test_adv), 1.0)
635641
self.assertGreaterEqual(np.amin(x_test_adv), 0.0)
@@ -699,7 +705,8 @@ def test_5_pytorch_iris(self):
699705
classifier = get_tabular_classifier_pt()
700706
attack = ElasticNet(classifier, targeted=False, max_iter=10, verbose=False)
701707
x_test_adv = attack.generate(self.x_test_iris.astype(np.float32))
702-
expected_x_test_adv = np.asarray([0.852286, 0.434626, 0.703376, 0.293738])
708+
expected_x_test_adv = np.asarray([0.84810126, 0.43320203, 0.70404345, 0.29160658])
709+
print(x_test_adv[0, :])
703710
np.testing.assert_array_almost_equal(x_test_adv[0, :], expected_x_test_adv, decimal=6)
704711
self.assertLessEqual(np.amax(x_test_adv), 1.0)
705712
self.assertGreaterEqual(np.amin(x_test_adv), 0.0)

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