def test_torch_input(self):
fgsm = FGSM(data='x', loss='loss', outputs='y')
x = self.torch_data * self.torch_data
output = fgsm.forward(data=[self.torch_data, x], state={'tape': None})
self.assertTrue(is_equal(output, self.torch_output))
def test_tf_input(self):
fgsm = FGSM(data='x', loss='loss', outputs='y')
with tf.GradientTape(persistent=True) as tape:
x = self.tf_data * self.tf_data
output = fgsm.forward(data=[self.tf_data, x], state={'tape': tape})
self.assertTrue(np.array_equal(output, self.tf_output))