def test_binary_cross_entropy(self):
x = np.arange(-160, 160, 40)
expected1 = [0., 0., 0., 0., 0.6931471805599453, 40., 80., 120.]
actual1 = binary_cross_entropy(x, 0).tolist()
self.assertEqual(expected1, actual1)
expected2 = [160., 120., 80., 40., 0.6931471805599453, 0., 0., 0.]
actual2 = binary_cross_entropy(x, 1).tolist()
self.assertEqual(expected2, actual2)
def test_binary_cross_entropy(self):
x = np.arange(-160, 160, 40)
expected1 = [0., 0., 0., 0., 0.6931471805599453, 40., 80., 120.]
actual1 = binary_cross_entropy(x, 0).tolist()
self.assertEqual(expected1, actual1)
expected2 = [160., 120., 80., 40., 0.6931471805599453, 0., 0., 0.]
actual2 = binary_cross_entropy(x, 1).tolist()
self.assertEqual(expected2, actual2)
expected3 = 7.686442000846165
actual3 = binary_cross_entropy(sigmoid(x), 0).sum(0).tolist()
self.assertEqual(expected3, actual3)
def loss(self, graph, vertex_size, label, step_size=2):
s = self.forward(graph, vertex_size, step_size)
loss = binary_cross_entropy(s, label)
return loss