def test_numeric_gradient(self):
l = SigmoidLayer()
x = np.random.rand(2)
gradient = l.numeric_gradient(x)
l.forward(x)
delta = l.backward([1, 1])
assert_almost_equal(np.diag(gradient), delta)
def test_forward_backward(self):
l = SigmoidLayer()
y = l.forward(np.array([5, 5]))
self.assertEqual(y.shape, (2, ))
assert_almost_equal(y, np.array([0.993307, 0.993307]), decimal=5)
d = l.backward(np.array([2, 3]))
self.assertEqual(d.shape, (2, ))
assert_almost_equal(d, np.array([0.0132961, 0.0199442]), decimal=5)
return