def test_backward(self):
a = as_variable(6.0)
b = as_variable(4.0)
c = div(a, b)
c.backward()
self.assertEqual(a.grad.data, np.array(1/4))
self.assertEqual(b.grad.data, np.array(-6/4**2))
def test_backward_with_broadcast(self):
x0 = Variable(np.array([10, 11, 12]))
x1 = Variable(np.array([2]))
y = div(x0, x1)
y.backward()
assert_equal(x0.grad.data, np.array([0.5, 0.5, 0.5]))
assert_equal(x1.grad.data, np.array([-10/4-11/4-12/4]))
def test_div_backward(self, culc_object):
x0 = culc_object[0]
x1 = culc_object[1]
y = div(x0, x1)
y.backward()
assert x0.grad.data == 1 / 3 and x1.grad.data == -2 / 9
def test_div(self, culc_object):
assert div(culc_object[0], culc_object[1]).data == 2 / 3
def test_forward(self):
a = as_variable(6.0)
b = as_variable(4.0)
c = div(a, b)
self.assertEqual(c.data, np.array(1.5))