def test_mutiple():
x1 = Variable(np.array(1))
x2 = Variable(np.array(2))
x3 = Variable(np.array(3))
y = add(mutiple(x3, x2), x1)
y.backward()
assert (y.data == np.array(7)) and (x2.grad == 3) and (x3.grad == 2)
def test_v2_function():
x1 = Variable(np.array(1))
x2 = Variable(np.array(2))
y = square(x1)
y.backward()
num_grad = numerical_diff(square, x1)
assert np.allclose(x1.grad, num_grad)
def test_check_square():
# P8
# F(x) == x**2
x = Variable(np.array(20.0))
#f = Function()
f = Square()
y = f(x)
assert y == Variable(np.array(20 * 20))
def test_mutiple2():
# P117
x1 = Variable(np.array(1))
x2 = Variable(np.array(2))
x3 = Variable(np.array(3))
y = x3 * x2 + x1
y.backward()
assert (y.data == np.array(7)) and (x2.grad == 3) and (x3.grad == 2)
def test_retain_grad():
x0 = Variable(np.array(1))
x1 = Variable(np.array(1))
t = add(x0, x1)
y = add(x0, t)
y.backward()
assert (y.grad, t.grad) == (np.array(1), None)
assert (x0.grad, x1.grad) == (2, np.array(1)) # y = 2x0 + x1
def test_check_square_exp_square():
# test for composite function
x = Variable(np.array(3.0))
A = Square()
B = Exp()
C = Square()
y = C(B(A(x)))
assert y == Variable(np.array(np.exp(3 * 3)**2))
def test_double_usage_same_variable():
x = Variable(np.array(1))
y = add(add(x, x), x)
y.backward()
assert (x.grad == 3)
x.cleargrad()
y = add(x, x)
y.backward()
assert (x.grad == 2)
def test_inputs():
# P120
x = Variable(np.array(2)) + np.array(3)
assert np.array(5) == x.data
# P121
x = Variable(np.array(2)) + 3.0
assert np.array(5) == x.data
# P123
x = 3.0 * Variable(np.array(2))
assert np.array(6) == x.data
# P123
x = np.array([3.0]) * Variable(np.array([2]))
assert np.array(6) == x.data
def test_auto_grad_and_numerical_grad():
# P50
x = Variable(np.random.rand(1))
y = square(x)
y.backward()
num_grad = numerical_diff(square, x)
assert np.allclose(x.grad, num_grad)
def test_default_grad():
x = Variable(np.array(2.0))
y = square(x)
y.backward()
assert y.grad != np.array(1)
# P101
assert y.grad is None
def test_auto_grad():
# P34
v = 0.5
grad = 1
x = Variable(np.array(v))
A = Square()
B = Exp()
C = Square()
a = A(x)
b = B(a)
y = C(b)
y.grad = np.array(grad)
C.inputs[0].grad = C.backward(y.grad)
B.inputs[0].grad = B.backward(C.inputs[0].grad)
A.inputs[0].grad = A.backward(B.inputs[0].grad)
x2 = Variable(np.array(v))
A2 = Square()
B2 = Exp()
C2 = Square()
y2 = C2(B2(A2(x2)))
y2.grad = np.array(grad)
y2.backward()
assert x2.grad == x.grad
def test_auto_link():
# P32
x = Variable(np.array(1.5))
A = Exp()
B = Square()
C = Square()
a = A(x)
b = B(a)
y = C(b)
assert y.creator == C
assert y.creator.inputs[0] == b
assert y.creator.inputs[0].creator == B
assert y.creator.inputs[0].creator.inputs[0] == a
assert y.creator.inputs[0].creator.inputs[0].creator == A
assert y.creator.inputs[0].creator.inputs[0].creator.inputs[0] == x
def test_memory():
for i in range(100):
x = Variable(np.random.rand(10000))
for j in range(100):
x = square(x)
def test_property():
x = Variable(np.ones((2, 3)))
assert x.shape == (2, 3)
assert x.size == 6
assert x.dtype == np.float64
assert len(x) == 2
def test_variable_name():
x = Variable(np.array(1))
assert x.name == None
v_name = '1244'
x = Variable(np.array(1), v_name)
assert x.name == v_name
def test_complex_path():
x = Variable(np.array(2))
a = square(x)
y = add(square(a), square(a))
y.backward()
assert y.data == np.array(32) and x.grad == np.array(64)
def test_check_not_eq_function():
x = Variable(np.array(2.0))
y = Variable(np.array(3.0))
assert x != y
def test_check_data_is_different():
# P4
data = np.array(1.0)
x = Variable(data)
assert x.data != np.array(2.0)
def test_check_data_unchanged():
# P4
data = np.array(1.0)
x = Variable(data)
assert x.data == np.array(1.0)
def test_add():
x1 = Variable(np.array(1))
x2 = Variable(np.array(2))
y = add(x1, x2)
y.backward()
assert (x1.grad == 1) and (x2.grad == 1)
def test_check_exp():
x = Variable(np.array(3.0))
f = Exp()
y = f(x)
assert y == Variable(np.array(np.exp(x.data)))
def test_config_v1():
Config.enable_backprob = True
x = Variable(np.ones((100, 100, 100)))
y = square(square(square(x)))
y.backward()
def test_exp_diff():
x = Variable(np.array(2.0))
f = Exp()
y = f(x)
gy = f.backward(np.array(3.0))
assert gy == np.array(np.exp(2.0) * 3)
def test_square_diff():
x = Variable(np.array(2.0))
f = Square()
y = f(x)
gy = f.backward(np.array(3))
assert gy == np.array(2 * 2 * 3)
def test_config_v2():
Config.enable_backprob = False
x = Variable(np.ones((100, 100, 100)))
y = square(square(square(x)))
def test_add_two_same_variable():
x1 = Variable(np.array(1))
x2 = Variable(np.array(2))
y = add(x1, x1)
y.backward()
assert (x1.grad == 2)