def test_concat_exception():
X = Variable([1, 2, 3])
Y = Variable([1, 2])
_, _, x = X.unroll()
_, y = Y.unroll()
with pytest.raises(AssertionError):
f = F.concat([x, y])
with pytest.raises(AssertionError):
f = F.concat([])
def test_unroll_exception():
X = Variable([1, 2, 3])
with pytest.raises(TypeError):
var_list = X.unroll(1)
with pytest.raises(ValueError):
var_list = X.unroll(['a'])
with pytest.raises(ValueError):
var_list = X.unroll([0, 1, 2])
with pytest.raises(ValueError):
var_list = X.unroll([2, 1, 1])
y = Variable(1)
with pytest.raises(ValueError):
var_list = y.unroll([1, 1])
def test_rpow_exception():
X = Variable([1, 3, 3, 1, 2])
var_list = X.unroll([2, 2, 1])
x = var_list[0]
y = var_list[1]
z = var_list[2]
a = x + y
with pytest.raises(TypeError):
b = "g"**y
with pytest.raises(ValueError):
b = 2**a
def test_mul_exception():
X = Variable([1, 2, 2, 1, 4])
var_list = X.unroll([2, 2, 1])
x = var_list[0]
y = var_list[1]
z = var_list[2]
a = x + y
with pytest.raises(TypeError):
b = a * "g"
with pytest.raises(TypeError):
b = False * y
def test_sub_exception():
X = Variable([1, 2, 2, 1])
var_list = X.unroll([2, 2])
x = var_list[0]
y = var_list[1]
z = y + x
a = z + [4.4, 3.3]
b = a + z
with pytest.raises(TypeError):
c = b - "g"
with pytest.raises(TypeError):
c = True - b
def test_create_variable():
X = Variable([1, 2, 3])
assert close(X.val, np.asarray([[1], [2], [3]]))
assert close(X.grad, np.eye(3))
var_list = X.unroll()
x = var_list[0]
assert close(x.val, 1)
assert close(x.grad, np.asarray([[1, 0, 0]]))
var_list = X.unroll([2, 1])
x = var_list[0]
assert close(x.val, np.asarray([[1], [2]]))
assert close(x.grad, np.asarray([[1, 0, 0], [0, 1, 0]]))
y = Variable(1)
var_list = y.unroll()
x = var_list[0]
assert close(x.val, 1)
assert close(x.grad, 1)
var_list = y.unroll([1])
x = var_list[0]
assert close(x.val, 1)
assert close(x.grad, 1)
def test_neg():
X = Variable([1, 3, 3, 1, 4])
var_list = X.unroll([2, 2, 1])
x = var_list[0]
y = var_list[1]
z = var_list[2]
a = x + y
b = a / z
c = -b
assert close(c.val, -np.asarray([[1], [1]]))
assert close(
c.grad,
np.asarray([[-0.25, 0, -0.25, 0, 0.25], [0, -0.25, 0, -0.25, 0.25]]))
def test_pow_exception():
X = Variable([1, 3, 3, 1, 2])
var_list = X.unroll([2, 2, 1])
x = var_list[0]
y = var_list[1]
z = var_list[2]
a = x + y
with pytest.raises(TypeError):
b = a**"g"
with pytest.raises(ValueError):
b = a**[3, 3]
with pytest.raises(ValueError):
b = a**z
with pytest.raises(ValueError):
b = z**a
def test_add():
X = Variable([1, 2, 2, 1])
var_list = X.unroll([2, 2])
x = var_list[0]
y = var_list[1]
z = x + y
assert close(z.val, np.asarray([[3], [3]]))
assert close(z.grad, np.asarray([[1, 0, 1, 0], [0, 1, 0, 1]]))
a = z + [4.4, 3.3]
b = a + z
assert close(b.val, np.asarray([[10.4], [9.3]]))
assert close(b.grad, np.asarray([[2, 0, 2, 0], [0, 2, 0, 2]]))
c = [4.4, 3.3] + b
assert close(c.val, np.asarray([[14.8], [12.6]]))
assert close(c.grad, np.asarray([[2, 0, 2, 0], [0, 2, 0, 2]]))
def test_mul():
X = Variable([1, 2, 2, 1, 4])
var_list = X.unroll([2, 2, 1])
x = var_list[0]
y = var_list[1]
z = var_list[2]
a = x + y
b = a * z
assert close(b.val, np.asarray([[12], [12]]))
assert close(b.grad, np.asarray([[4, 0, 4, 0, 3], [0, 4, 0, 4, 3]]))
c = b * 4
assert close(c.val, np.asarray([[48], [48]]))
assert close(c.grad, np.asarray([[16, 0, 16, 0, 12], [0, 16, 0, 16, 12]]))
d = 2 * b
assert close(d.val, np.asarray([[24], [24]]))
assert close(d.grad, np.asarray([[8, 0, 8, 0, 6], [0, 8, 0, 8, 6]]))
def test_eq():
X = Variable([1, 3, 3, 1, 4])
var_list = X.unroll([2, 2, 1])
x = var_list[0]
y = var_list[1]
z = var_list[2]
a = x + y
b = a + [4.4, 3.3]
c = a - x
assert c == y
assert c != x
c = b - a
assert c == [4.4, 3.3]
assert [4.4, 3.3] == c
assert [1, 1] != c
assert c != [1, 1]
def test_pow():
X = Variable([1, 3, 3, 1, 2])
var_list = X.unroll([2, 2, 1])
x = var_list[0]
y = var_list[1]
z = var_list[2]
a = x + y
b = z**2
assert close(b.val, 4)
assert close(b.grad, np.asarray([[0, 0, 0, 0, 4]]))
b = a**2
assert close(b.val, np.asarray([[16], [16]]))
assert close(b.grad, np.asarray([[8, 0, 8, 0, 0], [0, 8, 0, 8, 0]]))
c = z
d = z**c
assert close(d.val, 4)
assert close(d.grad, np.asarray([[0, 0, 0, 0, 4 * (np.log(2) + 1)]]))
def test_sub():
X = Variable([1, 2, 2, 1])
var_list = X.unroll([2, 2])
x = var_list[0]
y = var_list[1]
z = y + x
a = z + [4.4, 3.3]
b = a + z
c = b - x
assert close(c.val, np.asarray([[9.4], [7.3]]))
assert close(c.grad, np.asarray([[1, 0, 2, 0], [0, 1, 0, 2]]))
d = 3 - c
assert close(d.val, np.asarray([[-6.4], [-4.3]]))
assert close(d.grad, np.asarray([[-1, 0, -2, 0], [0, -1, 0, -2]]))
e = c - 2.1
assert close(e.val, np.asarray([[7.3], [5.2]]))
assert close(e.grad, np.asarray([[1, 0, 2, 0], [0, 1, 0, 2]]))
def test_div():
X = Variable([1, 3, 3, 1, 4])
var_list = X.unroll([2, 2, 1])
x = var_list[0]
y = var_list[1]
z = var_list[2]
a = x + y
b = a / z
assert close(b.val, np.asarray([[1], [1]]))
assert close(
b.grad,
np.asarray([[0.25, 0, 0.25, 0, -0.25], [0, 0.25, 0, 0.25, -0.25]]))
c = b / 0.25
assert close(c.val, np.asarray([[4], [4]]))
assert close(c.grad, np.asarray([[1, 0, 1, 0, -1], [0, 1, 0, 1, -1]]))
d = 4 / z
assert close(d.val, 1)
assert close(d.grad, np.asarray([[0, 0, 0, 0, -0.25]]))
def test_div_exception():
X = Variable([1, 3, 3, 1, 0])
var_list = X.unroll([2, 2, 1])
x = var_list[0]
y = var_list[1]
z = var_list[2]
a = x + y
with pytest.raises(ValueError):
b = a / x
with pytest.raises(ValueError):
b = a / z
with pytest.raises(ValueError):
b = 4.0 / z
with pytest.raises(ValueError):
b = a / 0.0
with pytest.raises(ValueError):
b = a / np.asarray([1, 1])
with pytest.raises(ValueError):
b = 4.0 / x
with pytest.raises(TypeError):
b = a / "g"
with pytest.raises(TypeError):
a = True / y
def test_concat_values_shapes():
X = Variable([1, 2, 3])
x, y, z = X.unroll()
f1 = x + y
f2 = x * y + z
#=========================
#Concatenate 2 scalar
#=========================
conc = F.concat([f1, f2])
real_v = np.array([[3, 5]], dtype=np.float64).T
real_gradients = np.array([[1, 1, 0], [2, 1, 1]], dtype=np.float64)
assert (real_v == conc.val).all(), "Value or Shape Error for the value"
assert (real_gradients == conc.grad
).all(), "Value or Shape Error for the value"
#), "Value or Shape Error for the value"
#=========================
#Concatenate scalar and vector
#=========================
new_conc = F.concat([f1, conc])
real_v = np.array([[3, 3, 5]], dtype=np.float64).T
real_gradients = np.array([[1, 1, 0], [1, 1, 0], [2, 1, 1]],
dtype=np.float64)
assert (real_v == new_conc.val).all(), "Value or Shape Error for the value"
assert (real_gradients == new_conc.grad
).all(), "Value or Shape Error for the value"
#=========================
#Concatenate vector and vector
#=========================
full_conc = F.concat([new_conc, conc])
real_v = np.array([[3, 3, 5, 3, 5]], dtype=np.float64).T
real_gradients = np.array(
[[1, 1, 0], [1, 1, 0], [2, 1, 1], [1, 1, 0], [2, 1, 1]],
dtype=np.float64)
assert (
real_v == full_conc.val).all(), "Value or Shape Error for the value"
assert (real_gradients == full_conc.grad
).all(), "Value or Shape Error for the value"
ew_exp = ew_Exponent()
ew_sin = ew_Sinus()
if __name__ == "__main__":
#=====================
#DEMO
#===================
from autodiff.variable import Variable, ReverseVariable
import autodiff.function as F
X = Variable(np.array([1, 5, 10]))
#x = Variable(2.)
Y = Variable(np.array([3, 7, 12]))
#print(x)
print(X.val)
Z = X + Y
x, y, z = X.unroll()
print(x.val, x.grad.shape)
xyz = (x + y) * z
xy = x + y
print(xyz.val, xy.grad.shape)
print(xy.val, xy.grad.shape)
f = concat([xyz, xy])
print(f.val, f.val.shape, f.grad, f.grad.shape)
#=============
#Dirty old demos
#==============
"""
def first_demos(X):
x,y,z = unroll(X)
print(x,y,z)