def axis_dim_id(a):
if all_close(a, AXIS3_X.normal):
return 0
if all_close(a, AXIS3_Y.normal):
return 1
if all_close(a, AXIS3_Z.normal):
return 2
raise ValueError(f"Invalid axis for axis dim id: {a}")
def test_init(self):
a1 = Axis(normal=Vector([0.0, 1.0, 0.0]),
origin=Vector([1.0, 2.0, 0.0]))
a2 = Axis(normal=Vector([0.0, 1.0, 0.0]))
assert all_close(a1.normal, Vector([0.0, 1.0, 0.0]))
assert all_close(a1.origin, Vector([1.0, 2.0, 0.0]))
assert all_close(a2.normal, Vector([0.0, 1.0, 0.0]))
assert all_close(a2.origin, Vector([0.0, 0.0, 0.0]))
self.assertTrue(isinstance(a1, Axis))
self.assertTrue(isinstance(a2, Axis))
def test_fmap():
t = Tensor([[1, 2], [3, 4]])
def func(data):
return data * 2
assert all_close(t.fmap(func), [[2, 4], [6, 8]])
def test_residual_basic(clean_config):
m1 = Conv2D('conv1', 3, 3)
r = Residual('res1', m1)
x = tf.ones([32, 64, 64, 3], dtype=tf.float32)
res1 = r(x)
res2 = m1(x)
assert shape(res1) == [32, 64, 64, 3]
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
a, b = sess.run([res1, res2])
assert all_close(a, b) is False
def test_random_axis(self, src, tar):
# data = np.concatenate([RANDOM_VECTORS, AXIS_VECTORS])
# axis = [Axis(np.array(data[i, :]))
# for i in range(data.shape[0])]
# for src in axis:
# for tar in axis:
# v_tar = tar.normal
# v_src = src.normal
# print(type(v_src))
# print(type(v_tar))
m = axis_to_axis(src, tar)
det = np.linalg.det(m.unbox())
assert abs(det) == pytest.approx(1.0)
assert all_close(m @ src, tar)
def test_init(self):
b1 = Box([10, 10, 10], [1.0, 2.0, 0.0], [0, 1, 0])
b2 = Box([10, 10, 10])
assert all_close(b1.shape, [10, 10, 10])
assert all_close(b1.origin, [1.0, 2.0, 0.0])
assert all_close(b1.normal, [0, 1, 0])
assert all_close(b1.shape, [10, 10, 10])
assert all_close(b2.origin, [0, 0, 0])
assert all_close(b2.normal, [0, 0, 1])
def test_rotate_on_direction(self):
a = Axis(normal=Vector([0.0, 1.0, 0.0]),
origin=Vector([1.0, 2.0, 0.0]))
direction_x = Vector([1.0, 0.0, 0.0])
direction_y = Vector([0.0, 1.0, 0.0])
direction_z = Vector([0.0, 0.0, 1.0])
theta = math.pi / 2
a_rot_x = a.rotate_on_direction(direction_x, theta)
a_rot_y = a.rotate_on_direction(direction_y, theta)
a_rot_z = a.rotate_on_direction(direction_z, theta)
assert all_close(a_rot_x.origin, Vector([1.0, 0.0, 2.0]))
assert all_close(a_rot_x.normal, Vector([0.0, 0.0, 1.0]))
assert all_close(a_rot_y.origin, Vector([0.0, 2.0, -1.0]))
assert all_close(a_rot_y.normal, Vector([0.0, 1.0, 0.0]))
assert all_close(a_rot_z.origin, Vector([-2.0, 1.0, 0.0]))
assert all_close(a_rot_z.normal, Vector([-1.0, 0.0, 0.0]))
def test_rotate2(self):
rot = rotate2(math.pi / 3)
assert all_close(rot,
[[0.5, -math.sqrt(3) / 2], [math.sqrt(3) / 2, 0.5]])
def test_rotate3(self, v, expect):
rot = rotate3(math.pi / 2, v)
assert all_close(rot @ POINT_VECTORS[0], expect)
def test_to_tensor_like():
assert all_close(to_tensor_like([1, 2]), np.array([1, 2]))
def test_to_tensor_like_Tensor():
n = np.array([[1, 2, 3], [4, 5, 6]])
assert all_close(to_tensor_like(n) == np.array([[1, 2, 3], [4, 5, 6]]))
def tests_abs_():
assert all_close(abs_(Tensor([[-1, -2], [-3, 4]])), [[1, 2], [3, 4]])
def test_rmatmul():
t1 = Tensor([[1, 2], [1, 2]])
t2 = Tensor([[1, 2], [1, 2]])
assert all_close(t1.__rmatmaul__(t2), [[3, 6], [3, 6]])
def test_Vector_Vector_ndarray():
v = Vector([[1, 1], [1, 1]])
n = np.array([[1, 1], [1, 1]])
assert all_close(project(v, n), np.array([[0.5, 0.5], [0.5, 0.5]]))
def test_add():
a, b = Tensor([1, 2]), Tensor([3, 4])
c = Tensor([4, 6])
assert all_close(a + b, c)
def test_argmax():
assert np.argmax(Tensor([[1, 2], [2, 7]])) == 3
assert all_close(np.argmax(Tensor([[1, 2], [2, 7]]), axis=0), [1, 1])
assert all_close(np.argmax(Tensor([[1, 2], [2, 7]]), axis=1), [1, 1])
def test_unbox():
assert all_close(Tensor([1, 2]).unbox(), [1, 2])
def test_init():
assert all_close(Tensor([1, 2]), [1, 2])
def test_all_close():
assert all_close(Tensor([1]), Tensor([1])) == True
assert all_close(Tensor([1]), Tensor([2])) == False
def test_norm():
t = Tensor([-4, -3, -2, -1, 0, 1, 2, 3, 4])
assert all_close(norm(t), 7.745966692414834)
def test_random_vectors(self, v):
rot = axis_to_z(v)
assert all_close(rot @ v, AXIS3_Z.normal)
def test_unit_ndarry():
assert all_close(unit(np.array([1, 0])), np.array([1, 0], dtype=np.float))
def test_random_vectors(self, v):
rot = z_to_axis(Vector(v))
assert all_close(rot @ (AXIS3_Z.normal), v)
def test_square():
assert all_close(square(Tensor([[1, 2], [3, 4]])),
np.array([[1, 4], [9, 16]]))
def test_setitem():
t = Tensor([[1, 2], [3, 4]])
t[-1] = [2]
assert all_close(t.data[-1], [2, 2])
def test_unit():
assert all_close(unit(Tensor([0, 1])), np.array([0, 1], dtype=np.float64))
def test_abs_ndarray():
assert all_close(abs(np.array([[-1, -2], [-3, 4]])), [[1, 2], [3, 4]])
def test_matmul():
t1 = Tensor([[1, 2], [1, 2]])
t2 = Tensor([[1, 2], [1, 2]])
assert all_close(t1 @ t2, [[3, 6], [3, 6]])
def test_sub_box_shape():
assert all_close(sub_box_shape(Box([1.0, 2.0, 3.0]), [10, 40, 30]),
Vector([0.1, 0.05, 0.1]))
def test_square_ndarry():
assert all_close(square(np.array([-1j, 1])), [-1. + 0.j, 1. + 0.j])
