def test_message_to_parent(self):
"""
Test the message to parents of Concatenate node.
"""
# Two parents without shapes
X1 = GaussianARD(0, 1, plates=(2, ), shape=())
X2 = GaussianARD(0, 1, plates=(3, ), shape=())
Z = Concatenate(X1, X2)
Y = GaussianARD(Z, 1)
Y.observe(np.random.randn(*Y.get_shape(0)))
m1 = X1._message_from_children()
m2 = X2._message_from_children()
m = Z._message_from_children()
self.assertAllClose((m[0] * np.ones((5, )))[:2], m1[0] * np.ones(
(2, )))
self.assertAllClose((m[1] * np.ones((5, )))[:2], m1[1] * np.ones(
(2, )))
self.assertAllClose((m[0] * np.ones((5, )))[2:], m2[0] * np.ones(
(3, )))
self.assertAllClose((m[1] * np.ones((5, )))[2:], m2[1] * np.ones(
(3, )))
# Two parents with shapes
with warnings.catch_warnings():
warnings.simplefilter("ignore", FutureWarning)
X1 = GaussianARD(0, 1, plates=(2, ), shape=(4, 6))
X2 = GaussianARD(0, 1, plates=(3, ), shape=(4, 6))
Z = Concatenate(X1, X2)
Y = GaussianARD(Z, 1)
Y.observe(np.random.randn(*Y.get_shape(0)))
m1 = X1._message_from_children()
m2 = X2._message_from_children()
m = Z._message_from_children()
self.assertAllClose((m[0] * np.ones((5, 4, 6)))[:2],
m1[0] * np.ones((2, 4, 6)))
self.assertAllClose((m[1] * np.ones((5, 4, 6, 4, 6)))[:2],
m1[1] * np.ones((2, 4, 6, 4, 6)))
self.assertAllClose((m[0] * np.ones((5, 4, 6)))[2:],
m2[0] * np.ones((3, 4, 6)))
self.assertAllClose((m[1] * np.ones((5, 4, 6, 4, 6)))[2:],
m2[1] * np.ones((3, 4, 6, 4, 6)))
# Two parents with non-default concatenation axis
X1 = GaussianARD(0, 1, plates=(2, 4), shape=())
X2 = GaussianARD(0, 1, plates=(3, 4), shape=())
Z = Concatenate(X1, X2, axis=-2)
Y = GaussianARD(Z, 1)
Y.observe(np.random.randn(*Y.get_shape(0)))
m1 = X1._message_from_children()
m2 = X2._message_from_children()
m = Z._message_from_children()
self.assertAllClose((m[0] * np.ones((5, 4)))[:2], m1[0] * np.ones(
(2, 4)))
self.assertAllClose((m[1] * np.ones((5, 4)))[:2], m1[1] * np.ones(
(2, 4)))
self.assertAllClose((m[0] * np.ones((5, 4)))[2:], m2[0] * np.ones(
(3, 4)))
self.assertAllClose((m[1] * np.ones((5, 4)))[2:], m2[1] * np.ones(
(3, 4)))
# Constant parent
X1 = np.random.randn(2, 4, 6)
X2 = GaussianARD(0, 1, plates=(3, ), shape=(4, 6))
Z = Concatenate(X1, X2)
Y = GaussianARD(Z, 1)
Y.observe(np.random.randn(*Y.get_shape(0)))
m1 = Z._message_to_parent(0)
m2 = X2._message_from_children()
m = Z._message_from_children()
self.assertAllClose((m[0] * np.ones((5, 4, 6)))[:2],
m1[0] * np.ones((2, 4, 6)))
self.assertAllClose((m[1] * np.ones((5, 4, 6, 4, 6)))[:2],
m1[1] * np.ones((2, 4, 6, 4, 6)))
self.assertAllClose((m[0] * np.ones((5, 4, 6)))[2:],
m2[0] * np.ones((3, 4, 6)))
self.assertAllClose((m[1] * np.ones((5, 4, 6, 4, 6)))[2:],
m2[1] * np.ones((3, 4, 6, 4, 6)))
pass
def test_message_to_parent(self):
"""
Test the message to parents of Concatenate node.
"""
# Two parents without shapes
X1 = GaussianARD(0, 1, plates=(2,), shape=())
X2 = GaussianARD(0, 1, plates=(3,), shape=())
Z = Concatenate(X1, X2)
Y = GaussianARD(Z, 1)
Y.observe(np.random.randn(*Y.get_shape(0)))
m1 = X1._message_from_children()
m2 = X2._message_from_children()
m = Z._message_from_children()
self.assertAllClose((m[0]*np.ones((5,)))[:2],
m1[0]*np.ones((2,)))
self.assertAllClose((m[1]*np.ones((5,)))[:2],
m1[1]*np.ones((2,)))
self.assertAllClose((m[0]*np.ones((5,)))[2:],
m2[0]*np.ones((3,)))
self.assertAllClose((m[1]*np.ones((5,)))[2:],
m2[1]*np.ones((3,)))
# Two parents with shapes
with warnings.catch_warnings():
warnings.simplefilter("ignore", FutureWarning)
X1 = GaussianARD(0, 1, plates=(2,), shape=(4,6))
X2 = GaussianARD(0, 1, plates=(3,), shape=(4,6))
Z = Concatenate(X1, X2)
Y = GaussianARD(Z, 1)
Y.observe(np.random.randn(*Y.get_shape(0)))
m1 = X1._message_from_children()
m2 = X2._message_from_children()
m = Z._message_from_children()
self.assertAllClose((m[0]*np.ones((5,4,6)))[:2],
m1[0]*np.ones((2,4,6)))
self.assertAllClose((m[1]*np.ones((5,4,6,4,6)))[:2],
m1[1]*np.ones((2,4,6,4,6)))
self.assertAllClose((m[0]*np.ones((5,4,6)))[2:],
m2[0]*np.ones((3,4,6)))
self.assertAllClose((m[1]*np.ones((5,4,6,4,6)))[2:],
m2[1]*np.ones((3,4,6,4,6)))
# Two parents with non-default concatenation axis
X1 = GaussianARD(0, 1, plates=(2,4), shape=())
X2 = GaussianARD(0, 1, plates=(3,4), shape=())
Z = Concatenate(X1, X2, axis=-2)
Y = GaussianARD(Z, 1)
Y.observe(np.random.randn(*Y.get_shape(0)))
m1 = X1._message_from_children()
m2 = X2._message_from_children()
m = Z._message_from_children()
self.assertAllClose((m[0]*np.ones((5,4)))[:2],
m1[0]*np.ones((2,4)))
self.assertAllClose((m[1]*np.ones((5,4)))[:2],
m1[1]*np.ones((2,4)))
self.assertAllClose((m[0]*np.ones((5,4)))[2:],
m2[0]*np.ones((3,4)))
self.assertAllClose((m[1]*np.ones((5,4)))[2:],
m2[1]*np.ones((3,4)))
# Constant parent
X1 = np.random.randn(2,4,6)
X2 = GaussianARD(0, 1, plates=(3,), shape=(4,6))
Z = Concatenate(X1, X2)
Y = GaussianARD(Z, 1)
Y.observe(np.random.randn(*Y.get_shape(0)))
m1 = Z._message_to_parent(0)
m2 = X2._message_from_children()
m = Z._message_from_children()
self.assertAllClose((m[0]*np.ones((5,4,6)))[:2],
m1[0]*np.ones((2,4,6)))
self.assertAllClose((m[1]*np.ones((5,4,6,4,6)))[:2],
m1[1]*np.ones((2,4,6,4,6)))
self.assertAllClose((m[0]*np.ones((5,4,6)))[2:],
m2[0]*np.ones((3,4,6)))
self.assertAllClose((m[1]*np.ones((5,4,6,4,6)))[2:],
m2[1]*np.ones((3,4,6,4,6)))
pass
