def test_graph_crf_loss_augment():
x = (x_1, g_1)
y = y_1
crf = GraphCRF()
crf.initialize([x], [y])
y_hat, energy = crf.loss_augmented_inference(x, y, w, return_energy=True)
# check that y_hat fulfills energy + loss condition
assert_almost_equal(np.dot(w, crf.joint_feature(x, y_hat)) + crf.loss(y, y_hat),
-energy)
def test_initialize():
x = (x_1, g_1)
y = y_1
crf = GraphCRF(n_states=2, n_features=2)
# no-op
crf.initialize([x], [y])
#test initialization works
crf = GraphCRF()
crf.initialize([x], [y])
assert_equal(crf.n_states, 2)
assert_equal(crf.n_features, 2)
crf = GraphCRF(n_states=3)
assert_raises(ValueError, crf.initialize, X=[x], Y=[y])
