def test_blocks_crf_unaries():
X, Y = toy.generate_blocks(n_samples=1)
x, y = X[0], Y[0]
w = np.array([1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
crf = LatentGridCRF(n_labels=2, n_states_per_label=2)
h_hat = crf.inference(x, w)
assert_array_equal(h_hat / 2, np.argmax(x, axis=-1))
def test_latent_consistency():
crf = LatentGridCRF(n_labels=2, n_states_per_label=2)
for i in xrange(10):
w = np.random.normal(size=14)
y = np.random.randint(2, size=(4, 4))
x = np.random.normal(size=(4, 4, 2))
h = crf.latent(x, y, w)
assert_array_equal(h / 2, y)
def test_loss_augmented_inference_exhaustive():
crf = LatentGridCRF(n_labels=2, n_states_per_label=2, inference_method="dai")
for i in xrange(10):
w = np.random.normal(size=14)
y = np.random.randint(2, size=(2, 2))
x = np.random.normal(size=(2, 2, 2))
h_hat = crf.loss_augmented_inference(x, y * 2, w)
h = exhaustive_loss_augmented_inference(crf, x, y * 2, w)
assert_array_equal(h, h_hat)
def test_blocks_crf():
X, Y = toy.generate_blocks(n_samples=1)
x, y = X[0], Y[0]
w = np.array([1, 1, 1, 1, 0, 0, 0, -4, -4, 0, -4, -4, 0, 0])
crf = LatentGridCRF(n_labels=2, n_states_per_label=2)
h_hat = crf.inference(x, w)
assert_array_equal(y, h_hat / 2)
h = crf.latent(x, y, w)
assert_equal(crf.loss(h, h_hat), 0)
