def test_inside_outside2():
pcfg = FixedPCFG("x",
terminals=["c", "d"],
nonterminals=["x"],
preterminals=["b"],
productions=[("b", "b"), ("b", "x")],
binary_weights=np.array([[0.25, 0.75]]),
unary_weights=np.array([[0.5, 0.5]]))
sentence = "c d d".split()
alphas, betas, backtrace = parse(pcfg, sentence)
from pprint import pprint
pprint(list(zip(pcfg.nonterminals, alphas)))
pprint(list(zip(pcfg.nonterminals, betas)))
tree_from_backtrace(pcfg, sentence, backtrace).pretty_print()
assert_equal(tree_from_backtrace(pcfg, sentence, backtrace),
Tree.fromstring("(x (b c) (x (b d) (b d)))"))
# check alpha[x]
np.testing.assert_allclose(alphas[0], [[0, 0.0625, 0.023438],
[0, 0, 0.0625],
[0, 0, 0]], atol=1e-5)
# check alpha[b] (preterminals)
np.testing.assert_allclose(alphas[1], [[0.5, 0, 0],
[0, 0.5, 0],
[0, 0, 0.5]])
def test_inside_outside_em_update():
pcfg = FixedPCFG("x",
terminals=["c", "d"],
nonterminals=["x"],
preterminals=["b"],
productions=[("b", "b"), ("b", "x")])
sentence = "c d d".split()
prev_total_prob = 0
for i in range(20):
alphas, betas, backtrace = parse(pcfg, sentence)
total_prob = alphas[pcfg.nonterm2idx[pcfg.start], 0, len(sentence) - 1]
tree_from_backtrace(pcfg, sentence, backtrace).pretty_print()
print("%d\t%f" % (i, total_prob))
# NB include small tolerance due to float imprecision
assert total_prob - prev_total_prob >= 0, \
"Total prob should never decrease: %f -> %f (iter %d)" % \
(prev_total_prob, total_prob, i)
prev_total_prob = total_prob
pcfg = update_em(pcfg, sentence)
pcfg = P.FixedPCFG("S",
terminals=list(vocabulary),
nonterminals=["S", "NP", "VP", "VP$"],
preterminals=["N", "V", "D"],
productions=[("NP", "VP"), ("V", "NP"), ("V", "VP$"),
("NP", "NP"), ("D", "N")])
prev_ll = -np.inf
for e in trange(40, desc="Epoch"):
for sentence in tqdm(sentences):
pcfg = I.update_em(pcfg, sentence)
# Calculate total probability of corpus.
ll = 0
for sentence in tqdm(sentences):
alphas, betas, _ = I.parse(pcfg, sentence)
total_prob = alphas[pcfg.nonterm2idx[pcfg.start], 0, len(sentence) - 1]
ll += np.log(total_prob)
tqdm.write("%i ll: %f" % (e, ll))
if ll - prev_ll > 0 and ll - prev_ll <= 1e-3:
break
prev_ll = ll
for sentence in sentences:
print(" ".join(sentence))
alphas, betas, backtrace = I.parse(pcfg, sentence)
tree = P.tree_from_backtrace(pcfg, sentence, backtrace)
tree.pretty_print()