2018-07-25 00:38:44 +03:00
|
|
|
# coding: utf8
|
2017-10-09 04:42:35 +03:00
|
|
|
from __future__ import unicode_literals
|
2018-07-25 00:38:44 +03:00
|
|
|
|
2017-10-09 04:42:35 +03:00
|
|
|
import pytest
|
|
|
|
from thinc.neural.optimizers import Adam
|
|
|
|
from thinc.neural.ops import NumpyOps
|
2018-07-25 00:38:44 +03:00
|
|
|
from spacy.attrs import NORM
|
|
|
|
from spacy.gold import GoldParse
|
|
|
|
from spacy.vocab import Vocab
|
|
|
|
from spacy.tokens import Doc
|
|
|
|
from spacy.pipeline import DependencyParser
|
2017-10-09 04:42:35 +03:00
|
|
|
|
|
|
|
|
|
|
|
@pytest.fixture
|
|
|
|
def vocab():
|
|
|
|
return Vocab(lex_attr_getters={NORM: lambda s: s})
|
|
|
|
|
|
|
|
|
|
|
|
@pytest.fixture
|
|
|
|
def parser(vocab):
|
2017-10-26 13:38:23 +03:00
|
|
|
parser = DependencyParser(vocab)
|
2018-11-27 03:09:36 +03:00
|
|
|
parser.cfg["token_vector_width"] = 8
|
|
|
|
parser.cfg["hidden_width"] = 30
|
|
|
|
parser.cfg["hist_size"] = 0
|
|
|
|
parser.add_label("left")
|
2017-10-09 04:42:35 +03:00
|
|
|
parser.begin_training([], **parser.cfg)
|
|
|
|
sgd = Adam(NumpyOps(), 0.001)
|
|
|
|
|
2017-10-10 23:57:41 +03:00
|
|
|
for i in range(10):
|
2017-10-09 04:42:35 +03:00
|
|
|
losses = {}
|
2018-11-27 03:09:36 +03:00
|
|
|
doc = Doc(vocab, words=["a", "b", "c", "d"])
|
|
|
|
gold = GoldParse(doc, heads=[1, 1, 3, 3], deps=["left", "ROOT", "left", "ROOT"])
|
2017-10-09 04:42:35 +03:00
|
|
|
parser.update([doc], [gold], sgd=sgd, losses=losses)
|
|
|
|
return parser
|
|
|
|
|
2018-07-25 00:38:44 +03:00
|
|
|
|
2017-10-10 23:57:41 +03:00
|
|
|
def test_init_parser(parser):
|
|
|
|
pass
|
2017-10-09 04:42:35 +03:00
|
|
|
|
2018-07-25 00:38:44 +03:00
|
|
|
|
2017-10-28 14:16:06 +03:00
|
|
|
# TODO: This is flakey, because it depends on what the parser first learns.
|
2018-08-15 16:37:04 +03:00
|
|
|
# TODO: This now seems to be implicated in segfaults. Not sure what's up!
|
|
|
|
@pytest.mark.skip
|
2017-10-09 04:42:35 +03:00
|
|
|
def test_add_label(parser):
|
2018-11-27 03:09:36 +03:00
|
|
|
doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
|
2017-10-09 04:42:35 +03:00
|
|
|
doc = parser(doc)
|
|
|
|
assert doc[0].head.i == 1
|
2018-11-27 03:09:36 +03:00
|
|
|
assert doc[0].dep_ == "left"
|
2017-10-09 04:42:35 +03:00
|
|
|
assert doc[1].head.i == 1
|
|
|
|
assert doc[2].head.i == 3
|
|
|
|
assert doc[2].head.i == 3
|
2018-11-27 03:09:36 +03:00
|
|
|
parser.add_label("right")
|
|
|
|
doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
|
2017-10-09 04:42:35 +03:00
|
|
|
doc = parser(doc)
|
|
|
|
assert doc[0].head.i == 1
|
2018-11-27 03:09:36 +03:00
|
|
|
assert doc[0].dep_ == "left"
|
2017-10-09 04:42:35 +03:00
|
|
|
assert doc[1].head.i == 1
|
|
|
|
assert doc[2].head.i == 3
|
|
|
|
assert doc[2].head.i == 3
|
|
|
|
sgd = Adam(NumpyOps(), 0.001)
|
|
|
|
for i in range(10):
|
|
|
|
losses = {}
|
2018-11-27 03:09:36 +03:00
|
|
|
doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
|
|
|
|
gold = GoldParse(
|
|
|
|
doc, heads=[1, 1, 3, 3], deps=["right", "ROOT", "left", "ROOT"]
|
|
|
|
)
|
2017-10-09 04:42:35 +03:00
|
|
|
parser.update([doc], [gold], sgd=sgd, losses=losses)
|
2018-11-27 03:09:36 +03:00
|
|
|
doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
|
2017-10-09 04:42:35 +03:00
|
|
|
doc = parser(doc)
|
2018-11-27 03:09:36 +03:00
|
|
|
assert doc[0].dep_ == "right"
|
|
|
|
assert doc[2].dep_ == "left"
|