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db55577c45
* Remove unicode declarations * Remove Python 3.5 and 2.7 from CI * Don't require pathlib * Replace compat helpers * Remove OrderedDict * Use f-strings * Set Cython compiler language level * Fix typo * Re-add OrderedDict for Table * Update setup.cfg * Revert CONTRIBUTING.md * Revert lookups.md * Revert top-level.md * Small adjustments and docs [ci skip]
73 lines
2.0 KiB
Python
73 lines
2.0 KiB
Python
import pytest
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from thinc.neural.optimizers import Adam
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from thinc.neural.ops import NumpyOps
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from spacy.attrs import NORM
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from spacy.gold import GoldParse
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from spacy.vocab import Vocab
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from spacy.tokens import Doc
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from spacy.pipeline import DependencyParser
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@pytest.fixture
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def vocab():
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return Vocab(lex_attr_getters={NORM: lambda s: s})
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@pytest.fixture
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def parser(vocab):
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parser = DependencyParser(vocab)
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parser.cfg["token_vector_width"] = 4
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parser.cfg["hidden_width"] = 32
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# parser.add_label('right')
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parser.add_label("left")
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parser.begin_training([], **parser.cfg)
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sgd = Adam(NumpyOps(), 0.001)
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for i in range(10):
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losses = {}
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doc = Doc(vocab, words=["a", "b", "c", "d"])
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gold = GoldParse(doc, heads=[1, 1, 3, 3], deps=["left", "ROOT", "left", "ROOT"])
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parser.update((doc, gold), sgd=sgd, losses=losses)
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return parser
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def test_no_sentences(parser):
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doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
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doc = parser(doc)
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assert len(list(doc.sents)) >= 1
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def test_sents_1(parser):
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doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
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doc[2].sent_start = True
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doc = parser(doc)
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assert len(list(doc.sents)) >= 2
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doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
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doc[1].sent_start = False
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doc[2].sent_start = True
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doc[3].sent_start = False
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doc = parser(doc)
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assert len(list(doc.sents)) == 2
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def test_sents_1_2(parser):
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doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
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doc[1].sent_start = True
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doc[2].sent_start = True
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doc = parser(doc)
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assert len(list(doc.sents)) >= 3
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def test_sents_1_3(parser):
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doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
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doc[1].sent_start = True
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doc[3].sent_start = True
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doc = parser(doc)
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assert len(list(doc.sents)) >= 3
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doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
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doc[1].sent_start = True
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doc[2].sent_start = False
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doc[3].sent_start = True
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doc = parser(doc)
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assert len(list(doc.sents)) == 3
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