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74 lines
2.1 KiB
Python
74 lines
2.1 KiB
Python
'''Test that the parser respects preset sentence boundaries.'''
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from __future__ import unicode_literals
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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 ...attrs import NORM
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from ...gold import GoldParse
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from ...vocab import Vocab
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from ...tokens import Doc
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from ...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],
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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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