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https://github.com/explosion/spaCy.git
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55 lines
1.6 KiB
Python
55 lines
1.6 KiB
Python
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import pytest
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from thinc.api import Adam
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from spacy.attrs import NORM
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from spacy.vocab import Vocab
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from spacy import registry
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from spacy.training import Example
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from spacy.pipeline.dep_parser import DEFAULT_PARSER_MODEL
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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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def _parser_example(parser):
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doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
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gold = {"heads": [1, 1, 3, 3], "deps": ["right", "ROOT", "left", "ROOT"]}
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return Example.from_dict(doc, gold)
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@pytest.fixture
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def parser(vocab):
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vocab.strings.add("ROOT")
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cfg = {"model": DEFAULT_PARSER_MODEL}
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model = registry.resolve(cfg, validate=True)["model"]
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parser = DependencyParser(vocab, model)
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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.initialize(lambda: [_parser_example(parser)])
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sgd = Adam(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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example = Example.from_dict(
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doc, {"heads": [1, 1, 3, 3], "deps": ["left", "ROOT", "left", "ROOT"]}
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)
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parser.update([example], sgd=sgd, losses=losses)
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return parser
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@pytest.mark.xfail(reason="Not fixed yet")
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def test_partial_annotation(parser):
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doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
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doc[2].is_sent_start = False
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# Note that if the following line is used, then doc[2].is_sent_start == False
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# doc[3].is_sent_start = False
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doc = parser(doc)
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assert doc[2].is_sent_start == False
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