mirror of
https://github.com/explosion/spaCy.git
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71 lines
2.2 KiB
Python
71 lines
2.2 KiB
Python
# coding: utf8
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from __future__ import unicode_literals
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import pytest
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from spacy.tokens import Doc
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from spacy.displacy import render
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from spacy.gold import iob_to_biluo
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from spacy.lang.it import Italian
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from ..util import add_vecs_to_vocab
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@pytest.mark.xfail
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def test_issue2179():
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"""Test that spurious 'extra_labels' aren't created when initializing NER."""
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nlp = Italian()
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ner = nlp.create_pipe('ner')
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ner.add_label('CITIZENSHIP')
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nlp.add_pipe(ner)
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nlp.begin_training()
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nlp2 = Italian()
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nlp2.add_pipe(nlp2.create_pipe('ner'))
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nlp2.from_bytes(nlp.to_bytes())
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assert 'extra_labels' not in nlp2.get_pipe('ner').cfg
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assert nlp2.get_pipe('ner').labels == ['CITIZENSHIP']
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def test_issue2219(en_vocab):
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vectors = [("a", [1, 2, 3]), ("letter", [4, 5, 6])]
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add_vecs_to_vocab(en_vocab, vectors)
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[(word1, vec1), (word2, vec2)] = vectors
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doc = Doc(en_vocab, words=[word1, word2])
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assert doc[0].similarity(doc[1]) == doc[1].similarity(doc[0])
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def test_issue2361(de_tokenizer):
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chars = ('<', '>', '&', '"')
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doc = de_tokenizer('< > & " ')
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doc.is_parsed = True
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doc.is_tagged = True
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html = render(doc)
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for char in chars:
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assert char in html
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def test_issue2385():
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"""Test that IOB tags are correctly converted to BILUO tags."""
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# fix bug in labels with a 'b' character
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tags1 = ('B-BRAWLER', 'I-BRAWLER', 'I-BRAWLER')
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assert iob_to_biluo(tags1) == ['B-BRAWLER', 'I-BRAWLER', 'L-BRAWLER']
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# maintain support for iob1 format
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tags2 = ('I-ORG', 'I-ORG', 'B-ORG')
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assert iob_to_biluo(tags2) == ['B-ORG', 'L-ORG', 'U-ORG']
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# maintain support for iob2 format
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tags3 = ('B-PERSON', 'I-PERSON', 'B-PERSON')
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assert iob_to_biluo(tags3) ==['B-PERSON', 'L-PERSON', 'U-PERSON']
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@pytest.mark.parametrize('tags', [
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('B-ORG', 'L-ORG'), ('B-PERSON', 'I-PERSON', 'L-PERSON'), ('U-BRAWLER', 'U-BRAWLER')])
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def test_issue2385_biluo(tags):
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"""Test that BILUO-compatible tags aren't modified."""
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assert iob_to_biluo(tags) == list(tags)
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def test_issue2482():
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'''Test we can serialize and deserialize a blank NER or parser model.'''
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nlp = Italian()
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nlp.add_pipe(nlp.create_pipe('ner'))
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b = nlp.to_bytes()
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nlp2 = Italian().from_bytes(b)
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