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32 lines
834 B
Python
32 lines
834 B
Python
# coding: utf8
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from __future__ import unicode_literals
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from spacy.lang.en import English
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from spacy.tokens import Doc
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from spacy.vocab import Vocab
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def test_issue4133(en_vocab):
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nlp = English()
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vocab_bytes = nlp.vocab.to_bytes()
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words = ["Apple", "is", "looking", "at", "buying", "a", "startup"]
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pos = ["NOUN", "VERB", "ADP", "VERB", "PROPN", "NOUN", "ADP"]
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doc = Doc(en_vocab, words=words)
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for i, token in enumerate(doc):
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token.pos_ = pos[i]
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# usually this is already True when starting from proper models instead of blank English
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doc.is_tagged = True
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doc_bytes = doc.to_bytes()
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vocab = Vocab()
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vocab = vocab.from_bytes(vocab_bytes)
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doc = Doc(vocab).from_bytes(doc_bytes)
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actual = []
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for token in doc:
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actual.append(token.pos_)
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assert actual == pos
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