mirror of https://github.com/explosion/spaCy.git
56 lines
1.9 KiB
Python
56 lines
1.9 KiB
Python
import pytest
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from spacy.pipeline.functions import merge_subtokens
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from spacy.language import Language
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from spacy.tokens import Span, Doc
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@pytest.fixture
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def doc(en_vocab):
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# fmt: off
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words = ["This", "is", "a", "sentence", ".", "This", "is", "another", "sentence", ".", "And", "a", "third", "."]
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heads = [1, 1, 3, 1, 1, 6, 6, 8, 6, 6, 11, 12, 13, 13]
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deps = ["nsubj", "ROOT", "subtok", "attr", "punct", "nsubj", "ROOT",
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"subtok", "attr", "punct", "subtok", "subtok", "subtok", "ROOT"]
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# fmt: on
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return Doc(en_vocab, words=words, heads=heads, deps=deps)
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@pytest.fixture
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def doc2(en_vocab):
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words = ["I", "like", "New", "York", "in", "Autumn", "."]
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heads = [1, 1, 3, 1, 1, 4, 1]
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tags = ["PRP", "IN", "NNP", "NNP", "IN", "NNP", "."]
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pos = ["PRON", "VERB", "PROPN", "PROPN", "ADP", "PROPN", "PUNCT"]
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deps = ["ROOT", "prep", "compound", "pobj", "prep", "pobj", "punct"]
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doc = Doc(en_vocab, words=words, heads=heads, tags=tags, pos=pos, deps=deps)
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doc.ents = [Span(doc, 2, 4, label="GPE")]
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return doc
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def test_merge_subtokens(doc):
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doc = merge_subtokens(doc)
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# Doc doesn't have spaces, so the result is "And a third ."
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# fmt: off
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assert [t.text for t in doc] == ["This", "is", "a sentence", ".", "This", "is", "another sentence", ".", "And a third ."]
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# fmt: on
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def test_factories_merge_noun_chunks(doc2):
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assert len(doc2) == 7
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nlp = Language()
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merge_noun_chunks = nlp.create_pipe("merge_noun_chunks")
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merge_noun_chunks(doc2)
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assert len(doc2) == 6
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assert doc2[2].text == "New York"
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def test_factories_merge_ents(doc2):
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assert len(doc2) == 7
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assert len(list(doc2.ents)) == 1
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nlp = Language()
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merge_entities = nlp.create_pipe("merge_entities")
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merge_entities(doc2)
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assert len(doc2) == 6
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assert len(list(doc2.ents)) == 1
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assert doc2[2].text == "New York"
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