mirror of
https://github.com/explosion/spaCy.git
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e2b70df012
* Use isort with Black profile * isort all the things * Fix import cycles as a result of import sorting * Add DOCBIN_ALL_ATTRS type definition * Add isort to requirements * Remove isort from build dependencies check * Typo
54 lines
1.6 KiB
Python
54 lines
1.6 KiB
Python
import pytest
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from spacy.tokens import Doc
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def test_noun_chunks_is_parsed(la_tokenizer):
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"""Test that noun_chunks raises Value Error for 'la' language if Doc is not parsed.
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To check this test, we're constructing a Doc
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with a new Vocab here and forcing is_parsed to 'False'
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to make sure the noun chunks don't run.
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"""
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doc = la_tokenizer("Haec est sententia.")
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with pytest.raises(ValueError):
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list(doc.noun_chunks)
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LA_NP_TEST_EXAMPLES = [
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(
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"Haec narrantur a poetis de Perseo.",
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["DET", "VERB", "ADP", "NOUN", "ADP", "PROPN", "PUNCT"],
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["nsubj:pass", "ROOT", "case", "obl", "case", "obl", "punct"],
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[1, 0, -1, -1, -3, -1, -5],
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["poetis", "Perseo"],
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),
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(
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"Perseus autem in sinu matris dormiebat.",
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["NOUN", "ADV", "ADP", "NOUN", "NOUN", "VERB", "PUNCT"],
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["nsubj", "discourse", "case", "obl", "nmod", "ROOT", "punct"],
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[5, 4, 3, -1, -1, 0, -1],
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["Perseus", "sinu matris"],
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),
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]
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@pytest.mark.parametrize(
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"text,pos,deps,heads,expected_noun_chunks", LA_NP_TEST_EXAMPLES
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)
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def test_la_noun_chunks(la_tokenizer, text, pos, deps, heads, expected_noun_chunks):
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tokens = la_tokenizer(text)
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assert len(heads) == len(pos)
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doc = Doc(
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tokens.vocab,
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words=[t.text for t in tokens],
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heads=[head + i for i, head in enumerate(heads)],
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deps=deps,
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pos=pos,
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)
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noun_chunks = list(doc.noun_chunks)
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assert len(noun_chunks) == len(expected_noun_chunks)
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for i, np in enumerate(noun_chunks):
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assert np.text == expected_noun_chunks[i]
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