mirror of
https://github.com/explosion/spaCy.git
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7d50804644
* Migrate regressions 1-1000 * Move serialize test to correct file * Remove tests that won't work in v3 * Migrate regressions 1000-1500 Removed regression test 1250 because v3 doesn't support the old LEX scheme anymore. * Add missing imports in serializer tests * Migrate tests 1500-2000 * Migrate regressions from 2000-2500 * Migrate regressions from 2501-3000 * Migrate regressions from 3000-3501 * Migrate regressions from 3501-4000 * Migrate regressions from 4001-4500 * Migrate regressions from 4501-5000 * Migrate regressions from 5001-5501 * Migrate regressions from 5501 to 7000 * Migrate regressions from 7001 to 8000 * Migrate remaining regression tests * Fixing missing imports * Update docs with new system [ci skip] * Update CONTRIBUTING.md - Fix formatting - Update wording * Remove lemmatizer tests in el lang * Move a few tests into the general tokenizer * Separate Doc and DocBin tests
137 lines
4.8 KiB
Python
137 lines
4.8 KiB
Python
import numpy
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import pytest
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from spacy.tokens import Doc
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from spacy.attrs import ORTH, SHAPE, POS, DEP, MORPH
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@pytest.mark.issue(2203)
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def test_issue2203(en_vocab):
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"""Test that lemmas are set correctly in doc.from_array."""
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words = ["I", "'ll", "survive"]
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tags = ["PRP", "MD", "VB"]
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lemmas = ["-PRON-", "will", "survive"]
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tag_ids = [en_vocab.strings.add(tag) for tag in tags]
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lemma_ids = [en_vocab.strings.add(lemma) for lemma in lemmas]
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doc = Doc(en_vocab, words=words)
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# Work around lemma corruption problem and set lemmas after tags
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doc.from_array("TAG", numpy.array(tag_ids, dtype="uint64"))
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doc.from_array("LEMMA", numpy.array(lemma_ids, dtype="uint64"))
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assert [t.tag_ for t in doc] == tags
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assert [t.lemma_ for t in doc] == lemmas
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# We need to serialize both tag and lemma, since this is what causes the bug
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doc_array = doc.to_array(["TAG", "LEMMA"])
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new_doc = Doc(doc.vocab, words=words).from_array(["TAG", "LEMMA"], doc_array)
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assert [t.tag_ for t in new_doc] == tags
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assert [t.lemma_ for t in new_doc] == lemmas
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def test_doc_array_attr_of_token(en_vocab):
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doc = Doc(en_vocab, words=["An", "example", "sentence"])
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example = doc.vocab["example"]
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assert example.orth != example.shape
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feats_array = doc.to_array((ORTH, SHAPE))
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assert feats_array[0][0] != feats_array[0][1]
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assert feats_array[0][0] != feats_array[0][1]
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def test_doc_stringy_array_attr_of_token(en_vocab):
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doc = Doc(en_vocab, words=["An", "example", "sentence"])
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example = doc.vocab["example"]
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assert example.orth != example.shape
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feats_array = doc.to_array((ORTH, SHAPE))
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feats_array_stringy = doc.to_array(("ORTH", "SHAPE"))
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assert feats_array_stringy[0][0] == feats_array[0][0]
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assert feats_array_stringy[0][1] == feats_array[0][1]
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def test_doc_scalar_attr_of_token(en_vocab):
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doc = Doc(en_vocab, words=["An", "example", "sentence"])
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example = doc.vocab["example"]
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assert example.orth != example.shape
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feats_array = doc.to_array(ORTH)
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assert feats_array.shape == (3,)
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def test_doc_array_tag(en_vocab):
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words = ["A", "nice", "sentence", "."]
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pos = ["DET", "ADJ", "NOUN", "PUNCT"]
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doc = Doc(en_vocab, words=words, pos=pos)
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assert doc[0].pos != doc[1].pos != doc[2].pos != doc[3].pos
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feats_array = doc.to_array((ORTH, POS))
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assert feats_array[0][1] == doc[0].pos
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assert feats_array[1][1] == doc[1].pos
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assert feats_array[2][1] == doc[2].pos
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assert feats_array[3][1] == doc[3].pos
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def test_doc_array_morph(en_vocab):
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words = ["Eat", "blue", "ham"]
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morph = ["Feat=V", "Feat=J", "Feat=N"]
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doc = Doc(en_vocab, words=words, morphs=morph)
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assert morph[0] == str(doc[0].morph)
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assert morph[1] == str(doc[1].morph)
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assert morph[2] == str(doc[2].morph)
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feats_array = doc.to_array((ORTH, MORPH))
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assert feats_array[0][1] == doc[0].morph.key
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assert feats_array[1][1] == doc[1].morph.key
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assert feats_array[2][1] == doc[2].morph.key
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def test_doc_array_dep(en_vocab):
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words = ["A", "nice", "sentence", "."]
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deps = ["det", "amod", "ROOT", "punct"]
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doc = Doc(en_vocab, words=words, deps=deps)
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feats_array = doc.to_array((ORTH, DEP))
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assert feats_array[0][1] == doc[0].dep
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assert feats_array[1][1] == doc[1].dep
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assert feats_array[2][1] == doc[2].dep
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assert feats_array[3][1] == doc[3].dep
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@pytest.mark.parametrize("attrs", [["ORTH", "SHAPE"], "IS_ALPHA"])
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def test_doc_array_to_from_string_attrs(en_vocab, attrs):
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"""Test that both Doc.to_array and Doc.from_array accept string attrs,
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as well as single attrs and sequences of attrs.
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"""
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words = ["An", "example", "sentence"]
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doc = Doc(en_vocab, words=words)
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Doc(en_vocab, words=words).from_array(attrs, doc.to_array(attrs))
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def test_doc_array_idx(en_vocab):
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"""Test that Doc.to_array can retrieve token start indices"""
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words = ["An", "example", "sentence"]
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offsets = Doc(en_vocab, words=words).to_array("IDX")
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assert offsets[0] == 0
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assert offsets[1] == 3
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assert offsets[2] == 11
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def test_doc_from_array_heads_in_bounds(en_vocab):
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"""Test that Doc.from_array doesn't set heads that are out of bounds."""
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words = ["This", "is", "a", "sentence", "."]
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doc = Doc(en_vocab, words=words)
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for token in doc:
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token.head = doc[0]
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# correct
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arr = doc.to_array(["HEAD"])
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doc_from_array = Doc(en_vocab, words=words)
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doc_from_array.from_array(["HEAD"], arr)
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# head before start
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arr = doc.to_array(["HEAD"])
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arr[0] = -1
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doc_from_array = Doc(en_vocab, words=words)
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with pytest.raises(ValueError):
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doc_from_array.from_array(["HEAD"], arr)
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# head after end
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arr = doc.to_array(["HEAD"])
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arr[0] = 5
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doc_from_array = Doc(en_vocab, words=words)
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with pytest.raises(ValueError):
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doc_from_array.from_array(["HEAD"], arr)
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