spaCy/spacy/tests/doc/test_array.py
Lj Miranda 7d50804644
Migrate regression tests into the main test suite (#9655)
* 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
2021-12-04 20:34:48 +01:00

137 lines
4.8 KiB
Python

import numpy
import pytest
from spacy.tokens import Doc
from spacy.attrs import ORTH, SHAPE, POS, DEP, MORPH
@pytest.mark.issue(2203)
def test_issue2203(en_vocab):
"""Test that lemmas are set correctly in doc.from_array."""
words = ["I", "'ll", "survive"]
tags = ["PRP", "MD", "VB"]
lemmas = ["-PRON-", "will", "survive"]
tag_ids = [en_vocab.strings.add(tag) for tag in tags]
lemma_ids = [en_vocab.strings.add(lemma) for lemma in lemmas]
doc = Doc(en_vocab, words=words)
# Work around lemma corruption problem and set lemmas after tags
doc.from_array("TAG", numpy.array(tag_ids, dtype="uint64"))
doc.from_array("LEMMA", numpy.array(lemma_ids, dtype="uint64"))
assert [t.tag_ for t in doc] == tags
assert [t.lemma_ for t in doc] == lemmas
# We need to serialize both tag and lemma, since this is what causes the bug
doc_array = doc.to_array(["TAG", "LEMMA"])
new_doc = Doc(doc.vocab, words=words).from_array(["TAG", "LEMMA"], doc_array)
assert [t.tag_ for t in new_doc] == tags
assert [t.lemma_ for t in new_doc] == lemmas
def test_doc_array_attr_of_token(en_vocab):
doc = Doc(en_vocab, words=["An", "example", "sentence"])
example = doc.vocab["example"]
assert example.orth != example.shape
feats_array = doc.to_array((ORTH, SHAPE))
assert feats_array[0][0] != feats_array[0][1]
assert feats_array[0][0] != feats_array[0][1]
def test_doc_stringy_array_attr_of_token(en_vocab):
doc = Doc(en_vocab, words=["An", "example", "sentence"])
example = doc.vocab["example"]
assert example.orth != example.shape
feats_array = doc.to_array((ORTH, SHAPE))
feats_array_stringy = doc.to_array(("ORTH", "SHAPE"))
assert feats_array_stringy[0][0] == feats_array[0][0]
assert feats_array_stringy[0][1] == feats_array[0][1]
def test_doc_scalar_attr_of_token(en_vocab):
doc = Doc(en_vocab, words=["An", "example", "sentence"])
example = doc.vocab["example"]
assert example.orth != example.shape
feats_array = doc.to_array(ORTH)
assert feats_array.shape == (3,)
def test_doc_array_tag(en_vocab):
words = ["A", "nice", "sentence", "."]
pos = ["DET", "ADJ", "NOUN", "PUNCT"]
doc = Doc(en_vocab, words=words, pos=pos)
assert doc[0].pos != doc[1].pos != doc[2].pos != doc[3].pos
feats_array = doc.to_array((ORTH, POS))
assert feats_array[0][1] == doc[0].pos
assert feats_array[1][1] == doc[1].pos
assert feats_array[2][1] == doc[2].pos
assert feats_array[3][1] == doc[3].pos
def test_doc_array_morph(en_vocab):
words = ["Eat", "blue", "ham"]
morph = ["Feat=V", "Feat=J", "Feat=N"]
doc = Doc(en_vocab, words=words, morphs=morph)
assert morph[0] == str(doc[0].morph)
assert morph[1] == str(doc[1].morph)
assert morph[2] == str(doc[2].morph)
feats_array = doc.to_array((ORTH, MORPH))
assert feats_array[0][1] == doc[0].morph.key
assert feats_array[1][1] == doc[1].morph.key
assert feats_array[2][1] == doc[2].morph.key
def test_doc_array_dep(en_vocab):
words = ["A", "nice", "sentence", "."]
deps = ["det", "amod", "ROOT", "punct"]
doc = Doc(en_vocab, words=words, deps=deps)
feats_array = doc.to_array((ORTH, DEP))
assert feats_array[0][1] == doc[0].dep
assert feats_array[1][1] == doc[1].dep
assert feats_array[2][1] == doc[2].dep
assert feats_array[3][1] == doc[3].dep
@pytest.mark.parametrize("attrs", [["ORTH", "SHAPE"], "IS_ALPHA"])
def test_doc_array_to_from_string_attrs(en_vocab, attrs):
"""Test that both Doc.to_array and Doc.from_array accept string attrs,
as well as single attrs and sequences of attrs.
"""
words = ["An", "example", "sentence"]
doc = Doc(en_vocab, words=words)
Doc(en_vocab, words=words).from_array(attrs, doc.to_array(attrs))
def test_doc_array_idx(en_vocab):
"""Test that Doc.to_array can retrieve token start indices"""
words = ["An", "example", "sentence"]
offsets = Doc(en_vocab, words=words).to_array("IDX")
assert offsets[0] == 0
assert offsets[1] == 3
assert offsets[2] == 11
def test_doc_from_array_heads_in_bounds(en_vocab):
"""Test that Doc.from_array doesn't set heads that are out of bounds."""
words = ["This", "is", "a", "sentence", "."]
doc = Doc(en_vocab, words=words)
for token in doc:
token.head = doc[0]
# correct
arr = doc.to_array(["HEAD"])
doc_from_array = Doc(en_vocab, words=words)
doc_from_array.from_array(["HEAD"], arr)
# head before start
arr = doc.to_array(["HEAD"])
arr[0] = -1
doc_from_array = Doc(en_vocab, words=words)
with pytest.raises(ValueError):
doc_from_array.from_array(["HEAD"], arr)
# head after end
arr = doc.to_array(["HEAD"])
arr[0] = 5
doc_from_array = Doc(en_vocab, words=words)
with pytest.raises(ValueError):
doc_from_array.from_array(["HEAD"], arr)