mirror of
https://github.com/explosion/spaCy.git
synced 2024-12-27 10:26:35 +03:00
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
196 lines
6.9 KiB
Python
196 lines
6.9 KiB
Python
import pickle
|
|
|
|
import pytest
|
|
from thinc.api import get_current_ops
|
|
|
|
import spacy
|
|
from spacy.lang.en import English
|
|
from spacy.strings import StringStore
|
|
from spacy.tokens import Doc
|
|
from spacy.util import ensure_path, load_model
|
|
from spacy.vectors import Vectors
|
|
from spacy.vocab import Vocab
|
|
|
|
from ..util import make_tempdir
|
|
|
|
test_strings = [([], []), (["rats", "are", "cute"], ["i", "like", "rats"])]
|
|
test_strings_attrs = [(["rats", "are", "cute"], "Hello")]
|
|
|
|
|
|
@pytest.mark.issue(599)
|
|
def test_issue599(en_vocab):
|
|
doc = Doc(en_vocab)
|
|
doc2 = Doc(doc.vocab)
|
|
doc2.from_bytes(doc.to_bytes())
|
|
assert doc2.has_annotation("DEP")
|
|
|
|
|
|
@pytest.mark.issue(4054)
|
|
def test_issue4054(en_vocab):
|
|
"""Test that a new blank model can be made with a vocab from file,
|
|
and that serialization does not drop the language at any point."""
|
|
nlp1 = English()
|
|
vocab1 = nlp1.vocab
|
|
with make_tempdir() as d:
|
|
vocab_dir = ensure_path(d / "vocab")
|
|
if not vocab_dir.exists():
|
|
vocab_dir.mkdir()
|
|
vocab1.to_disk(vocab_dir)
|
|
vocab2 = Vocab().from_disk(vocab_dir)
|
|
nlp2 = spacy.blank("en", vocab=vocab2)
|
|
nlp_dir = ensure_path(d / "nlp")
|
|
if not nlp_dir.exists():
|
|
nlp_dir.mkdir()
|
|
nlp2.to_disk(nlp_dir)
|
|
nlp3 = load_model(nlp_dir)
|
|
assert nlp3.lang == "en"
|
|
|
|
|
|
@pytest.mark.issue(4133)
|
|
def test_issue4133(en_vocab):
|
|
nlp = English()
|
|
vocab_bytes = nlp.vocab.to_bytes()
|
|
words = ["Apple", "is", "looking", "at", "buying", "a", "startup"]
|
|
pos = ["NOUN", "VERB", "ADP", "VERB", "PROPN", "NOUN", "ADP"]
|
|
doc = Doc(en_vocab, words=words)
|
|
for i, token in enumerate(doc):
|
|
token.pos_ = pos[i]
|
|
# usually this is already True when starting from proper models instead of blank English
|
|
doc_bytes = doc.to_bytes()
|
|
vocab = Vocab()
|
|
vocab = vocab.from_bytes(vocab_bytes)
|
|
doc = Doc(vocab).from_bytes(doc_bytes)
|
|
actual = []
|
|
for token in doc:
|
|
actual.append(token.pos_)
|
|
assert actual == pos
|
|
|
|
|
|
@pytest.mark.parametrize("text", ["rat"])
|
|
def test_serialize_vocab(en_vocab, text):
|
|
text_hash = en_vocab.strings.add(text)
|
|
vocab_bytes = en_vocab.to_bytes(exclude=["lookups"])
|
|
new_vocab = Vocab().from_bytes(vocab_bytes)
|
|
assert new_vocab.strings[text_hash] == text
|
|
assert new_vocab.to_bytes(exclude=["lookups"]) == vocab_bytes
|
|
|
|
|
|
@pytest.mark.parametrize("strings1,strings2", test_strings)
|
|
def test_serialize_vocab_roundtrip_bytes(strings1, strings2):
|
|
vocab1 = Vocab(strings=strings1)
|
|
vocab2 = Vocab(strings=strings2)
|
|
vocab1_b = vocab1.to_bytes()
|
|
vocab2_b = vocab2.to_bytes()
|
|
if strings1 == strings2:
|
|
assert vocab1_b == vocab2_b
|
|
else:
|
|
assert vocab1_b != vocab2_b
|
|
vocab1 = vocab1.from_bytes(vocab1_b)
|
|
assert vocab1.to_bytes() == vocab1_b
|
|
new_vocab1 = Vocab().from_bytes(vocab1_b)
|
|
assert new_vocab1.to_bytes() == vocab1_b
|
|
assert len(new_vocab1.strings) == len(strings1)
|
|
assert sorted([s for s in new_vocab1.strings]) == sorted(strings1)
|
|
|
|
|
|
@pytest.mark.parametrize("strings1,strings2", test_strings)
|
|
def test_serialize_vocab_roundtrip_disk(strings1, strings2):
|
|
vocab1 = Vocab(strings=strings1)
|
|
vocab2 = Vocab(strings=strings2)
|
|
with make_tempdir() as d:
|
|
file_path1 = d / "vocab1"
|
|
file_path2 = d / "vocab2"
|
|
vocab1.to_disk(file_path1)
|
|
vocab2.to_disk(file_path2)
|
|
vocab1_d = Vocab().from_disk(file_path1)
|
|
vocab2_d = Vocab().from_disk(file_path2)
|
|
# check strings rather than lexemes, which are only reloaded on demand
|
|
assert set(strings1) == set([s for s in vocab1_d.strings])
|
|
assert set(strings2) == set([s for s in vocab2_d.strings])
|
|
if set(strings1) == set(strings2):
|
|
assert [s for s in vocab1_d.strings] == [s for s in vocab2_d.strings]
|
|
else:
|
|
assert [s for s in vocab1_d.strings] != [s for s in vocab2_d.strings]
|
|
|
|
|
|
@pytest.mark.parametrize("strings,lex_attr", test_strings_attrs)
|
|
def test_serialize_vocab_lex_attrs_bytes(strings, lex_attr):
|
|
vocab1 = Vocab(strings=strings)
|
|
vocab2 = Vocab()
|
|
vocab1[strings[0]].norm_ = lex_attr
|
|
assert vocab1[strings[0]].norm_ == lex_attr
|
|
assert vocab2[strings[0]].norm_ != lex_attr
|
|
vocab2 = vocab2.from_bytes(vocab1.to_bytes())
|
|
assert vocab2[strings[0]].norm_ == lex_attr
|
|
|
|
|
|
@pytest.mark.parametrize("strings,lex_attr", test_strings_attrs)
|
|
def test_deserialize_vocab_seen_entries(strings, lex_attr):
|
|
# Reported in #2153
|
|
vocab = Vocab(strings=strings)
|
|
vocab.from_bytes(vocab.to_bytes())
|
|
assert len(vocab.strings) == len(strings)
|
|
|
|
|
|
@pytest.mark.parametrize("strings,lex_attr", test_strings_attrs)
|
|
def test_serialize_vocab_lex_attrs_disk(strings, lex_attr):
|
|
vocab1 = Vocab(strings=strings)
|
|
vocab2 = Vocab()
|
|
vocab1[strings[0]].norm_ = lex_attr
|
|
assert vocab1[strings[0]].norm_ == lex_attr
|
|
assert vocab2[strings[0]].norm_ != lex_attr
|
|
with make_tempdir() as d:
|
|
file_path = d / "vocab"
|
|
vocab1.to_disk(file_path)
|
|
vocab2 = vocab2.from_disk(file_path)
|
|
assert vocab2[strings[0]].norm_ == lex_attr
|
|
|
|
|
|
@pytest.mark.parametrize("strings1,strings2", test_strings)
|
|
def test_serialize_stringstore_roundtrip_bytes(strings1, strings2):
|
|
sstore1 = StringStore(strings=strings1)
|
|
sstore2 = StringStore(strings=strings2)
|
|
sstore1_b = sstore1.to_bytes()
|
|
sstore2_b = sstore2.to_bytes()
|
|
if set(strings1) == set(strings2):
|
|
assert sstore1_b == sstore2_b
|
|
else:
|
|
assert sstore1_b != sstore2_b
|
|
sstore1 = sstore1.from_bytes(sstore1_b)
|
|
assert sstore1.to_bytes() == sstore1_b
|
|
new_sstore1 = StringStore().from_bytes(sstore1_b)
|
|
assert new_sstore1.to_bytes() == sstore1_b
|
|
assert set(new_sstore1) == set(strings1)
|
|
|
|
|
|
@pytest.mark.parametrize("strings1,strings2", test_strings)
|
|
def test_serialize_stringstore_roundtrip_disk(strings1, strings2):
|
|
sstore1 = StringStore(strings=strings1)
|
|
sstore2 = StringStore(strings=strings2)
|
|
with make_tempdir() as d:
|
|
file_path1 = d / "strings1"
|
|
file_path2 = d / "strings2"
|
|
sstore1.to_disk(file_path1)
|
|
sstore2.to_disk(file_path2)
|
|
sstore1_d = StringStore().from_disk(file_path1)
|
|
sstore2_d = StringStore().from_disk(file_path2)
|
|
assert set(sstore1_d) == set(sstore1)
|
|
assert set(sstore2_d) == set(sstore2)
|
|
if set(strings1) == set(strings2):
|
|
assert set(sstore1_d) == set(sstore2_d)
|
|
else:
|
|
assert set(sstore1_d) != set(sstore2_d)
|
|
|
|
|
|
@pytest.mark.parametrize("strings,lex_attr", test_strings_attrs)
|
|
def test_pickle_vocab(strings, lex_attr):
|
|
vocab = Vocab(strings=strings)
|
|
ops = get_current_ops()
|
|
vectors = Vectors(data=ops.xp.zeros((10, 10)), mode="floret", hash_count=1)
|
|
vocab.vectors = vectors
|
|
vocab[strings[0]].norm_ = lex_attr
|
|
vocab_pickled = pickle.dumps(vocab)
|
|
vocab_unpickled = pickle.loads(vocab_pickled)
|
|
assert vocab.to_bytes() == vocab_unpickled.to_bytes()
|
|
assert vocab_unpickled.vectors.mode == "floret"
|