spaCy/spacy/tests/test_lemmatizer.py

50 lines
1.8 KiB
Python
Raw Normal View History

# coding: utf8
from __future__ import unicode_literals
import pytest
from spacy.tokens import Doc
from spacy.language import Language
from spacy.lookups import Lookups
def test_lemmatizer_reflects_lookups_changes():
"""Test for an issue that'd cause lookups available in a model loaded from
disk to not be reflected in the lemmatizer."""
nlp = Language()
assert Doc(nlp.vocab, words=["foo"])[0].lemma_ == "foo"
table = nlp.vocab.lookups.add_table("lemma_lookup")
table["foo"] = "bar"
assert Doc(nlp.vocab, words=["foo"])[0].lemma_ == "bar"
table = nlp.vocab.lookups.get_table("lemma_lookup")
table["hello"] = "world"
# The update to the table should be reflected in the lemmatizer
assert Doc(nlp.vocab, words=["hello"])[0].lemma_ == "world"
new_nlp = Language()
table = new_nlp.vocab.lookups.add_table("lemma_lookup")
table["hello"] = "hi"
assert Doc(new_nlp.vocab, words=["hello"])[0].lemma_ == "hi"
nlp_bytes = nlp.to_bytes()
new_nlp.from_bytes(nlp_bytes)
# Make sure we have the previously saved lookup table
assert len(new_nlp.vocab.lookups) == 1
assert len(new_nlp.vocab.lookups.get_table("lemma_lookup")) == 2
assert new_nlp.vocab.lookups.get_table("lemma_lookup")["hello"] == "world"
assert Doc(new_nlp.vocab, words=["foo"])[0].lemma_ == "bar"
assert Doc(new_nlp.vocab, words=["hello"])[0].lemma_ == "world"
def test_tagger_warns_no_lemma_lookups():
nlp = Language()
nlp.vocab.lookups = Lookups()
assert not len(nlp.vocab.lookups)
tagger = nlp.create_pipe("tagger")
with pytest.warns(UserWarning):
tagger.begin_training()
nlp.add_pipe(tagger)
with pytest.warns(UserWarning):
nlp.begin_training()
nlp.vocab.lookups.add_table("lemma_lookup")
with pytest.warns(None) as record:
nlp.begin_training()
assert not record.list