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=================================== FAILURES ===================================
______________________________ test_new_tokenizer ______________________________
    def test_new_tokenizer():
        assert len(pytest.nlp.make_doc("ceci est un test")) == 4
        assert len(pytest.nlp.make_doc("ceci est un -test")) == 5
        assert len(pytest.nlp.make_doc("ceci est un te-st")) == 6
>       assert len(pytest.nlp.make_doc("ceci est un l'test")) == 6
E       assert 5 == 6
E        +  where 5 = len(ceci est un l'test)
E        +    where ceci est un l'test = <bound method Language.make_doc of <spacy.lang.fr.French object at 0x7f6a565f34e0>>("ceci est un l'test")
E        +      where <bound method Language.make_doc of <spacy.lang.fr.French object at 0x7f6a565f34e0>> = <spacy.lang.fr.French object at 0x7f6a565f34e0>.make_doc
E        +        where <spacy.lang.fr.French object at 0x7f6a565f34e0> = pytest.nlp
test/spacy_annotations_test.py:60: AssertionError
=============================== warnings summary ===============================
test/spacy_annotations_test.py::test_tokenizer
  /home/travis/build/ELS-RD/anonymisation/test/spacy_annotations_test.py:50: UserWarning: [W030] Some entities could not be aligned in the text "Ceci est un test." with entities "[(0, 4, 'PERS'), (9, 12, 'PERS')]". Use `spacy.gold.biluo_tags_from_offsets(nlp.make_doc(text), entities)` to check the alignment. Misaligned entities ('-') will be ignored during training.
    gold: GoldParse = GoldParse(doc, entities=offsets)
-- Docs: https://docs.pytest.org/en/latest/warnings.html
=============== 1 failed, 7 passed, 1 warnings in 32.06 seconds ================
The command "pytest" exited with 1.