import pytest import numpy from spacy.tokens import Doc from spacy.matcher import Matcher from spacy.displacy import render from spacy.gold import iob_to_biluo from spacy.lang.it import Italian from spacy.lang.en import English from ..util import add_vecs_to_vocab, get_doc @pytest.mark.skip( reason="Can not be fixed without iterative looping between prefix/suffix and infix" ) def test_issue2070(): """Test that checks that a dot followed by a quote is handled appropriately. """ # Problem: The dot is now properly split off, but the prefix/suffix rules # are not applied again afterwards. This means that the quote will still be # attached to the remaining token. nlp = English() doc = nlp('First sentence."A quoted sentence" he said ...') assert len(doc) == 11 @pytest.mark.filterwarnings("ignore::UserWarning") def test_issue2179(): """Test that spurious 'extra_labels' aren't created when initializing NER.""" nlp = Italian() ner = nlp.add_pipe("ner") ner.add_label("CITIZENSHIP") nlp.begin_training() nlp2 = Italian() nlp2.add_pipe("ner") assert len(nlp2.get_pipe("ner").labels) == 0 model = nlp2.get_pipe("ner").model model.attrs["resize_output"](model, nlp.get_pipe("ner").moves.n_moves) nlp2.from_bytes(nlp.to_bytes()) assert "extra_labels" not in nlp2.get_pipe("ner").cfg assert nlp2.get_pipe("ner").labels == ("CITIZENSHIP",) 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_issue2219(en_vocab): vectors = [("a", [1, 2, 3]), ("letter", [4, 5, 6])] add_vecs_to_vocab(en_vocab, vectors) [(word1, vec1), (word2, vec2)] = vectors doc = Doc(en_vocab, words=[word1, word2]) assert doc[0].similarity(doc[1]) == doc[1].similarity(doc[0]) def test_issue2361(de_tokenizer): chars = ("<", ">", "&", """) doc = de_tokenizer('< > & " ') doc.is_parsed = True doc.is_tagged = True html = render(doc) for char in chars: assert char in html def test_issue2385(): """Test that IOB tags are correctly converted to BILUO tags.""" # fix bug in labels with a 'b' character tags1 = ("B-BRAWLER", "I-BRAWLER", "I-BRAWLER") assert iob_to_biluo(tags1) == ["B-BRAWLER", "I-BRAWLER", "L-BRAWLER"] # maintain support for iob1 format tags2 = ("I-ORG", "I-ORG", "B-ORG") assert iob_to_biluo(tags2) == ["B-ORG", "L-ORG", "U-ORG"] # maintain support for iob2 format tags3 = ("B-PERSON", "I-PERSON", "B-PERSON") assert iob_to_biluo(tags3) == ["B-PERSON", "L-PERSON", "U-PERSON"] @pytest.mark.parametrize( "tags", [ ("B-ORG", "L-ORG"), ("B-PERSON", "I-PERSON", "L-PERSON"), ("U-BRAWLER", "U-BRAWLER"), ], ) def test_issue2385_biluo(tags): """Test that BILUO-compatible tags aren't modified.""" assert iob_to_biluo(tags) == list(tags) def test_issue2396(en_vocab): words = ["She", "created", "a", "test", "for", "spacy"] heads = [1, 0, 1, -2, -1, -1] matrix = numpy.array( [ [0, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1], [1, 1, 2, 3, 3, 3], [1, 1, 3, 3, 3, 3], [1, 1, 3, 3, 4, 4], [1, 1, 3, 3, 4, 5], ], dtype=numpy.int32, ) doc = get_doc(en_vocab, words=words, heads=heads) span = doc[:] assert (doc.get_lca_matrix() == matrix).all() assert (span.get_lca_matrix() == matrix).all() def test_issue2464(en_vocab): """Test problem with successive ?. This is the same bug, so putting it here.""" matcher = Matcher(en_vocab) doc = Doc(en_vocab, words=["a", "b"]) matcher.add("4", [[{"OP": "?"}, {"OP": "?"}]]) matches = matcher(doc) assert len(matches) == 3 @pytest.mark.filterwarnings("ignore::UserWarning") def test_issue2482(): """Test we can serialize and deserialize a blank NER or parser model.""" nlp = Italian() nlp.add_pipe("ner") b = nlp.to_bytes() Italian().from_bytes(b)