# coding: utf-8 from __future__ import unicode_literals import pytest from spacy.vocab import Vocab from spacy.tokens import Doc from ..util import get_doc def test_doc_split(en_vocab): words = ["LosAngeles", "start", "."] heads = [1, 1, 0] doc = get_doc(en_vocab, words=words, heads=heads) assert len(doc) == 3 assert len(str(doc)) == 19 assert doc[0].head.text == "start" assert doc[1].head.text == "." with doc.retokenize() as retokenizer: attrs = {"tag": "NNP", "lemma": "Los Angeles", "ent_type": "GPE"} retokenizer.split(doc[0], ["Los", "Angeles"], [1, 0], attrs=attrs) assert len(doc) == 4 assert doc[0].text == "Los" assert doc[0].head.text == "Angeles" assert doc[0].idx == 0 assert doc[1].idx == 3 assert doc[1].text == "Angeles" assert doc[1].head.text == "start" assert doc[2].text == "start" assert doc[2].head.text == "." assert doc[3].text == "." assert doc[3].head.text == "." assert len(str(doc)) == 19 def test_split_dependencies(en_vocab): doc = Doc(en_vocab, words=["LosAngeles", "start", "."]) dep1 = doc.vocab.strings.add("amod") dep2 = doc.vocab.strings.add("subject") with doc.retokenize() as retokenizer: retokenizer.split(doc[0], ["Los", "Angeles"], [1, 0], [dep1, dep2]) assert doc[0].dep == dep1 assert doc[1].dep == dep2 def test_split_heads_error(en_vocab): doc = Doc(en_vocab, words=["LosAngeles", "start", "."]) # Not enough heads with pytest.raises(ValueError): with doc.retokenize() as retokenizer: retokenizer.split(doc[0], ["Los", "Angeles"], [0]) # Too many heads with pytest.raises(ValueError): with doc.retokenize() as retokenizer: retokenizer.split(doc[0], ["Los", "Angeles"], [1, 1, 0]) # No token head with pytest.raises(ValueError): with doc.retokenize() as retokenizer: retokenizer.split(doc[0], ["Los", "Angeles"], [1, 1]) # Several token heads with pytest.raises(ValueError): with doc.retokenize() as retokenizer: retokenizer.split(doc[0], ["Los", "Angeles"], [0, 0]) def test_spans_entity_merge_iob(): # Test entity IOB stays consistent after merging words = ["abc", "d", "e"] doc = Doc(Vocab(), words=words) doc.ents = [(doc.vocab.strings.add("ent-abcd"), 0, 2)] assert doc[0].ent_iob_ == "B" assert doc[1].ent_iob_ == "I" with doc.retokenize() as retokenizer: retokenizer.split(doc[0], ["a", "b", "c"], [1, 1, 0]) assert doc[0].ent_iob_ == "B" assert doc[1].ent_iob_ == "I" assert doc[2].ent_iob_ == "I" assert doc[3].ent_iob_ == "I" def test_spans_sentence_update_after_merge(en_vocab): # fmt: off words = ["StewartLee", "is", "a", "stand", "up", "comedian", ".", "He", "lives", "in", "England", "and", "loves", "JoePasquale", "."] heads = [1, 0, 1, 2, -1, -4, -5, 1, 0, -1, -1, -3, -4, 1, -2] deps = ["nsubj", "ROOT", "det", "amod", "prt", "attr", "punct", "nsubj", "ROOT", "prep", "pobj", "cc", "conj", "compound", "punct"] # fmt: on doc = get_doc(en_vocab, words=words, heads=heads, deps=deps) sent1, sent2 = list(doc.sents) init_len = len(sent1) init_len2 = len(sent2) with doc.retokenize() as retokenizer: retokenizer.split(doc[0], ["Stewart", "Lee"], [1, 0]) retokenizer.split(doc[14], ["Joe", "Pasquale"], [1, 0]) sent1, sent2 = list(doc.sents) assert len(sent1) == init_len + 1 assert len(sent2) == init_len2 + 1