spaCy/spacy/tests/doc/test_doc_split.py

117 lines
4.1 KiB
Python
Raw Normal View History

# coding: utf-8
from __future__ import unicode_literals
import pytest
2019-02-14 18:56:38 +00:00
from spacy.vocab import Vocab
from spacy.tokens import Doc
from ..util import get_doc
2019-02-15 11:56:51 +00:00
def test_doc_split(en_vocab):
words = ["LosAngeles", "start", "."]
heads = [1, 1, 0]
2019-02-15 11:56:51 +00:00
doc = get_doc(en_vocab, words=words, heads=heads)
assert len(doc) == 3
assert len(str(doc)) == 19
2019-02-14 18:56:38 +00:00
assert doc[0].head.text == "start"
assert doc[1].head.text == "."
with doc.retokenize() as retokenizer:
retokenizer.split(
doc[0],
["Los", "Angeles"],
[(doc[0], 1), doc[1]],
attrs={
"tag": ["NNP"]*2,
"lemma": ["Los", "Angeles"],
"ent_type": ["GPE"]*2
},
)
assert len(doc) == 4
2019-02-14 18:56:38 +00:00
assert doc[0].text == "Los"
assert doc[0].head.text == "Angeles"
assert doc[0].idx == 0
assert doc[1].idx == 3
2019-02-14 18:56:38 +00:00
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
2019-02-14 18:56:38 +00:00
2019-02-15 11:56:51 +00:00
def test_split_dependencies(en_vocab):
doc = Doc(en_vocab, words=["LosAngeles", "start", "."])
2019-02-14 18:56:38 +00:00
dep1 = doc.vocab.strings.add("amod")
dep2 = doc.vocab.strings.add("subject")
with doc.retokenize() as retokenizer:
retokenizer.split(doc[0], ["Los", "Angeles"],
[(doc[0], 1), doc[1]], attrs={'dep': [dep1, dep2]})
assert doc[0].dep == dep1
assert doc[1].dep == dep2
2019-02-15 11:56:51 +00:00
def test_split_heads_error(en_vocab):
doc = Doc(en_vocab, words=["LosAngeles", "start", "."])
2019-02-14 18:56:38 +00:00
# Not enough heads
with pytest.raises(ValueError):
with doc.retokenize() as retokenizer:
retokenizer.split(doc[0], ["Los", "Angeles"], [doc[1]])
2019-02-14 18:56:38 +00:00
# Too many heads
with pytest.raises(ValueError):
with doc.retokenize() as retokenizer:
retokenizer.split(doc[0], ["Los", "Angeles"], [doc[1], doc[1], doc[1]])
def test_spans_entity_merge_iob():
# Test entity IOB stays consistent after merging
words = ["abc", "d", "e"]
doc = Doc(Vocab(), words=words)
2019-02-14 18:56:38 +00:00
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"],
[(doc[0], 1), (doc[0], 2), doc[1]])
assert doc[0].ent_iob_ == "B"
assert doc[1].ent_iob_ == "I"
assert doc[2].ent_iob_ == "I"
assert doc[3].ent_iob_ == "I"
2019-02-14 18:56:38 +00:00
2019-02-15 11:56:51 +00:00
def test_spans_sentence_update_after_merge(en_vocab):
2019-02-14 18:56:38 +00:00
# fmt: off
2019-02-15 11:56:51 +00:00
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]
2019-02-14 18:56:38 +00:00
deps = ["nsubj", "ROOT", "det", "amod", "prt", "attr", "punct", "nsubj",
"ROOT", "prep", "pobj", "cc", "conj", "compound", "punct"]
# fmt: on
2019-02-15 11:56:51 +00:00
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"], [(doc[0], 1), doc[1]],
attrs={"dep": ["compound", "nsubj"]})
retokenizer.split(doc[13], ["Joe", "Pasquale"], [(doc[13], 1), doc[12]],
attrs={"dep": ["compound", "dobj"]})
sent1, sent2 = list(doc.sents)
assert len(sent1) == init_len + 1
assert len(sent2) == init_len2 + 1
def test_split_orths_mismatch(en_vocab):
"""Test that the regular retokenizer.split raises an error if the orths
don't match the original token text. There might still be a method that
allows this, but for the default use cases, merging and splitting should
always conform with spaCy's non-destructive tokenization policy. Otherwise,
it can lead to very confusing and unexpected results.
"""
doc = Doc(en_vocab, words=["LosAngeles", "start", "."])
with pytest.raises(ValueError):
with doc.retokenize() as retokenizer:
retokenizer.split(doc[0], ["L", "A"], [(doc[0], 0), (doc[0], 0)])