mirror of
https://github.com/explosion/spaCy.git
synced 2024-12-27 10:26:35 +03:00
102 lines
3.1 KiB
Python
102 lines
3.1 KiB
Python
import pytest
|
|
from spacy.pipeline.functions import merge_subtokens
|
|
from spacy.language import Language
|
|
from spacy.tokens import Span, Doc
|
|
|
|
from ..doc.test_underscore import clean_underscore # noqa: F401
|
|
|
|
|
|
@pytest.fixture
|
|
def doc(en_vocab):
|
|
# fmt: off
|
|
words = ["This", "is", "a", "sentence", ".", "This", "is", "another", "sentence", ".", "And", "a", "third", "."]
|
|
heads = [1, 1, 3, 1, 1, 6, 6, 8, 6, 6, 11, 12, 13, 13]
|
|
deps = ["nsubj", "ROOT", "subtok", "attr", "punct", "nsubj", "ROOT",
|
|
"subtok", "attr", "punct", "subtok", "subtok", "subtok", "ROOT"]
|
|
# fmt: on
|
|
return Doc(en_vocab, words=words, heads=heads, deps=deps)
|
|
|
|
|
|
@pytest.fixture
|
|
def doc2(en_vocab):
|
|
words = ["I", "like", "New", "York", "in", "Autumn", "."]
|
|
heads = [1, 1, 3, 1, 1, 4, 1]
|
|
tags = ["PRP", "IN", "NNP", "NNP", "IN", "NNP", "."]
|
|
pos = ["PRON", "VERB", "PROPN", "PROPN", "ADP", "PROPN", "PUNCT"]
|
|
deps = ["ROOT", "prep", "compound", "pobj", "prep", "pobj", "punct"]
|
|
doc = Doc(en_vocab, words=words, heads=heads, tags=tags, pos=pos, deps=deps)
|
|
doc.ents = [Span(doc, 2, 4, label="GPE")]
|
|
return doc
|
|
|
|
|
|
def test_merge_subtokens(doc):
|
|
doc = merge_subtokens(doc)
|
|
# Doc doesn't have spaces, so the result is "And a third ."
|
|
# fmt: off
|
|
assert [t.text for t in doc] == ["This", "is", "a sentence", ".", "This", "is", "another sentence", ".", "And a third ."]
|
|
# fmt: on
|
|
|
|
|
|
def test_factories_merge_noun_chunks(doc2):
|
|
assert len(doc2) == 7
|
|
nlp = Language()
|
|
merge_noun_chunks = nlp.create_pipe("merge_noun_chunks")
|
|
merge_noun_chunks(doc2)
|
|
assert len(doc2) == 6
|
|
assert doc2[2].text == "New York"
|
|
|
|
|
|
def test_factories_merge_ents(doc2):
|
|
assert len(doc2) == 7
|
|
assert len(list(doc2.ents)) == 1
|
|
nlp = Language()
|
|
merge_entities = nlp.create_pipe("merge_entities")
|
|
merge_entities(doc2)
|
|
assert len(doc2) == 6
|
|
assert len(list(doc2.ents)) == 1
|
|
assert doc2[2].text == "New York"
|
|
|
|
|
|
def test_token_splitter():
|
|
nlp = Language()
|
|
config = {"min_length": 20, "split_length": 5}
|
|
token_splitter = nlp.add_pipe("token_splitter", config=config)
|
|
doc = nlp("aaaaabbbbbcccccdddd e f g")
|
|
assert [t.text for t in doc] == ["aaaaabbbbbcccccdddd", "e", "f", "g"]
|
|
doc = nlp("aaaaabbbbbcccccdddddeeeeeff g h i")
|
|
assert [t.text for t in doc] == [
|
|
"aaaaa",
|
|
"bbbbb",
|
|
"ccccc",
|
|
"ddddd",
|
|
"eeeee",
|
|
"ff",
|
|
"g",
|
|
"h",
|
|
"i",
|
|
]
|
|
assert all(len(t.text) <= token_splitter.split_length for t in doc)
|
|
|
|
|
|
@pytest.mark.usefixtures("clean_underscore")
|
|
def test_factories_doc_cleaner():
|
|
nlp = Language()
|
|
nlp.add_pipe("doc_cleaner")
|
|
doc = nlp.make_doc("text")
|
|
doc.tensor = [1, 2, 3]
|
|
doc = nlp(doc)
|
|
assert doc.tensor is None
|
|
|
|
nlp = Language()
|
|
nlp.add_pipe("doc_cleaner", config={"silent": False})
|
|
with pytest.warns(UserWarning):
|
|
doc = nlp("text")
|
|
|
|
Doc.set_extension("test_attr", default=-1)
|
|
nlp = Language()
|
|
nlp.add_pipe("doc_cleaner", config={"attrs": {"_.test_attr": 0}})
|
|
doc = nlp.make_doc("text")
|
|
doc._.test_attr = 100
|
|
doc = nlp(doc)
|
|
assert doc._.test_attr == 0
|