mirror of https://github.com/explosion/spaCy.git
168 lines
7.7 KiB
Python
168 lines
7.7 KiB
Python
import pytest
|
|
|
|
from ...tokenizer.test_naughty_strings import NAUGHTY_STRINGS
|
|
from spacy.lang.ja import Japanese, DetailedToken
|
|
|
|
# fmt: off
|
|
TOKENIZER_TESTS = [
|
|
("日本語だよ", ['日本', '語', 'だ', 'よ']),
|
|
("東京タワーの近くに住んでいます。", ['東京', 'タワー', 'の', '近く', 'に', '住ん', 'で', 'い', 'ます', '。']),
|
|
("吾輩は猫である。", ['吾輩', 'は', '猫', 'で', 'ある', '。']),
|
|
("月に代わって、お仕置きよ!", ['月', 'に', '代わっ', 'て', '、', 'お', '仕置き', 'よ', '!']),
|
|
("すもももももももものうち", ['すもも', 'も', 'もも', 'も', 'もも', 'の', 'うち'])
|
|
]
|
|
|
|
TAG_TESTS = [
|
|
("日本語だよ", ['名詞-固有名詞-地名-国', '名詞-普通名詞-一般', '助動詞', '助詞-終助詞']),
|
|
("東京タワーの近くに住んでいます。", ['名詞-固有名詞-地名-一般', '名詞-普通名詞-一般', '助詞-格助詞', '名詞-普通名詞-副詞可能', '助詞-格助詞', '動詞-一般', '助詞-接続助詞', '動詞-非自立可能', '助動詞', '補助記号-句点']),
|
|
("吾輩は猫である。", ['代名詞', '助詞-係助詞', '名詞-普通名詞-一般', '助動詞', '動詞-非自立可能', '補助記号-句点']),
|
|
("月に代わって、お仕置きよ!", ['名詞-普通名詞-助数詞可能', '助詞-格助詞', '動詞-一般', '助詞-接続助詞', '補助記号-読点', '接頭辞', '名詞-普通名詞-一般', '助詞-終助詞', '補助記号-句点']),
|
|
("すもももももももものうち", ['名詞-普通名詞-一般', '助詞-係助詞', '名詞-普通名詞-一般', '助詞-係助詞', '名詞-普通名詞-一般', '助詞-格助詞', '名詞-普通名詞-副詞可能'])
|
|
]
|
|
|
|
POS_TESTS = [
|
|
('日本語だよ', ['PROPN', 'NOUN', 'AUX', 'PART']),
|
|
('東京タワーの近くに住んでいます。', ['PROPN', 'NOUN', 'ADP', 'NOUN', 'ADP', 'VERB', 'SCONJ', 'AUX', 'AUX', 'PUNCT']),
|
|
('吾輩は猫である。', ['PRON', 'ADP', 'NOUN', 'AUX', 'AUX', 'PUNCT']),
|
|
('月に代わって、お仕置きよ!', ['NOUN', 'ADP', 'VERB', 'SCONJ', 'PUNCT', 'NOUN', 'NOUN', 'PART', 'PUNCT']),
|
|
('すもももももももものうち', ['NOUN', 'ADP', 'NOUN', 'ADP', 'NOUN', 'ADP', 'NOUN'])
|
|
]
|
|
|
|
SENTENCE_TESTS = [
|
|
("あれ。これ。", ["あれ。", "これ。"]),
|
|
("「伝染るんです。」という漫画があります。", ["「伝染るんです。」という漫画があります。"]),
|
|
]
|
|
|
|
tokens1 = [
|
|
DetailedToken(surface="委員", tag="名詞-普通名詞-一般", inf="", lemma="委員", norm="委員", reading="イイン", sub_tokens=None),
|
|
DetailedToken(surface="会", tag="名詞-普通名詞-一般", inf="", lemma="会", norm="会", reading="カイ", sub_tokens=None),
|
|
]
|
|
tokens2 = [
|
|
DetailedToken(surface="選挙", tag="名詞-普通名詞-サ変可能", inf="", lemma="選挙", norm="選挙", reading="センキョ", sub_tokens=None),
|
|
DetailedToken(surface="管理", tag="名詞-普通名詞-サ変可能", inf="", lemma="管理", norm="管理", reading="カンリ", sub_tokens=None),
|
|
DetailedToken(surface="委員", tag="名詞-普通名詞-一般", inf="", lemma="委員", norm="委員", reading="イイン", sub_tokens=None),
|
|
DetailedToken(surface="会", tag="名詞-普通名詞-一般", inf="", lemma="会", norm="会", reading="カイ", sub_tokens=None),
|
|
]
|
|
tokens3 = [
|
|
DetailedToken(surface="選挙", tag="名詞-普通名詞-サ変可能", inf="", lemma="選挙", norm="選挙", reading="センキョ", sub_tokens=None),
|
|
DetailedToken(surface="管理", tag="名詞-普通名詞-サ変可能", inf="", lemma="管理", norm="管理", reading="カンリ", sub_tokens=None),
|
|
DetailedToken(surface="委員会", tag="名詞-普通名詞-一般", inf="", lemma="委員会", norm="委員会", reading="イインカイ", sub_tokens=None),
|
|
]
|
|
SUB_TOKEN_TESTS = [
|
|
("選挙管理委員会", [None, None, [tokens1]], [[tokens2, tokens3]])
|
|
]
|
|
# fmt: on
|
|
|
|
|
|
@pytest.mark.issue(2901)
|
|
def test_issue2901():
|
|
"""Test that `nlp` doesn't fail."""
|
|
try:
|
|
nlp = Japanese()
|
|
except ImportError:
|
|
pytest.skip()
|
|
|
|
doc = nlp("pythonが大好きです")
|
|
assert doc
|
|
|
|
|
|
@pytest.mark.parametrize("text,expected_tokens", TOKENIZER_TESTS)
|
|
def test_ja_tokenizer(ja_tokenizer, text, expected_tokens):
|
|
tokens = [token.text for token in ja_tokenizer(text)]
|
|
assert tokens == expected_tokens
|
|
|
|
|
|
@pytest.mark.parametrize("text,expected_tags", TAG_TESTS)
|
|
def test_ja_tokenizer_tags(ja_tokenizer, text, expected_tags):
|
|
tags = [token.tag_ for token in ja_tokenizer(text)]
|
|
assert tags == expected_tags
|
|
|
|
|
|
@pytest.mark.parametrize("text,expected_pos", POS_TESTS)
|
|
def test_ja_tokenizer_pos(ja_tokenizer, text, expected_pos):
|
|
pos = [token.pos_ for token in ja_tokenizer(text)]
|
|
assert pos == expected_pos
|
|
|
|
|
|
@pytest.mark.skip(reason="sentence segmentation in tokenizer is buggy")
|
|
@pytest.mark.parametrize("text,expected_sents", SENTENCE_TESTS)
|
|
def test_ja_tokenizer_sents(ja_tokenizer, text, expected_sents):
|
|
sents = [str(sent) for sent in ja_tokenizer(text).sents]
|
|
assert sents == expected_sents
|
|
|
|
|
|
def test_ja_tokenizer_extra_spaces(ja_tokenizer):
|
|
# note: three spaces after "I"
|
|
tokens = ja_tokenizer("I like cheese.")
|
|
assert tokens[1].orth_ == " "
|
|
|
|
|
|
@pytest.mark.parametrize("text", NAUGHTY_STRINGS)
|
|
def test_ja_tokenizer_naughty_strings(ja_tokenizer, text):
|
|
tokens = ja_tokenizer(text)
|
|
assert tokens.text_with_ws == text
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"text,len_a,len_b,len_c",
|
|
[
|
|
("選挙管理委員会", 4, 3, 1),
|
|
("客室乗務員", 3, 2, 1),
|
|
("労働者協同組合", 4, 3, 1),
|
|
("機能性食品", 3, 2, 1),
|
|
],
|
|
)
|
|
def test_ja_tokenizer_split_modes(ja_tokenizer, text, len_a, len_b, len_c):
|
|
nlp_a = Japanese.from_config({"nlp": {"tokenizer": {"split_mode": "A"}}})
|
|
nlp_b = Japanese.from_config({"nlp": {"tokenizer": {"split_mode": "B"}}})
|
|
nlp_c = Japanese.from_config({"nlp": {"tokenizer": {"split_mode": "C"}}})
|
|
|
|
assert len(ja_tokenizer(text)) == len_a
|
|
assert len(nlp_a(text)) == len_a
|
|
assert len(nlp_b(text)) == len_b
|
|
assert len(nlp_c(text)) == len_c
|
|
|
|
|
|
@pytest.mark.parametrize("text,sub_tokens_list_b,sub_tokens_list_c", SUB_TOKEN_TESTS)
|
|
def test_ja_tokenizer_sub_tokens(
|
|
ja_tokenizer, text, sub_tokens_list_b, sub_tokens_list_c
|
|
):
|
|
nlp_a = Japanese.from_config({"nlp": {"tokenizer": {"split_mode": "A"}}})
|
|
nlp_b = Japanese.from_config({"nlp": {"tokenizer": {"split_mode": "B"}}})
|
|
nlp_c = Japanese.from_config({"nlp": {"tokenizer": {"split_mode": "C"}}})
|
|
|
|
assert ja_tokenizer(text).user_data.get("sub_tokens") is None
|
|
assert nlp_a(text).user_data.get("sub_tokens") is None
|
|
assert nlp_b(text).user_data["sub_tokens"] == sub_tokens_list_b
|
|
assert nlp_c(text).user_data["sub_tokens"] == sub_tokens_list_c
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"text,inflections,reading_forms",
|
|
[
|
|
(
|
|
"取ってつけた",
|
|
(["五段-ラ行;連用形-促音便"], [], ["下一段-カ行;連用形-一般"], ["助動詞-タ;終止形-一般"]),
|
|
(["トッ"], ["テ"], ["ツケ"], ["タ"]),
|
|
),
|
|
("2=3", ([], [], []), (["ニ"], ["_"], ["サン"])),
|
|
],
|
|
)
|
|
def test_ja_tokenizer_inflections_reading_forms(
|
|
ja_tokenizer, text, inflections, reading_forms
|
|
):
|
|
tokens = ja_tokenizer(text)
|
|
test_inflections = [tt.morph.get("Inflection") for tt in tokens]
|
|
assert test_inflections == list(inflections)
|
|
test_readings = [tt.morph.get("Reading") for tt in tokens]
|
|
assert test_readings == list(reading_forms)
|
|
|
|
|
|
def test_ja_tokenizer_emptyish_texts(ja_tokenizer):
|
|
doc = ja_tokenizer("")
|
|
assert len(doc) == 0
|
|
doc = ja_tokenizer(" ")
|
|
assert len(doc) == 1
|
|
doc = ja_tokenizer("\n\n\n \t\t \n\n\n")
|
|
assert len(doc) == 1
|