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Replace python-mecab3 with fugashi for Japanese (#4621)
* Switch from mecab-python3 to fugashi mecab-python3 has been the best MeCab binding for a long time but it's not very actively maintained, and since it's based on old SWIG code distributed with MeCab there's a limit to how effectively it can be maintained. Fugashi is a new Cython-based MeCab wrapper I wrote. Since it's not based on the old SWIG code it's easier to keep it current and make small deviations from the MeCab C/C++ API where that makes sense. * Change mecab-python3 to fugashi in setup.cfg * Change "mecab tags" to "unidic tags" The tags come from MeCab, but the tag schema is specified by Unidic, so it's more proper to refer to it that way. * Update conftest * Add fugashi link to external deps list for Japanese
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@ -73,7 +73,7 @@ cuda100 =
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cupy-cuda100>=5.0.0b4
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# Language tokenizers with external dependencies
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ja =
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mecab-python3==0.7
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fugashi>=0.1.3
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ko =
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natto-py==0.9.0
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th =
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@ -12,21 +12,23 @@ from ...tokens import Doc
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from ...compat import copy_reg
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from ...util import DummyTokenizer
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# Handling for multiple spaces in a row is somewhat awkward, this simplifies
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# the flow by creating a dummy with the same interface.
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DummyNode = namedtuple("DummyNode", ["surface", "pos", "feature"])
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DummyNodeFeatures = namedtuple("DummyNodeFeatures", ["lemma"])
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DummySpace = DummyNode(' ', ' ', DummyNodeFeatures(' '))
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ShortUnitWord = namedtuple("ShortUnitWord", ["surface", "lemma", "pos"])
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def try_mecab_import():
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"""Mecab is required for Japanese support, so check for it.
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def try_fugashi_import():
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"""Fugashi is required for Japanese support, so check for it.
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It it's not available blow up and explain how to fix it."""
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try:
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import MeCab
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import fugashi
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return MeCab
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return fugashi
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except ImportError:
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raise ImportError(
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"Japanese support requires MeCab: "
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"https://github.com/SamuraiT/mecab-python3"
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"Japanese support requires Fugashi: "
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"https://github.com/polm/fugashi"
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)
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@ -39,7 +41,7 @@ def resolve_pos(token):
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"""
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# this is only used for consecutive ascii spaces
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if token.pos == "空白":
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if token.surface == " ":
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return "空白"
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# TODO: This is a first take. The rules here are crude approximations.
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@ -53,55 +55,45 @@ def resolve_pos(token):
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return token.pos + ",ADJ"
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return token.pos
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def get_words_and_spaces(tokenizer, text):
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"""Get the individual tokens that make up the sentence and handle white space.
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Japanese doesn't usually use white space, and MeCab's handling of it for
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multiple spaces in a row is somewhat awkward.
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"""
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tokens = tokenizer.parseToNodeList(text)
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def detailed_tokens(tokenizer, text):
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"""Format Mecab output into a nice data structure, based on Janome."""
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node = tokenizer.parseToNode(text)
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node = node.next # first node is beginning of sentence and empty, skip it
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words = []
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spaces = []
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while node.posid != 0:
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surface = node.surface
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base = surface # a default value. Updated if available later.
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parts = node.feature.split(",")
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pos = ",".join(parts[0:4])
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if len(parts) > 7:
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# this information is only available for words in the tokenizer
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# dictionary
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base = parts[7]
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words.append(ShortUnitWord(surface, base, pos))
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# The way MeCab stores spaces is that the rlength of the next token is
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# the length of that token plus any preceding whitespace, **in bytes**.
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# also note that this is only for half-width / ascii spaces. Full width
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# spaces just become tokens.
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scount = node.next.rlength - node.next.length
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spaces.append(bool(scount))
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while scount > 1:
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words.append(ShortUnitWord(" ", " ", "空白"))
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for token in tokens:
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# If there's more than one space, spaces after the first become tokens
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for ii in range(len(token.white_space) - 1):
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words.append(DummySpace)
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spaces.append(False)
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scount -= 1
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node = node.next
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words.append(token)
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spaces.append(bool(token.white_space))
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return words, spaces
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class JapaneseTokenizer(DummyTokenizer):
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def __init__(self, cls, nlp=None):
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self.vocab = nlp.vocab if nlp is not None else cls.create_vocab(nlp)
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self.tokenizer = try_mecab_import().Tagger()
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self.tokenizer.parseToNode("") # see #2901
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self.tokenizer = try_fugashi_import().Tagger()
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self.tokenizer.parseToNodeList("") # see #2901
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def __call__(self, text):
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dtokens, spaces = detailed_tokens(self.tokenizer, text)
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dtokens, spaces = get_words_and_spaces(self.tokenizer, text)
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words = [x.surface for x in dtokens]
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doc = Doc(self.vocab, words=words, spaces=spaces)
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mecab_tags = []
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unidic_tags = []
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for token, dtoken in zip(doc, dtokens):
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mecab_tags.append(dtoken.pos)
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unidic_tags.append(dtoken.pos)
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token.tag_ = resolve_pos(dtoken)
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token.lemma_ = dtoken.lemma
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doc.user_data["mecab_tags"] = mecab_tags
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# if there's no lemma info (it's an unk) just use the surface
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token.lemma_ = dtoken.feature.lemma or dtoken.surface
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doc.user_data["unidic_tags"] = unidic_tags
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return doc
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@ -131,5 +123,4 @@ def pickle_japanese(instance):
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copy_reg.pickle(Japanese, pickle_japanese)
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__all__ = ["Japanese"]
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@ -125,7 +125,7 @@ def it_tokenizer():
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@pytest.fixture(scope="session")
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def ja_tokenizer():
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pytest.importorskip("MeCab")
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pytest.importorskip("fugashi")
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return get_lang_class("ja").Defaults.create_tokenizer()
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@ -155,7 +155,8 @@
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"name": "Japanese",
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"dependencies": [
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{ "name": "Unidic", "url": "http://unidic.ninjal.ac.jp/back_number#unidic_cwj" },
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{ "name": "Mecab", "url": "https://github.com/taku910/mecab" }
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{ "name": "Mecab", "url": "https://github.com/taku910/mecab" },
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{ "name": "fugashi", "url": "https://github.com/polm/fugashi" }
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],
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"example": "これは文章です。",
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"has_examples": true
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