mirror of
https://github.com/explosion/spaCy.git
synced 2024-09-22 11:59:14 +03:00
0b9a5f4074
* Rework Chinese language initialization * Create a `ChineseTokenizer` class * Modify jieba post-processing to handle whitespace correctly * Modify non-jieba character tokenization to handle whitespace correctly * Add a `create_tokenizer()` method to `ChineseDefaults` * Load lexical attributes * Update Chinese tag_map for UD v2 * Add very basic Chinese tests * Test tokenization with and without jieba * Test `like_num` attribute * Fix try_jieba_import() * Fix zh code formatting
104 lines
3.5 KiB
Python
104 lines
3.5 KiB
Python
# coding: utf8
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from __future__ import unicode_literals
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from ...attrs import LANG
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from ...language import Language
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from ...tokens import Doc
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from ...util import DummyTokenizer
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from ..tokenizer_exceptions import BASE_EXCEPTIONS
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from .lex_attrs import LEX_ATTRS
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from .stop_words import STOP_WORDS
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from .tag_map import TAG_MAP
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def try_jieba_import(use_jieba):
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try:
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import jieba
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return jieba
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except ImportError:
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if use_jieba:
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msg = (
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"Jieba not installed. Either set Chinese.use_jieba = False, "
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"or install it https://github.com/fxsjy/jieba"
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)
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raise ImportError(msg)
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class ChineseTokenizer(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.use_jieba = cls.use_jieba
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self.jieba_seg = try_jieba_import(self.use_jieba)
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self.tokenizer = Language.Defaults().create_tokenizer(nlp)
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def __call__(self, text):
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# use jieba
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if self.use_jieba:
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jieba_words = list([x for x in self.jieba_seg.cut(text, cut_all=False) if x])
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words = [jieba_words[0]]
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spaces = [False]
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for i in range(1, len(jieba_words)):
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word = jieba_words[i]
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if word.isspace():
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# second token in adjacent whitespace following a
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# non-space token
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if spaces[-1]:
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words.append(word)
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spaces.append(False)
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# first space token following non-space token
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elif word == " " and not words[-1].isspace():
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spaces[-1] = True
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# token is non-space whitespace or any whitespace following
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# a whitespace token
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else:
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# extend previous whitespace token with more whitespace
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if words[-1].isspace():
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words[-1] += word
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# otherwise it's a new whitespace token
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else:
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words.append(word)
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spaces.append(False)
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else:
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words.append(word)
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spaces.append(False)
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return Doc(self.vocab, words=words, spaces=spaces)
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# split into individual characters
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words = []
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spaces = []
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for token in self.tokenizer(text):
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if token.text.isspace():
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words.append(token.text)
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spaces.append(False)
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else:
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words.extend(list(token.text))
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spaces.extend([False] * len(token.text))
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spaces[-1] = bool(token.whitespace_)
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return Doc(self.vocab, words=words, spaces=spaces)
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class ChineseDefaults(Language.Defaults):
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lex_attr_getters = dict(Language.Defaults.lex_attr_getters)
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lex_attr_getters.update(LEX_ATTRS)
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lex_attr_getters[LANG] = lambda text: "zh"
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tokenizer_exceptions = BASE_EXCEPTIONS
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stop_words = STOP_WORDS
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tag_map = TAG_MAP
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writing_system = {"direction": "ltr", "has_case": False, "has_letters": False}
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use_jieba = True
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@classmethod
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def create_tokenizer(cls, nlp=None):
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return ChineseTokenizer(cls, nlp)
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class Chinese(Language):
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lang = "zh"
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Defaults = ChineseDefaults # override defaults
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def make_doc(self, text):
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return self.tokenizer(text)
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__all__ = ["Chinese"]
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