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	* Use isort with Black profile * isort all the things * Fix import cycles as a result of import sorting * Add DOCBIN_ALL_ATTRS type definition * Add isort to requirements * Remove isort from build dependencies check * Typo
		
			
				
	
	
		
			169 lines
		
	
	
		
			5.4 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			169 lines
		
	
	
		
			5.4 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
import re
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import string
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from pathlib import Path
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from typing import Any, Dict, Union
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import srsly
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from ... import util
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from ...language import BaseDefaults, Language
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from ...tokens import Doc
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from ...util import DummyTokenizer, load_config_from_str, registry
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from ...vocab import Vocab
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from .lex_attrs import LEX_ATTRS
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from .stop_words import STOP_WORDS
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DEFAULT_CONFIG = """
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[nlp]
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[nlp.tokenizer]
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@tokenizers = "spacy.vi.VietnameseTokenizer"
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use_pyvi = true
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"""
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@registry.tokenizers("spacy.vi.VietnameseTokenizer")
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def create_vietnamese_tokenizer(use_pyvi: bool = True):
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    def vietnamese_tokenizer_factory(nlp):
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        return VietnameseTokenizer(nlp.vocab, use_pyvi=use_pyvi)
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    return vietnamese_tokenizer_factory
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class VietnameseTokenizer(DummyTokenizer):
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    def __init__(self, vocab: Vocab, use_pyvi: bool = False):
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        self.vocab = vocab
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        self.use_pyvi = use_pyvi
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        if self.use_pyvi:
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            try:
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                from pyvi import ViTokenizer
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                self.ViTokenizer = ViTokenizer
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            except ImportError:
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                msg = (
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                    "Pyvi not installed. Either set use_pyvi = False, "
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                    "or install it https://pypi.python.org/pypi/pyvi"
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                )
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                raise ImportError(msg) from None
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    def __reduce__(self):
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        return VietnameseTokenizer, (self.vocab, self.use_pyvi)
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    def __call__(self, text: str) -> Doc:
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        if self.use_pyvi:
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            words = self.pyvi_tokenize(text)
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            words, spaces = util.get_words_and_spaces(words, text)
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            return Doc(self.vocab, words=words, spaces=spaces)
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        else:
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            words, spaces = util.get_words_and_spaces(text.split(), text)
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            return Doc(self.vocab, words=words, spaces=spaces)
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    # The methods pyvi_sylabelize_with_ws and pyvi_tokenize are adapted from
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    # pyvi v0.1, MIT License, Copyright (c) 2016 Viet-Trung Tran.
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    # See licenses/3rd_party_licenses.txt
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    def pyvi_sylabelize_with_ws(self, text):
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        """Modified from pyvi to preserve whitespace and skip unicode
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        normalization."""
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        specials = [r"==>", r"->", r"\.\.\.", r">>"]
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        digit = r"\d+([\.,_]\d+)+"
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        email = r"([a-zA-Z0-9_.+-]+@([a-zA-Z0-9-]+\.)+[a-zA-Z0-9-]+)"
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        web = r"\w+://[^\s]+"
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        word = r"\w+"
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        non_word = r"[^\w\s]"
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        abbreviations = [
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            r"[A-ZĐ]+\.",
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            r"Tp\.",
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            r"Mr\.",
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            r"Mrs\.",
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            r"Ms\.",
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            r"Dr\.",
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            r"ThS\.",
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        ]
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        patterns = []
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        patterns.extend(abbreviations)
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        patterns.extend(specials)
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        patterns.extend([web, email])
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        patterns.extend([digit, non_word, word])
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        patterns = r"(\s+|" + "|".join(patterns) + ")"
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        tokens = re.findall(patterns, text, re.UNICODE)
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        return [token[0] for token in tokens]
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    def pyvi_tokenize(self, text):
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        """Modified from pyvi to preserve text and whitespace."""
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        if len(text) == 0:
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            return []
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        elif text.isspace():
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            return [text]
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        segs = self.pyvi_sylabelize_with_ws(text)
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        words = []
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        preceding_ws = []
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        for i, token in enumerate(segs):
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            if not token.isspace():
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                words.append(token)
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                preceding_ws.append(
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                    "" if (i == 0 or not segs[i - 1].isspace()) else segs[i - 1]
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                )
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        labels = self.ViTokenizer.ViTokenizer.model.predict(
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            [self.ViTokenizer.ViTokenizer.sent2features(words, False)]
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        )
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        token = words[0]
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        tokens = []
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        for i in range(1, len(labels[0])):
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            if (
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                labels[0][i] == "I_W"
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                and words[i] not in string.punctuation
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                and words[i - 1] not in string.punctuation
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                and not words[i][0].isdigit()
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                and not words[i - 1][0].isdigit()
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                and not (words[i][0].istitle() and not words[i - 1][0].istitle())
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            ):
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                token = token + preceding_ws[i] + words[i]
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            else:
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                tokens.append(token)
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                token = words[i]
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        tokens.append(token)
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        return tokens
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    def _get_config(self) -> Dict[str, Any]:
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        return {"use_pyvi": self.use_pyvi}
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    def _set_config(self, config: Dict[str, Any] = {}) -> None:
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        self.use_pyvi = config.get("use_pyvi", False)
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    def to_bytes(self, **kwargs) -> bytes:
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        serializers = {"cfg": lambda: srsly.json_dumps(self._get_config())}
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        return util.to_bytes(serializers, [])
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    def from_bytes(self, data: bytes, **kwargs) -> "VietnameseTokenizer":
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        deserializers = {"cfg": lambda b: self._set_config(srsly.json_loads(b))}
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        util.from_bytes(data, deserializers, [])
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        return self
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    def to_disk(self, path: Union[str, Path], **kwargs) -> None:
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        path = util.ensure_path(path)
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        serializers = {"cfg": lambda p: srsly.write_json(p, self._get_config())}
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        util.to_disk(path, serializers, [])
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    def from_disk(self, path: Union[str, Path], **kwargs) -> "VietnameseTokenizer":
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        path = util.ensure_path(path)
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        serializers = {"cfg": lambda p: self._set_config(srsly.read_json(p))}
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        util.from_disk(path, serializers, [])
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        return self
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class VietnameseDefaults(BaseDefaults):
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    config = load_config_from_str(DEFAULT_CONFIG)
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    lex_attr_getters = LEX_ATTRS
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    stop_words = STOP_WORDS
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class Vietnamese(Language):
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    lang = "vi"
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    Defaults = VietnameseDefaults
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__all__ = ["Vietnamese"]
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