mirror of
https://github.com/explosion/spaCy.git
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69 lines
1.7 KiB
Python
69 lines
1.7 KiB
Python
from typing import Set, Dict, Callable, Any
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from thinc.api import Config
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from .stop_words import STOP_WORDS
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from .lex_attrs import LEX_ATTRS
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from ...language import Language
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from ...tokens import Doc
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from ...util import DummyTokenizer, registry
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DEFAULT_CONFIG = """
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[nlp]
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lang = "th"
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stop_words = {"@language_data": "spacy.th.stop_words"}
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lex_attr_getters = {"@language_data": "spacy.th.lex_attr_getters"}
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[nlp.tokenizer]
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@tokenizers = "spacy.ThaiTokenizer.v1"
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[nlp.vocab_data]
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@language_data = "spacy-lookups-data"
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lang = ${nlp:lang}
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tables = ["lexeme_norm"]
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"""
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@registry.language_data("spacy.th.stop_words")
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def stop_words() -> Set[str]:
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return STOP_WORDS
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@registry.language_data("spacy.th.lex_attr_getters")
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def lex_attr_getters() -> Dict[int, Callable[[str], Any]]:
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return LEX_ATTRS
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@registry.tokenizers("spacy.ThaiTokenizer.v1")
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def create_thai_tokenizer():
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def thai_tokenizer_factory(nlp):
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return ThaiTokenizer(nlp)
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return thai_tokenizer_factory
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class ThaiTokenizer(DummyTokenizer):
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def __init__(self, nlp: Language) -> None:
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try:
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from pythainlp.tokenize import word_tokenize
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except ImportError:
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raise ImportError(
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"The Thai tokenizer requires the PyThaiNLP library: "
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"https://github.com/PyThaiNLP/pythainlp"
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)
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self.word_tokenize = word_tokenize
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self.vocab = nlp.vocab
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def __call__(self, text: str) -> Doc:
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words = list(self.word_tokenize(text))
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spaces = [False] * len(words)
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return Doc(self.vocab, words=words, spaces=spaces)
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class Thai(Language):
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lang = "th"
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default_config = Config().from_str(DEFAULT_CONFIG)
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__all__ = ["Thai"]
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