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			39 lines
		
	
	
		
			1.1 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			39 lines
		
	
	
		
			1.1 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| from typing import Optional
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| from thinc.api import Model
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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 .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
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| from .punctuation import TOKENIZER_SUFFIXES
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| from .syntax_iterators import SYNTAX_ITERATORS
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| from ...language import Language
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| from ...pipeline import Lemmatizer
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| 
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| 
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| class PersianDefaults(Language.Defaults):
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|     tokenizer_exceptions = TOKENIZER_EXCEPTIONS
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|     suffixes = TOKENIZER_SUFFIXES
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|     lex_attr_getters = LEX_ATTRS
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|     syntax_iterators = SYNTAX_ITERATORS
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|     stop_words = STOP_WORDS
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|     writing_system = {"direction": "rtl", "has_case": False, "has_letters": True}
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| 
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| 
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| class Persian(Language):
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|     lang = "fa"
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|     Defaults = PersianDefaults
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| 
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| 
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| @Persian.factory(
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|     "lemmatizer",
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|     assigns=["token.lemma"],
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|     default_config={"model": None, "mode": "rule", "overwrite": False},
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|     default_score_weights={"lemma_acc": 1.0},
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| )
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| def make_lemmatizer(
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|     nlp: Language, model: Optional[Model], name: str, mode: str, overwrite: bool
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| ):
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|     return Lemmatizer(nlp.vocab, model, name, mode=mode, overwrite=overwrite)
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| 
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| 
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| __all__ = ["Persian"]
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