



'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


snake_case_ :	str         =  logging.get_logger(__name__)

snake_case_ :	str         =  {'vocab_file': 'sentencepiece.bpe.model'}

snake_case_ :	Union[str, Any]         =  {
    'vocab_file': {
        'camembert-base': 'https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model',
    }
}

snake_case_ :	Optional[int]         =  {
    'camembert-base': 512,
}

snake_case_ :	List[Any]         =  '▁'






class 							lowercase__	(							lowercase   ):
	lowercase__  				=			VOCAB_FILES_NAMES
	lowercase__  				=			PRETRAINED_VOCAB_FILES_MAP
	lowercase__  				=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	lowercase__  				=			["""input_ids""", """attention_mask"""]





	def __init__( self					:				Optional[Any] ,lowerCamelCase__					:				int ,lowerCamelCase__					:				Optional[int]="<s>" ,lowerCamelCase__					:				Tuple="</s>" ,lowerCamelCase__					:				Any="</s>" ,lowerCamelCase__					:				Optional[int]="<s>" ,lowerCamelCase__					:				Dict="<unk>" ,lowerCamelCase__					:				str="<pad>" ,lowerCamelCase__					:				Optional[int]="<mask>" ,lowerCamelCase__					:				Any=["<s>NOTUSED", "</s>NOTUSED"] ,lowerCamelCase__					:				Optional[Dict[str, Any]] = None ,**lowerCamelCase__					:				List[str] ,):







							'''simple docstring'''
							# Mask token behave like a normal word, i.e. include the space before it
							_UpperCamelCase					:		Optional[Any] 				=   AddedToken(lowerCamelCase__ ,lstrip=lowerCamelCase__ ,rstrip=lowerCamelCase__ ) if isinstance(lowerCamelCase__ ,lowerCamelCase__ ) else mask_token

							_UpperCamelCase					:		Any 				=   {} if sp_model_kwargs is None else sp_model_kwargs

							super().__init__(
							    bos_token=lowerCamelCase__ ,eos_token=lowerCamelCase__ ,unk_token=lowerCamelCase__ ,sep_token=lowerCamelCase__ ,cls_token=lowerCamelCase__ ,pad_token=lowerCamelCase__ ,mask_token=lowerCamelCase__ ,additional_special_tokens=lowerCamelCase__ ,sp_model_kwargs=self.sp_model_kwargs ,**lowerCamelCase__ ,)
							_UpperCamelCase					:		Tuple 				=   spm.SentencePieceProcessor(**self.sp_model_kwargs )
							self.sp_model.Load(str(lowerCamelCase__ ) )
							_UpperCamelCase					:		Dict 				=   vocab_file
							# HACK: These tokens were added by fairseq but don't seem to be actually used when duplicated in the actual
							# sentencepiece vocabulary (this is the case for <s> and </s>
							_UpperCamelCase					:		Tuple 				=   {'<s>NOTUSED': 0, '<pad>': 1, '</s>NOTUSED': 2, '<unk>': 3}
							_UpperCamelCase					:		List[Any] 				=   len(self.fairseq_tokens_to_ids )
							_UpperCamelCase					:		int 				=   len(self.sp_model ) + len(self.fairseq_tokens_to_ids )
							_UpperCamelCase					:		Any 				=   {v: k for k, v in self.fairseq_tokens_to_ids.items()}





	def 	UpperCamelCase_  ( self					:				Optional[Any] ,lowerCamelCase__					:				List[int] ,lowerCamelCase__					:				Optional[List[int]] = None ):







							'''simple docstring'''

							if token_ids_a is None:
													return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
							_UpperCamelCase					:		Optional[Any] 				=   [self.cls_token_id]
							_UpperCamelCase					:		Dict 				=   [self.sep_token_id]
							return cls + token_ids_a + sep + sep + token_ids_a + sep





	def 	UpperCamelCase_  ( self					:				List[str] ,lowerCamelCase__					:				List[int] ,lowerCamelCase__					:				Optional[List[int]] = None ,lowerCamelCase__					:				bool = False ):







							'''simple docstring'''
							if already_has_special_tokens:
													return super().get_special_tokens_mask(
													    token_ids_a=lowerCamelCase__ ,token_ids_a=lowerCamelCase__ ,already_has_special_tokens=lowerCamelCase__ )

							if token_ids_a is None:
													return [1] + ([0] * len(lowerCamelCase__ )) + [1]
							return [1] + ([0] * len(lowerCamelCase__ )) + [1, 1] + ([0] * len(lowerCamelCase__ )) + [1]





	def 	UpperCamelCase_  ( self					:				Optional[Any] ,lowerCamelCase__					:				List[int] ,lowerCamelCase__					:				Optional[List[int]] = None ):







							'''simple docstring'''
							_UpperCamelCase					:		int 				=   [self.sep_token_id]
							_UpperCamelCase					:		int 				=   [self.cls_token_id]

							if token_ids_a is None:
													return len(cls + token_ids_a + sep ) * [0]
							return len(cls + token_ids_a + sep + sep + token_ids_a + sep ) * [0]





	@property
	def 	UpperCamelCase_  ( self					:				List[str] ):







							'''simple docstring'''
							return len(self.fairseq_tokens_to_ids ) + len(self.sp_model )





	def 	UpperCamelCase_  ( self					:				Union[str, Any] ):







							'''simple docstring'''
							_UpperCamelCase					:		Optional[Any] 				=   {self.convert_ids_to_tokens(lowerCamelCase__ ): i for i in range(self.vocab_size )}
							vocab.update(self.added_tokens_encoder )
							return vocab





	def 	UpperCamelCase_  ( self					:				Any ,lowerCamelCase__					:				str ):







							'''simple docstring'''
							return self.sp_model.encode(lowerCamelCase__ ,out_type=lowerCamelCase__ )





	def 	UpperCamelCase_  ( self					:				List[Any] ,lowerCamelCase__					:				Optional[Any] ):







							'''simple docstring'''
							if token in self.fairseq_tokens_to_ids:
													return self.fairseq_tokens_to_ids[token]
							elif self.sp_model.PieceToId(lowerCamelCase__ ) == 0:
													# Convert sentence piece unk token to fairseq unk token index
													return self.unk_token_id
							return self.fairseq_offset + self.sp_model.PieceToId(lowerCamelCase__ )





	def 	UpperCamelCase_  ( self					:				Tuple ,lowerCamelCase__					:				Dict ):







							'''simple docstring'''
							if index in self.fairseq_ids_to_tokens:
													return self.fairseq_ids_to_tokens[index]
							return self.sp_model.IdToPiece(index - self.fairseq_offset )





	def 	UpperCamelCase_  ( self					:				Optional[int] ,lowerCamelCase__					:				Optional[int] ):







							'''simple docstring'''
							_UpperCamelCase					:		Dict 				=   []
							_UpperCamelCase					:		Optional[int] 				=   ''
							_UpperCamelCase					:		Optional[Any] 				=   False
							for token in tokens:
													# make sure that special tokens are not decoded using sentencepiece model
													if token in self.all_special_tokens:
																			if not prev_is_special:
																									out_string += " "
																			out_string += self.sp_model.decode(lowerCamelCase__ ) + token
																			_UpperCamelCase					:		Union[str, Any] 				=   True
																			_UpperCamelCase					:		List[str] 				=   []
													else:
																			current_sub_tokens.append(lowerCamelCase__ )
																			_UpperCamelCase					:		Union[str, Any] 				=   False
							out_string += self.sp_model.decode(lowerCamelCase__ )
							return out_string.strip()





	def __getstate__( self					:				Dict ):







							'''simple docstring'''
							_UpperCamelCase					:		List[str] 				=   self.__dict__.copy()
							_UpperCamelCase					:		int 				=   None
							return state





	def __setstate__( self					:				Any ,lowerCamelCase__					:				Dict ):







							'''simple docstring'''
							_UpperCamelCase					:		Optional[Any] 				=   d

							# for backward compatibility
							if not hasattr(self ,'sp_model_kwargs' ):
													_UpperCamelCase					:		Optional[Any] 				=   {}

							_UpperCamelCase					:		Optional[int] 				=   spm.SentencePieceProcessor(**self.sp_model_kwargs )
							self.sp_model.Load(self.vocab_file )





	def 	UpperCamelCase_  ( self					:				Optional[int] ,lowerCamelCase__					:				str ,lowerCamelCase__					:				Optional[str] = None ):







							'''simple docstring'''
							if not os.path.isdir(lowerCamelCase__ ):
													logger.error(F'Vocabulary path ({save_directory}) should be a directory' )
													return
							_UpperCamelCase					:		List[Any] 				=   os.path.join(
							    lowerCamelCase__ ,(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'] )

							if os.path.abspath(self.vocab_file ) != os.path.abspath(lowerCamelCase__ ) and os.path.isfile(self.vocab_file ):
													copyfile(self.vocab_file ,lowerCamelCase__ )
							elif not os.path.isfile(self.vocab_file ):
													with open(lowerCamelCase__ ,'wb' ) as fi:
																			_UpperCamelCase					:		int 				=   self.sp_model.serialized_model_proto()
																			fi.write(lowerCamelCase__ )

							return (out_vocab_file,)






'''simple docstring'''


def 			snake_case_   (  SCREAMING_SNAKE_CASE__     ):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE :       str     		=      0
				for ch in input_str:
								_SCREAMING_SNAKE_CASE :       Optional[Any]     		=      ord(SCREAMING_SNAKE_CASE__     )
								_SCREAMING_SNAKE_CASE :       Union[str, Any]     		=      pow(2							,      SCREAMING_SNAKE_CASE__     )

								# If we already turned on bit for current character's unicode
								if bitmap >> ch_unicode & 1 == 1:
												return False
								bitmap |= ch_bit_index_on
				return True


if __name__ == "__main__":
				import doctest

				doctest.testmod()




