



import os
import unicodedata
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 SPIECE_UNDERLINE, logging


A__  :  List[Any]								=					logging.get_logger(__name__)

A__  :  Tuple								=					{'''vocab_file''': '''spiece.model'''}

A__  :  Tuple								=					{
    '''vocab_file''': {
        '''TsinghuaAI/CPM-Generate''': '''https://huggingface.co/TsinghuaAI/CPM-Generate/resolve/main/spiece.model''',
    }
}



class 				__snake_case						(     UpperCAmelCase__						):




							def __init__(       self     :       Union[str, Any]				,				A_     :       Union[str, Any]				,				A_     :       List[str]=False				,				A_     :       Any=True				,				A_     :       Tuple=False				,				A_     :       List[Any]="<s>"				,				A_     :       int="</s>"				,				A_     :       Optional[int]="<unk>"				,				A_     :       Any="<sep>"				,				A_     :       List[str]="<pad>"				,				A_     :       List[str]="<cls>"				,				A_     :       Optional[Any]="<mask>"				,				A_     :       Tuple=["<eop>", "<eod>"]				,				A_     :       Optional[Dict[str, Any]] = None				,				**A_     :       List[str]				,				):
									lowerCAmelCase_			:     List[str]									= AddedToken(lowerCamelCase__				,				lstrip=lowerCamelCase__				,				rstrip=lowerCamelCase__) if isinstance(lowerCamelCase__				,				lowerCamelCase__) else mask_token

									lowerCAmelCase_			:     Dict									= {} if sp_model_kwargs is None else sp_model_kwargs

									super().__init__(
									    do_lower_case=lowerCamelCase__				,				remove_space=lowerCamelCase__				,				keep_accents=lowerCamelCase__				,				bos_token=lowerCamelCase__				,				eos_token=lowerCamelCase__				,				unk_token=lowerCamelCase__				,				sep_token=lowerCamelCase__				,				pad_token=lowerCamelCase__				,				cls_token=lowerCamelCase__				,				mask_token=lowerCamelCase__				,				additional_special_tokens=lowerCamelCase__				,				sp_model_kwargs=self.sp_model_kwargs				,				**lowerCamelCase__				,				)

									lowerCAmelCase_			:     List[Any]									= 3

									lowerCAmelCase_			:     Optional[Any]									= do_lower_case
									lowerCAmelCase_			:     int									= remove_space
									lowerCAmelCase_			:     Any									= keep_accents
									lowerCAmelCase_			:     Any									= vocab_file

									lowerCAmelCase_			:     Optional[Any]									= spm.SentencePieceProcessor(**self.sp_model_kwargs)
									self.sp_model.Load(lowerCamelCase__)

									try:
											import jieba
									except ModuleNotFoundError as error:
											raise error.__class__(
											    '''You need to install jieba to use CpmTokenizer or CpmTokenizerFast. '''
											    '''See https://pypi.org/project/jieba/ for installation.''')
									lowerCAmelCase_			:     Any									= jieba
									lowerCAmelCase_			:     Union[str, Any]									= str.maketrans(''' \n'''				,				'''\u2582\u2583''')




							@property
							# Copied from transformers.models.xlnet.tokenization_xlnet.XLNetTokenizer.vocab_size
							def    UpperCAmelCase__			(       self     :       int):
									return len(self.sp_model)




							def    UpperCAmelCase__			(       self     :       str):
									lowerCAmelCase_			:     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 __getstate__(       self     :       Union[str, Any]):
									lowerCAmelCase_			:     Optional[int]									= self.__dict__.copy()
									lowerCAmelCase_			:     int									= None
									return state




							def __setstate__(       self     :       Union[str, Any]				,				A_     :       int):
									lowerCAmelCase_			:     Tuple									= d

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

									lowerCAmelCase_			:     str									= spm.SentencePieceProcessor(**self.sp_model_kwargs)
									self.sp_model.Load(self.vocab_file)




							def    UpperCAmelCase__			(       self     :       Tuple				,				A_     :       Union[str, Any]):







									if self.remove_space:
											lowerCAmelCase_			:     str									= " ".join(inputs.strip().split())
									else:
											lowerCAmelCase_			:     str									= inputs
									lowerCAmelCase_			:     str									= outputs.replace('''``'''				,				'''\"''').replace('''\'\''''				,				'''\"''')

									if not self.keep_accents:
											lowerCAmelCase_			:     List[str]									= unicodedata.normalize('''NFKD'''				,				lowerCamelCase__)
											lowerCAmelCase_			:     str									= "".join([c for c in outputs if not unicodedata.combining(lowerCamelCase__)])
									if self.do_lower_case:
											lowerCAmelCase_			:     Union[str, Any]									= outputs.lower()

									return outputs




							def    UpperCAmelCase__			(       self     :       Optional[Any]				,				A_     :       str):
									lowerCAmelCase_			:     Optional[Any]									= self.preprocess_text(lowerCamelCase__)
									lowerCAmelCase_			:     int									= self.sp_model.encode(lowerCamelCase__				,				out_type=lowerCamelCase__)
									lowerCAmelCase_			:     List[Any]									= []
									for piece in pieces:
											if len(lowerCamelCase__) > 1 and piece[-1] == str(''',''') and piece[-2].isdigit():
													lowerCAmelCase_			:     Dict									= self.sp_model.EncodeAsPieces(piece[:-1].replace(lowerCamelCase__				,				''''''))
													if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
															if len(cur_pieces[0]) == 1:
																	lowerCAmelCase_			:     Tuple									= cur_pieces[1:]
															else:
																	lowerCAmelCase_			:     str									= cur_pieces[0][1:]
													cur_pieces.append(piece[-1])
													new_pieces.extend(lowerCamelCase__)
											else:
													new_pieces.append(lowerCamelCase__)

									return new_pieces




							def    UpperCAmelCase__			(       self     :       int				,				A_     :       Optional[int]):
									return self.sp_model.PieceToId(lowerCamelCase__)




							def    UpperCAmelCase__			(       self     :       Tuple				,				A_     :       Any):
									return self.sp_model.IdToPiece(lowerCamelCase__)




							def    UpperCAmelCase__			(       self     :       int				,				A_     :       Union[str, Any]):
									lowerCAmelCase_			:     List[Any]									= "".join(lowerCamelCase__).replace(lowerCamelCase__				,				''' ''').strip()
									return out_string




							def    UpperCAmelCase__			(       self     :       str				,				A_     :       List[int]				,				A_     :       Optional[List[int]] = None):
									lowerCAmelCase_			:     Dict									= [self.sep_token_id]
									lowerCAmelCase_			:     Tuple									= [self.cls_token_id]
									if token_ids_a is None:
											return token_ids_a + sep + cls
									return token_ids_a + sep + token_ids_a + sep + cls




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







									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 not None:
											return ([0] * len(lowerCamelCase__)) + [1] + ([0] * len(lowerCamelCase__)) + [1, 1]
									return ([0] * len(lowerCamelCase__)) + [1, 1]




							def    UpperCAmelCase__			(       self     :       str				,				A_     :       List[int]				,				A_     :       Optional[List[int]] = None):
									lowerCAmelCase_			:     List[Any]									= [self.sep_token_id]
									lowerCAmelCase_			:     List[Any]									= [2]

									if token_ids_a is None:
											return len(token_ids_a + sep) * [0] + cls_segment_id
									return len(token_ids_a + sep) * [0] + len(token_ids_a + sep) * [1] + cls_segment_id




							def    UpperCAmelCase__			(       self     :       Optional[int]				,				A_     :       str				,				A_     :       Optional[str] = None):







									if not os.path.isdir(lowerCamelCase__):
											logger.error(F"""Vocabulary path ({save_directory}) should be a directory""")
											return
									lowerCAmelCase_			:     Dict									= 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:
													lowerCAmelCase_			:     int									= self.sp_model.serialized_model_proto()
													fi.write(lowerCamelCase__)

									return (out_vocab_file,)







							def    UpperCAmelCase__			(       self     :       str				,				*A_     :       Tuple				,				**A_     :       str):
									lowerCAmelCase_			:     List[Any]									= super()._decode(*lowerCamelCase__				,				**lowerCamelCase__)
									lowerCAmelCase_			:     Union[str, Any]									= text.replace(''' '''				,				'''''').replace('''\u2582'''				,				''' ''').replace('''\u2583'''				,				'''\n''')
									return text









'''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


lowerCamelCase__					=   logging.get_logger(__name__)

lowerCamelCase__					=   {'vocab_file': 'sentencepiece.bpe.model'}

lowerCamelCase__					=   {
    'vocab_file': {
        'moussaKam/mbarthez': 'https://huggingface.co/moussaKam/mbarthez/resolve/main/sentencepiece.bpe.model',
        'moussaKam/barthez': 'https://huggingface.co/moussaKam/barthez/resolve/main/sentencepiece.bpe.model',
        'moussaKam/barthez-orangesum-title': (
            'https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/sentencepiece.bpe.model'
        ),
    },
}

lowerCamelCase__					=   {
    'moussaKam/mbarthez': 1_024,
    'moussaKam/barthez': 1_024,
    'moussaKam/barthez-orangesum-title': 1_024,
}

lowerCamelCase__					=   '▁'






class 		lowerCAmelCase__	(	UpperCAmelCase__		):
			lowerCAmelCase       :		Any				      =   VOCAB_FILES_NAMES
			lowerCAmelCase       :		Any				      =   PRETRAINED_VOCAB_FILES_MAP
			lowerCAmelCase       :		Union[str, Any]				      =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCAmelCase       :		int				      =   ["input_ids", "attention_mask"]




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



					'''simple docstring'''







					_UpperCAmelCase						:				Dict	    =					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__		,     sp_model_kwargs=self.sp_model_kwargs		,     **lowerCamelCase__		,     )

					_UpperCAmelCase						:				Union[str, Any]	    =					vocab_file
					_UpperCAmelCase						:				Dict	    =					spm.SentencePieceProcessor(**self.sp_model_kwargs       )
					self.sp_model.Load(str(lowerCamelCase__       )       )

					_UpperCAmelCase						:				Optional[int]	    =					{"<s>": 0, "<pad>": 1, "</s>": 2, "<unk>": 3}

					_UpperCAmelCase						:				List[str]	    =					len(self.sp_model       ) - 1
					_UpperCAmelCase						:				List[str]	    =					{v: k for k, v in self.fairseq_tokens_to_ids.items()}




			def 							lowerCAmelCase__			(						self     :   Dict		,     lowerCamelCase__     :   List[int]		,     lowerCamelCase__     :   Optional[List[int]] = None       )      ->List[int]:



					'''simple docstring'''







					if token_ids_a is None:
							return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
					_UpperCAmelCase						:				Union[str, Any]	    =					[self.cls_token_id]
					_UpperCAmelCase						:				str	    =					[self.sep_token_id]
					return cls + token_ids_a + sep + sep + token_ids_a + sep




			def 							lowerCAmelCase__			(						self     :   int		,     lowerCamelCase__     :   List[int]		,     lowerCamelCase__     :   Optional[List[int]] = None		,     lowerCamelCase__     :   bool = False       )      ->List[int]:



					'''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 							lowerCAmelCase__			(						self     :   List[str]		,     lowerCamelCase__     :   List[int]		,     lowerCamelCase__     :   Optional[List[int]] = None       )      ->List[int]:



					'''simple docstring'''







					_UpperCAmelCase						:				Optional[int]	    =					[self.sep_token_id]
					_UpperCAmelCase						:				Optional[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 							lowerCAmelCase__			(						self     :   List[Any]       )      ->List[str]:



					'''simple docstring'''







					return len(self.sp_model       )




			def 							lowerCAmelCase__			(						self     :   int       )      ->int:



					'''simple docstring'''







					_UpperCAmelCase						:				List[Any]	    =					{self.convert_ids_to_tokens(lowerCamelCase__       ): i for i in range(self.vocab_size       )}
					vocab.update(self.added_tokens_encoder       )
					return vocab




			def 							lowerCAmelCase__			(						self     :   int		,     lowerCamelCase__     :   str       )      ->List[str]:



					'''simple docstring'''







					return self.sp_model.encode(lowerCamelCase__		,     out_type=lowerCamelCase__       )




			def 							lowerCAmelCase__			(						self     :   Dict		,     lowerCamelCase__     :   Union[str, Any]       )      ->List[Any]:



					'''simple docstring'''







					if token in self.fairseq_tokens_to_ids:
							return self.fairseq_tokens_to_ids[token]
					_UpperCAmelCase						:				Optional[Any]	    =					self.sp_model.PieceToId(lowerCamelCase__       )

					return spm_id if spm_id else self.unk_token_id




			def 							lowerCAmelCase__			(						self     :   str		,     lowerCamelCase__     :   Any       )      ->Optional[Any]:



					'''simple docstring'''







					if index in self.fairseq_ids_to_tokens:
							return self.fairseq_ids_to_tokens[index]
					return self.sp_model.IdToPiece(lowerCamelCase__       )




			def 							lowerCAmelCase__			(						self     :   Any		,     lowerCamelCase__     :   List[Any]       )      ->Optional[int]:



					'''simple docstring'''







					_UpperCAmelCase						:				Union[str, Any]	    =					[]
					_UpperCAmelCase						:				Optional[Any]	    =					""
					_UpperCAmelCase						:				Optional[int]	    =					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						:				Union[str, Any]	    =					[]
							else:
									current_sub_tokens.append(lowerCamelCase__       )
									_UpperCAmelCase						:				int	    =					False
					out_string += self.sp_model.decode(lowerCamelCase__       )
					return out_string.strip()




			def __getstate__(						self     :   Dict       )      ->List[Any]:



					'''simple docstring'''







					_UpperCAmelCase						:				List[str]	    =					self.__dict__.copy()
					_UpperCAmelCase						:				Optional[int]	    =					None
					return state




			def __setstate__(						self     :   Any		,     lowerCamelCase__     :   Dict       )      ->Tuple:



					'''simple docstring'''







					_UpperCAmelCase						:				Dict	    =					d

					# for backward compatibility
					if not hasattr(self		,     "sp_model_kwargs"       ):
							_UpperCAmelCase						:				List[Any]	    =					{}

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






			def 							lowerCAmelCase__			(						self     :   Optional[Any]		,     lowerCamelCase__     :   str		,     lowerCamelCase__     :   Optional[str] = None       )      ->Tuple[str]:



					'''simple docstring'''







					if not os.path.isdir(lowerCamelCase__       ):
							logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""       )
							return
					_UpperCAmelCase						:				Union[str, 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						:				Dict	    =					self.sp_model.serialized_model_proto()
									fi.write(lowerCamelCase__       )

					return (out_vocab_file,)



