


'''simple docstring'''




import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
       from .tokenization_camembert import CamembertTokenizer
else:
       _a   :   List[Any]												=   None


_a   :   Dict												=   logging.get_logger(__name__)

_a   :   List[str]												=   {"vocab_file": "sentencepiece.bpe.model", "tokenizer_file": "tokenizer.json"}

_a   :   Optional[Any]												=   {
    "vocab_file": {
        "camembert-base": "https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model",
    },
    "tokenizer_file": {
        "camembert-base": "https://huggingface.co/camembert-base/resolve/main/tokenizer.json",
    },
}

_a   :   Union[str, Any]												=   {
    "camembert-base": 512,
}

_a   :   List[str]												=   "▁"




class 			_lowercase (	__lowercase							):
   _SCREAMING_SNAKE_CASE  :  Dict          =	VOCAB_FILES_NAMES
   _SCREAMING_SNAKE_CASE  :  str          =	PRETRAINED_VOCAB_FILES_MAP
   _SCREAMING_SNAKE_CASE  :  Optional[Any]          =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   _SCREAMING_SNAKE_CASE  :  List[Any]          =	["input_ids", "attention_mask"]
   _SCREAMING_SNAKE_CASE  :  Optional[int]          =	CamembertTokenizer
   def __init__(						self       :      List[Any]       ,   SCREAMING_SNAKE_CASE_       :      Dict=None       ,   SCREAMING_SNAKE_CASE_       :      Union[str, Any]=None       ,   SCREAMING_SNAKE_CASE_       :      Union[str, Any]="<s>"       ,   SCREAMING_SNAKE_CASE_       :      List[str]="</s>"       ,   SCREAMING_SNAKE_CASE_       :      List[Any]="</s>"       ,   SCREAMING_SNAKE_CASE_       :      str="<s>"       ,   SCREAMING_SNAKE_CASE_       :      Any="<unk>"       ,   SCREAMING_SNAKE_CASE_       :      Dict="<pad>"       ,   SCREAMING_SNAKE_CASE_       :      List[Any]="<mask>"       ,   SCREAMING_SNAKE_CASE_       :      List[Any]=["<s>NOTUSED", "</s>NOTUSED"]       ,   **SCREAMING_SNAKE_CASE_       :      int       ,   ) ->							Dict:
        # Mask token behave like a normal word, i.e. include the space before it
        __snake_case           =						AddedToken(SCREAMING_SNAKE_CASE_       ,   lstrip=SCREAMING_SNAKE_CASE_       ,   rstrip=SCREAMING_SNAKE_CASE_      ) if isinstance(SCREAMING_SNAKE_CASE_       ,   SCREAMING_SNAKE_CASE_      ) else mask_token

        super().__init__(
            SCREAMING_SNAKE_CASE_       ,   tokenizer_file=SCREAMING_SNAKE_CASE_       ,   bos_token=SCREAMING_SNAKE_CASE_       ,   eos_token=SCREAMING_SNAKE_CASE_       ,   sep_token=SCREAMING_SNAKE_CASE_       ,   cls_token=SCREAMING_SNAKE_CASE_       ,   unk_token=SCREAMING_SNAKE_CASE_       ,   pad_token=SCREAMING_SNAKE_CASE_       ,   mask_token=SCREAMING_SNAKE_CASE_       ,   additional_special_tokens=SCREAMING_SNAKE_CASE_       ,   **SCREAMING_SNAKE_CASE_       ,   )

        __snake_case           =						vocab_file
        __snake_case           =						False if not self.vocab_file else True
   def a  (						self       :      str       ,   SCREAMING_SNAKE_CASE_       :      List[int]       ,   SCREAMING_SNAKE_CASE_       :      Optional[List[int]] = None      ) ->							List[int]:

        if token_ids_a is None:
             return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
        __snake_case           =						[self.cls_token_id]
        __snake_case           =						[self.sep_token_id]
        return cls + token_ids_a + sep + sep + token_ids_a + sep
   def a  (						self       :      Optional[Any]       ,   SCREAMING_SNAKE_CASE_       :      List[int]       ,   SCREAMING_SNAKE_CASE_       :      Optional[List[int]] = None      ) ->							List[int]:
        __snake_case           =						[self.sep_token_id]
        __snake_case           =						[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]





   def a  (						self       :      Optional[Any]       ,   SCREAMING_SNAKE_CASE_       :      str       ,   SCREAMING_SNAKE_CASE_       :      Optional[str] = None      ) ->							Tuple[str]:
        if not self.can_save_slow_tokenizer:
             raise ValueError(
                 'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
                 'tokenizer.'      )

        if not os.path.isdir(SCREAMING_SNAKE_CASE_      ):
             logger.error(f'Vocabulary path ({save_directory}) should be a directory'      )
             return
        __snake_case           =						os.path.join(
            SCREAMING_SNAKE_CASE_       ,   (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']      )

        if os.path.abspath(self.vocab_file      ) != os.path.abspath(SCREAMING_SNAKE_CASE_      ):
             copyfile(self.vocab_file       ,   SCREAMING_SNAKE_CASE_      )

        return (out_vocab_file,)












'''simple docstring'''



import warnings
from typing import Dict, List, Optional, Tuple

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


__UpperCamelCase   :							int         =   logging.get_logger(__name__)
class 				__SCREAMING_SNAKE_CASE							(				_lowerCAmelCase  ):
      __a	       =["input_ids", "attention_mask"]




      def __init__(	self			, lowerCamelCase="</s>"			, lowerCamelCase="<unk>"			, lowerCamelCase="<pad>"			, lowerCamelCase=125			, lowerCamelCase=None			, **lowerCamelCase			, )				->None:



         '''simple docstring'''
         # Add extra_ids to the special token list
         if extra_ids > 0 and additional_special_tokens is None:
            __a					  =     [F"""<extra_id_{i}>""" for i in range(lowerCamelCase   )]
         elif extra_ids > 0 and additional_special_tokens is not None:
            # Check that we have the right number of extra_id special tokens
            __a					  =     len(set(filter(lambda lowerCamelCase   : bool('extra_id' in str(lowerCamelCase   )   )			, lowerCamelCase   )   )   )
            if extra_tokens != extra_ids:
               raise ValueError(
                   F"""Both extra_ids ({extra_ids}) and additional_special_tokens ({additional_special_tokens}) are"""
                   ' provided to ByT5Tokenizer. In this case the additional_special_tokens must include the'
                   ' extra_ids tokens'   )

         __a					  =     AddedToken(lowerCamelCase			, lstrip=lowerCamelCase			, rstrip=lowerCamelCase   ) if isinstance(lowerCamelCase			, lowerCamelCase   ) else pad_token
         __a					  =     AddedToken(lowerCamelCase			, lstrip=lowerCamelCase			, rstrip=lowerCamelCase   ) if isinstance(lowerCamelCase			, lowerCamelCase   ) else eos_token
         __a					  =     AddedToken(lowerCamelCase			, lstrip=lowerCamelCase			, rstrip=lowerCamelCase   ) if isinstance(lowerCamelCase			, lowerCamelCase   ) else unk_token

         super().__init__(
             eos_token=lowerCamelCase			, unk_token=lowerCamelCase			, pad_token=lowerCamelCase			, extra_ids=lowerCamelCase			, additional_special_tokens=lowerCamelCase			, **lowerCamelCase			, )

         __a					  =     extra_ids

         __a					  =     2**8  # utf is 8 bits

         # define special tokens dict
         __a					  =     {
             self.pad_token: 0,
             self.eos_token: 1,
             self.unk_token: 2,
         }
         __a					  =     len(self.special_tokens_encoder   )
         __a					  =     len(lowerCamelCase   )
         for i, token in enumerate(lowerCamelCase   ):
            __a					  =     self.vocab_size + i - n
         __a					  =     {v: k for k, v in self.special_tokens_encoder.items()}




      @property
      def 			__UpperCamelCase				(	self   )				->Any:



         '''simple docstring'''
         return self._utf_vocab_size + self._num_special_tokens + self._extra_ids




      def 			__UpperCamelCase				(	self			, lowerCamelCase			, lowerCamelCase = None			, lowerCamelCase = 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   )

         # normal case: some special tokens
         if token_ids_a is None:
            return ([0] * len(lowerCamelCase   )) + [1]
         return ([0] * len(lowerCamelCase   )) + [1] + ([0] * len(lowerCamelCase   )) + [1]




      def 			__UpperCamelCase				(	self			, lowerCamelCase   )				->List[int]:



         '''simple docstring'''
         if len(lowerCamelCase   ) > 0 and token_ids[-1] == self.eos_token_id:
            warnings.warn(
                F"""This sequence already has {self.eos_token}. In future versions this behavior may lead to duplicated"""
                ' eos tokens being added.'   )
            return token_ids
         else:
            return token_ids + [self.eos_token_id]




      def 			__UpperCamelCase				(	self			, lowerCamelCase			, lowerCamelCase = None   )				->List[int]:



         '''simple docstring'''
         __a					  =     [self.eos_token_id]

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




      def 			__UpperCamelCase				(	self			, lowerCamelCase			, lowerCamelCase = None   )				->List[int]:



         '''simple docstring'''
         __a					  =     self._add_eos_if_not_present(lowerCamelCase   )
         if token_ids_a is None:
            return token_ids_a
         else:
            __a					  =     self._add_eos_if_not_present(lowerCamelCase   )
            return token_ids_a + token_ids_a




      def 			__UpperCamelCase				(	self			, lowerCamelCase   )				->List[str]:



         '''simple docstring'''
         __a					  =     [chr(lowerCamelCase   ) for i in text.encode('utf-8'   )]
         return tokens




      def 			__UpperCamelCase				(	self			, lowerCamelCase   )				->Optional[Any]:



         '''simple docstring'''
         if token in self.special_tokens_encoder:
            __a					  =     self.special_tokens_encoder[token]
         elif token in self.added_tokens_encoder:
            __a					  =     self.added_tokens_encoder[token]
         elif len(lowerCamelCase   ) != 1:
            __a					  =     self.unk_token_id
         else:
            __a					  =     ord(lowerCamelCase   ) + self._num_special_tokens
         return token_id




      def 			__UpperCamelCase				(	self			, lowerCamelCase   )				->Tuple:



         '''simple docstring'''
         if index in self.special_tokens_decoder:
            __a					  =     self.special_tokens_decoder[index]
         else:
            __a					  =     chr(index - self._num_special_tokens   )
         return token




      def 			__UpperCamelCase				(	self			, lowerCamelCase   )				->Optional[Any]:



         '''simple docstring'''
         __a					  =     B''
         for token in tokens:
            if token in self.special_tokens_decoder:
               __a					  =     self.special_tokens_decoder[token].encode('utf-8'   )
            elif token in self.added_tokens_decoder:
               __a					  =     self.special_tokens_decoder[token].encode('utf-8'   )
            elif token in self.special_tokens_encoder:
               __a					  =     token.encode('utf-8'   )
            elif token in self.added_tokens_encoder:
               __a					  =     token.encode('utf-8'   )
            else:
               __a					  =     bytes([ord(lowerCamelCase   )]   )
            bstring += tok_string
         __a					  =     bstring.decode('utf-8'			, errors='ignore'   )
         return string






      def 			__UpperCamelCase				(	self			, lowerCamelCase			, lowerCamelCase = None   )				->Tuple[str]:



         '''simple docstring'''
         return ()