'''simple docstring'''





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


SCREAMING_SNAKE_CASE_:     Optional[Any]  =logging.get_logger(__name__)

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

SCREAMING_SNAKE_CASE_:     int  ={
    'vocab_file': {
        'xlnet-base-cased': 'https://huggingface.co/xlnet-base-cased/resolve/main/spiece.model',
        'xlnet-large-cased': 'https://huggingface.co/xlnet-large-cased/resolve/main/spiece.model',
    }
}

SCREAMING_SNAKE_CASE_:     str  ={
    'xlnet-base-cased': None,
    'xlnet-large-cased': None,
}

# Segments (not really needed)
SCREAMING_SNAKE_CASE_:     Dict  =0
SCREAMING_SNAKE_CASE_:     Tuple  =1
SCREAMING_SNAKE_CASE_:     Optional[int]  =2
SCREAMING_SNAKE_CASE_:     List[str]  =3
SCREAMING_SNAKE_CASE_:     Optional[int]  =4




class        __A      ( lowerCAmelCase__	):
    a__       :						Dict          =  VOCAB_FILES_NAMES
    a__       :						Optional[Any]          =  PRETRAINED_VOCAB_FILES_MAP
    a__       :						Optional[int]          =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    a__       :						List[str]          =  """left"""



    def __init__(self    :    Tuple   ,			__a    :    int   ,			__a    :    Any=False   ,			__a    :    Tuple=True   ,			__a    :    Optional[Any]=False   ,			__a    :    Dict="<s>"   ,			__a    :    Dict="</s>"   ,			__a    :    int="<unk>"   ,			__a    :    Tuple="<sep>"   ,			__a    :    Any="<pad>"   ,			__a    :    Optional[Any]="<cls>"   ,			__a    :    Any="<mask>"   ,			__a    :    Optional[int]=["<eop>", "<eod>"]   ,			__a    :    int = None   ,			**__a    :    List[str]   ,			):
         # Mask token behave like a normal word, i.e. include the space before it
         UpperCAmelCase_           =   AddedToken(UpperCamelCase__   ,			lstrip=UpperCamelCase__   ,			rstrip=UpperCamelCase__ ) if isinstance(UpperCamelCase__   ,			UpperCamelCase__ ) else mask_token

         UpperCAmelCase_           =   {} if sp_model_kwargs is None else sp_model_kwargs

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

         UpperCAmelCase_           =   3

         UpperCAmelCase_           =   do_lower_case
         UpperCAmelCase_           =   remove_space
         UpperCAmelCase_           =   keep_accents
         UpperCAmelCase_           =   vocab_file

         UpperCAmelCase_           =   spm.SentencePieceProcessor(**self.sp_model_kwargs )
         self.sp_model.Load(UpperCamelCase__ )



    @property
    def 					_lowercase						(self    :    List[Any] ):
         return len(self.sp_model )



    def 					_lowercase						(self    :    Dict ):
         UpperCAmelCase_           =   {self.convert_ids_to_tokens(UpperCamelCase__ ): i for i in range(self.vocab_size )}
         vocab.update(self.added_tokens_encoder )
         return vocab



    def __getstate__(self    :    Dict ):
         UpperCAmelCase_           =   self.__dict__.copy()
         UpperCAmelCase_           =   None
         return state



    def __setstate__(self    :    Union[str, Any]   ,			__a    :    int ):
         UpperCAmelCase_           =   d

         # for backward compatibility
         if not hasattr(self   ,			"sp_model_kwargs" ):
              UpperCAmelCase_           =   {}

         UpperCAmelCase_           =   spm.SentencePieceProcessor(**self.sp_model_kwargs )
         self.sp_model.Load(self.vocab_file )



    def 					_lowercase						(self    :    Any   ,			__a    :    List[Any] ):
         if self.remove_space:
              UpperCAmelCase_           =   " ".join(inputs.strip().split() )
         else:
              UpperCAmelCase_           =   inputs
         UpperCAmelCase_           =   outputs.replace("``"   ,			"\"" ).replace("''"   ,			"\"" )

         if not self.keep_accents:
              UpperCAmelCase_           =   unicodedata.normalize("NFKD"   ,			UpperCamelCase__ )
              UpperCAmelCase_           =   "".join([c for c in outputs if not unicodedata.combining(UpperCamelCase__ )] )
         if self.do_lower_case:
              UpperCAmelCase_           =   outputs.lower()

         return outputs



    def 					_lowercase						(self    :    Optional[Any]   ,			__a    :    Any ):
         UpperCAmelCase_           =   self.preprocess_text(UpperCamelCase__ )
         UpperCAmelCase_           =   self.sp_model.encode(UpperCamelCase__   ,			out_type=UpperCamelCase__ )
         UpperCAmelCase_           =   []
         for piece in pieces:
              if len(UpperCamelCase__ ) > 1 and piece[-1] == str("," ) and piece[-2].isdigit():
                   UpperCAmelCase_           =   self.sp_model.EncodeAsPieces(piece[:-1].replace(UpperCamelCase__   ,			"" ) )
                   if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
                        if len(cur_pieces[0] ) == 1:
                             UpperCAmelCase_           =   cur_pieces[1:]
                        else:
                             UpperCAmelCase_           =   cur_pieces[0][1:]
                   cur_pieces.append(piece[-1] )
                   new_pieces.extend(UpperCamelCase__ )
              else:
                   new_pieces.append(UpperCamelCase__ )

         return new_pieces



    def 					_lowercase						(self    :    List[Any]   ,			__a    :    Union[str, Any] ):
         return self.sp_model.PieceToId(UpperCamelCase__ )



    def 					_lowercase						(self    :    List[str]   ,			__a    :    Any ):
         return self.sp_model.IdToPiece(UpperCamelCase__ )



    def 					_lowercase						(self    :    Any   ,			__a    :    int ):
         UpperCAmelCase_           =   "".join(UpperCamelCase__ ).replace(UpperCamelCase__   ,			" " ).strip()
         return out_string



    def 					_lowercase						(self    :    str   ,			__a    :    Union[str, Any]   ,			__a    :    str = False   ,			__a    :    Dict = None   ,			__a    :    str = True   ,			**__a    :    List[Any]   ,			):
         UpperCAmelCase_           =   kwargs.pop("use_source_tokenizer"   ,			UpperCamelCase__ )

         UpperCAmelCase_           =   self.convert_ids_to_tokens(UpperCamelCase__   ,			skip_special_tokens=UpperCamelCase__ )

         # To avoid mixing byte-level and unicode for byte-level BPT
         # we need to build string separately for added tokens and byte-level tokens
         # cf. https://github.com/huggingface/transformers/issues/1133
         UpperCAmelCase_           =   []
         UpperCAmelCase_           =   []
         for token in filtered_tokens:
              if skip_special_tokens and token in self.all_special_ids:
                   continue
              if token in self.added_tokens_encoder:
                   if current_sub_text:
                        sub_texts.append(self.convert_tokens_to_string(UpperCamelCase__ ) )
                        UpperCAmelCase_           =   []
                   sub_texts.append(UpperCamelCase__ )
              else:
                   current_sub_text.append(UpperCamelCase__ )
         if current_sub_text:
              sub_texts.append(self.convert_tokens_to_string(UpperCamelCase__ ) )

         # Mimic the behavior of the Rust tokenizer:
         # By default, there are no spaces between special tokens
         UpperCAmelCase_           =   "".join(UpperCamelCase__ )

         UpperCAmelCase_           =   (
             clean_up_tokenization_spaces
             if clean_up_tokenization_spaces is not None
             else self.clean_up_tokenization_spaces
         )
         if clean_up_tokenization_spaces:
              UpperCAmelCase_           =   self.clean_up_tokenization(UpperCamelCase__ )
              return clean_text
         else:
              return text



    def 					_lowercase						(self    :    Any   ,			__a    :    str   ,			__a    :    Tuple = None ):
         UpperCAmelCase_           =   [self.sep_token_id]
         UpperCAmelCase_           =   [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 					_lowercase						(self    :    int   ,			__a    :    List[str]   ,			__a    :    List[str] = None   ,			__a    :    Tuple = False ):

         if already_has_special_tokens:
              return super().get_special_tokens_mask(
                  token_ids_a=UpperCamelCase__   ,			token_ids_a=UpperCamelCase__   ,			already_has_special_tokens=UpperCamelCase__ )

         if token_ids_a is not None:
              return ([0] * len(UpperCamelCase__ )) + [1] + ([0] * len(UpperCamelCase__ )) + [1, 1]
         return ([0] * len(UpperCamelCase__ )) + [1, 1]



    def 					_lowercase						(self    :    int   ,			__a    :    int   ,			__a    :    Union[str, Any] = None ):
         UpperCAmelCase_           =   [self.sep_token_id]
         UpperCAmelCase_           =   [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 					_lowercase						(self    :    Optional[Any]   ,			__a    :    str   ,			__a    :    List[Any] = None ):
         if not os.path.isdir(UpperCamelCase__ ):
              logger.error(f"""Vocabulary path ({save_directory}) should be a directory""" )
              return
         UpperCAmelCase_           =   os.path.join(
             UpperCamelCase__   ,			(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"] )

         if os.path.abspath(self.vocab_file ) != os.path.abspath(UpperCamelCase__ ) and os.path.isfile(self.vocab_file ):
              copyfile(self.vocab_file   ,			UpperCamelCase__ )
         elif not os.path.isfile(self.vocab_file ):
              with open(UpperCamelCase__   ,			"wb" ) as fi:
                   UpperCAmelCase_           =   self.sp_model.serialized_model_proto()
                   fi.write(UpperCamelCase__ )

         return (out_vocab_file,)










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


SCREAMING_SNAKE_CASE__       :      Optional[Any]  =   logging.get_logger(__name__)

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

SCREAMING_SNAKE_CASE__       :      int  =   {
    'vocab_file': {
        'xlnet-base-cased': 'https://huggingface.co/xlnet-base-cased/resolve/main/spiece.model',
        'xlnet-large-cased': 'https://huggingface.co/xlnet-large-cased/resolve/main/spiece.model',
    }
}

SCREAMING_SNAKE_CASE__       :      str  =   {
    'xlnet-base-cased': None,
    'xlnet-large-cased': None,
}

# Segments (not really needed)
SCREAMING_SNAKE_CASE__       :      Dict  =   0
SCREAMING_SNAKE_CASE__       :      Tuple  =   1
SCREAMING_SNAKE_CASE__       :      Optional[int]  =   2
SCREAMING_SNAKE_CASE__       :      List[str]  =   3
SCREAMING_SNAKE_CASE__       :      Optional[int]  =   4




class 		UpperCamelCase__	(lowerCAmelCase__     ):

    '''simple docstring'''



    lowerCamelCase_      :	Dict	     =      VOCAB_FILES_NAMES
    lowerCamelCase_      :	Optional[Any]	     =      PRETRAINED_VOCAB_FILES_MAP
    lowerCamelCase_      :	Optional[int]	     =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    lowerCamelCase_      :	List[str]	     =      """left"""







    def __init__(    self     ,  UpperCamelCase__     ,  UpperCamelCase__=False     ,  UpperCamelCase__=True     ,  UpperCamelCase__=False     ,  UpperCamelCase__="<s>"     ,  UpperCamelCase__="</s>"     ,  UpperCamelCase__="<unk>"     ,  UpperCamelCase__="<sep>"     ,  UpperCamelCase__="<pad>"     ,  UpperCamelCase__="<cls>"     ,  UpperCamelCase__="<mask>"     ,  UpperCamelCase__=["<eop>", "<eod>"]     ,  UpperCamelCase__ = None     ,  **UpperCamelCase__     ,  )     ->      None:
           # Mask token behave like a normal word, i.e. include the space before it
           lowerCamelCase   :      str			 =					AddedToken(UpperCamelCase__     ,  lstrip=UpperCamelCase__     ,  rstrip=UpperCamelCase__     ) if isinstance(UpperCamelCase__     ,  UpperCamelCase__     ) else mask_token

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

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

           lowerCamelCase   :      Any			 =					3

           lowerCamelCase   :      Optional[Any]			 =					do_lower_case
           lowerCamelCase   :      List[Any]			 =					remove_space
           lowerCamelCase   :      str			 =					keep_accents
           lowerCamelCase   :      List[Any]			 =					vocab_file

           lowerCamelCase   :      int			 =					spm.SentencePieceProcessor(**self.sp_model_kwargs     )
           self.sp_model.Load(UpperCamelCase__     )







    @property
    def     _lowercase     (    self     )     ->      Optional[Any]:
           return len(self.sp_model     )







    def     _lowercase     (    self     )     ->      Optional[int]:
           lowerCamelCase   :      int			 =					{self.convert_ids_to_tokens(UpperCamelCase__     ): i for i in range(self.vocab_size     )}
           vocab.update(self.added_tokens_encoder     )
           return vocab







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







    def __setstate__(    self     ,  UpperCamelCase__     )     ->      int:
           lowerCamelCase   :      int			 =					d

           # for backward compatibility
           if not hasattr(self     ,  "sp_model_kwargs"     ):
                  lowerCamelCase   :      Any			 =					{}

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







    def     _lowercase     (    self     ,  UpperCamelCase__     )     ->      Any:
           if self.remove_space:
                  lowerCamelCase   :      Dict			 =					" ".join(inputs.strip().split()     )
           else:
                  lowerCamelCase   :      Union[str, Any]			 =					inputs
           lowerCamelCase   :      Optional[Any]			 =					outputs.replace("``"     ,  "\""     ).replace("''"     ,  "\""     )

           if not self.keep_accents:
                  lowerCamelCase   :      Optional[int]			 =					unicodedata.normalize("NFKD"     ,  UpperCamelCase__     )
                  lowerCamelCase   :      List[Any]			 =					"".join([c for c in outputs if not unicodedata.combining(UpperCamelCase__     )]     )
           if self.do_lower_case:
                  lowerCamelCase   :      List[str]			 =					outputs.lower()

           return outputs







    def     _lowercase     (    self     ,  UpperCamelCase__     )     ->      List[str]:
           lowerCamelCase   :      Optional[Any]			 =					self.preprocess_text(UpperCamelCase__     )
           lowerCamelCase   :      Dict			 =					self.sp_model.encode(UpperCamelCase__     ,  out_type=UpperCamelCase__     )
           lowerCamelCase   :      Dict			 =					[]
           for piece in pieces:
                  if len(UpperCamelCase__     ) > 1 and piece[-1] == str(","     ) and piece[-2].isdigit():
                         lowerCamelCase   :      List[Any]			 =					self.sp_model.EncodeAsPieces(piece[:-1].replace(UpperCamelCase__     ,  ""     )     )
                         if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
                                if len(cur_pieces[0]     ) == 1:
                                       lowerCamelCase   :      Union[str, Any]			 =					cur_pieces[1:]
                                else:
                                       lowerCamelCase   :      Optional[int]			 =					cur_pieces[0][1:]
                         cur_pieces.append(piece[-1]     )
                         new_pieces.extend(UpperCamelCase__     )
                  else:
                         new_pieces.append(UpperCamelCase__     )

           return new_pieces







    def     _lowercase     (    self     ,  UpperCamelCase__     )     ->      int:
           return self.sp_model.PieceToId(UpperCamelCase__     )







    def     _lowercase     (    self     ,  UpperCamelCase__     )     ->      Tuple:
           return self.sp_model.IdToPiece(UpperCamelCase__     )







    def     _lowercase     (    self     ,  UpperCamelCase__     )     ->      List[str]:
           lowerCamelCase   :      Union[str, Any]			 =					"".join(UpperCamelCase__     ).replace(UpperCamelCase__     ,  " "     ).strip()
           return out_string







    def     _lowercase     (    self     ,  UpperCamelCase__     ,  UpperCamelCase__ = False     ,  UpperCamelCase__ = None     ,  UpperCamelCase__ = True     ,  **UpperCamelCase__     ,  )     ->      str:
           lowerCamelCase   :      Optional[int]			 =					kwargs.pop("use_source_tokenizer"     ,  UpperCamelCase__     )

           lowerCamelCase   :      Optional[int]			 =					self.convert_ids_to_tokens(UpperCamelCase__     ,  skip_special_tokens=UpperCamelCase__     )

           # To avoid mixing byte-level and unicode for byte-level BPT
           # we need to build string separately for added tokens and byte-level tokens
           # cf. https://github.com/huggingface/transformers/issues/1133
           lowerCamelCase   :      Any			 =					[]
           lowerCamelCase   :      Any			 =					[]
           for token in filtered_tokens:
                  if skip_special_tokens and token in self.all_special_ids:
                         continue
                  if token in self.added_tokens_encoder:
                         if current_sub_text:
                                sub_texts.append(self.convert_tokens_to_string(UpperCamelCase__     )     )
                                lowerCamelCase   :      int			 =					[]
                         sub_texts.append(UpperCamelCase__     )
                  else:
                         current_sub_text.append(UpperCamelCase__     )
           if current_sub_text:
                  sub_texts.append(self.convert_tokens_to_string(UpperCamelCase__     )     )

           # Mimic the behavior of the Rust tokenizer:
           # By default, there are no spaces between special tokens
           lowerCamelCase   :      Union[str, Any]			 =					"".join(UpperCamelCase__     )

           lowerCamelCase   :      Tuple			 =					(
               clean_up_tokenization_spaces
               if clean_up_tokenization_spaces is not None
               else self.clean_up_tokenization_spaces
           )
           if clean_up_tokenization_spaces:
                  lowerCamelCase   :      int			 =					self.clean_up_tokenization(UpperCamelCase__     )
                  return clean_text
           else:
                  return text







    def     _lowercase     (    self     ,  UpperCamelCase__     ,  UpperCamelCase__ = None     )     ->      List[int]:
           lowerCamelCase   :      str			 =					[self.sep_token_id]
           lowerCamelCase   :      Optional[int]			 =					[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     _lowercase     (    self     ,  UpperCamelCase__     ,  UpperCamelCase__ = None     ,  UpperCamelCase__ = False     )     ->      List[int]:

           if already_has_special_tokens:
                  return super().get_special_tokens_mask(
                      token_ids_a=UpperCamelCase__     ,  token_ids_a=UpperCamelCase__     ,  already_has_special_tokens=UpperCamelCase__     )

           if token_ids_a is not None:
                  return ([0] * len(UpperCamelCase__     )) + [1] + ([0] * len(UpperCamelCase__     )) + [1, 1]
           return ([0] * len(UpperCamelCase__     )) + [1, 1]







    def     _lowercase     (    self     ,  UpperCamelCase__     ,  UpperCamelCase__ = None     )     ->      List[int]:
           lowerCamelCase   :      Any			 =					[self.sep_token_id]
           lowerCamelCase   :      List[str]			 =					[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     _lowercase     (    self     ,  UpperCamelCase__     ,  UpperCamelCase__ = None     )     ->      Tuple[str]:
           if not os.path.isdir(UpperCamelCase__     ):
                  logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''     )
                  return
           lowerCamelCase   :      Union[str, Any]			 =					os.path.join(
               UpperCamelCase__     ,  (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]     )

           if os.path.abspath(self.vocab_file     ) != os.path.abspath(UpperCamelCase__     ) and os.path.isfile(self.vocab_file     ):
                  copyfile(self.vocab_file     ,  UpperCamelCase__     )
           elif not os.path.isfile(self.vocab_file     ):
                  with open(UpperCamelCase__     ,  "wb"     ) as fi:
                         lowerCamelCase   :      str			 =					self.sp_model.serialized_model_proto()
                         fi.write(UpperCamelCase__     )

           return (out_vocab_file,)






