
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_xlnet import XLNetTokenizer
else:
    lowerCamelCase  =None


lowerCamelCase  =logging.get_logger(__name__)

lowerCamelCase  ={"vocab_file": "spiece.model", "tokenizer_file": "tokenizer.json"}

lowerCamelCase  ={
    "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",
    },
    "tokenizer_file": {
        "xlnet-base-cased": "https://huggingface.co/xlnet-base-cased/resolve/main/tokenizer.json",
        "xlnet-large-cased": "https://huggingface.co/xlnet-large-cased/resolve/main/tokenizer.json",
    },
}

lowerCamelCase  ={
    "xlnet-base-cased": None,
    "xlnet-large-cased": None,
}

lowerCamelCase  ="▁"

# Segments (not really needed)
lowerCamelCase  =0
lowerCamelCase  =1
lowerCamelCase  =2
lowerCamelCase  =3
lowerCamelCase  =4




class 					_lowerCamelCase			(   UpperCamelCase_			):





     """simple docstring"""







     SCREAMING_SNAKE_CASE_		 =	VOCAB_FILES_NAMES
     SCREAMING_SNAKE_CASE_		 =	PRETRAINED_VOCAB_FILES_MAP
     SCREAMING_SNAKE_CASE_		 =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     SCREAMING_SNAKE_CASE_		 =	'''left'''
     SCREAMING_SNAKE_CASE_		 =	XLNetTokenizer






     def __init__(				self    ,    __SCREAMING_SNAKE_CASE=None    ,    __SCREAMING_SNAKE_CASE=None    ,    __SCREAMING_SNAKE_CASE=False    ,    __SCREAMING_SNAKE_CASE=True    ,    __SCREAMING_SNAKE_CASE=False    ,    __SCREAMING_SNAKE_CASE="<s>"    ,    __SCREAMING_SNAKE_CASE="</s>"    ,    __SCREAMING_SNAKE_CASE="<unk>"    ,    __SCREAMING_SNAKE_CASE="<sep>"    ,    __SCREAMING_SNAKE_CASE="<pad>"    ,    __SCREAMING_SNAKE_CASE="<cls>"    ,    __SCREAMING_SNAKE_CASE="<mask>"    ,    __SCREAMING_SNAKE_CASE=["<eop>", "<eod>"]    ,    **__SCREAMING_SNAKE_CASE    ,    )	-> Optional[int]:




           """simple docstring"""







           UpperCamelCase__     : Optional[Any]											=					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__(
               vocab_file=__SCREAMING_SNAKE_CASE    ,    tokenizer_file=__SCREAMING_SNAKE_CASE    ,    do_lower_case=__SCREAMING_SNAKE_CASE    ,    remove_space=__SCREAMING_SNAKE_CASE    ,    keep_accents=__SCREAMING_SNAKE_CASE    ,    bos_token=__SCREAMING_SNAKE_CASE    ,    eos_token=__SCREAMING_SNAKE_CASE    ,    unk_token=__SCREAMING_SNAKE_CASE    ,    sep_token=__SCREAMING_SNAKE_CASE    ,    pad_token=__SCREAMING_SNAKE_CASE    ,    cls_token=__SCREAMING_SNAKE_CASE    ,    mask_token=__SCREAMING_SNAKE_CASE    ,    additional_special_tokens=__SCREAMING_SNAKE_CASE    ,    **__SCREAMING_SNAKE_CASE    ,    )

           UpperCamelCase__     : Optional[int]											=					3
           UpperCamelCase__     : Any											=					do_lower_case
           UpperCamelCase__     : Tuple											=					remove_space
           UpperCamelCase__     : Optional[Any]											=					keep_accents
           UpperCamelCase__     : Optional[Any]											=					vocab_file
           UpperCamelCase__     : Any											=					False if not self.vocab_file else True






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




           """simple docstring"""







           UpperCamelCase__     : Any											=					[self.sep_token_id]
           UpperCamelCase__     : str											=					[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  __SCREAMING_SNAKE_CASE      (				self    ,    __SCREAMING_SNAKE_CASE    ,    __SCREAMING_SNAKE_CASE = None	)	-> List[int]:




           """simple docstring"""







           UpperCamelCase__     : str											=					[self.sep_token_id]
           UpperCamelCase__     : Optional[int]											=					[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  __SCREAMING_SNAKE_CASE      (				self    ,    __SCREAMING_SNAKE_CASE    ,    __SCREAMING_SNAKE_CASE = None	)	-> Tuple[str]:




           """simple docstring"""







           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
           UpperCamelCase__     : List[Any]											=					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,)




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

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


lowerCamelCase  =logging.get_logger(__name__)


lowerCamelCase  ="▁"

lowerCamelCase  ={"vocab_file": "spiece.model"}

lowerCamelCase  ={
    "vocab_file": {
        "google/reformer-crime-and-punishment": (
            "https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model"
        )
    }
}

lowerCamelCase  ={
    "google/reformer-crime-and-punishment": 5_2_4_2_8_8,
}




class 					_lowerCamelCase			(   UpperCamelCase_			):





     """simple docstring"""







     SCREAMING_SNAKE_CASE_		 =	VOCAB_FILES_NAMES
     SCREAMING_SNAKE_CASE_		 =	PRETRAINED_VOCAB_FILES_MAP
     SCREAMING_SNAKE_CASE_		 =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     SCREAMING_SNAKE_CASE_		 =	['''input_ids''', '''attention_mask''']






     def __init__(				self    ,    __SCREAMING_SNAKE_CASE    ,    __SCREAMING_SNAKE_CASE="</s>"    ,    __SCREAMING_SNAKE_CASE="<unk>"    ,    __SCREAMING_SNAKE_CASE=[]    ,    __SCREAMING_SNAKE_CASE = None    ,    **__SCREAMING_SNAKE_CASE    ,    )	-> None:




           """simple docstring"""







           UpperCamelCase__     : int											=					{} if sp_model_kwargs is None else sp_model_kwargs

           super().__init__(
               eos_token=__SCREAMING_SNAKE_CASE    ,    unk_token=__SCREAMING_SNAKE_CASE    ,    additional_special_tokens=__SCREAMING_SNAKE_CASE    ,    sp_model_kwargs=self.sp_model_kwargs    ,    **__SCREAMING_SNAKE_CASE    ,    )

           UpperCamelCase__     : Dict											=					vocab_file
           UpperCamelCase__     : Any											=					spm.SentencePieceProcessor(**self.sp_model_kwargs	)
           self.sp_model.Load(__SCREAMING_SNAKE_CASE	)






     @property
     def  __SCREAMING_SNAKE_CASE      (				self	)	-> List[Any]:




           """simple docstring"""







           return self.sp_model.get_piece_size()






     def  __SCREAMING_SNAKE_CASE      (				self	)	-> Dict[str, int]:




           """simple docstring"""







           UpperCamelCase__     : Tuple											=					{self.convert_ids_to_tokens(__SCREAMING_SNAKE_CASE	): i for i in range(self.vocab_size	)}
           vocab.update(self.added_tokens_encoder	)
           return vocab






     def __getstate__(				self	)	-> Any:




           """simple docstring"""







           UpperCamelCase__     : Dict											=					self.__dict__.copy()
           UpperCamelCase__     : int											=					None
           return state






     def __setstate__(				self    ,    __SCREAMING_SNAKE_CASE	)	-> str:




           """simple docstring"""







           UpperCamelCase__     : int											=					d

           # for backward compatibility
           if not hasattr(self    ,    '''sp_model_kwargs'''	):
                 UpperCamelCase__     : int											=					{}

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






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




           """simple docstring"""







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






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




           """simple docstring"""







           return self.sp_model.piece_to_id(__SCREAMING_SNAKE_CASE	)






     def  __SCREAMING_SNAKE_CASE      (				self    ,    __SCREAMING_SNAKE_CASE	)	-> List[Any]:




           """simple docstring"""







           if index < self.sp_model.get_piece_size():
                 UpperCamelCase__     : str											=					self.sp_model.IdToPiece(__SCREAMING_SNAKE_CASE	)
           return token






     def  __SCREAMING_SNAKE_CASE      (				self    ,    __SCREAMING_SNAKE_CASE	)	-> Dict:




           """simple docstring"""







           UpperCamelCase__     : List[str]											=					[]
           UpperCamelCase__     : Union[str, Any]											=					''''''
           for token in tokens:
                 # make sure that special tokens are not decoded using sentencepiece model
                 if token in self.all_special_tokens:
                       out_string += self.sp_model.decode(__SCREAMING_SNAKE_CASE	) + token
                       UpperCamelCase__     : str											=					[]
                 else:
                       current_sub_tokens.append(__SCREAMING_SNAKE_CASE	)
           out_string += self.sp_model.decode(__SCREAMING_SNAKE_CASE	)
           return out_string.strip()






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




           """simple docstring"""







           if not os.path.isdir(__SCREAMING_SNAKE_CASE	):
                 logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''	)
                 return
           UpperCamelCase__     : Optional[int]											=					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	) and os.path.isfile(self.vocab_file	):
                 copyfile(self.vocab_file    ,    __SCREAMING_SNAKE_CASE	)
           elif not os.path.isfile(self.vocab_file	):
                 with open(__SCREAMING_SNAKE_CASE    ,    '''wb'''	) as fi:
                       UpperCamelCase__     : int											=					self.sp_model.serialized_model_proto()
                       fi.write(__SCREAMING_SNAKE_CASE	)

           return (out_vocab_file,)


