
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 logging


lowerCamelCase  =logging.get_logger(__name__)
lowerCamelCase  ={"vocab_file": "spiece.model"}

lowerCamelCase  ={
    "vocab_file": {
        "albert-base-v1": "https://huggingface.co/albert-base-v1/resolve/main/spiece.model",
        "albert-large-v1": "https://huggingface.co/albert-large-v1/resolve/main/spiece.model",
        "albert-xlarge-v1": "https://huggingface.co/albert-xlarge-v1/resolve/main/spiece.model",
        "albert-xxlarge-v1": "https://huggingface.co/albert-xxlarge-v1/resolve/main/spiece.model",
        "albert-base-v2": "https://huggingface.co/albert-base-v2/resolve/main/spiece.model",
        "albert-large-v2": "https://huggingface.co/albert-large-v2/resolve/main/spiece.model",
        "albert-xlarge-v2": "https://huggingface.co/albert-xlarge-v2/resolve/main/spiece.model",
        "albert-xxlarge-v2": "https://huggingface.co/albert-xxlarge-v2/resolve/main/spiece.model",
    }
}

lowerCamelCase  ={
    "albert-base-v1": 5_1_2,
    "albert-large-v1": 5_1_2,
    "albert-xlarge-v1": 5_1_2,
    "albert-xxlarge-v1": 5_1_2,
    "albert-base-v2": 5_1_2,
    "albert-large-v2": 5_1_2,
    "albert-xlarge-v2": 5_1_2,
    "albert-xxlarge-v2": 5_1_2,
}

lowerCamelCase  ="▁"




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






     def __init__(				self    ,    __SCREAMING_SNAKE_CASE    ,    __SCREAMING_SNAKE_CASE=True    ,    __SCREAMING_SNAKE_CASE=True    ,    __SCREAMING_SNAKE_CASE=False    ,    __SCREAMING_SNAKE_CASE="[CLS]"    ,    __SCREAMING_SNAKE_CASE="[SEP]"    ,    __SCREAMING_SNAKE_CASE="<unk>"    ,    __SCREAMING_SNAKE_CASE="[SEP]"    ,    __SCREAMING_SNAKE_CASE="<pad>"    ,    __SCREAMING_SNAKE_CASE="[CLS]"    ,    __SCREAMING_SNAKE_CASE="[MASK]"    ,    __SCREAMING_SNAKE_CASE = None    ,    **__SCREAMING_SNAKE_CASE    ,    )	-> None:




           """simple docstring"""







           UpperCamelCase__     : List[str]											=					(
               AddedToken(__SCREAMING_SNAKE_CASE    ,    lstrip=__SCREAMING_SNAKE_CASE    ,    rstrip=__SCREAMING_SNAKE_CASE    ,    normalized=__SCREAMING_SNAKE_CASE	)
               if isinstance(__SCREAMING_SNAKE_CASE    ,    __SCREAMING_SNAKE_CASE	)
               else mask_token
           )

           UpperCamelCase__     : List[str]											=					{} if sp_model_kwargs is None else sp_model_kwargs

           super().__init__(
               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    ,    sp_model_kwargs=self.sp_model_kwargs    ,    **__SCREAMING_SNAKE_CASE    ,    )

           UpperCamelCase__     : List[str]											=					do_lower_case
           UpperCamelCase__     : Union[str, Any]											=					remove_space
           UpperCamelCase__     : Optional[Any]											=					keep_accents
           UpperCamelCase__     : Tuple											=					vocab_file

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






     @property
     def  __SCREAMING_SNAKE_CASE      (				self	)	-> int:




           """simple docstring"""







           return len(self.sp_model	)






     def  __SCREAMING_SNAKE_CASE      (				self	)	-> Tuple:




           """simple docstring"""







           UpperCamelCase__     : Union[str, Any]											=					{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	)	-> str:




           """simple docstring"""







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






     def __setstate__(				self    ,    __SCREAMING_SNAKE_CASE	)	-> Optional[int]:




           """simple docstring"""







           UpperCamelCase__     : str											=					d

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

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






     def  __SCREAMING_SNAKE_CASE      (				self    ,    __SCREAMING_SNAKE_CASE	)	-> Any:




           """simple docstring"""







           if self.remove_space:
                 UpperCamelCase__     : Optional[Any]											=					''' '''.join(inputs.strip().split()	)
           else:
                 UpperCamelCase__     : Any											=					inputs
           UpperCamelCase__     : Optional[int]											=					outputs.replace('''``'''    ,    '''"'''	).replace('''\'\''''    ,    '''"'''	)

           if not self.keep_accents:
                 UpperCamelCase__     : int											=					unicodedata.normalize('''NFKD'''    ,    __SCREAMING_SNAKE_CASE	)
                 UpperCamelCase__     : Dict											=					''''''.join([c for c in outputs if not unicodedata.combining(__SCREAMING_SNAKE_CASE	)]	)
           if self.do_lower_case:
                 UpperCamelCase__     : List[str]											=					outputs.lower()

           return outputs






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




           """simple docstring"""







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

           return new_pieces






     def  __SCREAMING_SNAKE_CASE      (				self    ,    __SCREAMING_SNAKE_CASE	)	-> Any:




           """simple docstring"""







           return self.sp_model.PieceToId(__SCREAMING_SNAKE_CASE	)






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




           """simple docstring"""







           return self.sp_model.IdToPiece(__SCREAMING_SNAKE_CASE	)






     def  __SCREAMING_SNAKE_CASE      (				self    ,    __SCREAMING_SNAKE_CASE	)	-> str:




           """simple docstring"""







           UpperCamelCase__     : Optional[Any]											=					[]
           UpperCamelCase__     : List[Any]											=					''''''
           UpperCamelCase__     : List[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(__SCREAMING_SNAKE_CASE	) + token
                       UpperCamelCase__     : Tuple											=					True
                       UpperCamelCase__     : Optional[Any]											=					[]
                 else:
                       current_sub_tokens.append(__SCREAMING_SNAKE_CASE	)
                       UpperCamelCase__     : List[str]											=					False
           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	)	-> List[int]:




           """simple docstring"""







           UpperCamelCase__     : Optional[int]											=					[self.sep_token_id]
           UpperCamelCase__     : Tuple											=					[self.cls_token_id]
           if token_ids_a is None:
                 return cls + token_ids_a + sep
           return cls + token_ids_a + sep + token_ids_a + sep






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




           """simple docstring"""







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

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






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




           """simple docstring"""







           UpperCamelCase__     : str											=					[self.sep_token_id]
           UpperCamelCase__     : str											=					[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	) * [0] + len(token_ids_a + sep	) * [1]






     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__     : Tuple											=					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__     : Any											=					self.sp_model.serialized_model_proto()
                       fi.write(__SCREAMING_SNAKE_CASE	)

           return (out_vocab_file,)




def 				SCREAMING_SNAKE_CASE_   (      UpperCamelCase__			,		UpperCamelCase__			,		UpperCamelCase__			,		UpperCamelCase__			,		UpperCamelCase__		):
      if index == number_of_items:
            return 0
      UpperCamelCase__     : str											=					0
      UpperCamelCase__     : Optional[Any]											=					0
      UpperCamelCase__     : int											=					knapsack(UpperCamelCase__			,		UpperCamelCase__			,		UpperCamelCase__			,		UpperCamelCase__			,		index + 1		)
      if weights[index] <= max_weight:
            UpperCamelCase__     : List[Any]											=					values[index] + knapsack(
                UpperCamelCase__			,		UpperCamelCase__			,		UpperCamelCase__			,		max_weight - weights[index]			,		index + 1		)
      return max(UpperCamelCase__			,		UpperCamelCase__		)


if __name__ == "__main__":
    import doctest

    doctest.testmod()


