






"""simple docstring"""





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


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


A__					: Optional[int]=	"▁"

A__					: Dict=	{"vocab_file": "spiece.model"}

A__					: Optional[int]=	{
    "vocab_file": {
        "google/reformer-crime-and-punishment": (
            "https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model"
        )
    }
}

A__					: Union[str, Any]=	{
    "google/reformer-crime-and-punishment": 52_42_88,
}
class    __lowerCamelCase    (  __lowerCAmelCase  ):
   a      :				List[str] 						=VOCAB_FILES_NAMES
   a      :				str 						=PRETRAINED_VOCAB_FILES_MAP
   a      :				List[str] 						=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   a      :				List[Any] 						=["""input_ids""", """attention_mask"""]

   def __init__(					self ,				snake_case_ ,				snake_case_="</s>" ,				snake_case_="<unk>" ,				snake_case_=[] ,				snake_case_ = None ,				**snake_case_ ,				)		->       None:
       UpperCamelCase__         =    {} if sp_model_kwargs is None else sp_model_kwargs

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

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

   @property
   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       Any:
       return self.sp_model.get_piece_size()

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       Dict[str, int]:
       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      )		->       List[str]:
       UpperCamelCase__         =    self.__dict__.copy()
       UpperCamelCase__         =    None
       return state

   def __setstate__(					self ,				snake_case_      )		->       List[str]:
       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 						SCREAMING_SNAKE_CASE__ (					self ,				snake_case_      )		->       List[str]:
       return self.sp_model.encode(_UpperCamelCase ,				out_type=_UpperCamelCase      )

   def 						SCREAMING_SNAKE_CASE__ (					self ,				snake_case_      )		->       Optional[int]:
       return self.sp_model.piece_to_id(_UpperCamelCase      )

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


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

   def 						SCREAMING_SNAKE_CASE__ (					self ,				snake_case_      )		->       List[Any]:
       UpperCamelCase__         =    []
       UpperCamelCase__         =    """"""
       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(_UpperCamelCase      ) + token
               UpperCamelCase__         =    []
           else:
               current_sub_tokens.append(_UpperCamelCase      )
       out_string += self.sp_model.decode(_UpperCamelCase      )
       return out_string.strip()







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


       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,)












"""simple docstring"""





from copy import deepcopy
class    __lowerCamelCase    :

   def __init__(					self ,				snake_case_ = None ,				snake_case_ = None      )		->       None:

       if arr is None and size is not None:
           UpperCamelCase__         =    size
           UpperCamelCase__         =    [0] * size
       elif arr is not None:
           self.init(snake_case_      )
       else:
           raise ValueError('Either arr or size must be specified'      )

   def 						SCREAMING_SNAKE_CASE__ (					self ,				snake_case_      )		->       None:
       UpperCamelCase__         =    len(snake_case_      )
       UpperCamelCase__         =    deepcopy(snake_case_      )
       for i in range(1 ,				self.size      ):
           UpperCamelCase__         =    self.next_(snake_case_      )
           if j < self.size:
               self.tree[j] += self.tree[i]

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       list[int]:
       UpperCamelCase__         =    self.tree[:]
       for i in range(self.size - 1 ,				0 ,				-1      ):
           UpperCamelCase__         =    self.next_(snake_case_      )
           if j < self.size:
               arr[j] -= arr[i]
       return arr

   @staticmethod
   def 						SCREAMING_SNAKE_CASE__ (					snake_case_      )		->       int:
       return index + (index & (-index))

   @staticmethod
   def 						SCREAMING_SNAKE_CASE__ (					snake_case_      )		->       int:
       return index - (index & (-index))

   def 						SCREAMING_SNAKE_CASE__ (					self ,				snake_case_ ,				snake_case_      )		->       None:
       if index == 0:
           self.tree[0] += value
           return
       while index < self.size:
           self.tree[index] += value
           UpperCamelCase__         =    self.next_(snake_case_      )

   def 						SCREAMING_SNAKE_CASE__ (					self ,				snake_case_ ,				snake_case_      )		->       None:
       self.add(snake_case_ ,				value - self.get(snake_case_      )      )

   def 						SCREAMING_SNAKE_CASE__ (					self ,				snake_case_      )		->       int:
       if right == 0:
           return 0
       UpperCamelCase__         =    self.tree[0]
       right -= 1  # make right inclusive
       while right > 0:
           result += self.tree[right]
           UpperCamelCase__         =    self.prev(snake_case_      )
       return result

   def 						SCREAMING_SNAKE_CASE__ (					self ,				snake_case_ ,				snake_case_      )		->       int:
       return self.prefix(snake_case_      ) - self.prefix(snake_case_      )

   def 						SCREAMING_SNAKE_CASE__ (					self ,				snake_case_      )		->       int:
       return self.query(snake_case_ ,				index + 1      )







   def 						SCREAMING_SNAKE_CASE__ (					self ,				snake_case_      )		->       int:
       value -= self.tree[0]
       if value < 0:
           return -1

       UpperCamelCase__         =    1  # Largest power of 2 <= size
       while j * 2 < self.size:
           j *= 2

       UpperCamelCase__         =    0

       while j > 0:
           if i + j < self.size and self.tree[i + j] <= value:
               value -= self.tree[i + j]
               i += j
           j //= 2
       return i


if __name__ == "__main__":
  import doctest

  doctest.testmod()




