
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


_snake_case      = logging.get_logger(__name__)


_snake_case      = '''▁'''

_snake_case      = {'''vocab_file''': '''spiece.model'''}

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

_snake_case      = {
    '''google/reformer-crime-and-punishment''': 524_288,
}
class       _lowerCAmelCase  (		__magic_name__							):

 """simple docstring"""
 SCREAMING_SNAKE_CASE_				:					int       						=VOCAB_FILES_NAMES
 SCREAMING_SNAKE_CASE_				:					Any       						=PRETRAINED_VOCAB_FILES_MAP
 SCREAMING_SNAKE_CASE_				:					Dict       						=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 SCREAMING_SNAKE_CASE_				:					Any       						=["input_ids", "attention_mask"]

 def __init__(						self			:			str					, SCREAMING_SNAKE_CASE__			:			Union[str, Any]					, SCREAMING_SNAKE_CASE__			:			str="</s>"					, SCREAMING_SNAKE_CASE__			:			Optional[Any]="<unk>"					, SCREAMING_SNAKE_CASE__			:			Any=[]					, SCREAMING_SNAKE_CASE__			:			Optional[Dict[str, Any]] = None					, **SCREAMING_SNAKE_CASE__			:			Dict					, ):






      """simple docstring"""



      UpperCamelCase						    =					{} 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						    =					vocab_file
      UpperCamelCase						    =					spm.SentencePieceProcessor(**self.sp_model_kwargs   )
      self.sp_model.Load(SCREAMING_SNAKE_CASE__   )

 @property
 def      __lowerCAmelCase  (						self			:			Tuple   ):






      """simple docstring"""



      return self.sp_model.get_piece_size()

 def      __lowerCAmelCase  (						self			:			Tuple   ):






      """simple docstring"""



      UpperCamelCase						    =					{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			:			List[Any]   ):






      """simple docstring"""



      UpperCamelCase						    =					self.__dict__.copy()
      UpperCamelCase						    =					None
      return state

 def __setstate__(						self			:			Optional[int]					, SCREAMING_SNAKE_CASE__			:			int   ):






      """simple docstring"""



      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      __lowerCAmelCase  (						self			:			Any					, SCREAMING_SNAKE_CASE__			:			str   ):






      """simple docstring"""



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

 def      __lowerCAmelCase  (						self			:			Tuple					, SCREAMING_SNAKE_CASE__			:			Tuple   ):






      """simple docstring"""



      return self.sp_model.piece_to_id(SCREAMING_SNAKE_CASE__   )

 def      __lowerCAmelCase  (						self			:			List[str]					, SCREAMING_SNAKE_CASE__			:			str   ):






      """simple docstring"""



      if index < self.sp_model.get_piece_size():
           UpperCamelCase						    =					self.sp_model.IdToPiece(SCREAMING_SNAKE_CASE__   )
      return token

 def      __lowerCAmelCase  (						self			:			Dict					, SCREAMING_SNAKE_CASE__			:			int   ):






      """simple docstring"""



      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(SCREAMING_SNAKE_CASE__   ) + token
                UpperCamelCase						    =					[]
           else:
                current_sub_tokens.append(SCREAMING_SNAKE_CASE__   )
      out_string += self.sp_model.decode(SCREAMING_SNAKE_CASE__   )
      return out_string.strip()






 def      __lowerCAmelCase  (						self			:			Optional[Any]					, SCREAMING_SNAKE_CASE__			:			str					, SCREAMING_SNAKE_CASE__			:			Optional[str] = None   ):






      """simple docstring"""



      if not os.path.isdir(SCREAMING_SNAKE_CASE__   ):
           logger.error(F'Vocabulary path ({save_directory}) should be a directory'   )
           return
      UpperCamelCase						    =					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						    =					self.sp_model.serialized_model_proto()
                fi.write(SCREAMING_SNAKE_CASE__   )

      return (out_vocab_file,)




def  __lowerCamelCase					( _lowercase = 50000000			)       ->      int:
     UpperCamelCase						    =					set()
     UpperCamelCase						    =					int((limit - 24) ** (1 / 2)			)

     UpperCamelCase						    =					set(range(3						,     prime_square_limit + 1						,     2			)			)
     primes.add(2			)
     for p in range(3						,     prime_square_limit + 1						,     2			):
          if p not in primes:
               continue
          primes.difference_update(set(range(p * p						,     prime_square_limit + 1						,     _lowercase			)			)			)

     for primea in primes:
          UpperCamelCase						    =					primea * primea
          for primea in primes:
               UpperCamelCase						    =					primea * primea * primea
               if square + cube >= limit - 16:
                    break
               for primea in primes:
                    UpperCamelCase						    =					primea * primea * primea * primea
                    UpperCamelCase						    =					square + cube + tetr
                    if total >= limit:
                         break
                    ret.add(_lowercase			)

     return len(_lowercase			)


if __name__ == "__main__":
 print(F"{solution() = }")


