




'''simple docstring'''



from math import pow




def    lowercase__(       __UpperCamelCase: int	,__UpperCamelCase: int	,__UpperCamelCase: int	,__UpperCamelCase: int	,__UpperCamelCase: int	,):

      """simple docstring"""






      if current_sum == needed_sum:
            # If the sum of the powers is equal to needed_sum, then we have a solution.
            solutions_count += 1
            return current_sum, solutions_count

      SCREAMING_SNAKE_CASE					:	Dict   =		int(pow(__UpperCamelCase	,__UpperCamelCase  )  )
      if current_sum + i_to_n <= needed_sum:
            # If the sum of the powers is less than needed_sum, then continue adding powers.
            current_sum += i_to_n
            SCREAMING_SNAKE_CASE ,  SCREAMING_SNAKE_CASE					:	List[str]   =		backtrack(
                __UpperCamelCase	,__UpperCamelCase	,current_number + 1	,__UpperCamelCase	,__UpperCamelCase  )
            current_sum -= i_to_n
      if i_to_n < needed_sum:
            # If the power of i is less than needed_sum, then try with the next power.
            SCREAMING_SNAKE_CASE ,  SCREAMING_SNAKE_CASE					:	List[str]   =		backtrack(
                __UpperCamelCase	,__UpperCamelCase	,current_number + 1	,__UpperCamelCase	,__UpperCamelCase  )
      return current_sum, solutions_count




def    lowercase__(       __UpperCamelCase: int	,__UpperCamelCase: int  ):

      """simple docstring"""






      if not (1 <= needed_sum <= 10_00 and 2 <= power <= 10):
            raise ValueError(
                'Invalid input\n'
                'needed_sum must be between 1 and 1000, power between 2 and 10.'  )

      return backtrack(__UpperCamelCase	,__UpperCamelCase	,1	,0	,0  )[1]  # Return the solutions_count


if __name__ == "__main__":
      import doctest

      doctest.testmod()









"""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


SCREAMING_SNAKE_CASE__					=   "▁"

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

SCREAMING_SNAKE_CASE__					=   {
    "vocab_file": {"google/pegasus-xsum": "https://huggingface.co/google/pegasus-xsum/resolve/main/spiece.model"}
}

SCREAMING_SNAKE_CASE__					=   {
    "google/pegasus-xsum": 512,
}


SCREAMING_SNAKE_CASE__					=   logging.get_logger(__name__)

class 		lowercase					(					_UpperCAmelCase					):
      _SCREAMING_SNAKE_CASE					=      VOCAB_FILES_NAMES

      _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      ,						lowercase      ,						lowercase="<pad>"      ,						lowercase="</s>"      ,						lowercase="<unk>"      ,						lowercase="<mask_2>"      ,						lowercase="<mask_1>"      ,						lowercase=None      ,						lowercase=103      ,						lowercase = None      ,						**lowercase      ,						)		->     None:
            lowerCAmelCase  						=       offset
            if additional_special_tokens is not None:
                  if not isinstance(lowercase      ,						lowercase ):
                        raise TypeError(
                            f'additional_special_tokens should be of type {type(lowercase )}, but is'
                            f' {type(lowercase )}' )

                  lowerCAmelCase  						=       (
                      ([mask_token_sent] + additional_special_tokens)
                      if mask_token_sent not in additional_special_tokens and mask_token_sent is not None
                      else additional_special_tokens
                  )
                  # fill additional tokens with ..., <unk_token_102> in case not all additional tokens are already taken
                  additional_special_tokens_extended += [
                      f'<unk_{i}>' for i in range(len(lowercase )      ,						self.offset - 1 )
                  ]

                  if len(set(lowercase ) ) != len(lowercase ):
                        raise ValueError(
                            """Please make sure that the provided additional_special_tokens do not contain an incorrectly"""
                            f' shifted list of <unk_x> tokens. Found {additional_special_tokens_extended}.' )
                  lowerCAmelCase  						=       additional_special_tokens_extended
            else:
                  lowerCAmelCase  						=       [mask_token_sent] if mask_token_sent is not None else []
                  additional_special_tokens += [f'<unk_{i}>' for i in range(2      ,						self.offset )]

            lowerCAmelCase  						=       {} if sp_model_kwargs is None else sp_model_kwargs

            super().__init__(
                eos_token=lowercase      ,						unk_token=lowercase      ,						mask_token=lowercase      ,						pad_token=lowercase      ,						mask_token_sent=lowercase      ,						offset=lowercase      ,						additional_special_tokens=lowercase      ,						sp_model_kwargs=self.sp_model_kwargs      ,						**lowercase      ,						)
            lowerCAmelCase  						=       mask_token_sent
            lowerCAmelCase  						=       vocab_file
            lowerCAmelCase  						=       spm.SentencePieceProcessor(**self.sp_model_kwargs )
            self.sp_model.Load(lowercase )

            # add special tokens to encoder dict
            lowerCAmelCase  						=       {
                0: self.pad_token,
                1: self.eos_token,
            }

            if self.mask_token_sent is not None:
                  self.encoder.update(
                      {
                          2: self.mask_token_sent,
                          3: self.mask_token,
                      } )

            if self.offset > 0:
                  # entries 2-104 are only used for pretraining and called <mask_1>, <mask_2>, unk_2, ...unk_102
                  # mask_token_sent is already added to list -> so start at 1
                  self.encoder.update({i + 3: additional_special_tokens[i] for i in range(1      ,						self.offset - 1 )} )

            lowerCAmelCase  						=       {v: k for k, v in self.encoder.items()}





      @property
      def     _snake_case			(       self )		->     int:
            return len(self.sp_model ) + self.offset





      def     _snake_case			(       self )		->     Dict[str, int]:
            lowerCAmelCase  						=       {self.convert_ids_to_tokens(lowercase ): i for i in range(self.vocab_size )}
            vocab.update(self.added_tokens_encoder )
            return vocab





      def __getstate__(       self )		->     Optional[int]:
            lowerCAmelCase  						=       self.__dict__.copy()
            lowerCAmelCase  						=       None
            return state





      def __setstate__(       self      ,						lowercase )		->     List[Any]:
            lowerCAmelCase  						=       d

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

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





      def     _snake_case			(       self      ,						lowercase )		->     List[str]:
            return self.sp_model.encode(lowercase      ,						out_type=lowercase )





      def     _snake_case			(       self      ,						lowercase )		->     int:
            if token in self.decoder:
                  return self.decoder[token]
            elif token in self.added_tokens_decoder:
                  return self.added_tokens_decoder[token]
            lowerCAmelCase  						=       self.sp_model.piece_to_id(lowercase )
            return sp_id + self.offset





      def     _snake_case			(       self      ,						lowercase )		->     str:
            if index in self.encoder:
                  return self.encoder[index]
            elif index in self.added_tokens_encoder:
                  return self.added_tokens_encoder[index]
            else:
                  lowerCAmelCase  						=       self.sp_model.IdToPiece(index - self.offset )
            return token





      def     _snake_case			(       self      ,						lowercase )		->     Optional[int]:
            lowerCAmelCase  						=       []
            lowerCAmelCase  						=       """"""
            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(lowercase ) + token
                        lowerCAmelCase  						=       []
                  else:
                        current_sub_tokens.append(lowercase )
            out_string += self.sp_model.decode(lowercase )
            return out_string.strip()





      def     _snake_case			(       self      ,						lowercase=False )		->     Tuple:
            return 1





      def     _snake_case			(       self      ,						lowercase )		->     Tuple:
            lowerCAmelCase  						=       set(self.all_special_ids )  # call it once instead of inside list comp
            all_special_ids.remove(self.unk_token_id )  # <unk> is only sometimes special

            return [1 if x in all_special_ids else 0 for x in seq]





      def     _snake_case			(       self      ,						lowercase      ,						lowercase = None      ,						lowercase = False )		->     List[int]:
            if already_has_special_tokens:
                  return self._special_token_mask(lowercase )
            elif token_ids_a is None:
                  return self._special_token_mask(lowercase ) + [1]
            else:
                  return self._special_token_mask(token_ids_a + token_ids_a ) + [1]





      def     _snake_case			(       self      ,						lowercase      ,						lowercase=None )		->     List[int]:
            if token_ids_a is None:
                  return token_ids_a + [self.eos_token_id]
            # We don't expect to process pairs, but leave the pair logic for API consistency
            return token_ids_a + token_ids_a + [self.eos_token_id]





      def     _snake_case			(       self      ,						lowercase      ,						lowercase = None )		->     Tuple[str]:
            if not os.path.isdir(lowercase ):
                  logger.error(f'Vocabulary path ({save_directory}) should be a directory' )
                  return
            lowerCAmelCase  						=       os.path.join(
                lowercase      ,						(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""] )

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

            return (out_vocab_file,)






