

'''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


lowerCAmelCase__											=	logging.get_logger(__name__)

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

lowerCAmelCase__											=	{
    '''vocab_file''': {
        '''bert_for_seq_generation''': (
            '''https://huggingface.co/google/bert_for_seq_generation_L-24_bbc_encoder/resolve/main/spiece.model'''
        ),
    }
}

lowerCAmelCase__											=	{'''bert_for_seq_generation''': 512}






class 			lowercase_	(lowerCamelCase__      ):




  """simple docstring"""




  SCREAMING_SNAKE_CASE    :  List[Any]							=			VOCAB_FILES_NAMES
  SCREAMING_SNAKE_CASE    :  Dict							=			PRETRAINED_VOCAB_FILES_MAP
  SCREAMING_SNAKE_CASE    :  Optional[int]							=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  SCREAMING_SNAKE_CASE    :  List[int]							=			[]
  SCREAMING_SNAKE_CASE    :  Any							=			['input_ids', 'attention_mask']






  def __init__(      self   :     Optional[Any]					,lowercase__   :     Tuple					,lowercase__   :     Tuple="<s>"					,lowercase__   :     Union[str, Any]="</s>"					,lowercase__   :     str="<unk>"					,lowercase__   :     Tuple="<pad>"					,lowercase__   :     Union[str, Any]="<::::>"					,lowercase__   :     Optional[Dict[str, Any]] = None					,**lowercase__   :     Any					,):
   __lowercase							  = {} if sp_model_kwargs is None else sp_model_kwargs

   # Add extra_ids to the special token list
   super().__init__(
       bos_token=lowercase__					,eos_token=lowercase__					,unk_token=lowercase__					,pad_token=lowercase__					,sep_token=lowercase__					,sp_model_kwargs=self.sp_model_kwargs					,**lowercase__					,)

   __lowercase							  = vocab_file

   __lowercase							  = spm.SentencePieceProcessor(**self.sp_model_kwargs			)
   self.sp_model.Load(lowercase__			)






  @property
  def 					SCREAMING_SNAKE_CASE      (      self   :     Optional[int]			):
   return self.sp_model.get_piece_size()






  def 					SCREAMING_SNAKE_CASE      (      self   :     Union[str, Any]			):
   __lowercase							  = {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   :     str			):
   __lowercase							  = self.__dict__.copy()
   __lowercase							  = None
   return state






  def __setstate__(      self   :     Optional[int]					,lowercase__   :     Optional[Any]			):
   __lowercase							  = d

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

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






  def 					SCREAMING_SNAKE_CASE      (      self   :     str					,lowercase__   :     str			):
   return self.sp_model.encode(lowercase__					,out_type=lowercase__			)






  def 					SCREAMING_SNAKE_CASE      (      self   :     Tuple					,lowercase__   :     Union[str, Any]			):
   return self.sp_model.piece_to_id(lowercase__			)






  def 					SCREAMING_SNAKE_CASE      (      self   :     Any					,lowercase__   :     Tuple			):
   __lowercase							  = self.sp_model.IdToPiece(lowercase__			)
   return token






  def 					SCREAMING_SNAKE_CASE      (      self   :     Optional[int]					,lowercase__   :     int			):
   __lowercase							  = []
   __lowercase							  = ''''''
   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
     __lowercase							  = []
    else:
     current_sub_tokens.append(lowercase__			)
   out_string += self.sp_model.decode(lowercase__			)
   return out_string.strip()






  def 					SCREAMING_SNAKE_CASE      (      self   :     int					,lowercase__   :     str					,lowercase__   :     Optional[str] = None			):
   if not os.path.isdir(lowercase__			):
    logger.error(F"Vocabulary path ({save_directory}) should be a directory"			)
    return
   __lowercase							  = 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:
     __lowercase							  = self.sp_model.serialized_model_proto()
     fi.write(lowercase__			)

   return (out_vocab_file,)







"""simple docstring"""


def 					UpperCAmelCase__       (snake_case__							:					list    ):
  """simple docstring"""

  if len(snake_case__    ) <= 1:
    return [tuple(snake_case__    )]

  _snake_case							:		List[Any]								=  []

  def generate(snake_case__							:					int		,   snake_case__							:					list    ):
    if k == 1:
      res.append(tuple(arr[:]    )    )
      return

    generate(k - 1		,   snake_case__    )

    for i in range(k - 1    ):
      if k % 2 == 0:  # k is even
        _snake_case		,					_snake_case							:		Optional[Any]								=  arr[k - 1], arr[i]
      else:  # k is odd
        _snake_case		,					_snake_case							:		List[str]								=  arr[k - 1], arr[0]
      generate(k - 1		,   snake_case__    )

  generate(len(snake_case__    )		,   snake_case__    )
  return res


if __name__ == "__main__":
     A_						=				input('''Enter numbers separated by a comma:\n''').strip()
     A_						=				[int(item) for item in user_input.split(''',''')]
     print(heaps(arr))


