





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 			__A       (      lowerCamelCase__  ):




      """simple docstring"""







      UpperCAmelCase__						=      VOCAB_FILES_NAMES
      UpperCAmelCase__						=      PRETRAINED_VOCAB_FILES_MAP
      UpperCAmelCase__						=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      UpperCAmelCase__						=      []
      UpperCAmelCase__						=      ["""input_ids""", """attention_mask"""]


      def __init__(		self      ,							a__      ,							a__="<s>"      ,							a__="</s>"      ,							a__="<unk>"      ,							a__="<pad>"      ,							a__="<::::>"      ,							a__ = None      ,							**a__      ,							):



             """simple docstring"""





             _lowerCamelCase							:     str	=		{} if sp_model_kwargs is None else sp_model_kwargs

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

             _lowerCamelCase							:     List[Any]	=		vocab_file

             _lowerCamelCase							:     Optional[int]	=		spm.SentencePieceProcessor(**self.sp_model_kwargs)
             self.sp_model.Load(a__)


      @property
      def 				__snake_case			(		self):



             """simple docstring"""





             return self.sp_model.get_piece_size()


      def 				__snake_case			(		self):



             """simple docstring"""





             _lowerCamelCase							:     Optional[Any]	=		{self.convert_ids_to_tokens(a__): i for i in range(self.vocab_size)}
             vocab.update(self.added_tokens_encoder)
             return vocab


      def __getstate__(		self):



             """simple docstring"""





             _lowerCamelCase							:     Optional[int]	=		self.__dict__.copy()
             _lowerCamelCase							:     Optional[Any]	=		None
             return state


      def __setstate__(		self      ,							a__):



             """simple docstring"""





             _lowerCamelCase							:     List[Any]	=		d

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

             _lowerCamelCase							:     Optional[int]	=		spm.SentencePieceProcessor(**self.sp_model_kwargs)
             self.sp_model.Load(self.vocab_file)


      def 				__snake_case			(		self      ,							a__):



             """simple docstring"""





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


      def 				__snake_case			(		self      ,							a__):



             """simple docstring"""





             return self.sp_model.piece_to_id(a__)


      def 				__snake_case			(		self      ,							a__):



             """simple docstring"""





             _lowerCamelCase							:     Optional[int]	=		self.sp_model.IdToPiece(a__)
             return token


      def 				__snake_case			(		self      ,							a__):



             """simple docstring"""





             _lowerCamelCase							:     Dict	=		[]
             _lowerCamelCase							:     List[Any]	=		''''''
             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(a__) + token
                           _lowerCamelCase							:     Tuple	=		[]
                    else:
                           current_sub_tokens.append(a__)
             out_string += self.sp_model.decode(a__)
             return out_string.strip()



      def 				__snake_case			(		self      ,							a__      ,							a__ = None):



             """simple docstring"""





             if not os.path.isdir(a__):
                    logger.error(F"""Vocabulary path ({save_directory}) should be a directory""")
                    return
             _lowerCamelCase							:     int	=		os.path.join(
                 a__      ,							(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file'''])

             if os.path.abspath(self.vocab_file) != os.path.abspath(a__) and os.path.isfile(self.vocab_file):
                    copyfile(self.vocab_file      ,							a__)
             elif not os.path.isfile(self.vocab_file):
                    with open(a__      ,							'''wb''') as fi:
                           _lowerCamelCase							:     Tuple	=		self.sp_model.serialized_model_proto()
                           fi.write(a__)

             return (out_vocab_file,)








import math




def    __UpperCAmelCase(      lowercase_ ,    lowercase_      ):
       _lowerCamelCase							:     List[str]	=		len(lowercase_      )
       _lowerCamelCase							:     Optional[int]	=		int(math.floor(math.sqrt(lowercase_      )      )      )
       _lowerCamelCase							:     Tuple	=		0
       while arr[min(lowercase_ ,    lowercase_      ) - 1] < x:
              _lowerCamelCase							:     Optional[Any]	=		step
              step += int(math.floor(math.sqrt(lowercase_      )      )      )
              if prev >= n:
                     return -1

       while arr[prev] < x:
              _lowerCamelCase							:     int	=		prev + 1
              if prev == min(lowercase_ ,    lowercase_      ):
                     return -1
       if arr[prev] == x:
              return prev
       return -1


if __name__ == "__main__":
       _lowerCamelCase			       =      input('Enter numbers separated by a comma:\n').strip()
       _lowerCamelCase			       =      [int(item) for item in user_input.split(',')]
       _lowerCamelCase			       =      int(input('Enter the number to be searched:\n'))
       _lowerCamelCase			       =      jump_search(arr, x)
       if res == -1:
              print('Number not found!')
       else:
              print(F'''Number {x} is at index {res}''')

