
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging


__magic_name__            =  logging.get_logger(__name__)

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

__magic_name__            =  {
    '''vocab_file''': {
        '''xlnet-base-cased''': '''https://huggingface.co/xlnet-base-cased/resolve/main/spiece.model''',
        '''xlnet-large-cased''': '''https://huggingface.co/xlnet-large-cased/resolve/main/spiece.model''',
    }
}

__magic_name__            =  {
    '''xlnet-base-cased''': None,
    '''xlnet-large-cased''': None,
}

# Segments (not really needed)
__magic_name__            =  0
__magic_name__            =  1
__magic_name__            =  2
__magic_name__            =  3
__magic_name__            =  4




class 					_SCREAMING_SNAKE_CASE  (      __UpperCamelCase ):
      _A						:		List[str]    	=     VOCAB_FILES_NAMES
      _A						:		str    	=     PRETRAINED_VOCAB_FILES_MAP
      _A						:		int    	=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      _A						:		int    	=     'left'
      def __init__(			self		,	lowerCamelCase		,	lowerCamelCase=False		,	lowerCamelCase=True		,	lowerCamelCase=False		,	lowerCamelCase="<s>"		,	lowerCamelCase="</s>"		,	lowerCamelCase="<unk>"		,	lowerCamelCase="<sep>"		,	lowerCamelCase="<pad>"		,	lowerCamelCase="<cls>"		,	lowerCamelCase="<mask>"		,	lowerCamelCase=["<eop>", "<eod>"]		,	lowerCamelCase = None		,	**lowerCamelCase		,	):
          # Mask token behave like a normal word, i.e. include the space before it
          snake_case__						=				AddedToken(lowerCamelCase		,	lstrip=lowerCamelCase		,	rstrip=lowerCamelCase ) if isinstance(lowerCamelCase		,	lowerCamelCase ) else mask_token

          snake_case__						=				{} if sp_model_kwargs is None else sp_model_kwargs

          super().__init__(
              do_lower_case=lowerCamelCase		,	remove_space=lowerCamelCase		,	keep_accents=lowerCamelCase		,	bos_token=lowerCamelCase		,	eos_token=lowerCamelCase		,	unk_token=lowerCamelCase		,	sep_token=lowerCamelCase		,	pad_token=lowerCamelCase		,	cls_token=lowerCamelCase		,	mask_token=lowerCamelCase		,	additional_special_tokens=lowerCamelCase		,	sp_model_kwargs=self.sp_model_kwargs		,	**lowerCamelCase		,	)

          snake_case__						=				3

          snake_case__						=				do_lower_case
          snake_case__						=				remove_space
          snake_case__						=				keep_accents
          snake_case__						=				vocab_file

          snake_case__						=				spm.SentencePieceProcessor(**self.sp_model_kwargs )
          self.sp_model.Load(lowerCamelCase )
      @property
      def A_			(			self ):
          return len(self.sp_model )
      def A_			(			self ):
          snake_case__						=				{self.convert_ids_to_tokens(lowerCamelCase ): i for i in range(self.vocab_size )}
          vocab.update(self.added_tokens_encoder )
          return vocab
      def __getstate__(			self ):
          snake_case__						=				self.__dict__.copy()
          snake_case__						=				None
          return state
      def __setstate__(			self		,	lowerCamelCase ):
          snake_case__						=				d

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

          snake_case__						=				spm.SentencePieceProcessor(**self.sp_model_kwargs )
          self.sp_model.Load(self.vocab_file )
      def A_			(			self		,	lowerCamelCase ):
          if self.remove_space:
              snake_case__						=				" ".join(inputs.strip().split() )
          else:
              snake_case__						=				inputs
          snake_case__						=				outputs.replace("``"		,	"\"" ).replace("''"		,	"\"" )

          if not self.keep_accents:
              snake_case__						=				unicodedata.normalize("NFKD"		,	lowerCamelCase )
              snake_case__						=				"".join([c for c in outputs if not unicodedata.combining(lowerCamelCase )] )
          if self.do_lower_case:
              snake_case__						=				outputs.lower()

          return outputs
      def A_			(			self		,	lowerCamelCase ):
          snake_case__						=				self.preprocess_text(lowerCamelCase )
          snake_case__						=				self.sp_model.encode(lowerCamelCase		,	out_type=lowerCamelCase )
          snake_case__						=				[]
          for piece in pieces:
              if len(lowerCamelCase ) > 1 and piece[-1] == str("," ) and piece[-2].isdigit():
                  snake_case__						=				self.sp_model.EncodeAsPieces(piece[:-1].replace(lowerCamelCase		,	"" ) )
                  if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
                      if len(cur_pieces[0] ) == 1:
                          snake_case__						=				cur_pieces[1:]
                      else:
                          snake_case__						=				cur_pieces[0][1:]
                  cur_pieces.append(piece[-1] )
                  new_pieces.extend(lowerCamelCase )
              else:
                  new_pieces.append(lowerCamelCase )

          return new_pieces
      def A_			(			self		,	lowerCamelCase ):
          return self.sp_model.PieceToId(lowerCamelCase )
      def A_			(			self		,	lowerCamelCase ):
          return self.sp_model.IdToPiece(lowerCamelCase )
      def A_			(			self		,	lowerCamelCase ):
          snake_case__						=				"".join(lowerCamelCase ).replace(lowerCamelCase		,	" " ).strip()
          return out_string
      def A_			(			self		,	lowerCamelCase		,	lowerCamelCase = False		,	lowerCamelCase = None		,	lowerCamelCase = True		,	**lowerCamelCase		,	):
          snake_case__						=				kwargs.pop("use_source_tokenizer"		,	lowerCamelCase )

          snake_case__						=				self.convert_ids_to_tokens(lowerCamelCase		,	skip_special_tokens=lowerCamelCase )

          # To avoid mixing byte-level and unicode for byte-level BPT
          # we need to build string separately for added tokens and byte-level tokens
          # cf. https://github.com/huggingface/transformers/issues/1133
          snake_case__						=				[]
          snake_case__						=				[]
          for token in filtered_tokens:
              if skip_special_tokens and token in self.all_special_ids:
                  continue
              if token in self.added_tokens_encoder:
                  if current_sub_text:
                      sub_texts.append(self.convert_tokens_to_string(lowerCamelCase ) )
                      snake_case__						=				[]
                  sub_texts.append(lowerCamelCase )
              else:
                  current_sub_text.append(lowerCamelCase )
          if current_sub_text:
              sub_texts.append(self.convert_tokens_to_string(lowerCamelCase ) )

          # Mimic the behavior of the Rust tokenizer:
          # By default, there are no spaces between special tokens
          snake_case__						=				"".join(lowerCamelCase )

          snake_case__						=				(
              clean_up_tokenization_spaces
              if clean_up_tokenization_spaces is not None
              else self.clean_up_tokenization_spaces
          )
          if clean_up_tokenization_spaces:
              snake_case__						=				self.clean_up_tokenization(lowerCamelCase )
              return clean_text
          else:
              return text
      def A_			(			self		,	lowerCamelCase		,	lowerCamelCase = None ):
          snake_case__						=				[self.sep_token_id]
          snake_case__						=				[self.cls_token_id]
          if token_ids_a is None:
              return token_ids_a + sep + cls
          return token_ids_a + sep + token_ids_a + sep + cls
      def A_			(			self		,	lowerCamelCase		,	lowerCamelCase = None		,	lowerCamelCase = False ):

          if already_has_special_tokens:
              return super().get_special_tokens_mask(
                  token_ids_a=lowerCamelCase		,	token_ids_a=lowerCamelCase		,	already_has_special_tokens=lowerCamelCase )

          if token_ids_a is not None:
              return ([0] * len(lowerCamelCase )) + [1] + ([0] * len(lowerCamelCase )) + [1, 1]
          return ([0] * len(lowerCamelCase )) + [1, 1]
      def A_			(			self		,	lowerCamelCase		,	lowerCamelCase = None ):
          snake_case__						=				[self.sep_token_id]
          snake_case__						=				[2]

          if token_ids_a is None:
              return len(token_ids_a + sep ) * [0] + cls_segment_id
          return len(token_ids_a + sep ) * [0] + len(token_ids_a + sep ) * [1] + cls_segment_id



      def A_			(			self		,	lowerCamelCase		,	lowerCamelCase = None ):
          if not os.path.isdir(lowerCamelCase ):
              logger.error(F"""Vocabulary path ({save_directory}) should be a directory""" )
              return
          snake_case__						=				os.path.join(
              lowerCamelCase		,	(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"] )

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

          return (out_vocab_file,)





from __future__ import annotations





def 	SCREAMING_SNAKE_CASE__    (      __lowerCAmelCase    ,		__lowerCAmelCase							):
    if len(__lowerCAmelCase							) == 0:
        return False
    snake_case__						=				len(__lowerCAmelCase							) // 2
    if a_list[midpoint] == item:
        return True
    if item < a_list[midpoint]:
        return binary_search(a_list[:midpoint]    ,		__lowerCAmelCase							)
    else:
        return binary_search(a_list[midpoint + 1 :]    ,		__lowerCAmelCase							)


if __name__ == "__main__":
     __magic_name__            =  input('''Enter numbers separated by comma:\n''').strip()
     __magic_name__            =  [int(item.strip()) for item in user_input.split(''',''')]
     __magic_name__            =  int(input('''Enter the number to be found in the list:\n''').strip())
     __magic_name__            =  '''''' if binary_search(sequence, target) else '''not '''
     print(F'''{target} was {not_str}found in {sequence}''')



