code: 
  """simple docstring"""
  from typing import List, Optional, Tuple
  
  from tokenizers import pre_tokenizers
  
  from ...tokenization_utils_fast import PreTrainedTokenizerFast
  from ...utils import logging
  from .tokenization_clip import CLIPTokenizer
  
  
  _lowerCAmelCase					:Dict  =      logging.get_logger(__name__)
  
  _lowerCAmelCase					:Tuple  =      {'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}
  
  _lowerCAmelCase					:str  =      {
      'vocab_file': {
          'openai/clip-vit-base-patch32': 'https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/vocab.json',
      },
      'merges_file': {
          'openai/clip-vit-base-patch32': 'https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/merges.txt',
      },
      'tokenizer_file': {
          'openai/clip-vit-base-patch32': (
              'https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/tokenizer.json'
          ),
      },
  }
  
  _lowerCAmelCase					:Optional[int]  =      {
      'openai/clip-vit-base-patch32': 77,
  }
  class 							_UpperCAmelCase							(				lowercase_   ):
  
  
  
  
  
       '''simple docstring'''
  
  
  
       a__             =VOCAB_FILES_NAMES
       a__             =PRETRAINED_VOCAB_FILES_MAP
       a__             =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       a__             =["""input_ids""", """attention_mask"""]
       a__             =CLIPTokenizer
  
  
  
  
  
       def __init__(      self ,			A=None ,			A=None ,			A=None ,			A="<|endoftext|>" ,			A="<|startoftext|>" ,			A="<|endoftext|>" ,			A="<|endoftext|>" ,			**A ,			)							->      str:
           super().__init__(
               A ,			A ,			tokenizer_file=A ,			unk_token=A ,			bos_token=A ,			eos_token=A ,			pad_token=A ,			**A ,			)
  
           if not isinstance(self.backend_tokenizer.pre_tokenizer ,			pre_tokenizers.Sequence	):
               raise ValueError(
                   '''The `backend_tokenizer` provided does not match the expected format. The CLIP tokenizer has been'''
                   ''' heavily modified from transformers version 4.17.0. You need to convert the tokenizer you are using'''
                   ''' to be compatible with this version.The easiest way to do so is'''
                   ''' `CLIPTokenizerFast.from_pretrained("path_to_local_folder_or_hub_repo, from_slow=True)`. If you want'''
                   ''' to use your existing tokenizer, you will have to revert to a version prior to 4.17.0 of'''
                   ''' transformers.'''	)
  
           self._wrap_decode_method_backend_tokenizer()
  
  
  
  
  
       def 				__lowerCAmelCase			(      self	)							->      List[Any]:
           _UpperCAmelCase							:						Tuple       							=					self.backend_tokenizer.decode
  
           def new_decode_method(*A ,			**A	):
               _UpperCAmelCase							:						Optional[Any]       							=					orig_decode_method(*A ,			**A	)
               _UpperCAmelCase							:						List[Any]       							=					text.replace(self.backend_tokenizer.model.end_of_word_suffix ,			''' '''	).strip()
               return text
  
           _UpperCAmelCase							:						int       							=					new_decode_method
  
  
  
  
  
       def 				__lowerCAmelCase			(      self ,			A ,			A = None	)							->      Dict:
           _UpperCAmelCase							:						str       							=					[self.bos_token_id]
           _UpperCAmelCase							:						Dict       							=					[self.eos_token_id]
  
           if token_ids_a is None:
               return bos_token + token_ids_a + eos_token
           return bos_token + token_ids_a + eos_token + eos_token + token_ids_a + eos_token
  
  
  
  
  
       def 				__lowerCAmelCase			(      self ,			A ,			A = None	)							->      str:
           _UpperCAmelCase							:						Tuple       							=					[self.bos_token_id]
           _UpperCAmelCase							:						Tuple       							=					[self.eos_token_id]
  
           if token_ids_a is None:
               return len(bos_token + token_ids_a + eos_token	) * [0]
           return len(bos_token + token_ids_a + eos_token + eos_token + token_ids_a + eos_token	) * [0]
  
  
  
  
  
       def 				__lowerCAmelCase			(      self ,			A ,			A = None	)							->      List[Any]:
           _UpperCAmelCase							:						Optional[Any]       							=					self._tokenizer.model.save(A ,			name=A	)
           return tuple(A	)
  
  
  
style_context: 
  
  
  
  """simple docstring"""
  def 				lowerCamelCase_		(UpperCamelCase__	:	List[Any]  , UpperCamelCase__	:	int							):
      sequence.append(UpperCamelCase__							)
  
      _UpperCAmelCase							:						str       							=					0
      while sequence[index] != target:
          index += 1
  
      sequence.pop()
  
      if index == len(UpperCamelCase__							):
          return None
  
      return index
  
  
  if __name__ == "__main__":
    _lowerCAmelCase					:Dict  =      input('Enter numbers separated by comma:\n').strip()
    _lowerCAmelCase					:List[Any]  =      [int(item) for item in user_input.split(',')]
  
    _lowerCAmelCase					:int  =      input('Enter a single number to be found in the list:\n')
    _lowerCAmelCase					:List[Any]  =      int(target_input)
    _lowerCAmelCase					:Optional[int]  =      sentinel_linear_search(sequence, target)
    if result is not None:
      print(f"{target} found at positions: {result}")
    else:
      print('Not found')
  
  
  