
"""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	)







"""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')


