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
  
  
  _UpperCAmelCase   :      str 						=  logging.get_logger(__name__)
  
  _UpperCAmelCase   :      List[str] 						=  {"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}
  
  _UpperCAmelCase   :      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"""
          ),
      },
  }
  
  _UpperCAmelCase   :      Dict 						=  {
      """openai/clip-vit-base-patch32""": 77,
  }
  
  class 			UpperCAmelCase				(					a_ ):
  
  
  
  
  
  		"""simple docstring"""
  
  
  
  
  
  		A__  :   List[Any]          =    VOCAB_FILES_NAMES
  		A__  :   str          =    PRETRAINED_VOCAB_FILES_MAP
  		A__  :   List[Any]          =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  		A__  :   Tuple          =    ['input_ids', 'attention_mask']
  		A__  :   List[str]          =    CLIPTokenizer
  		def __init__(    self  ,					_snake_case=None  ,					_snake_case=None  ,					_snake_case=None  ,					_snake_case="<|endoftext|>"  ,					_snake_case="<|startoftext|>"  ,					_snake_case="<|endoftext|>"  ,					_snake_case="<|endoftext|>"  ,					**_snake_case  ,					)				->    Union[str, Any]:
  				super().__init__(
  				    _snake_case  ,					_snake_case  ,					tokenizer_file=_snake_case  ,					unk_token=_snake_case  ,					bos_token=_snake_case  ,					eos_token=_snake_case  ,					pad_token=_snake_case  ,					**_snake_case  ,					)
  
  				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 _lowercase  (    self     )				->    int:
  				_UpperCamelCase       : Optional[Any]    =      self.backend_tokenizer.decode
  
  				def new_decode_method(*_snake_case  ,					**_snake_case     ):
  						_UpperCamelCase       : Optional[int]    =      orig_decode_method(*_snake_case  ,					**_snake_case     )
  						_UpperCamelCase       : str    =      text.replace(self.backend_tokenizer.model.end_of_word_suffix  ,					''' '''     ).strip()
  						return text
  
  				_UpperCamelCase       : List[str]    =      new_decode_method
  		def _lowercase  (    self  ,					_snake_case  ,					_snake_case = None     )				->    List[int]:
  				_UpperCamelCase       : Tuple    =      [self.bos_token_id]
  				_UpperCamelCase       : str    =      [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 _lowercase  (    self  ,					_snake_case  ,					_snake_case = None     )				->    List[int]:
  				_UpperCamelCase       : Union[str, Any]    =      [self.bos_token_id]
  				_UpperCamelCase       : List[Any]    =      [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 _lowercase  (    self  ,					_snake_case  ,					_snake_case = None     )				->    Tuple[str]:
  				_UpperCamelCase       : Tuple    =      self._tokenizer.model.save(_snake_case  ,					name=_snake_case     )
  				return tuple(_snake_case     )
  
  
  
  
  
  
style_context: 
  '''simple docstring'''
  
  import os
  
  
  
  
  
  
  
  def 						snake_case__	(      ) ->      Tuple:
  		_UpperCamelCase       : Dict    =      os.path.dirname(os.path.realpath(UpperCamelCase	)	)
  		_UpperCamelCase       : str    =      os.path.join(UpperCamelCase			,'''triangle.txt'''	)
  
  		with open(UpperCamelCase	) as f:
  				_UpperCamelCase       : Optional[Any]    =      f.readlines()
  
  		_UpperCamelCase       : List[str]    =      [[int(UpperCamelCase	) for y in x.rstrip('''\r\n'''	).split(''' '''	)] for x in triangle]
  
  		for i in range(1			,len(UpperCamelCase	)	):
  				for j in range(len(a[i]	)	):
  						_UpperCamelCase       : str    =      a[i - 1][j] if j != len(a[i - 1]	) else 0
  						_UpperCamelCase       : Any    =      a[i - 1][j - 1] if j > 0 else 0
  						a[i][j] += max(UpperCamelCase			,UpperCamelCase	)
  		return max(a[-1]	)
  
  
  if __name__ == "__main__":
  	print(solution())
  
  
  
  
  
  