
'''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     )







'''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())





