





from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__lowerCamelCase	:					Union[str, Any]			  =					logging.get_logger(__name__)

__lowerCamelCase	:					Tuple			  =					{
    """roberta-base""": """https://huggingface.co/roberta-base/resolve/main/config.json""",
    """roberta-large""": """https://huggingface.co/roberta-large/resolve/main/config.json""",
    """roberta-large-mnli""": """https://huggingface.co/roberta-large-mnli/resolve/main/config.json""",
    """distilroberta-base""": """https://huggingface.co/distilroberta-base/resolve/main/config.json""",
    """roberta-base-openai-detector""": """https://huggingface.co/roberta-base-openai-detector/resolve/main/config.json""",
    """roberta-large-openai-detector""": """https://huggingface.co/roberta-large-openai-detector/resolve/main/config.json""",
}



class  A__       (	__snake_case      ):
      _UpperCAmelCase     :Optional[int]						   =       'roberta'





      def __init__(			self	,							A_=5_0265	,							A_=768	,							A_=12	,							A_=12	,							A_=3072	,							A_="gelu"	,							A_=0.1	,							A_=0.1	,							A_=512	,							A_=2	,							A_=0.02	,							A_=1e-12	,							A_=1	,							A_=0	,							A_=2	,							A_="absolute"	,							A_=True	,							A_=None	,							**A_	,							):
       '''simple docstring'''




       super().__init__(pad_token_id=A_	,							bos_token_id=A_	,							eos_token_id=A_	,							**A_       )

       UpperCamelCase     : Dict	     =       vocab_size
       UpperCamelCase     : Dict	     =       hidden_size
       UpperCamelCase     : int	     =       num_hidden_layers
       UpperCamelCase     : List[Any]	     =       num_attention_heads
       UpperCamelCase     : Union[str, Any]	     =       hidden_act
       UpperCamelCase     : Tuple	     =       intermediate_size
       UpperCamelCase     : List[Any]	     =       hidden_dropout_prob
       UpperCamelCase     : List[str]	     =       attention_probs_dropout_prob
       UpperCamelCase     : Optional[Any]	     =       max_position_embeddings
       UpperCamelCase     : Any	     =       type_vocab_size
       UpperCamelCase     : Tuple	     =       initializer_range
       UpperCamelCase     : List[Any]	     =       layer_norm_eps
       UpperCamelCase     : Any	     =       position_embedding_type
       UpperCamelCase     : Union[str, Any]	     =       use_cache
       UpperCamelCase     : Tuple	     =       classifier_dropout



class  A__       (	__snake_case      ):





      @property
      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       if self.task == "multiple-choice":
        UpperCamelCase     : Optional[Any]	     =       {0: "batch", 1: "choice", 2: "sequence"}
       else:
        UpperCamelCase     : List[str]	     =       {0: "batch", 1: "sequence"}
       return OrderedDict(
           [
               ("input_ids", dynamic_axis),
               ("attention_mask", dynamic_axis),
           ]       )







import os



def 		A_    (					)						->			int:
 UpperCamelCase     : List[str]	     =       os.path.dirname(os.path.realpath(_lowerCAmelCase					)					)
 UpperCamelCase     : Any	     =       os.path.join(_lowerCAmelCase							,       "triangle.txt"					)

 with open(_lowerCAmelCase					) as f:
  UpperCamelCase     : Optional[Any]	     =       f.readlines()

 UpperCamelCase     : Tuple	     =       []
 for line in triangle:
  UpperCamelCase     : List[str]	     =       []
  for number in line.strip().split(" "					):
   numbers_from_line.append(int(_lowerCAmelCase					)					)
  a.append(_lowerCAmelCase					)

 for i in range(1							,       len(_lowerCAmelCase					)					):
  for j in range(len(a[i]					)					):
   UpperCamelCase     : List[Any]	     =       a[i - 1][j] if j != len(a[i - 1]					) else 0
   UpperCamelCase     : Dict	     =       a[i - 1][j - 1] if j > 0 else 0
   a[i][j] += max(_lowerCAmelCase							,       _lowerCAmelCase					)
 return max(a[-1]					)


if __name__ == "__main__":
    print(solution())
