




'''simple docstring'''



import os







def       _UpperCamelCase			()-> Union[str, Any]:




     '''simple docstring'''





     __snake_case            =	os.path.dirname(os.path.realpath(_lowerCamelCase						)						)
     __snake_case            =	os.path.join(_lowerCamelCase ,						'''triangle.txt'''						)

     with open(_lowerCamelCase						) as f:
          __snake_case            =	f.readlines()

     __snake_case            =	[]
     for line in triangle:
          __snake_case            =	[]
          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]						)						):
               __snake_case            =	a[i - 1][j] if j != len(a[i - 1]						) else 0
               __snake_case            =	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())













from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


a__: int							   =						{
    'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
    'tokenization_m2m_100': ['M2M100Tokenizer'],
}


try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a__: List[Any]							   =						[
           'M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST',
           'M2M100ForConditionalGeneration',
           'M2M100Model',
           'M2M100PreTrainedModel',
       ]


if TYPE_CHECKING:
       from .configuration_mam_aaa import M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP, MaMaaaConfig, MaMaaaOnnxConfig
       from .tokenization_mam_aaa import MaMaaaTokenizer

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_mam_aaa import (
                  M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST,
                  MaMaaaForConditionalGeneration,
                  MaMaaaModel,
                  MaMaaaPreTrainedModel,
              )


else:
       import sys

       a__: List[str]							   =						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





