code: 
  
  
  
  
  
  import os
  
  
  
  
  
  
  
  def       lowerCAmelCase__(	) ->    int:
    __snake_case   :				List[Any]        =       os.path.dirname(os.path.realpath(lowercase				)				)
    __snake_case   :				Dict        =       os.path.join(lowercase   ,     "triangle.txt"				)
  
    with open(lowercase				) as in_file:
      __snake_case   :				Dict        =       [[int(lowercase				) for i in line.split()] for line in in_file]
  
    while len(lowercase				) != 1:
      __snake_case   :				Optional[Any]        =       triangle.pop()
      __snake_case   :				Tuple        =       triangle[-1]
      for j in range(len(lowercase				) - 1				):
        curr_row[j] += max(last_row[j]   ,     last_row[j + 1]				)
    return triangle[0][0]
  
  
  if __name__ == "__main__":
       print(solution())
  
  
style_context: 
  
  
  
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
  
  
  _UpperCamelCase       = {
      '''configuration_deta''': ['''DETA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DetaConfig'''],
  }
  
  try:
       if not is_vision_available():
            raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
       pass
  else:
       _UpperCamelCase       = ['''DetaImageProcessor''']
  
  try:
       if not is_torch_available():
            raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
       pass
  else:
       _UpperCamelCase       = [
           '''DETA_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''DetaForObjectDetection''',
           '''DetaModel''',
           '''DetaPreTrainedModel''',
       ]
  
  
  if TYPE_CHECKING:
       from .configuration_deta import DETA_PRETRAINED_CONFIG_ARCHIVE_MAP, DetaConfig
  
       try:
            if not is_vision_available():
                 raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
            pass
       else:
            from .image_processing_deta import DetaImageProcessor
  
       try:
            if not is_torch_available():
                 raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
            pass
       else:
            from .modeling_deta import (
                DETA_PRETRAINED_MODEL_ARCHIVE_LIST,
                DetaForObjectDetection,
                DetaModel,
                DetaPreTrainedModel,
            )
  
  else:
       import sys
  
       _UpperCamelCase       = _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
  
  