



import os


def 	_UpperCAmelCase       (   ):





     """simple docstring"""

     _lowerCAmelCase      			=					os.path.dirname(os.path.realpath(snake_case    )    )
     _lowerCAmelCase      			=					os.path.join(snake_case			,		"""triangle.txt"""    )

     with open(snake_case    ) as f:
          _lowerCAmelCase      			=					f.readlines()

     _lowerCAmelCase      			=					[[int(snake_case    ) for y in x.rstrip("""\r\n"""    ).split(""" """    )] for x in triangle]

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


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








from typing import TYPE_CHECKING

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


A__			   = {
    """configuration_videomae""": ["""VIDEOMAE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """VideoMAEConfig"""],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A__			   = [
	    """VIDEOMAE_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """VideoMAEForPreTraining""",
	    """VideoMAEModel""",
	    """VideoMAEPreTrainedModel""",
	    """VideoMAEForVideoClassification""",
	]

try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A__			   = ["""VideoMAEFeatureExtractor"""]
	A__			   = ["""VideoMAEImageProcessor"""]

if TYPE_CHECKING:
	from .configuration_videomae import VIDEOMAE_PRETRAINED_CONFIG_ARCHIVE_MAP, VideoMAEConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_videomae import (
		    VIDEOMAE_PRETRAINED_MODEL_ARCHIVE_LIST,
		    VideoMAEForPreTraining,
		    VideoMAEForVideoClassification,
		    VideoMAEModel,
		    VideoMAEPreTrainedModel,
		)

	try:
		if not is_vision_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .feature_extraction_videomae import VideoMAEFeatureExtractor
		from .image_processing_videomae import VideoMAEImageProcessor

else:
	import sys

	A__			   = _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



