






import os



def      UpperCAmelCase						( ):


		'''simple docstring'''

		__A    =							os.path.dirname(os.path.realpath(lowerCAmelCase__	)	)
		__A    =							os.path.join(lowerCAmelCase__					,     "triangle.txt"	)

		with open(lowerCAmelCase__	) as f:
				__A    =							f.readlines()

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

		for i in range(1					,     len(lowerCAmelCase__	)	):
				for j in range(len(a[i]	)	):
						__A    =							a[i - 1][j] if j != len(a[i - 1]	) else 0
						__A    =							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())



"""simple docstring"""
from typing import TYPE_CHECKING

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


lowercase		:    Dict			=       {
    'configuration_mobilenet_v1': [
        'MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'MobileNetV1Config',
        'MobileNetV1OnnxConfig',
    ],
}

try:
			if not is_vision_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowercase		:    Optional[int]			=       ['MobileNetV1FeatureExtractor']
			lowercase		:    Union[str, Any]			=       ['MobileNetV1ImageProcessor']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowercase		:    Tuple			=       [
			    'MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'MobileNetV1ForImageClassification',
			    'MobileNetV1Model',
			    'MobileNetV1PreTrainedModel',
			    'load_tf_weights_in_mobilenet_v1',
			]


if TYPE_CHECKING:
			from .configuration_mobilenet_va import (
			    MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP,
			    MobileNetVaConfig,
			    MobileNetVaOnnxConfig,
			)

			try:
						if not is_vision_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .feature_extraction_mobilenet_va import MobileNetVaFeatureExtractor
						from .image_processing_mobilenet_va import MobileNetVaImageProcessor

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_mobilenet_va import (
						    MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST,
						    MobileNetVaForImageClassification,
						    MobileNetVaModel,
						    MobileNetVaPreTrainedModel,
						    load_tf_weights_in_mobilenet_va,
						)


else:
			import sys

			lowercase		:    Union[str, Any]			=       _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
