


import os





def 						_lowerCAmelCase							(     )    ->						int:


						'''simple docstring'''






						__snake_case				=		os.path.join(os.path.dirname(_lowerCAmelCase			)   ,						"num.txt"			)
						with open(_lowerCAmelCase			) as file_hand:
												return str(sum(int(_lowerCAmelCase			) for line in file_hand			)			)[:10]


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









from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A				:       List[str]      =  {
    'configuration_time_series_transformer': [
        'TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'TimeSeriesTransformerConfig',
    ],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A				:       str      =  [
	    'TIME_SERIES_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'TimeSeriesTransformerForPrediction',
	    'TimeSeriesTransformerModel',
	    'TimeSeriesTransformerPreTrainedModel',
	]


if TYPE_CHECKING:
	from .configuration_time_series_transformer import (
	    TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    TimeSeriesTransformerConfig,
	)

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_time_series_transformer import (
		    TIME_SERIES_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TimeSeriesTransformerForPrediction,
		    TimeSeriesTransformerModel,
		    TimeSeriesTransformerPreTrainedModel,
		)

else:
	import sys

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





