import os




def     UpperCamelCase						(	):
		'''simple docstring'''




		with open(os.path.dirname(__lowercase     ) + '/grid.txt'     ) as f:
				A_		:    List[str]         =				[]  # noqa: E741
				for _ in range(20     ):
						l.append([int(__lowercase     ) for x in f.readline().split()]     )

				A_		:    Union[str, Any]         =				0

				# right
				for i in range(20     ):
						for j in range(17     ):
								A_		:    str         =				l[i][j] * l[i][j + 1] * l[i][j + 2] * l[i][j + 3]
								if temp > maximum:
										A_		:    Dict         =				temp

        # down
				for i in range(17     ):
						for j in range(20     ):
								A_		:    Any         =				l[i][j] * l[i + 1][j] * l[i + 2][j] * l[i + 3][j]
								if temp > maximum:
										A_		:    str         =				temp

        # diagonal 1
				for i in range(17     ):
						for j in range(17     ):
								A_		:    List[str]         =				l[i][j] * l[i + 1][j + 1] * l[i + 2][j + 2] * l[i + 3][j + 3]
								if temp > maximum:
										A_		:    str         =				temp

        # diagonal 2
				for i in range(17     ):
						for j in range(3						,20     ):
								A_		:    List[str]         =				l[i][j] * l[i + 1][j - 1] * l[i + 2][j - 2] * l[i + 3][j - 3]
								if temp > maximum:
										A_		:    Dict         =				temp
				return maximum


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







from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_UpperCAmelCase            =		{
    """configuration_autoformer""": [
        """AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """AutoformerConfig""",
    ],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_UpperCAmelCase            =		[
	    """AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """AutoformerForPrediction""",
	    """AutoformerModel""",
	    """AutoformerPreTrainedModel""",
	]


if TYPE_CHECKING:
	from .configuration_autoformer import (
	    AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    AutoformerConfig,
	)

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_autoformer import (
		    AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    AutoformerForPrediction,
		    AutoformerModel,
		    AutoformerPreTrainedModel,
		)

else:
	import sys

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






