






from itertools import combinations, product






def 				A	(			a_				,a_				,a_				,a_   )	->		bool:
					if xa == ya == 0 or xa == ya == 0:
										return False
					__UpperCamelCase :   Tuple									=xa * xa + ya * ya
					__UpperCamelCase :   Optional[int]									=xa * xa + ya * ya
					__UpperCamelCase :   List[str]									=(xa - xa) * (xa - xa) + (ya - ya) * (ya - ya)
					return (
					    a_square + b_square == c_square
					    or a_square + c_square == b_square
					    or b_square + c_square == a_square
					)






def 				A	(			a_ = 50   )	->		int:
					return sum(
					    1
					    for pta, pta in combinations(product(range(limit + 1   )				,repeat=2   )				,2   )
					    if is_right(*a_				,*a_   )   )


if __name__ == "__main__":
							print(f"{solution() = }")









from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A_			:Union[str, Any]	    =		{'''configuration_nat''': ['''NAT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''NatConfig''']}


try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A_			:Optional[Any]	    =		[
							    '''NAT_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''NatForImageClassification''',
							    '''NatModel''',
							    '''NatPreTrainedModel''',
							    '''NatBackbone''',
							]

if TYPE_CHECKING:
							from .configuration_nat import NAT_PRETRAINED_CONFIG_ARCHIVE_MAP, NatConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_nat import (
														    NAT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    NatBackbone,
														    NatForImageClassification,
														    NatModel,
														    NatPreTrainedModel,
														)

else:
							import sys

							A_			:Tuple	    =		_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)

