



'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


UpperCamelCase__:       str							     =      {"configuration_regnet": ["REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "RegNetConfig"]}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase__:       Optional[int]							     =      [
						    "REGNET_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "RegNetForImageClassification",
						    "RegNetModel",
						    "RegNetPreTrainedModel",
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase__:       Optional[int]							     =      [
						    "TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "TFRegNetForImageClassification",
						    "TFRegNetModel",
						    "TFRegNetPreTrainedModel",
						]

try:
						if not is_flax_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase__:       Dict							     =      [
						    "FlaxRegNetForImageClassification",
						    "FlaxRegNetModel",
						    "FlaxRegNetPreTrainedModel",
						]


if TYPE_CHECKING:
						from .configuration_regnet import REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP, RegNetConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_regnet import (
												    REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
												    RegNetForImageClassification,
												    RegNetModel,
												    RegNetPreTrainedModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_regnet import (
												    TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TFRegNetForImageClassification,
												    TFRegNetModel,
												    TFRegNetPreTrainedModel,
												)

						try:
												if not is_flax_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_flax_regnet import (
												    FlaxRegNetForImageClassification,
												    FlaxRegNetModel,
												    FlaxRegNetPreTrainedModel,
												)


else:
						import sys

						UpperCamelCase__:       Any							     =      _LazyModule(__name__, globals()["__file__"], _import_structure)










'''simple docstring'''






UpperCamelCase__:       Any							     =      [[0, 1, 1], [0, 0, 1], [1, 0, 0]]

class     SCREAMING_SNAKE_CASE:







	"""simple docstring"""






	def __init__(						self      :					List[str]		,      __snake_case      :					int		)      ->		int:
								UpperCAmelCase			:	Any										=		name
								UpperCAmelCase			:	Optional[Any]										=		[]
								UpperCAmelCase			:	Any										=		[]







	def 					A     (						self      :					Dict		,      __snake_case      :					str		)      ->		Tuple:
								self.inbound.append(__snake_case		)







	def 					A     (						self      :					Union[str, Any]		,      __snake_case      :					str		)      ->		Optional[int]:
								self.outbound.append(__snake_case		)







	def __repr__(						self      :					Optional[int]		)      ->		Optional[int]:
								return F"""<node={self.name} inbound={self.inbound} outbound={self.outbound}>"""


def 			snake_case_					( _lowerCAmelCase  :						Tuple       ,				_lowerCAmelCase  :						Dict=3       ,				_lowerCAmelCase  :						Tuple=0.8_5  )				->       Optional[Any]:
							UpperCAmelCase			:	Tuple										=		{}
							for node in nodes:
														UpperCAmelCase			:	List[str]										=		1

							UpperCAmelCase			:	List[Any]										=		{}
							for node in nodes:
														UpperCAmelCase			:	str										=		len(node.outbound  )

							for i in range(_lowerCAmelCase  ):
														print(f"""======= Iteration {i + 1} ======="""  )
														for _, node in enumerate(_lowerCAmelCase  ):
																					UpperCAmelCase			:	str										=		(1 - d) + d * sum(
																					    ranks[ib] / outbounds[ib] for ib in node.inbound  )
														print(_lowerCAmelCase  )


def 			snake_case_					( )				->       List[str]:
							UpperCAmelCase			:	str										=		list(input('''Enter Names of the Nodes: '''  ).split()  )

							UpperCAmelCase			:	Dict										=		[Node(_lowerCAmelCase  ) for name in names]

							for ri, row in enumerate(_lowerCAmelCase  ):
														for ci, col in enumerate(_lowerCAmelCase  ):
																					if col == 1:
																												nodes[ci].add_inbound(names[ri]  )
																												nodes[ri].add_outbound(names[ci]  )

							print('''======= Nodes ======='''  )
							for node in nodes:
														print(_lowerCAmelCase  )

							page_rank(_lowerCAmelCase  )


if __name__ == "__main__":
						main()





