


'''simple docstring'''



from __future__ import annotations

from typing import Generic, TypeVar

_lowercase      :      int            =					TypeVar("""T""")






class 	UpperCamelCase__(       Generic[T]	):




				def __init__(		self      :			Optional[int]				,   lowerCAmelCase      :			T				)->					None:

										"""simple docstring"""




										UpperCAmelCase					    =     data
										UpperCAmelCase					    =     self
										UpperCAmelCase					    =     0







class 	UpperCamelCase__(       Generic[T]	):




				def __init__(		self      :			List[Any]				)->					None:

										"""simple docstring"""




										UpperCAmelCase					    =     {}




				def 					a__(		self      :			str				,   lowerCAmelCase      :			T				)->					None:

										"""simple docstring"""




										UpperCAmelCase					    =     DisjointSetTreeNode(lowerCAmelCase				)




				def 					a__(		self      :			List[Any]				,   lowerCAmelCase      :			T				)->					DisjointSetTreeNode[T]:

										"""simple docstring"""




										UpperCAmelCase					    =     self.map[data]
										if elem_ref != elem_ref.parent:
																UpperCAmelCase					    =     self.find_set(elem_ref.parent.data				)
										return elem_ref.parent




				def 					a__(		self      :			List[Any]				,   lowerCAmelCase      :			DisjointSetTreeNode[T]				,   lowerCAmelCase      :			DisjointSetTreeNode[T]				)->					None:

										"""simple docstring"""




										if nodea.rank > nodea.rank:
																UpperCAmelCase					    =     nodea
										else:
																UpperCAmelCase					    =     nodea
																if nodea.rank == nodea.rank:
																						nodea.rank += 1





				def 					a__(		self      :			Union[str, Any]				,   lowerCAmelCase      :			T				,   lowerCAmelCase      :			T				)->					None:

										"""simple docstring"""




										self.link(self.find_set(lowerCAmelCase				)				,   self.find_set(lowerCAmelCase				)				)







class 	UpperCamelCase__(       Generic[T]	):




				def __init__(		self      :			Any				)->					None:

										"""simple docstring"""




										UpperCAmelCase					    =     {}




				def 					a__(		self      :			Optional[Any]				,   lowerCAmelCase      :			T				)->					None:

										"""simple docstring"""




										if node not in self.connections:
																UpperCAmelCase					    =     {}




				def 					a__(		self      :			Optional[Any]				,   lowerCAmelCase      :			T				,   lowerCAmelCase      :			T				,   lowerCAmelCase      :			int				)->					None:

										"""simple docstring"""




										self.add_node(lowerCAmelCase				)
										self.add_node(lowerCAmelCase				)
										UpperCAmelCase					    =     weight
										UpperCAmelCase					    =     weight





				def 					a__(		self      :			Dict				)->					GraphUndirectedWeighted[T]:

										"""simple docstring"""




										UpperCAmelCase					    =     []
										UpperCAmelCase					    =     set()
										for start in self.connections:
																for end in self.connections[start]:
																						if (start, end) not in seen:
																												seen.add((end, start)				)
																												edges.append((start, end, self.connections[start][end])				)
										edges.sort(key=lambda lowerCAmelCase				: x[2]				)

										# creating the disjoint set
										UpperCAmelCase					    =     DisjointSetTree[T]()
										for node in self.connections:
																disjoint_set.make_set(lowerCAmelCase				)

										# MST generation
										UpperCAmelCase					    =     0
										UpperCAmelCase					    =     0
										UpperCAmelCase					    =     GraphUndirectedWeighted[T]()
										while num_edges < len(self.connections				) - 1:
																UpperCAmelCase    ,    UpperCAmelCase    ,    UpperCAmelCase					    =     edges[index]
																index += 1
																UpperCAmelCase					    =     disjoint_set.find_set(lowerCAmelCase				)
																UpperCAmelCase					    =     disjoint_set.find_set(lowerCAmelCase				)
																if parent_u != parent_v:
																						num_edges += 1
																						graph.add_edge(lowerCAmelCase				,   lowerCAmelCase				,   lowerCAmelCase				)
																						disjoint_set.union(lowerCAmelCase				,   lowerCAmelCase				)
										return graph









'''simple docstring'''



from typing import TYPE_CHECKING

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


_lowercase      :      Union[str, Any]            =					{
    """configuration_poolformer""": [
        """POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """PoolFormerConfig""",
        """PoolFormerOnnxConfig""",
    ]
}

try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowercase      :      List[Any]            =					["""PoolFormerFeatureExtractor"""]
	_lowercase      :      Any            =					["""PoolFormerImageProcessor"""]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowercase      :      Tuple            =					[
	    """POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """PoolFormerForImageClassification""",
	    """PoolFormerModel""",
	    """PoolFormerPreTrainedModel""",
	]


if TYPE_CHECKING:
	from .configuration_poolformer import (
	    POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    PoolFormerConfig,
	    PoolFormerOnnxConfig,
	)

	try:
		if not is_vision_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .feature_extraction_poolformer import PoolFormerFeatureExtractor
		from .image_processing_poolformer import PoolFormerImageProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_poolformer import (
		    POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    PoolFormerForImageClassification,
		    PoolFormerModel,
		    PoolFormerPreTrainedModel,
		)


else:
	import sys

	_lowercase      :      Dict            =					_LazyModule(__name__, globals()["""__file__"""], _import_structure)





