






def 	lowerCamelCase__      (  lowercase					):

  """simple docstring"""






  SCREAMING_SNAKE_CASE							:   Optional[Any]						    =     set()
  # edges = list of graph's edges
  SCREAMING_SNAKE_CASE							:   List[Any]						    =     get_edges(lowercase					)

  # While there are still elements in edges list, take an arbitrary edge
  # (from_node, to_node) and add his extremity to chosen_vertices and then
  # remove all arcs adjacent to the from_node and to_node
  while edges:
    SCREAMING_SNAKE_CASE    ,	SCREAMING_SNAKE_CASE							:   Dict						    =     edges.pop()
    chosen_vertices.add(lowercase					)
    chosen_vertices.add(lowercase					)
    for edge in edges.copy():
      if from_node in edge or to_node in edge:
        edges.discard(lowercase					)
  return chosen_vertices


def 	lowerCamelCase__      (  lowercase					):

  """simple docstring"""






  SCREAMING_SNAKE_CASE							:   Optional[Any]						    =     set()
  for from_node, to_nodes in graph.items():
    for to_node in to_nodes:
      edges.add((from_node, to_node)					)
  return edges


if __name__ == "__main__":
   import doctest

   doctest.testmod()

   # graph = {0: [1, 3], 1: [0, 3], 2: [0, 3, 4], 3: [0, 1, 2], 4: [2, 3]}
   # print(f"Matching vertex cover:\n{matching_min_vertex_cover(graph)}")









from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a_      =     {
    'configuration_swinv2': ['SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Swinv2Config'],
}


try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			a_      =     [
			    'SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'Swinv2ForImageClassification',
			    'Swinv2ForMaskedImageModeling',
			    'Swinv2Model',
			    'Swinv2PreTrainedModel',
			]


if TYPE_CHECKING:
			from .configuration_swinva import SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinvaConfig

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_swinva import (
						    SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST,
						    SwinvaForImageClassification,
						    SwinvaForMaskedImageModeling,
						    SwinvaModel,
						    SwinvaPreTrainedModel,
						)


else:
			import sys

			a_      =     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)