'''simple docstring'''




import heapq

def       UpperCamelCase_				(   _UpperCAmelCase    : Dict       )       ->       Any:


       """simple docstring"""







       _UpperCAmelCase	:    list[list]				 =       []

       # for each node and his adjacency list add them and the rank of the node to queue
       # using heapq module the queue will be filled like a Priority Queue
       # heapq works with a min priority queue, so I used -1*len(v) to build it
       for key, value in graph.items():
              # O(log(n))
              heapq.heappush(lowerCamelCase_     ,      [-1 * len(lowerCamelCase_       ), (key, value)]       )

       # chosen_vertices = set of chosen vertices
       _UpperCAmelCase	:    str				 =       set()

       # while queue isn't empty and there are still edges
       #   (queue[0][0] is the rank of the node with max rank)
       while queue and queue[0][0] != 0:
              # extract vertex with max rank from queue and add it to chosen_vertices
              _UpperCAmelCase	:    List[Any]				 =       heapq.heappop(lowerCamelCase_       )[1][0]
              chosen_vertices.add(lowerCamelCase_       )

              # Remove all arcs adjacent to argmax
              for elem in queue:
                     # if v haven't adjacent node, skip
                     if elem[0] == 0:
                            continue
                     # if argmax is reachable from elem
                     # remove argmax from elem's adjacent list and update his rank
                     if argmax in elem[1][1]:
                            _UpperCAmelCase	:    Union[str, Any]				 =       elem[1][1].index(lowerCamelCase_       )
                            del elem[1][1][index]
                            elem[0] += 1
        # re-order the queue
              heapq.heapify(lowerCamelCase_       )
       return chosen_vertices


if __name__ == "__main__":
  import doctest

  doctest.testmod()

  __SCREAMING_SNAKE_CASE			:	Dict	=    {0: [1, 3], 1: [0, 3], 2: [0, 3, 4], 3: [0, 1, 2], 4: [2, 3]}
  print(F'Minimum vertex cover:\n{greedy_min_vertex_cover(graph)}')








'''simple docstring'''




import unittest

from transformers import DonutProcessor


__UpperCAmelCase            =       """naver-clova-ix/donut-base"""




class      UpperCamelCase__					(					unittest.TestCase			):




					"""simple docstring"""


					def lowerCamelCase_			(						self				:			List[str]						):

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				Any		=			DonutProcessor.from_pretrained(lowerCamelCase_						)



					def lowerCamelCase_			(						self				:			Tuple						):

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				Optional[int]		=			{
							    """name""": """John Doe""",
							    """age""": """99""",
							    """city""": """Atlanta""",
							    """state""": """GA""",
							    """zip""": """30301""",
							    """phone""": """123-4567""",
							    """nicknames""": [{"""nickname""": """Johnny"""}, {"""nickname""": """JD"""}],
							}

							SCREAMING_SNAKE_CASE :				List[Any]		=			(
							    """<s_name>John Doe</s_name><s_age>99</s_age><s_city>Atlanta</s_city>"""
							    """<s_state>GA</s_state><s_zip>30301</s_zip><s_phone>123-4567</s_phone>"""
							    """<s_nicknames><s_nickname>Johnny</s_nickname>"""
							    """<sep/><s_nickname>JD</s_nickname></s_nicknames>"""
							)
							SCREAMING_SNAKE_CASE :				List[Any]		=			self.processor.tokenajson(lowerCamelCase_						)

							self.assertDictEqual(lowerCamelCase_      ,						lowerCamelCase_						)



