


'''simple docstring'''



import heapq


def    lowerCamelCase__   ( A     :    dict  ):




						'''simple docstring'''






						UpperCAmelCase         =			[]

						# 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(A   ,     [-1 * len(A  ), (key, value)]  )

						# chosen_vertices = set of chosen vertices
						UpperCAmelCase         =			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         =			heapq.heappop(A  )[1][0]
												chosen_vertices.add(A  )

												# 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         =			elem[1][1].index(A  )
																								del elem[1][1][index]
																								elem[0] += 1
        # re-order the queue
												heapq.heapify(A  )
						return chosen_vertices


if __name__ == "__main__":
					import doctest

					doctest.testmod()

					_lowercase    :    Optional[int]			     =  {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'''



from ...configuration_utils import PretrainedConfig
from ...utils import logging


_lowercase    :    Any			     =  logging.get_logger(__name__)

_lowercase    :    Dict			     =  {
    """facebook/dpr-ctx_encoder-single-nq-base""": (
        """https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/config.json"""
    ),
    """facebook/dpr-question_encoder-single-nq-base""": (
        """https://huggingface.co/facebook/dpr-question_encoder-single-nq-base/resolve/main/config.json"""
    ),
    """facebook/dpr-reader-single-nq-base""": (
        """https://huggingface.co/facebook/dpr-reader-single-nq-base/resolve/main/config.json"""
    ),
    """facebook/dpr-ctx_encoder-multiset-base""": (
        """https://huggingface.co/facebook/dpr-ctx_encoder-multiset-base/resolve/main/config.json"""
    ),
    """facebook/dpr-question_encoder-multiset-base""": (
        """https://huggingface.co/facebook/dpr-question_encoder-multiset-base/resolve/main/config.json"""
    ),
    """facebook/dpr-reader-multiset-base""": (
        """https://huggingface.co/facebook/dpr-reader-multiset-base/resolve/main/config.json"""
    ),
}






class  UpperCamelCase__(     lowerCAmelCase ):
				__magic_name__       :   Optional[int]							= "dpr"




				def __init__(	self    :				Dict   ,					lowerCAmelCase    :				Any=30522   ,					lowerCAmelCase    :				List[str]=768   ,					lowerCAmelCase    :				Union[str, Any]=12   ,					lowerCAmelCase    :				Tuple=12   ,					lowerCAmelCase    :				Optional[int]=3072   ,					lowerCAmelCase    :				Optional[int]="gelu"   ,					lowerCAmelCase    :				Optional[Any]=0.1   ,					lowerCAmelCase    :				Any=0.1   ,					lowerCAmelCase    :				Optional[Any]=512   ,					lowerCAmelCase    :				List[Any]=2   ,					lowerCAmelCase    :				Tuple=0.02   ,					lowerCAmelCase    :				str=1E-12   ,					lowerCAmelCase    :				Optional[Any]=0   ,					lowerCAmelCase    :				Tuple="absolute"   ,					lowerCAmelCase    :				int = 0   ,					**lowerCAmelCase    :				Union[str, Any]   ,					)->  Optional[int]:

										"""simple docstring"""




										super().__init__(pad_token_id=lowerCAmelCase   ,					**lowerCAmelCase   )

										UpperCAmelCase         =			vocab_size
										UpperCAmelCase         =			hidden_size
										UpperCAmelCase         =			num_hidden_layers
										UpperCAmelCase         =			num_attention_heads
										UpperCAmelCase         =			hidden_act
										UpperCAmelCase         =			intermediate_size
										UpperCAmelCase         =			hidden_dropout_prob
										UpperCAmelCase         =			attention_probs_dropout_prob
										UpperCAmelCase         =			max_position_embeddings
										UpperCAmelCase         =			type_vocab_size
										UpperCAmelCase         =			initializer_range
										UpperCAmelCase         =			layer_norm_eps
										UpperCAmelCase         =			projection_dim
										UpperCAmelCase         =			position_embedding_type





