





lowercase_		:				Optional[Any]				=						{
    '''A''': ['''B''', '''C''', '''E'''],
    '''B''': ['''A''', '''D''', '''E'''],
    '''C''': ['''A''', '''F''', '''G'''],
    '''D''': ['''B'''],
    '''E''': ['''A''', '''B''', '''D'''],
    '''F''': ['''C'''],
    '''G''': ['''C'''],
}

def       A__(		__lowerCAmelCase	,			__lowerCAmelCase	,			__lowerCAmelCase ):
				_snake_case :			List[Any]  						=   set()
				# keep track of all the paths to be checked
				_snake_case :			Any  						=   [[start]]

				# return path if start is goal
				if start == goal:
								return [start]

				# keeps looping until all possible paths have been checked
				while queue:
								# pop the first path from the queue
								_snake_case :			Optional[int]  						=   queue.pop(0 )
								# get the last node from the path
								_snake_case :			str  						=   path[-1]
								if node not in explored:
												_snake_case :			Any  						=   graph[node]
												# go through all neighbour nodes, construct a new path and
												# push it into the queue
												for neighbour in neighbours:
																_snake_case :			Optional[int]  						=   list(UpperCamelCase__ )
																new_path.append(UpperCamelCase__ )
																queue.append(UpperCamelCase__ )
																# return path if neighbour is goal
																if neighbour == goal:
																				return new_path

            # mark node as explored
												explored.add(UpperCamelCase__ )

    # in case there's no path between the 2 nodes
				return []

def       A__(		__lowerCAmelCase	,			__lowerCAmelCase	,			__lowerCAmelCase ):
				if not graph or start not in graph or target not in graph:
								return -1
				if start == target:
								return 0
				_snake_case :			List[Any]  						=   [start]
				_snake_case :			List[Any]  						=   set(UpperCamelCase__ )
				# Keep tab on distances from `start` node.
				_snake_case :			int  						=   {start: 0, target: -1}
				while queue:
								_snake_case :			Dict  						=   queue.pop(0 )
								if node == target:
												_snake_case :			List[str]  						=   (
												    dist[node] if dist[target] == -1 else min(dist[target]	,			dist[node] )
												)
								for adjacent in graph[node]:
												if adjacent not in visited:
																visited.add(UpperCamelCase__ )
																queue.append(UpperCamelCase__ )
																_snake_case :			Optional[Any]  						=   dist[node] + 1
				return dist[target]


if __name__ == "__main__":
		print(bfs_shortest_path(demo_graph, '''G''', '''D'''))  # returns ['G', 'C', 'A', 'B', 'D']
		print(bfs_shortest_path_distance(demo_graph, '''G''', '''D'''))  # returns 4













import torch

from transformers import AutoModel


class 			lowercase				(							torch.nn.Module     ):



						"""simple docstring"""

						def __init__(    self			:		Tuple ,				lowerCamelCase_			:		Dict="sayef/fsner-bert-base-uncased"					):





										'''simple docstring'''







										super(lowerCamelCase_ ,				self					).__init__()

										_snake_case :			Optional[Any]  						=   AutoModel.from_pretrained(lowerCamelCase_ ,				return_dict=lowerCamelCase_					)
										_snake_case :			str  						=   torch.nn.CosineSimilarity(3 ,				1e-08					)
										_snake_case :			str  						=   torch.nn.Softmax(dim=1					)







						def 		__UpperCAmelCase       (    self			:		int ,				**lowerCamelCase_			:		List[str]					):





										'''simple docstring'''







										return self.bert(**lowerCamelCase_					).last_hidden_state







						def 		__UpperCAmelCase       (    self			:		List[Any] ,				lowerCamelCase_			:		Union[str, Any]					):





										'''simple docstring'''







										return token_embeddings.sum(2 ,				keepdim=lowerCamelCase_					)







						def 		__UpperCAmelCase       (    self			:		Dict ,				lowerCamelCase_			:		Dict ,				lowerCamelCase_			:		Tuple ,				lowerCamelCase_			:		Optional[Any]=1					):





										'''simple docstring'''







										return self.softmax(T * self.cos(lowerCamelCase_ ,				lowerCamelCase_					)					)







						def 		__UpperCAmelCase       (    self			:		Optional[Any] ,				lowerCamelCase_			:		Any ,				lowerCamelCase_			:		Union[str, Any]					):





										'''simple docstring'''







										_snake_case :			int  						=   W_supports['sizes'].tolist()
										_snake_case :			int  						=   W_supports['start_token_id'].item()
										_snake_case :			List[str]  						=   W_supports['end_token_id'].item()

										del W_supports["sizes"]
										del W_supports["start_token_id"]
										del W_supports["end_token_id"]

										_snake_case :			Optional[int]  						=   self.BERT(**lowerCamelCase_					)
										_snake_case :			Optional[Any]  						=   self.BERT(**lowerCamelCase_					)

										_snake_case :			Optional[int]  						=   None
										_snake_case :			Optional[int]  						=   None

										_snake_case :			List[str]  						=   W_supports['input_ids'] == start_token_id
										_snake_case :			Union[str, Any]  						=   W_supports['input_ids'] == end_token_id

										for i, size in enumerate(lowerCamelCase_					):
														if i == 0:
																		_snake_case :			str  						=   0
														else:
																		_snake_case :			Union[str, Any]  						=   support_sizes[i - 1]

														_snake_case :			Tuple  						=   S[s : s + size][start_token_masks[s : s + size]]
														_snake_case :			Optional[int]  						=   S[s : s + size][end_token_masks[s : s + size]]

														_snake_case :			Tuple  						=   torch.matmul(q[i] ,				s_start.T					).sum(1					).softmax(0					)
														_snake_case :			Union[str, Any]  						=   torch.matmul(q[i] ,				s_end.T					).sum(1					).softmax(0					)

														if p_starts is not None:
																		_snake_case :			Optional[Any]  						=   torch.vstack((p_starts, p_start)					)
																		_snake_case :			List[str]  						=   torch.vstack((p_ends, p_end)					)
														else:
																		_snake_case :			Union[str, Any]  						=   p_start
																		_snake_case :			Any  						=   p_end

										return p_starts, p_ends






