
'''simple docstring'''
lowercase__						       =      {
    "A": ["B", "C", "E"],
    "B": ["A", "D", "E"],
    "C": ["A", "F", "G"],
    "D": ["B"],
    "E": ["A", "B", "D"],
    "F": ["C"],
    "G": ["C"],
}




def    _UpperCamelCase						(       SCREAMING_SNAKE_CASE__ ,       SCREAMING_SNAKE_CASE__ ,       SCREAMING_SNAKE_CASE__			)  ->							list[str]:


		'''simple docstring'''


		snake_case  :       List[Any]     			=						set()
		# keep track of all the paths to be checked
		snake_case  :       Tuple     			=						[[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  :       List[str]     			=						queue.pop(0			)
				# get the last node from the path
				snake_case  :       int     			=						path[-1]
				if node not in explored:
						snake_case  :       Union[str, Any]     			=						graph[node]
						# go through all neighbour nodes, construct a new path and
						# push it into the queue
						for neighbour in neighbours:
								snake_case  :       Tuple     			=						list(SCREAMING_SNAKE_CASE__			)
								new_path.append(SCREAMING_SNAKE_CASE__			)
								queue.append(SCREAMING_SNAKE_CASE__			)
								# return path if neighbour is goal
								if neighbour == goal:
										return new_path

            # mark node as explored
						explored.add(SCREAMING_SNAKE_CASE__			)

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




def    _UpperCamelCase						(       SCREAMING_SNAKE_CASE__ ,       SCREAMING_SNAKE_CASE__ ,       SCREAMING_SNAKE_CASE__			)  ->							int:


		'''simple docstring'''


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




'''simple docstring'''
import numpy as np




def    _UpperCamelCase						(       SCREAMING_SNAKE_CASE__			)  ->							np.ndarray:


		'''simple docstring'''


		return 1 / (1 + np.exp(-vector			))




def    _UpperCamelCase						(       SCREAMING_SNAKE_CASE__			)  ->							np.ndarray:


		'''simple docstring'''


		return vector * sigmoid(SCREAMING_SNAKE_CASE__			)


if __name__ == "__main__":
						import doctest

						doctest.testmod()


