


A       :		Dict    =   {
    """A""": ["""B""", """C""", """E"""],
    """B""": ["""A""", """D""", """E"""],
    """C""": ["""A""", """F""", """G"""],
    """D""": ["""B"""],
    """E""": ["""A""", """B""", """D"""],
    """F""": ["""C"""],
    """G""": ["""C"""],
}






def  UpperCamelCase					(	__magic_name__     :							Optional[int]    ,    __magic_name__     :							str    ,    __magic_name__     :							List[str]     )   ->  list[str]:
		"""simple docstring"""




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

										       # mark node as explored
						explored.add(_lowerCAmelCase     )

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






def  UpperCamelCase					(	__magic_name__     :							Any    ,    __magic_name__     :							List[str]    ,    __magic_name__     :							Optional[Any]     )   ->  int:
		"""simple docstring"""




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








from typing import TYPE_CHECKING

from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__lowerCamelCase       :     Optional[int]   =     {"""configuration_mmbt""": ["""MMBTConfig"""]}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase       :     List[Any]   =     ["""MMBTForClassification""", """MMBTModel""", """ModalEmbeddings"""]


if TYPE_CHECKING:
    from .configuration_mmbt import MMBTConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_mmbt import MMBTForClassification, MMBTModel, ModalEmbeddings

else:
    import sys

    __lowerCamelCase       :     int   =     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
