





SCREAMING_SNAKE_CASE__       :			Dict			      =						{
    """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   ):
   a__	:						Union[str, Any]      		=  set()
   # keep track of all the paths to be checked
   a__	:						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
      a__	:						Dict      		=  queue.pop(0   )
      # get the last node from the path
      a__	:						int      		=  path[-1]
      if node not in explored:
         a__	:						Dict      		=  graph[node]
         # go through all neighbour nodes, construct a new path and
         # push it into the queue
         for neighbour in neighbours:
            a__	:						List[Any]      		=  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       _A  (      lowerCamelCase							, lowerCamelCase							, lowerCamelCase   ):
   if not graph or start not in graph or target not in graph:
      return -1
   if start == target:
      return 0
   a__	:						Optional[Any]      		=  [start]
   a__	:						Tuple      		=  set(lowerCamelCase   )
   # Keep tab on distances from `start` node.
   a__	:						str      		=  {start: 0, target: -1}
   while queue:
      a__	:						Dict      		=  queue.pop(0   )
      if node == target:
         a__	:						Tuple      		=  (
             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   )
            a__	:						str      		=  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, is_vision_available


SCREAMING_SNAKE_CASE__       :			List[str]			      =						{"""configuration_van""": ["""VAN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """VanConfig"""]}


try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  SCREAMING_SNAKE_CASE__       :			Optional[int]			      =						[
      """VAN_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """VanForImageClassification""",
      """VanModel""",
      """VanPreTrainedModel""",
  ]

if TYPE_CHECKING:
  from .configuration_van import VAN_PRETRAINED_CONFIG_ARCHIVE_MAP, VanConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_van import (
        VAN_PRETRAINED_MODEL_ARCHIVE_LIST,
        VanForImageClassification,
        VanModel,
        VanPreTrainedModel,
    )

else:
  import sys

  SCREAMING_SNAKE_CASE__       :			List[str]			      =						_LazyModule(__name__, globals()["""__file__"""], _import_structure)

