





import heapq







def       lowerCAmelCase__(	lowercase       :    Optional[Any]   ,     lowercase       :    List[str]   ,     lowercase       :    Optional[Any]				) ->    List[Any]:
  __snake_case   :				int        =       [(0, start)]  # cost from start node,end node
  __snake_case   :				List[Any]        =       set()
  while heap:
    ((__snake_case)    ,   (__snake_case))   :				int        =       heapq.heappop(_A				)
    if u in visited:
      continue
    visited.add(_A				)
    if u == end:
      return cost
    for v, c in graph[u]:
      if v in visited:
        continue
      __snake_case   :				Dict        =       cost + c
      heapq.heappush(_A   ,     (next_item, v)				)
  return -1


_UpperCamelCase       = {
    'A': [['B', 2], ['C', 5]],
    'B': [['A', 2], ['D', 3], ['E', 1], ['F', 1]],
    'C': [['A', 5], ['F', 3]],
    'D': [['B', 3]],
    'E': [['B', 4], ['F', 3]],
    'F': [['C', 3], ['E', 3]],
}
_UpperCamelCase       = {
    'B': [['C', 1]],
    'C': [['D', 1]],
    'D': [['F', 1]],
    'E': [['B', 1], ['F', 3]],
    'F': [],
}
_UpperCamelCase       = {
    'B': [['C', 1]],
    'C': [['D', 1]],
    'D': [['F', 1]],
    'E': [['B', 1], ['G', 2]],
    'F': [],
    'G': [['F', 1]],
}

_UpperCamelCase       = dijkstra(G, '''E''', '''C''')
print(short_distance)  # E -- 3 --> F -- 3 --> C == 6

_UpperCamelCase       = dijkstra(Ga, '''E''', '''F''')
print(short_distance)  # E -- 3 --> F == 3

_UpperCamelCase       = dijkstra(Ga, '''E''', '''F''')
print(short_distance)  # E -- 2 --> G -- 1 --> F == 3

if __name__ == "__main__":
     import doctest

     doctest.testmod()








from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_UpperCamelCase       = {'''configuration_nat''': ['''NAT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''NatConfig''']}


try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase       = [
         '''NAT_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''NatForImageClassification''',
         '''NatModel''',
         '''NatPreTrainedModel''',
         '''NatBackbone''',
     ]

if TYPE_CHECKING:
     from .configuration_nat import NAT_PRETRAINED_CONFIG_ARCHIVE_MAP, NatConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_nat import (
              NAT_PRETRAINED_MODEL_ARCHIVE_LIST,
              NatBackbone,
              NatForImageClassification,
              NatModel,
              NatPreTrainedModel,
          )

else:
     import sys

     _UpperCamelCase       = _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)

