






'''simple docstring'''





import heapq






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


a	: List[str]      =				{
    """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]],
}
a	: str      =				{
    """B""": [["""C""", 1]],
    """C""": [["""D""", 1]],
    """D""": [["""F""", 1]],
    """E""": [["""B""", 1], ["""F""", 3]],
    """F""": [],
}
a	: Dict      =				{
    """B""": [["""C""", 1]],
    """C""": [["""D""", 1]],
    """D""": [["""F""", 1]],
    """E""": [["""B""", 1], ["""G""", 2]],
    """F""": [],
    """G""": [["""F""", 1]],
}

a	: List[Any]      =				dijkstra(G, "E", "C")
print(short_distance)  # E -- 3 --> F -- 3 --> C == 6

a	: Tuple      =				dijkstra(Ga, "E", "F")
print(short_distance)  # E -- 3 --> F == 3

a	: List[Any]      =				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, is_vision_available


a	: Union[str, Any]      =				{
    "configuration_mobilenet_v1": [
        "MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "MobileNetV1Config",
        "MobileNetV1OnnxConfig",
    ],
}

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a	: int      =				["MobileNetV1FeatureExtractor"]
       a	: int      =				["MobileNetV1ImageProcessor"]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a	: int      =				[
           "MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST",
           "MobileNetV1ForImageClassification",
           "MobileNetV1Model",
           "MobileNetV1PreTrainedModel",
           "load_tf_weights_in_mobilenet_v1",
       ]


if TYPE_CHECKING:
       from .configuration_mobilenet_va import (
           MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP,
           MobileNetVaConfig,
           MobileNetVaOnnxConfig,
       )

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .feature_extraction_mobilenet_va import MobileNetVaFeatureExtractor
              from .image_processing_mobilenet_va import MobileNetVaImageProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_mobilenet_va import (
                  MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST,
                  MobileNetVaForImageClassification,
                  MobileNetVaModel,
                  MobileNetVaPreTrainedModel,
                  load_tf_weights_in_mobilenet_va,
              )


else:
       import sys

       a	: str      =				_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


