


def      _lowerCAmelCase  (							lowerCAmelCase_							:Any						,  lowerCAmelCase_							:Optional[int]							)->Any:
   '''simple docstring'''






   print("\nVertex Distance"							)
   for i in range(SCREAMING_SNAKE_CASE_							):
      if dist[i] != float("inf"							):
         print(SCREAMING_SNAKE_CASE_						,  "\t"						,  int(dist[i]							)						,  end="\t"							)
      else:
         print(SCREAMING_SNAKE_CASE_						,  "\t"						,  "INF"						,  end="\t"							)
      print()



def      _lowerCAmelCase  (							lowerCAmelCase_							:Optional[Any]						,  lowerCAmelCase_							:List[Any]						,  lowerCAmelCase_							:Optional[int]							)->Union[str, Any]:
   '''simple docstring'''






   snake_case_         =   float("inf"							)
   snake_case_         =   -1
   for i in range(SCREAMING_SNAKE_CASE_							):
      if (not vset[i]) and mdist[i] < min_val:
         snake_case_         =   i
         snake_case_         =   mdist[i]
   return min_ind



def      _lowerCAmelCase  (							lowerCAmelCase_							:List[str]						,  lowerCAmelCase_							:Optional[int]						,  lowerCAmelCase_							:Tuple							)->Dict:
   '''simple docstring'''






   snake_case_         =   [float("inf"							) for _ in range(SCREAMING_SNAKE_CASE_							)]
   snake_case_         =   [False for _ in range(SCREAMING_SNAKE_CASE_							)]
   snake_case_         =   0.0

   for _ in range(v - 1							):
      snake_case_         =   min_dist(SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_							)
      snake_case_         =   True

      for i in range(SCREAMING_SNAKE_CASE_							):
         if (
             (not vset[i])
             and graph[u][i] != float("inf"							)
             and mdist[u] + graph[u][i] < mdist[i]
         ):
            snake_case_         =   mdist[u] + graph[u][i]

   print_dist(SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_							)


if __name__ == "__main__":
   SCREAMING_SNAKE_CASE		:Optional[Any]											=       int(input('''Enter number of vertices: ''').strip())
   SCREAMING_SNAKE_CASE		:List[str]											=       int(input('''Enter number of edges: ''').strip())

   SCREAMING_SNAKE_CASE		:List[Any]											=       [[float('''inf''') for i in range(V)] for j in range(V)]

   for i in range(V):
      SCREAMING_SNAKE_CASE		:Dict											=       0.0

   for i in range(E):
      print('''\nEdge ''', i + 1)
      SCREAMING_SNAKE_CASE		:Union[str, Any]											=       int(input('''Enter source:''').strip())
      SCREAMING_SNAKE_CASE		:int											=       int(input('''Enter destination:''').strip())
      SCREAMING_SNAKE_CASE		:int											=       float(input('''Enter weight:''').strip())
      SCREAMING_SNAKE_CASE		:List[Any]											=       weight

   SCREAMING_SNAKE_CASE		:Dict											=       int(input('''\nEnter shortest path source:''').strip())
   dijkstra(graph, V, gsrc)








from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE		:str											=       {'''configuration_cvt''': ['''CVT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CvtConfig''']}


try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE		:Any											=       [
       '''CVT_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''CvtForImageClassification''',
       '''CvtModel''',
       '''CvtPreTrainedModel''',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE		:Any											=       [
       '''TF_CVT_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''TFCvtForImageClassification''',
       '''TFCvtModel''',
       '''TFCvtPreTrainedModel''',
   ]

if TYPE_CHECKING:
   from .configuration_cvt import CVT_PRETRAINED_CONFIG_ARCHIVE_MAP, CvtConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_cvt import (
          CVT_PRETRAINED_MODEL_ARCHIVE_LIST,
          CvtForImageClassification,
          CvtModel,
          CvtPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_cvt import (
          TF_CVT_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFCvtForImageClassification,
          TFCvtModel,
          TFCvtPreTrainedModel,
      )


else:
   import sys

   SCREAMING_SNAKE_CASE		:str											=       _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




