



def 	__snake_case      (     _UpperCAmelCase  ,					_UpperCAmelCase							):
    print('''\nVertex Distance'''							)
    for i in range(_A							):
        if dist[i] != float('''inf'''							):
            print(_A  ,					'''\t'''  ,					int(dist[i]							)  ,					end='''\t'''							)
        else:
            print(_A  ,					'''\t'''  ,					'''INF'''  ,					end='''\t'''							)
        print()





def 	__snake_case      (     _UpperCAmelCase  ,					_UpperCAmelCase  ,					_UpperCAmelCase							):
    __a					=							float('''inf'''							)
    __a					=							-1
    for i in range(_A							):
        if (not vset[i]) and mdist[i] < min_val:
            __a					=							i
            __a					=							mdist[i]
    return min_ind





def 	__snake_case      (     _UpperCAmelCase  ,					_UpperCAmelCase  ,					_UpperCAmelCase							):
    __a					=							[float('''inf'''							) for _ in range(_A							)]
    __a					=							[False for _ in range(_A							)]
    __a					=							0.0

    for _ in range(v - 1							):
        __a					=							min_dist(_A  ,					_A  ,					_A							)
        __a					=							True

        for i in range(_A							):
            if (
                (not vset[i])
                and graph[u][i] != float('''inf'''							)
                and mdist[u] + graph[u][i] < mdist[i]
            ):
                __a					=							mdist[u] + graph[u][i]

    print_dist(_A  ,					_A							)


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

 __snake_case		:Tuple 						=	[[float('''inf''') for i in range(V)] for j in range(V)]

 for i in range(V):
  __snake_case		:List[str] 						=	0.0

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

 __snake_case		:Optional[Any] 						=	int(input('''\nEnter shortest path source:''').strip())
 dijkstra(graph, V, gsrc)








import unittest

import numpy as np
import PIL
import torch

from diffusers.image_processor import VaeImageProcessor







class 		__magic_name__     (				unittest.TestCase				):

   '''simple docstring'''




   @property
   def 					_UpperCAmelCase					(							self			)				->       Tuple:






     """simple docstring"""






     a__    =1
     a__    =3
     a__    =8
     a__    =8

     a__    =torch.rand((batch_size, num_channels, height, width)			)

     return sample



   def 					_UpperCAmelCase					(							self,       lowercase_			)				->       int:






     """simple docstring"""






     if isinstance(image[0],       PIL.Image.Image			):
       return np.stack([np.array(lowercase_			) for i in image],       axis=0			)
     elif isinstance(lowercase_,       torch.Tensor			):
       return image.cpu().numpy().transpose(0,       2,       3,       1			)
     return image



   def 					_UpperCAmelCase					(							self			)				->       int:






     """simple docstring"""






     a__    =VaeImageProcessor(do_resize=lowercase_,       do_normalize=lowercase_			)

     a__    =self.dummy_sample
     a__    =self.to_np(lowercase_			)

     for output_type in ["pt", "np", "pil"]:
       a__    =image_processor.postprocess(
           image_processor.preprocess(lowercase_			),       output_type=lowercase_,       )
       a__    =self.to_np(lowercase_			)
       a__    =(input_np * 255).round() if output_type == '''pil''' else input_np
       assert (
           np.abs(in_np - out_np			).max() < 1E-6
       ), F"""decoded output does not match input for output_type {output_type}"""



   def 					_UpperCAmelCase					(							self			)				->       List[Any]:






     """simple docstring"""






     a__    =VaeImageProcessor(do_resize=lowercase_,       do_normalize=lowercase_			)
     a__    =self.dummy_sample.cpu().numpy().transpose(0,       2,       3,       1			)

     for output_type in ["pt", "np", "pil"]:
       a__    =image_processor.postprocess(image_processor.preprocess(lowercase_			),       output_type=lowercase_			)

       a__    =self.to_np(lowercase_			)
       a__    =(input_np * 255).round() if output_type == '''pil''' else input_np
       assert (
           np.abs(in_np - out_np			).max() < 1E-6
       ), F"""decoded output does not match input for output_type {output_type}"""



   def 					_UpperCAmelCase					(							self			)				->       Optional[Any]:






     """simple docstring"""






     a__    =VaeImageProcessor(do_resize=lowercase_,       do_normalize=lowercase_			)

     a__    =self.dummy_sample.cpu().numpy().transpose(0,       2,       3,       1			)
     a__    =image_processor.numpy_to_pil(lowercase_			)

     for output_type in ["pt", "np", "pil"]:
       a__    =image_processor.postprocess(image_processor.preprocess(lowercase_			),       output_type=lowercase_			)
       for i, o in zip(lowercase_,       lowercase_			):
         a__    =np.array(lowercase_			)
         a__    =self.to_np(lowercase_			) if output_type == '''pil''' else (self.to_np(lowercase_			) * 255).round()
         assert (
             np.abs(in_np - out_np			).max() < 1E-6
         ), F"""decoded output does not match input for output_type {output_type}"""



   def 					_UpperCAmelCase					(							self			)				->       Union[str, Any]:






     """simple docstring"""






     a__    =VaeImageProcessor(do_resize=lowercase_,       do_normalize=lowercase_			)

     a__    =self.dummy_sample
     a__    =input_pt_ad.squeeze(0			)

     a__    =image_processor.postprocess(
         image_processor.preprocess(lowercase_			),       output_type='''np''',       )
     a__    =image_processor.postprocess(
         image_processor.preprocess(lowercase_			),       output_type='''np''',       )

     a__    =self.to_np(self.dummy_sample			)
     a__    =input_np_ad.squeeze(0			)

     a__    =image_processor.postprocess(
         image_processor.preprocess(lowercase_			),       output_type='''np''',       )
     a__    =image_processor.postprocess(
         image_processor.preprocess(lowercase_			),       output_type='''np''',       )

     assert np.abs(out_pt_ad - out_pt_ad			).max() < 1E-6
     assert np.abs(out_np_ad - out_np_ad			).max() < 1E-6



   def 					_UpperCAmelCase					(							self			)				->       List[Any]:






     """simple docstring"""






     a__    =VaeImageProcessor(do_resize=lowercase_,       do_normalize=lowercase_			)

     a__    =self.dummy_sample
     a__    =list(lowercase_			)

     a__    =image_processor.postprocess(
         image_processor.preprocess(lowercase_			),       output_type='''np''',       )

     a__    =image_processor.postprocess(
         image_processor.preprocess(lowercase_			),       output_type='''np''',       )

     a__    =self.to_np(self.dummy_sample			)
     list(lowercase_			)

     a__    =image_processor.postprocess(
         image_processor.preprocess(lowercase_			),       output_type='''np''',       )

     a__    =image_processor.postprocess(
         image_processor.preprocess(lowercase_			),       output_type='''np''',       )

     assert np.abs(out_pt_ad - out_pt_list			).max() < 1E-6
     assert np.abs(out_np_ad - out_np_list			).max() < 1E-6
