




import numpy as np
import PIL
import torch
import torchvision.transforms as T
import torchvision.transforms.functional as TF
from PIL import Image






def    snake_case   (				A		,  A=256     )				->				Union[str, Any]:




	'''simple docstring'''


	lowerCamelCase_				:						Optional[Any]				  =				min(img.size     )

	if s < target_image_size:
		raise ValueError(f"min dim for image {s} < {target_image_size}"     )

	lowerCamelCase_				:						Optional[Any]				  =				target_image_size / s
	lowerCamelCase_				:						Optional[int]				  =				(round(r * img.size[1]     ), round(r * img.size[0]     ))
	lowerCamelCase_				:						Any				  =				TF.resize(A		,  A		,  interpolation=PIL.Image.LANCZOS     )
	lowerCamelCase_				:						str				  =				TF.center_crop(A		,  output_size=2 * [target_image_size]     )
	lowerCamelCase_				:						Union[str, Any]				  =				torch.unsqueeze(T.ToTensor()(A     )		,  0     )
	return img






def    snake_case   (				A     )				->				Optional[Any]:




	'''simple docstring'''


	lowerCamelCase_				:						Dict				  =				2.0 * x - 1.0
	return x






def    snake_case   (				A		,  A=True		,  A="RGB"     )				->				Optional[Any]:




	'''simple docstring'''


	lowerCamelCase_				:						List[Any]				  =				x.detach().cpu()
	if process:
		lowerCamelCase_				:						Dict				  =				post_process_tensor(A     )
	lowerCamelCase_				:						Tuple				  =				x.numpy()
	if process:
		lowerCamelCase_				:						Dict				  =				(255 * x).astype(np.uinta     )
	lowerCamelCase_				:						Tuple				  =				Image.fromarray(A     )
	if not x.mode == mode:
		lowerCamelCase_				:						List[str]				  =				x.convert(A     )
	return x






def    snake_case   (				A     )				->				Any:




	'''simple docstring'''


	lowerCamelCase_				:						Optional[int]				  =				torch.clamp(A		,  -1.0		,  1.0     )
	lowerCamelCase_				:						List[str]				  =				(x + 1.0) / 2.0
	lowerCamelCase_				:						Any				  =				x.permute(1		,  2		,  0     )
	return x






def    snake_case   (				A     )				->				Tuple:




	'''simple docstring'''


	lowerCamelCase_				:						Dict				  =				post_process_tensor(x.squeeze()     )
	return x.permute(2		,  0		,  1     ).unsqueeze(0     )






'''simple docstring'''







A					       =[[0, 1, 1], [0, 0, 1], [1, 0, 0]]


class      _a    :
       def __init__(      self		:      Optional[int]  ,							lowercase		:      str							):



           '''simple docstring'''

           UpperCAmelCase     			=						name
           UpperCAmelCase     			=						[]
           UpperCAmelCase     			=						[]
       def        A (      self		:      Union[str, Any]  ,							lowercase		:      int							):



           '''simple docstring'''

           self.inbound.append(lowercase							)
       def        A (      self		:      List[str]  ,							lowercase		:      Optional[Any]							):



           '''simple docstring'''

           self.outbound.append(lowercase							)







       def __repr__(      self		:      Any							):



           '''simple docstring'''

           return f"<node={self.name} inbound={self.inbound} outbound={self.outbound}>"






def 		snake_case_				(_a      :				str       ,  _a      :				str=3       ,  _a      :				Any=0.85	):
    UpperCAmelCase     			=						{}
    for node in nodes:
        UpperCAmelCase     			=						1

    UpperCAmelCase     			=						{}
    for node in nodes:
        UpperCAmelCase     			=						len(node.outbound	)

    for i in range(_a	):
        print(F"======= Iteration {i + 1} ======="	)
        for _, node in enumerate(_a	):
            UpperCAmelCase     			=						(1 - d) + d * sum(
                ranks[ib] / outbounds[ib] for ib in node.inbound	)
        print(_a	)





def 		snake_case_				():
    UpperCAmelCase     			=						list(input('''Enter Names of the Nodes: '''	).split()	)

    UpperCAmelCase     			=						[Node(_a	) for name in names]

    for ri, row in enumerate(_a	):
        for ci, col in enumerate(_a	):
            if col == 1:
                nodes[ci].add_inbound(names[ri]	)
                nodes[ri].add_outbound(names[ci]	)

    print('''======= Nodes ======='''	)
    for node in nodes:
        print(_a	)

    page_rank(_a	)


if __name__ == "__main__":
   main()




