


"""simple docstring"""




class   __a      :
 def __init__(       self    ,			lowerCAmelCase__    ,			lowerCAmelCase__    ,			lowerCAmelCase__			) ->    Tuple:




        '''simple docstring'''
        lowercase__:       List[str]        =       name
        lowercase__:       Any        =       value
        lowercase__:       str        =       weight
 def __repr__(       self			) ->    Dict:




        '''simple docstring'''
        return F'{self.__class__.__name__}({self.name}, {self.value}, {self.weight})'
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    str:




        '''simple docstring'''
        return self.value
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Optional[int]:




        '''simple docstring'''
        return self.name
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    int:




        '''simple docstring'''
        return self.weight
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Tuple:




        '''simple docstring'''
        return self.value / self.weight





def        snake_case_					(  snake_case      ,							snake_case      ,							snake_case					)  ->    Tuple:
       lowercase__:       List[Any]        =       []
       for i in range(len(snake_case					)					):
              menu.append(Things(name[i]      ,							value[i]      ,							weight[i]					)					)
       return menu




def        snake_case_					(  snake_case      ,							snake_case      ,							snake_case					)  ->    Any:
       lowercase__:       str        =       sorted(snake_case      ,							key=snake_case      ,							reverse=snake_case					)
       lowercase__:       Dict        =       []
       lowercase__:       List[str]        =       0.0, 0.0
       for i in range(len(snake_case					)					):
              if (total_cost + items_copy[i].get_weight()) <= max_cost:
                     result.append(items_copy[i]					)
                     total_cost += items_copy[i].get_weight()
                     total_value += items_copy[i].get_value()
       return (result, total_value)




def        snake_case_					(  )  ->    Optional[Any]:
       pass


if __name__ == "__main__":
 import doctest

 doctest.testmod()






import torch

from diffusers import StableDiffusionPipeline


__lowerCAmelCase			=							'''path-to-your-trained-model'''
__lowerCAmelCase			=							StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to('''cuda''')

__lowerCAmelCase			=							'''A photo of sks dog in a bucket'''
__lowerCAmelCase			=							pipe(prompt, num_inference_steps=50, guidance_scale=7.5).images[0]

image.save('''dog-bucket.png''')


