





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')








import os




def  __UpperCAmelCase(   ):
       with open(os.path.dirname(lowercase_   ) + '''/p022_names.txt'''   ) as file:
              _lowerCamelCase				:  Optional[int]						=		str(file.readlines()[0]   )
              _lowerCamelCase				:  List[Any]						=		names.replace('''"'''			,     ''''''   ).split(''','''   )

       names.sort()

       _lowerCamelCase				:  Optional[int]						=		0
       _lowerCamelCase				:  Tuple						=		0

       for i, name in enumerate(lowercase_   ):
              for letter in name:
                     name_score += ord(lowercase_   ) - 64

              total_score += (i + 1) * name_score
              _lowerCamelCase				:  Optional[int]						=		0
       return total_score


if __name__ == "__main__":
       print(solution())

