


def        snake_case_					(  snake_case      ,							snake_case					)  ->    List[str]:
       lowercase__:       int        =       0
       while b > 0:
              if b & 1:
                     res += a

              a += a
              b >>= 1

       return res




def        snake_case_					(  snake_case      ,							snake_case      ,							snake_case					)  ->    int:
       lowercase__:       Optional[int]        =       0
       while b > 0:
              if b & 1:
                     lowercase__:       Optional[int]        =       ((res % c) + (a % c)) % c

              a += a
              b >>= 1

       return res






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''')


