



from math import loga





def 		a__			(		_UpperCamelCase			: int							):
   if a < 0:
      raise ValueError('''Input value must be a positive integer'''							)
   elif isinstance(_UpperCamelCase ,_UpperCamelCase							):
      raise TypeError('''Input value must be a \'int\' type'''							)
   return 0 if (a == 0) else int(loga(a & -a							)							)


if __name__ == "__main__":
  import doctest

  doctest.testmod()











import torch

from diffusers import StableDiffusionPipeline


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

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

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






