





'''simple docstring'''






import torch

from diffusers import StableDiffusionPipeline


A__							:  Optional[int]    ='''path-to-your-trained-model'''
A__							:  Tuple    =StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to('''cuda''')

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

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













'''simple docstring'''






def   UpperCamelCase__ (						lowerCAmelCase    ):





      """simple docstring"""


      if not isinstance(lowerCAmelCase				,      lowerCAmelCase    ):
            raise ValueError("""Input must be an integer"""    )
      if input_num <= 0:
            raise ValueError("""Input must be positive"""    )
      return sum(
          divisor for divisor in range(1				,      input_num // 2 + 1    ) if input_num % divisor == 0    )


if __name__ == "__main__":
      import doctest

      doctest.testmod()






