
"""simple docstring"""



import torch

from diffusers import StableDiffusionPipeline


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

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

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



"""simple docstring"""



from __future__ import annotations

from collections.abc import Iterator





class 				a			:



      def __init__(   self     ,	UpperCamelCase_      ):
          UpperCAmelCase__	:      str     							=					value
          UpperCAmelCase__	:      Node | None     							=					None
          UpperCAmelCase__	:      Node | None     							=					None





class 				a			:



      def __init__(   self     ,	UpperCamelCase_      ):
          UpperCAmelCase__	:      str     							=					tree



      def  __snake_case							(   self     ,	UpperCamelCase_      ):
          if node is None:
              return 0
          return node.value + (
              self.depth_first_search(node.left      ) + self.depth_first_search(node.right      )
          )



      def __iter__(   self      ):
          yield self.depth_first_search(self.tree      )


if __name__ == "__main__":
    import doctest

    doctest.testmod()

