"""simple docstring"""







import torch

from diffusers import StableDiffusionPipeline


_a     :     Optional[Any]= 'path-to-your-trained-model'
_a     :     Union[str, Any]= StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to("cuda")

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

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







"""simple docstring"""




def lowercase_  (   _snake_case   ,_snake_case						):
							return 1 if input_a == input_a else 0

def lowercase_  (   ):
							assert xnor_gate(0   ,0						) == 1
							assert xnor_gate(0   ,1						) == 0
							assert xnor_gate(1   ,0						) == 0
							assert xnor_gate(1   ,1						) == 1


if __name__ == "__main__":
					print(xnor_gate(0, 0))
					print(xnor_gate(0, 1))
					print(xnor_gate(1, 0))
					print(xnor_gate(1, 1))




