



'''simple docstring'''
import torch

from diffusers import StableDiffusionPipeline


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

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

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







'''simple docstring'''
def A__       (	UpperCAmelCase_    ,    UpperCAmelCase_				):
						return int((input_a, input_a).count(0				) != 0				)






def A__       (	):
						assert nand_gate(0    ,    0				) == 1
						assert nand_gate(0    ,    1				) == 1
						assert nand_gate(1    ,    0				) == 1
						assert nand_gate(1    ,    1				) == 0


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


