s = latents.to(torch_device)

Denoise the image
	
Start by scaling the input with the initial noise distribution, sigma, the noise scale value, which is required for improved schedulers like UniPCMultistepScheduler:


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>>> latents = latents * scheduler.init_noise_sigma
The last step is to create the denoising loop that’ll progressively transform the pure noise in latents to an image described by your prompt. Remember, the denoising loop 