Start by scaling the input with the initial noise distribution, *sigma*, the noise scale value, which is required for improved schedulers like [`UniPCMultistepScheduler`]:  
```py
>>> 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 needs to do three things:  
1. Set the scheduler's timesteps to use during denoising.