* `beta_schedule`: the type of noise schedule to use for inference and training.
* `beta_start` and `beta_end`: the start and end noise values for the noise schedule.  
To predict a slightly less noisy image, pass the following to the scheduler's [`~diffusers.DDPMScheduler.step`] method: model output, `timestep`, and current `sample`.  
```py
>>> less_noisy_sample = scheduler.step(model_output=noisy_residual, timestep=2, sample=noisy_sample).prev_sample
>>> less_noisy_sample.shape