nd 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 step() method: model output, timestep, and current sample.   Copied >>> less_noisy_sample = scheduler.step(model_output=noisy_residual, timestep=2, sample=noisy_sample).prev_sample
>>> less_noisy_sample.shape
torch.Size([1, 3, 256, 256]) The less_noisy_sample can be passed to the next timestep where i