nerated by iterating forward n timesteps and inference occurs by propagating backward through the timesteps. Based on the timestep, a scheduler may be discrete in which case the timestep is an int or continuous in which case the timestep is a float. Depending on the context, a scheduler defines how to iteratively add noise to an image or how to update a sample based on a model’s output: during training, a scheduler adds noise (there are differe