KDPM2AncestralDiscreteScheduler The KDPM2DiscreteScheduler with ancestral sampling is inspired by the Elucidating the Design Space of Diffusion-Based Generative Models paper, and the scheduler is ported from and created by Katherine Crowson. The original codebase can be found at crowsonkb/k-diffusion.  KDPM2AncestralDiscreteScheduler  class diffusers.KDPM2AncestralDiscreteScheduler  < source > ( num_train_timesteps: int = 1000 beta_start: float = 0.00085 beta_end: float = 0.012 beta_schedule: str = 'linear' trained_betas: Union = None use_karras_sigmas: Optional = False prediction_type: str = 'epsilon' timestep_spacing: str = 'linspace' steps_offset: int = 0  )   Parameters   num_train_timesteps (int, defaults to 1000) —