 tensor.
  Predict the sample from the previous timestep by reversing the SDE. This function propagates the diffusion
process from the learned model outputs (most often the predicted noise).  CMStochasticIterativeSchedulerOutput  class diffusers.schedulers.scheduling_consistency_models.CMStochasticIterativeSchedulerOutput  < source > ( prev_sample: FloatTensor  )   Parameters   prev_sample (torch.FloatTensor of shape (batch_size, num_channels, 