class_docstr: Stochastic sampling from Karras et al. [1] tailored to the Variance-Expanding (VE) models [2]. Use Algorithm 2 and
  the VE column of Table 1 from [1] for reference.
  
  [1] Karras, Tero, et al. "Elucidating the Design Space of Diffusion-Based Generative Models."
  https://arxiv.org/abs/2206.00364 [2] Song, Yang, et al. "Score-based generative modeling through stochastic
  differential equations." https://arxiv.org/abs/2011.13456
class_docstr_tok: ["Stochastic","sampling","from","Karras","et","al",".","[","1","]","tailored","to","the","Variance-Expanding","(","VE",")","models","[","2","]",".","Use","Algorithm","2","and","the","VE","column","of","Table","1","from","[","1","]","for","reference",".","[","1","]","Karras",",","Tero",",","et","al",".","``","Elucidating","the","Design","Space","of","Diffusion-Based","Generative","Models",".","''","https",":","\/\/arxiv.org\/abs\/2206.00364","[","2","]","Song",",","Yang",",","et","al",".","``","Score-based","generative","modeling","through","stochastic","differential","equations",".","''","https",":","\/\/arxiv.org\/abs\/2011.13456"]
code: def step_correct(
      self,
      model_output: Union[paddle.Tensor, np.ndarray],
      sigma_hat: float,
      sigma_prev: float,
      sample_hat: Union[paddle.Tensor, np.ndarray],
      sample_prev: Union[paddle.Tensor, np.ndarray],
      derivative: Union[paddle.Tensor, np.ndarray],
  ):
      pred_original_sample = sample_prev + sigma_prev * model_output
      derivative_corr = (
          sample_prev - pred_original_sample
      ) / sigma_prev
      sample_prev = sample_hat + (sigma_prev - sigma_hat) * (
          0.5 * derivative + 0.5 * derivative_corr
      )
      return {"prev_sample": sample_prev, "derivative": derivative_corr}
  
file_path: PaddleHub/modules/image/text_to_image/stable_diffusion/diffusers/schedulers/scheduling_karras_ve.py
imports: from typing import Union
  import numpy
  import paddle
  from ..configuration_utils import ConfigMixin
  from ..configuration_utils import register_to_config
  from .scheduling_utils import SchedulerMixin
label_desc: Use image node_id 5 for calling the KarrasVeScheduler obj's underlying member method code with example usage: obj.step_correct(model_output, sigma_hat, sigma_prev, sample_hat, sample_prev, derivative) and returns: dict