class_docstr: The original annealed Langevin dynamics predictor in NCSN/NCSNv2.
class_docstr_tok: ["The","original","annealed","Langevin","dynamics","predictor","in","NCSN\/NCSNv2","."]
code: def __init__(self, sde, score_fn, snr, n_steps):
      super().__init__(sde, score_fn, snr, n_steps)
      if not isinstance(sde, (sdes.OUVESDE,)):
          raise NotImplementedError(
              f"SDE class {sde.__class__.__name__} not yet supported."
          )
      self.sde = sde
      self.score_fn = score_fn
      self.snr = snr
      self.n_steps = n_steps
  
file_path: espnet/espnet2/enh/diffusion/sampling/correctors.py
imports: import abc
  import torch
  import espnet2.enh.diffusion.sdes
label_desc: Use image node_id 1 to create a new AnnealedLangevinDynamics object from inherited base classes: Corrector with example: obj = AnnealedLangevinDynamics(sde, score_fn, snr, n_steps)