code: def __init__(self, **kwargs):
      super().__init__()
  
      score_model = kwargs["score_model"]
      score_model_class = score_choices.get_class(kwargs["score_model"])
      self.dnn = score_model_class(**kwargs["score_model_conf"])
      self.sde = sde_choices.get_class(kwargs["sde"])(
          **kwargs["sde_conf"]
      )
      self.loss_type = getattr(kwargs, "loss_type", "mse")
      self.t_eps = getattr(kwargs, "t_eps", 3e-2)
  
file_path: espnet/espnet2/enh/diffusion/score_based_diffusion.py
imports: import math
  from abc import ABC, abstractmethod
  from collections import OrderedDict
  from typing import Dict, Optional, Tuple
  import torch
  import espnet2.enh.diffusion.sampling
  from espnet2.enh.diffusion.abs_diffusion import AbsDiffusion
  from espnet2.enh.diffusion.sdes import OUVESDE, OUVPSDE, SDE
  from espnet2.enh.layers.dcunet import DCUNet
  from espnet2.enh.layers.ncsnpp import NCSNpp
  from espnet2.train.class_choices import ClassChoices
label_desc: Use image node_id 1 to create a new ScoreModel object from inherited base classes: AbsDiffusion with example: obj = ScoreModel()