code: def load_diffusion(self):
      model = instantiate_from_config(self.diffusion_config)
      self.diffusion_model = model.eval()
      self.diffusion_model.train = disabled_train
      for param in self.diffusion_model.parameters():
          param.requires_grad = False
  
imports: import os
  import torch
  import pytorch_lightning
  from omegaconf import OmegaConf
  from torch.nn import functional
  from torch.optim import AdamW
  from torch.optim.lr_scheduler import LambdaLR
  from copy import deepcopy
  from einops import rearrange
  from glob import glob
  from natsort import natsorted
  from ldm.modules.diffusionmodules.openaimodel import EncoderUNetModel, UNetModel
  from ldm.util import log_txt_as_img, default, ismap, instantiate_from_config
label_desc: Use image node_id 3 for calling the NoisyLatentImageClassifier obj's underlying member method code with example usage: obj.load_diffusion() without return types