code: def denoise(self, x, denoiser, sigma, cond, uc):
      denoised = denoiser(
          *self.guider.prepare_inputs(x, sigma, cond, uc)
      )
      denoised = self.guider(denoised, sigma)
      return denoised
  
imports: from typing import Dict, Union
  import torch
  from omegaconf import ListConfig, OmegaConf
  from tqdm import tqdm
  from ...modules.diffusionmodules.sampling_utils import get_ancestral_step, linear_multistep_coeff, to_d, to_neg_log_sigma, to_sigma
  from ...util import append_dims, default, instantiate_from_config
label_desc: Use image node_id 3 for calling the BaseDiffusionSampler obj's underlying member method code with example usage: obj.denoise(x, denoiser, sigma, cond, uc) and returns: denoised