code: def c_noise(self, sigma):
      if self.ddpm:
          return torch.abs(
              self.ddpm_sigmas - sigma
          ).argmin()  # iddpm practical (c.3.4: 3rd bullet)
      return 1 / 4 * sigma.log()
  
file_path: diffusion-for-beginners/samplers/heun.py
imports: import torch
  from math import sqrt
label_desc: Use image node_id 5 for calling the HeunSampler obj's underlying member method code with example usage: obj.c_noise(sigma) and returns: unknown, torch