code: def lmbd(self, t):
      log_alpha = self.log_alpha(t, self.schedule)
      # log_sigma = 0.5 * np.log(1. - np.exp(2. * log_alpha))
      sigma = np.sqrt(1.0 - np.exp(2 * log_alpha))
      log_sigma = np.log(sigma)
      return log_alpha, sigma, (log_alpha - log_sigma)
  
file_path: diffusion-for-beginners/samplers/dpm_solver.py
imports: import torch
  import numpy
label_desc: Use image node_id 7 for calling the DPMSampler obj's underlying member method code with example usage: obj.lmbd(t) and returns: log_alpha,  sigma,  unknown