code: def _converged(self):
          
          diff = self.local_prior - self.local_posterior_
          max_diff = np.max(np.fabs(diff))
          if self.verbose:
              _, mse = self._mse_converged()
              diff_ratio = np.sum(diff ** 2) / np.sum(self.local_posterior_ ** 2)
              logger.info(
                  'tfa prior posterior max diff %f mse %f diff_ratio %f' %
                  ((max_diff, mse, diff_ratio)))
          if max_diff > self.threshold:
              return False, max_diff
          else:
              return True, max_diff
docs: Check convergence based on maximum absolute difference
  
          Returns
          -------
  
          converged : boolean
              Whether the parameter estimation converged.
  
          max_diff : float
              Maximum absolute difference between prior and posterior.