code: def kldiv_model(prediction, fm):
      
      (_, r_x) = calc_resize_factor(prediction, fm.image_size)
      q = np.array(prediction, copy=True)
      q -= np.min(q.flatten())
      q /= np.sum(q.flatten())
      return kldiv(None, q, distp = fm, scale_factor = r_x)
docs: wraps kldiv functionality for model evaluation
  
      input:
          prediction: 2D matrix
              the model salience map
          fm : fixmat
              Should be filtered for the image corresponding to the prediction