code: def update(self, max_norm=None):
          
          if max_norm is not None:
              self._clip_by_global_norm(max_norm)
          self._module.update()
docs: Updates parameters according to the installed optimizer and the gradients computed
          in the previous forward-backward batch. Gradients are clipped by their global norm
          if `max_norm` is set.
  
          Parameters
          ----------
          max_norm: float, optional
              If set, clip values of all gradients the ratio of the sum of their norms.