code: def on_backward_end(self, **kwargs):
          "Clip the gradient before the optimizer step."
          if self.clip: nn.utils.clip_grad_norm_(self.learn.model.parameters(), self.clipf on_backward_end(self, **kwargs):
          "Clip the gradient before the optimizer step."
          if self.clip: nn.utils.clip_grad_norm_(self.learn.model.parameters(), self.clip)
docs: Clip the gradient before the optimizer step.