class_docstr: Training with exponentially growing learning rate
class_docstr_tok: ["Training","with","exponentially","growing","learning","rate"]
code: def after_batch(self):
      super().after_batch()
      if self.smooth_loss < self.best_loss:
          self.best_loss = self.smooth_loss
      if self.smooth_loss > 4 * self.best_loss and self.stop_div:
          raise CancelFitException()
      if self.train_iter >= self.num_it:
          raise CancelFitException()
  
imports: from __future__ import annotations
  from ..basics import *
  from .tracker import SaveModelCallback
label_desc: Use image node_id 4 for calling the LRFinder obj's underlying member method code with example usage: obj.after_batch() without return types