class_docstr: Accumulate gradients before updating weights
class_docstr_tok: ["Accumulate","gradients","before","updating","weights"]
code: def after_loss(self):
      self.learn.loss_grad /= self.n_acc / find_bs(self.learn.yb)
  
imports: from __future__ import annotations
  from ..basics import *
  from .progress import *
  from .fp16 import *
label_desc: Use image node_id 3 for calling the GradientAccumulation obj's underlying member method code with example usage: obj.after_loss() without return types