class_docstr: `Callback` that tracks the number of iterations done and properly sets training/eval mode
class_docstr_tok: ["`","Callback","`","that","tracks","the","number","of","iterations","done","and","properly","sets","training\/eval","mode"]
code: def after_create(self):
      self.learn.n_epoch = 1
  
imports: from __future__ import annotations
  from ..data.all import *
  from ..optimizer import *
  from ..losses import BaseLoss
label_desc: Use image node_id 1 for calling the TrainEvalCallback obj's underlying member method code with example usage: obj.after_create() without return types