code: def on_train_end(self, trainer, pl_module) -> None:
      # reset current epoch = 0 after each run
      super().on_train_end(trainer, pl_module)
      trainer.fit_loop.epoch_progress.current.processed = 0
  
imports: from typing import Any
  import torch
  import time
  from pytorch_lightning.callbacks import Callback
  from pytorch_lightning.loops.dataloader.evaluation_loop import EvaluationLoop
  from bigdl.nano.utils.common import invalidInputError
  from collections import ChainMap
  from torchmetrics import Metric
label_desc: Use image node_id 1 for calling the ResetCallback obj's underlying member method code with example usage: obj.on_train_end(trainer, pl_module) without return types