code: def on_train_epoch_end(self) -> None:
      # Logging privacy spent: (epsilon, delta)
      epsilon = self.privacy_engine.get_epsilon(self.delta)
      self.log("epsilon", epsilon, on_epoch=True, prog_bar=True)
  
imports: import os
  import warnings
  import pytorch_lightning
  import torch.nn
  import torch.nn.functional
  import torch.optim
  import torchmetrics
  from opacus import PrivacyEngine
  from opacus.data_loader import DPDataLoader
  from opacus.lightning import DPLightningDataModule
  from pl_bolts.datamodules import MNISTDataModule
  from pytorch_lightning.utilities.cli import LightningCLI
label_desc: Use image node_id 6 for calling the LitSampleConvNetClassifier obj's underlying member method code with example usage: obj.on_train_epoch_end() without return types