code: def on_train_epoch_end(
      self, trainer: "pl.Trainer", *args: Any
  ) -> None:
      trainer.fit_loop._skip_backward = False
  
imports: from copy import deepcopy
  from typing import Any, Callable, Dict, List, Optional, Union, cast
  import torch
  from torch import Tensor, nn
  from torch.optim.swa_utils import SWALR
  from typing_extensions import override
  import lightning.pytorch
  from lightning.fabric.utilities.types import LRScheduler
  from lightning.pytorch.callbacks.callback import Callback
  from lightning.pytorch.strategies import DeepSpeedStrategy
  from lightning.pytorch.strategies.fsdp import FSDPStrategy
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
  from lightning.pytorch.utilities.rank_zero import rank_zero_info, rank_zero_warn
  from lightning.pytorch.utilities.types import LRSchedulerConfig
label_desc: Use image node_id 8 for calling the StochasticWeightAveraging obj's underlying member method code with example usage: obj.on_train_epoch_end(trainer) without return types