code: def lr_scheduler_step(self, *args, **kwargs):
      # Needed for PyTorch 2.0 since the base class of LR schedulers changed.
      # TODO Remove once we only want to support PyTorch Lightning >= 2.0.
      return super().lr_scheduler_step(*args, **kwargs)
  
imports: import time
  from typing import Any, Dict, Tuple
  import torch
  from torch_geometric.graphgym.config import cfg
  from torch_geometric.graphgym.imports import LightningModule
  from torch_geometric.graphgym.loss import compute_loss
  from torch_geometric.graphgym.models.gnn import GNN
  from torch_geometric.graphgym.optim import create_optimizer, create_scheduler
  from torch_geometric.graphgym.register import network_dict, register_network
label_desc: Use image node_id 12 for calling the GraphGymModule obj's underlying member method code with example usage: obj.lr_scheduler_step() and returns: super