code: def update_U(U: Tensor, y_one_hot: Tensor, pred: Tensor, W: Tensor):
      global eta_sup
  
      # Update the smoothness loss via LGC:
      U = lazy_adj @ U
  
      # Update the supervised loss via SEB:
      dU_sup = 2 * (S @ (-y_one_hot + pred)) @ W
      U = U - eta_sup * dU_sup
  
      eta_sup = eta_sup * decline
      return U
  
file_path: pytorch_geometric/examples/ogc.py
imports: import argparse
  import os.path
  import time
  import warnings
  import torch
  import torch.nn.functional
  from torch import Tensor
  import torch_geometric.transforms
  from torch_geometric.data import Data
  from torch_geometric.datasets import Planetoid
  from torch_geometric.utils import one_hot
label_desc: Use image node_id 1 for calling a global function with example usage: update_U(U, y_one_hot, pred, W) and returns: U