code: def bn(self, i, x):
      batch_size, num_nodes, num_channels = x.size()
  
      x = x.view(-1, num_channels)
      x = getattr(self, f"bn{i}")(x)
      x = x.view(batch_size, num_nodes, num_channels)
      return x
  
file_path: pytorch_geometric/examples/proteins_diff_pool.py
imports: import os.path
  import time
  from math import ceil
  import torch
  import torch.nn.functional
  import torch_geometric.transforms
  from torch_geometric.datasets import TUDataset
  from torch_geometric.loader import DenseDataLoader
  from torch_geometric.nn import DenseSAGEConv, dense_diff_pool
label_desc: Use image node_id 2 for calling the GNN obj's underlying member method code with example usage: obj.bn(i, x) and returns: x