code: def forward(self, x, edge_index, batch=None):
      hists = []
      for conv in self.convs:
          x = conv(x, edge_index)
          hists.append(conv.histogram(x, batch, norm=True))
      return hists
  
file_path: pytorch_geometric/examples/wl_kernel.py
imports: import argparse
  import os.path
  import warnings
  import torch
  from sklearn.exceptions import ConvergenceWarning
  from sklearn.metrics import accuracy_score
  from sklearn.svm import LinearSVC
  from torch_geometric.data import Batch
  from torch_geometric.datasets import TUDataset
  from torch_geometric.nn import WLConv
label_desc: Use image node_id 2 for calling the WL obj's underlying member method code with example usage: obj.forward(x, edge_index, batch) and returns: hists