code: def _prepare(g, subgraph_dicts):
      edge_index = torch.stack(g.edges())
  
      identifiers = None
      for subgraph_dict in subgraph_dicts:
          counts = subgraph_isomorphism_edge_counts(
              edge_index, subgraph_dict
          )
          identifiers = (
              counts
              if identifiers is None
              else torch.cat((identifiers, counts), 1)
          )
  
      g.edata["subgraph_counts"] = identifiers.long()
  
      return g
  
file_path: dgl/examples/pytorch/ogb/directional_GSN/preprocessing.py
imports: import os
  import graph_tool
  import graph_tool.topology
  import networkx
  import numpy
  import torch
  from dgl.data.utils import load_graphs, save_graphs
  from ogb.graphproppred import DglGraphPropPredDataset
  from tqdm import tqdm
label_desc: Use image node_id 6 for calling a global function with example usage: _prepare(g, subgraph_dicts) and returns: g