code: def pretrans_edges(self, edges):
      z2 = torch.cat([edges.src["h"], edges.dst["h"]], dim=1)
      vector_field = edges.data["eig"]
      return {"e": self.pretrans(z2), "vector_field": vector_field}
  
imports: import argparse
  import random
  import dgl
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.optim
  from dgl.dataloading import GraphDataLoader
  from ogb.graphproppred import Evaluator
  from ogb.graphproppred.mol_encoder import AtomEncoder
  from preprocessing import prepare_dataset
  from torch.utils.data import Dataset
  from tqdm import tqdm
label_desc: Use image node_id 2 for calling the DGNLayer obj's underlying member method code with example usage: obj.pretrans_edges(edges) and returns: dict