code: def pred_den_msg(self, edges):
      prob = edges.data["prob_conn"]
      res = edges.data["raw_affine"] * (prob[:, 1] - prob[:, 0])
      return {"pred_den_msg": res}
  
file_path: dgl/examples/pytorch/hilander/models/lander.py
imports: import dgl
  import dgl.function
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from .focal_loss import FocalLoss
  from .graphconv import GraphConv
label_desc: Use image node_id 3 for calling the LANDER obj's underlying member method code with example usage: obj.pred_den_msg(edges) and returns: dict