code: def forward(self, adj, anext, s_l):
      link_pred_loss = (adj - s_l.matmul(s_l.transpose(-1, -2))).norm(
          dim=(1, 2)
      )
      link_pred_loss = link_pred_loss / (adj.size(1) * adj.size(2))
      return link_pred_loss.mean()
  
file_path: dgl/examples/pytorch/diffpool/model/loss.py
imports: import torch
  import torch.nn
label_desc: Use image node_id 1 for calling the LinkPredLoss obj's underlying member method code with example usage: obj.forward(adj, anext, s_l) and returns: link_pred_loss