code: def forward(self, z, edge_index, edge_type):
      z_src, z_dst = z[edge_index[0]], z[edge_index[1]]
      rel = self.rel_emb[edge_type]
      return torch.sum(z_src * rel * z_dst, dim=1)
  
imports: import os.path
  import time
  import torch
  import torch.nn.functional
  from torch.nn import Parameter
  from tqdm import tqdm
  from torch_geometric.datasets import RelLinkPredDataset
  from torch_geometric.nn import GAE, RGCNConv
label_desc: Use image node_id 3 for calling the DistMultDecoder obj's underlying member method code with example usage: obj.forward(z, edge_index, edge_type) and returns: torch