code: def __init__(self, num_nodes, h_dim, num_rels):
      super().__init__()
      # two-layer RGCN
      self.emb = nn.Embedding(num_nodes, h_dim)
      self.conv1 = RelGraphConv(
          h_dim,
          h_dim,
          num_rels,
          regularizer="bdd",
          num_bases=100,
          self_loop=True,
      )
      self.conv2 = RelGraphConv(
          h_dim,
          h_dim,
          num_rels,
          regularizer="bdd",
          num_bases=100,
          self_loop=True,
      )
      self.dropout = nn.Dropout(0.2)
  
imports: import dgl
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  import tqdm
  from dgl.data.knowledge_graph import FB15k237Dataset
  from dgl.dataloading import GraphDataLoader
  from dgl.nn.pytorch import RelGraphConv
label_desc: Use image node_id 1 to create a new RGCN object from inherited base classes: nn with example: obj = RGCN(num_nodes, h_dim, num_rels)