code: def __init__(self, num_nodes, h_dim, out_dim, num_rels):
      super().__init__()
      self.emb = nn.Embedding(num_nodes, h_dim)
      # two-layer RGCN
      self.conv1 = RelGraphConv(
          h_dim,
          h_dim,
          num_rels,
          regularizer="basis",
          num_bases=num_rels,
          self_loop=False,
      )
      self.conv2 = RelGraphConv(
          h_dim,
          out_dim,
          num_rels,
          regularizer="basis",
          num_bases=num_rels,
          self_loop=False,
      )
  
file_path: dgl/examples/pytorch/rgcn/entity.py
imports: import argparse
  import dgl
  import torch
  import torch.nn
  import torch.nn.functional
  from dgl.data.rdf import AIFBDataset, AMDataset, BGSDataset, MUTAGDataset
  from dgl.nn.pytorch import RelGraphConv
  from torchmetrics.functional import accuracy
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, out_dim, num_rels)