code: def __init__(self, num_nodes, num_rels, h_dim=500, reg_param=0.01):
      super().__init__()
      self.rgcn = RGCN(num_nodes, h_dim, num_rels * 2)
      self.reg_param = reg_param
      self.w_relation = nn.Parameter(torch.Tensor(num_rels, h_dim))
      nn.init.xavier_uniform_(
          self.w_relation, gain=nn.init.calculate_gain("relu")
      )
  
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 LinkPredict object from inherited base classes: nn with example: obj = LinkPredict(num_nodes, num_rels, h_dim, reg_param)