code: def __init__(
      self,
      g,
      h_dim,
      out_dim,
      num_bases,
      num_hidden_layers=1,
      dropout=0,
      use_self_loop=False,
  ):
      super(EntityClassify, self).__init__()
      self.g = g
      self.h_dim = h_dim
      self.out_dim = out_dim
      self.rel_names = list(set(g.etypes))
      self.rel_names.sort()
      if num_bases < 0 or num_bases > len(self.rel_names):
          self.num_bases = len(self.rel_names)
      else:
          self.num_bases = num_bases
      self.num_hidden_layers = num_hidden_layers
      self.dropout = dropout
      self.use_self_loop = use_self_loop
  
      self.embed_layer = RelGraphEmbed(g, self.h_dim)
      self.layers = nn.ModuleList()
      # i2h
      self.layers.append(
          RelGraphConvLayer(
              self.h_dim,
              self.h_dim,
              self.rel_names,
              self.num_bases,
              activation=F.relu,
              self_loop=self.use_self_loop,
              dropout=self.dropout,
              weight=False,
          )
      )
      # h2h
      for i in range(self.num_hidden_layers):
          self.layers.append(
              RelGraphConvLayer(
                  self.h_dim,
                  self.h_dim,
                  self.rel_names,
                  self.num_bases,
                  activation=F.relu,
                  self_loop=self.use_self_loop,
                  dropout=self.dropout,
              )
          )
      # h2o
      self.layers.append(
          RelGraphConvLayer(
              self.h_dim,
              self.out_dim,
              self.rel_names,
              self.num_bases,
              activation=None,
              self_loop=self.use_self_loop,
          )
      )
  
imports: from collections import defaultdict
  import dgl
  import dgl.function
  import dgl.nn
  import torch
  import torch.nn
  import torch.nn.functional
  import tqdm
label_desc: Use image node_id 1 to create a new EntityClassify object from inherited base classes: nn with example: obj = EntityClassify(g, h_dim, out_dim, num_bases, num_hidden_layers, dropout, use__loop)