code: def __init__(self, g, in_feats, n_hidden, activation, dropout=0.0):
      super(RECT_L, self).__init__()
      self.g = g
      self.gcn_1 = GraphConv(in_feats, n_hidden, activation=activation)
      self.fc = nn.Linear(n_hidden, in_feats)
      self.dropout = dropout
      nn.init.xavier_uniform_(self.fc.weight.data)
  
file_path: dgl/examples/pytorch/rect/model.py
imports: import torch.nn
  import torch.nn.functional
  from dgl.nn.pytorch import GraphConv
label_desc: Use image node_id 1 to create a new RECT_L object from inherited base classes: nn with example: obj = RECT_L(g, in_feats, n_hidden, activation, dropout)