code: def __init__(self, annotation_size, out_feats, n_steps, n_etypes):
      super(NodeSelectionGGNN, self).__init__()
  
      self.annotation_size = annotation_size
      self.out_feats = out_feats
  
      self.ggnn = GatedGraphConv(
          in_feats=out_feats,
          out_feats=out_feats,
          n_steps=n_steps,
          n_etypes=n_etypes,
      )
  
      self.output_layer = nn.Linear(annotation_size + out_feats, 1)
      self.loss_fn = nn.CrossEntropyLoss()
  
file_path: dgl/examples/pytorch/ggnn/ggnn_ns.py
imports: import dgl
  import torch
  from dgl.nn.pytorch import GatedGraphConv
  from torch import nn
label_desc: Use image node_id 1 to create a new NodeSelectionGGNN object from inherited base classes: nn with example: obj = NodeSelectionGGNN(annotation_size, out_feats, n_steps, n_etypes)