code: def __init__(
      self,
      g,
      in_feats,
      n_classes,
      n_hidden,
      n_layers,
      activation,
      dropout,
      aggregator_type,
  ):
      super(GraphSAGE, self).__init__()
      self.layers = nn.ModuleList()
      self.g = g
  
      # input layer
      self.layers.append(
          SAGEConv(
              in_feats,
              n_hidden,
              aggregator_type,
              feat_drop=dropout,
              activation=activation,
          )
      )
      # hidden layers
      for i in range(n_layers - 1):
          self.layers.append(
              SAGEConv(
                  n_hidden,
                  n_hidden,
                  aggregator_type,
                  feat_drop=dropout,
                  activation=activation,
              )
          )
      # output layer
      self.layers.append(
          SAGEConv(
              n_hidden,
              n_classes,
              aggregator_type,
              feat_drop=dropout,
              activation=None,
          )
      )
  
imports: import torch
  import torch.nn
  from dgl.nn.pytorch import AGNNConv, APPNPConv, ChebConv, GATConv, GINConv, GraphConv, SAGEConv, SGConv, TAGConv
label_desc: Use image node_id 1 to create a new GraphSAGE object from inherited base classes: nn with example: obj = GraphSAGE(g, in_feats, n_classes, n_hidden, n_layers, activation, dropout, aggregator_type)