code: def graphsage_lstm(gw, feature, hidden_size, act, name):
      inner_hidden_size = 128
      neigh_feature = fluid.layers.fc(
          feature, inner_hidden_size, act="relu"
      )
  
      hidden_dim = 128
      forward_proj = fluid.layers.fc(
          input=neigh_feature,
          size=hidden_dim * 4,
          bias_attr=False,
          name="lstm_proj",
      )
      msg = gw.send(copy_send, nfeat_list=[("h", forward_proj)])
      neigh_feature = gw.recv(msg, lstm_recv)
      neigh_feature = fluid.layers.fc(
          neigh_feature, hidden_size, act=act, name=name + "_r"
      )
  
      self_feature = feature
      self_feature = fluid.layers.fc(
          self_feature, hidden_size, act=act, name=name + "_l"
      )
      output = fluid.layers.concat(
          [self_feature, neigh_feature], axis=1
      )
      output = fluid.layers.l2_normalize(output, axis=1)
      return output
  
file_path: PGL/legacy/examples/graphsage/model.py
imports: import paddle
  import paddle.fluid
label_desc: Use image node_id 9 for calling a global function with example usage: graphsage_lstm(gw, feature, hidden_size, act, name) and returns: output