class_docstr: GraphSAGE is a general inductive framework that leverages node feature
  information (e.g., text attributes) to efficiently generate node embeddings
  for previously unseen data.
code: def forward(self, edge_index, feature):
      neigh_feature = self.send_recv(
          edge_index, feature, self.aggr_type
      )
      self_feature = self.self_linear(feature)
      neigh_feature = self.neigh_linear(neigh_feature)
      output = self_feature + neigh_feature
  
      output = F.normalize(output, axis=1)
      return output
  
file_path: PGL/examples/gnn_depoly/models/graphsage.py
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from .base_conv import BaseConv
label_desc: Use image node_id 2 for calling the SageConv obj's underlying member method code with example usage: obj.forward(edge_index, feature) and returns: output