class_docstr: LSTM aggregator for graphsage
class_docstr_tok: ["LSTM","aggregator","for","graphsage"]
code: def forward(self, node):
      neighbour = node.mailbox["m"]
      c = self.aggre(neighbour)
      return {"c": c}
  
imports: import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 4 for calling the LSTMAggregator obj's underlying member method code with example usage: obj.forward(node) and returns: dict