def _lstm_reducer(self, nodes):
        """LSTM reducer
        NOTE(zihao): lstm reducer with default schedule (degree bucketing)
        is slow, we could accelerate this with degree padding in the future.
        """
        m = nodes.mailbox["m"]  # (B, L, D)
        rst = self.lstm(m)
        return {"neigh": rst}
LSTM reducer
        NOTE(zihao): lstm reducer with default schedule (degree bucketing)
        is slow, we could accelerate this with degree padding in the future.
        
python/dgl/nn/tensorflow/conv/sageconv.py