code: def send_func(self, src_feat, dst_feat, edge_feat):
      # E * (M * D1)
      feat_query, feat_key = (
          dst_feat["feat_query"],
          src_feat["feat_key"],
      )
      # E * M * D1
      old = feat_query
      feat_query = fluid.layers.reshape(
          feat_query, [-1, self.heads, self.hidden_size_a]
      )
      feat_key = fluid.layers.reshape(
          feat_key, [-1, self.heads, self.hidden_size_a]
      )
      # E * M
      alpha = fluid.layers.reduce_sum(feat_key * feat_query, dim=-1)
  
      return {
          "dst_node_feat": dst_feat["node_feat"],
          "src_node_feat": src_feat["node_feat"],
          "feat_value": src_feat["feat_value"],
          "alpha": alpha,
          "feat_gate": src_feat["feat_gate"],
      }
  
imports: import os
  import re
  import time
  from random import random
  from functools import reduce, partial
  import numpy
  import multiprocessing
  import paddle
  import paddle.fluid
  import paddle.fluid
  import paddle.fluid.layers
  from pgl.graph_wrapper import GraphWrapper
  from pgl.layers.conv import gcn, gat
  from pgl.utils import paddle_helper
label_desc: Use image node_id 4 for calling the GaANModel obj's underlying member method code with example usage: obj.send_func(src_feat, dst_feat, edge_feat) and returns: dict