class_docstr: Implementation of Spatio-Temporal Graph Convolutional Networks
docstr: Message passing layer
docstr_tok: ["Message","passing","layer"]
code: def message_passing(self, gw, feature, name, norm=None):
      """Message passing layer"""
  
      def send_src_copy(src_feat, dst_feat, edge_feat):
          """send function"""
          return src_feat["h"] * edge_feat["w"]
  
      if norm is not None:
          feature = feature * norm
  
      msg = gw.send(
          send_src_copy,
          nfeat_list=[("h", feature)],
          efeat_list=[("w", gw.edge_feat["weights"])],
      )
      output = gw.recv(msg, "sum")
  
      if norm is not None:
          output = output * norm
  
      return output
  
file_path: PGL/legacy/examples/stgcn/models/model.py
imports: import numpy
  import paddle.fluid
  import paddle.fluid.layers
  import pgl
label_desc: Use image node_id 6 for calling the STGCNModel obj's underlying member method code with example usage: obj.message_passing(gw, feature, name, norm) and returns: output, unknown