code: def forward(self, virtual_node, embeddings, graph_node_id):
      if (
          graph_node_id.shape[0] > 0
      ):  # ...or the operation will crash for empty graphs
          G = pgl.math.segment_sum(embeddings, graph_node_id)
      else:
          G = paddle.zeros_like(virtual_node)
  
      if "gin" in self.conv_type:
          virtual_node = virtual_node + G
          virtual_node = self.mlp(virtual_node)
  
      elif "gcn" in self.conv_type:
          virtual_node = self.W0(virtual_node) + self.W1(G)
          virtual_node = self.nl_bn(virtual_node)
      else:
          raise NotImplementedError(
              "Unrecognised model conv : {}".format(self.conv_type)
          )
      return virtual_node
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  import pgl
  import pgl.nn
  from pgl.nn import functional
  from mol_encoder import AtomEncoder, BondEncoder
label_desc: Use image node_id 2 for calling the VNAgg obj's underlying member method code with example usage: obj.forward(virtual_node, embeddings, graph_node_id) and returns: virtual_node