code: def forward(self, graph):
      sum_pooled = self.pool_fun(
          graph, graph.node_feat["atom_feat"], pool_type="SUM"
      )
      ones_sum_pooled = self.pool_fun(
          graph,
          paddle.ones_like(
              graph.node_feat["atom_feat"], dtype="float32"
          ),
          pool_type="SUM",
      )
      pooled = sum_pooled / ones_sum_pooled
      return pooled
  
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 GlobalPool obj's underlying member method code with example usage: obj.forward(graph) and returns: pooled