code: def forward(self, graph, nfeat):
      sum_pooled = self.pool_fun(graph, nfeat)
      ones_sum_pooled = self.pool_fun(
          graph, paddle.ones_like(nfeat, dtype="float32")
      )
      pooled = sum_pooled / ones_sum_pooled
      return pooled
  
imports: import os
  import sys
  import math
  import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  import pgl.nn
  from pgl.utils.logger import log
  import models.conv
  import models.mol_encoder
  import models.layers
label_desc: Use image node_id 2 for calling the MeanGlobalPool obj's underlying member method code with example usage: obj.forward(graph, nfeat) and returns: pooled