code: def forward(self, g, action=None):
      graph_embed = self.graph_op["embed"](g)
  
      logit = self.add_node(graph_embed)
      prob = torch.sigmoid(logit)
  
      if not self.training:
          action = Bernoulli(prob).sample().item()
      stop = bool(action == self.stop)
  
      if not stop:
          g.add_nodes(1)
          self._initialize_node_repr(g, action, graph_embed)
  
      if self.training:
          sample_log_prob = bernoulli_action_log_prob(logit, action)
          self.log_prob.append(sample_log_prob)
  
      return stop
  
imports: from functools import partial
  import dgl
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.distributions import Bernoulli, Categorical
label_desc: Use image node_id 4 for calling the AddNode obj's underlying member method code with example usage: obj.forward(g, action) and returns: stop