code: def _get_graph_net(self, graph_feat_dim, graph_hiddens):
      layer = []
      layer.append(nn.Linear(graph_feat_dim, graph_hiddens[0]))
      for i in range(1, len(graph_hiddens)):
          layer.append(nn.ReLU())
          layer.append(
              nn.Linear(graph_hiddens[i - 1], graph_hiddens[i])
          )
  
      self.graph_net = nn.Sequential(*layer)
  
imports: import torch
  import torch.nn
  from torch_scatter import scatter
  from torch_geometric.nn import global_add_pool, global_mean_pool, global_max_pool, GINConv
  from dig.auggraph.method.GraphAug.constants import *
label_desc: Use image node_id 3 for calling the Readout obj's underlying member method code with example usage: obj._get_graph_net(graph_feat_dim, graph_hiddens) without return types