code: def _get_node_net(self, node_feat_dim, node_hiddens, use_gate):
      if use_gate:
          node_hiddens[-1] *= 2
  
      layer = []
      layer.append(nn.Linear(node_feat_dim, node_hiddens[0]))
      for i in range(1, len(node_hiddens)):
          layer.append(nn.ReLU())
          layer.append(nn.Linear(node_hiddens[i - 1], node_hiddens[i]))
  
      self.node_net = nn.Sequential(*layer)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch_scatter import scatter
  from torch_geometric.nn import global_add_pool, global_mean_pool, global_max_pool, GINConv
label_desc: Use image node_id 2 for calling the Readout obj's underlying member method code with example usage: obj._get_node_net(node_feat_dim, node_hiddens, use_gate) without return types