code: def load_state_dict(
      self, state_dict: "OrderedDict[str, Tensor]", strict: bool = True
  ):
      new_state_dict = OrderedDict()
      for key in state_dict.keys():
          if key in self.state_dict().keys():
              new_state_dict[key] = state_dict[key]
  
      super(GNNBase, self).load_state_dict(new_state_dict)
  
imports: import torch
  import torch.nn
  from functools import partial
  from typing import Union, List
  import torch.nn.functional
  from torch_geometric.data import Batch
  from torch_geometric.nn.conv.gcn_conv import gcn_norm
  from torch_geometric.nn.conv import GCNConv
  from torch_geometric.nn.glob import global_mean_pool, global_add_pool, global_max_pool
  from torch import Tensor
  from torch_sparse import SparseTensor, fill_diag
  from torch_geometric.typing import Adj, OptTensor, Size
  from torch_geometric.utils import add_self_loops
  from dig.xgraph.models import GNNPool
  from collections import OrderedDict
label_desc: Use image node_id 3 for calling the GNNBase obj's underlying member method code with example usage: obj.load_state_dict(state_dict, strict) without return types