code: def _initialize(self):
      self._model = GCN4GNNGuard(
          nfeat=self.input_dimension,
          nclass=self.output_dimension,
          nhid=self.hyper_parameters.get("hidden"),
          activation=self.hyper_parameters.get("act"),
          dropout=self.hyper_parameters.get("dropout", None),
          add_self_loops=bool(
              self.hyper_parameters.get("add_self_loops", True)
          ),
          normalize=bool(self.hyper_parameters.get("normalize", True)),
      ).to(self.device)
  
imports: import numpy
  from copy import deepcopy
  from numba import njit
  import torch.nn
  import torch.nn.functional
  import math
  import torch
  import torch.optim
  import typing
  from torch_geometric.data import Data
  from sklearn.metrics.pairwise import euclidean_distances, cosine_similarity
  from scipy.sparse import lil_matrix
  from sklearn.preprocessing import normalize
  import scipy.sparse
  import autogl.data
  from ..None import register_model
  from .None import utils
  from ..gcn import GCN
  from .nn import GCNConv
  from ..base import BaseAutoModel
  from .....utils import get_logger
  from .utils import accuracy
label_desc: Use image node_id 2 for calling the AutoGNNGuard obj's underlying member method code with example usage: obj._initialize() without return types