text: import os
  os.environ["AUTOGL_BACKEND"] = "dgl"
  
  from autogl.datasets import build_dataset_from_name
  from autogl.solver import AutoNodeClassifier
  from autogl.module.train import NodeClassificationFullTrainer
  from autogl.backend import DependentBackend
  
  key = "y" if DependentBackend.is_pyg() else "label"
  
  cora = build_dataset_from_name("cora")
  
  solver = AutoNodeClassifier(
      graph_models=("gin",),
      default_trainer=NodeClassificationFullTrainer(
          decoder=None,
          init=False,
          max_epoch=200,
          early_stopping_round=201,
          lr=0.01,
          weight_decay=0.0,
      ),
      hpo_module=None,
      device="auto"
  )
  
  solver.fit(cora, evaluation_method=["acc"])
  result = solver.predict(cora)
  print((result == cora[0].nodes.data[key][cora[0].nodes.data["test_mask"]].cpu().numpy()).astype('float').mean())
  