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- 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())
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