def METHOD_NAME():
    model.eval()
    out = model.inference(data.x)
    y_true = data.y.cpu()
    y_pred = out.argmax(dim=-1, keepdim=True)
    train_acc = evaluator.eval({
        'y_true': y_true[split_idx['train']],
        'y_pred': y_pred[split_idx['train']],
    })['acc']
    val_acc = evaluator.eval({
        'y_true': y_true[split_idx['valid']],
        'y_pred': y_pred[split_idx['valid']],
    })['acc']
    test_acc = evaluator.eval({
        'y_true': y_true[split_idx['test']],
        'y_pred': y_pred[split_idx['test']],
    })['acc']
    return train_acc, val_acc, test_acc