def METHOD_NAME(args):
    if args.task == "adult":
        df_train = TabularDataset('https://autogluon.s3.amazonaws.com/datasets/Inc/train.csv')
        df_test = TabularDataset('https://autogluon.s3.amazonaws.com/datasets/Inc/test.csv')
        label = "class"
    elif args.task == "TCGA_HNSC":
        df = data_loader(args.path)
        df_train, df_test = preprocess(df, args.test_size, args.shuffle)
        label = "vital_status"
    else:
        raise NotImplementedError
    metric = "accuracy"
    hyperparameters = {} if args.mode == "FT_Transformer" else get_hyperparameter_config('default')
    hyperparameters['FT_TRANSFORMER'] = {"env.num_gpus": args.num_gpus, "env.num_workers": args.num_workers}
    predictor = TabularPredictor(label=label,
                                 eval_metric=metric,
                                 ).fit(
        train_data=df_train,
        hyperparameters=hyperparameters,
        time_limit=900,
    )
    leaderboard = predictor.leaderboard(df_test)
    leaderboard.to_csv("./leaderboard.csv")
    return