import tensorflow as tf


    result_file = f"results/{args.problem}_test_{time.strftime('%Y%m%d-%H%M%S')}"

    result_file = result_file + '.csv'
    os.makedirs('results', exist_ok=True)

    ### TENSORFLOW SETUP ###
    if args.gpu == -1:
        os.environ['CUDA_VISIBLE_DEVICES'] = ''
    else:
        os.environ['CUDA_VISIBLE_DEVICES'] = f'{args.gpu}'
    config = tf.ConfigProto()
    config.gpu_options.allow_growth = True
    tf.enable_eager_execution(config)
    tf.executing_eagerly()

    test_files = list(pathlib.Path(f"data/samples/{problem_folder}/test").glob('sample_*.pkl'))
    test_files = [str(x) for x in test_files]

    print(f"{len(test_files)} test samples")

    evaluated_policies = [['gcnn', model] for model in gcnn_models] + \
            [['ml-competitor', model] for model in other_models]

    fieldnames = [
        'policy',
        'seed',
    ] + [
