def METHOD_NAME():
    global config
    config = load_config(FLAGS.config_path)
    dataset = config['EvalDataset']
    global val_loader
    val_loader = create('EvalReader')(config['EvalDataset'],
                                      config['worker_num'],
                                      return_list=True)
    metric = None
    if config['metric'] == 'COCO':
        clsid2catid = {v: k for k, v in dataset.catid2clsid.items()}
        anno_file = dataset.get_anno()
        metric = COCOMetric(
            anno_file=anno_file, clsid2catid=clsid2catid, IouType='bbox')
    elif config['metric'] == 'VOC':
        metric = VOCMetric(
            label_list=dataset.get_label_list(),
            class_num=config['num_classes'],
            map_type=config['map_type'])
    elif config['metric'] == 'KeyPointTopDownCOCOEval':
        anno_file = dataset.get_anno()
        metric = KeyPointTopDownCOCOEval(anno_file,
                                         len(dataset), 17, 'output_eval')
    else:
        raise ValueError("metric currently only supports COCO and VOC.")
    config['metric'] = metric
    eval()