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diff --git a/r_basicsr/test.py b/r_basicsr/test.py
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+import logging

+import torch

+from os import path as osp

+

+from r_basicsr.data import build_dataloader, build_dataset

+from r_basicsr.models import build_model

+from r_basicsr.utils import get_env_info, get_root_logger, get_time_str, make_exp_dirs

+from r_basicsr.utils.options import dict2str, parse_options

+

+

+def test_pipeline(root_path):

+    # parse options, set distributed setting, set ramdom seed

+    opt, _ = parse_options(root_path, is_train=False)

+

+    torch.backends.cudnn.benchmark = True

+    # torch.backends.cudnn.deterministic = True

+

+    # mkdir and initialize loggers

+    make_exp_dirs(opt)

+    log_file = osp.join(opt['path']['log'], f"test_{opt['name']}_{get_time_str()}.log")

+    logger = get_root_logger(logger_name='basicsr', log_level=logging.INFO, log_file=log_file)

+    logger.info(get_env_info())

+    logger.info(dict2str(opt))

+

+    # create test dataset and dataloader

+    test_loaders = []

+    for _, dataset_opt in sorted(opt['datasets'].items()):

+        test_set = build_dataset(dataset_opt)

+        test_loader = build_dataloader(

+            test_set, dataset_opt, num_gpu=opt['num_gpu'], dist=opt['dist'], sampler=None, seed=opt['manual_seed'])

+        logger.info(f"Number of test images in {dataset_opt['name']}: {len(test_set)}")

+        test_loaders.append(test_loader)

+

+    # create model

+    model = build_model(opt)

+

+    for test_loader in test_loaders:

+        test_set_name = test_loader.dataset.opt['name']

+        logger.info(f'Testing {test_set_name}...')

+        model.validation(test_loader, current_iter=opt['name'], tb_logger=None, save_img=opt['val']['save_img'])

+

+

+if __name__ == '__main__':

+    root_path = osp.abspath(osp.join(__file__, osp.pardir, osp.pardir))

+    test_pipeline(root_path)