# ----------------- get options ----------------- #
with open(osp.join(args.exp_dir, args.opt), 'r') as f:
opt = yaml.load(f.read(), Loader=yaml.FullLoader)
# ----------------- general configs ----------------- #
# experiment dir
opt['exp_dir'] = args.exp_dir
# random seed
base_utils.setup_random_seed(opt['manual_seed'])
# logger
base_utils.setup_logger('base')
opt['verbose'] = opt.get('verbose', False)
# device
if args.gpu_id >= 0:
os.environ['CUDA_VISIBLE_DEVICES'] = str(args.gpu_id)
if torch.cuda.is_available():
torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = False
opt['device'] = 'cuda'
else:
opt['device'] = 'cpu'
else:
opt['device'] = 'cpu'
# experiment dir
opt['exp_dir'] = args.exp_dir
# random seed
base_utils.setup_random_seed(opt['manual_seed'])
# logger
if args.mode == 'train' or args.mode == 'test':
if args.mode == 'train':
logpath = osp.join('results', opt['dataset']['train']['name'], opt['experiment'])
else:
logpath = osp.join('results', opt['dataset']['name'], opt['experiment'])
if not osp.exists(logpath):
os.mkdir(logpath)
logpath = logpath + '/train.log'
base_utils.setup_logger('base', filepath=logpath)
opt['verbose'] = opt.get('verbose', False)
# device
if args.gpu_id >= 0:
# os.environ['CUDA_VISIBLE_DEVICES'] = str(args.gpu_id)
if torch.cuda.is_available():
torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = False
opt['device'] = 'cuda'
else:
opt['device'] = 'cpu'
else:
opt['device'] = 'cpu'