nargs='?', default=True, help='Use CUDNN.') args_parser = parser.parse_args() if args_parser.seed is not None: random.seed(args_parser.seed) torch.manual_seed(args_parser.seed) cudnn.enabled = True cudnn.benchmark = args_parser.cudnn configer = Configer(args_parser=args_parser) abs_data_dir = os.path.expanduser(configer.get('data', 'data_dir')) configer.update(['data', 'data_dir'], abs_data_dir) if configer.get('gpu') is not None: os.environ["CUDA_VISIBLE_DEVICES"] = ','.join( str(gpu_id) for gpu_id in configer.get('gpu')) if configer.get('network', 'bn_type') is None: configer.update(['network', 'bn_type'], 'torchbn') project_dir = os.path.dirname(os.path.realpath(__file__)) configer.add(['project_dir'], project_dir) if configer.get('logging', 'log_to_file'): log_file = configer.get('logging', 'log_file') new_log_file = '{}_{}'.format( log_file, time.strftime("%Y-%m-%d_%X", time.localtime()))
nargs='?', default=True, help='Use CUDNN.') args_parser = parser.parse_args() if args_parser.seed is not None: random.seed(args_parser.seed) torch.manual_seed(args_parser.seed) cudnn.enabled = True cudnn.benchmark = args_parser.cudnn configer = Configer(args_parser=args_parser) abs_data_dir = os.path.expanduser(configer.get('data', 'data_dir')) configer.update(['data', 'data_dir'], abs_data_dir) if configer.get('gpu') is not None: os.environ["CUDA_VISIBLE_DEVICES"] = ','.join( str(gpu_id) for gpu_id in configer.get('gpu')) if configer.get('network', 'norm_type') is None: configer.update(['network', 'norm_type'], 'batchnorm') if configer.get('phase') == 'train': assert len(configer.get('gpu')) > 1 or 'sync' not in configer.get( 'network', 'norm_type') project_dir = os.path.dirname(os.path.realpath(__file__)) configer.add(['project_dir'], project_dir)
type=str2bool, nargs='?', default=True, help='Use CUDNN.') args_parser = parser.parse_args() if args_parser.seed is not None: random.seed(args_parser.seed) torch.manual_seed(args_parser.seed) cudnn.enabled = True cudnn.benchmark = args_parser.cudnn configer = Configer(args_parser=args_parser) abs_data_dir = os.path.expanduser(configer.get('data', 'data_dir')) configer.update(['data', 'data_dir'], abs_data_dir) if configer.get('gpu') is not None: os.environ["CUDA_VISIBLE_DEVICES"] = ','.join( str(gpu_id) for gpu_id in configer.get('gpu')) project_dir = os.path.dirname(os.path.realpath(__file__)) configer.add(['project_dir'], project_dir) if configer.get('logging', 'log_to_file'): log_file = configer.get('logging', 'log_file') new_log_file = '{}_{}'.format( log_file, time.strftime("%Y-%m-%d_%X", time.localtime())) configer.update(['logging', 'log_file'], new_log_file) else: configer.update(['logging', 'logfile_level'], None)