def train(): args = parse_args() if args.config_file is not None: print("cfg file: %s" % args.config_file) cfg_from_file(args.config_file) train_model()
def train(): args = parse_args() if args.config_file is not None: cfg_from_file(args.config_file) logger = setup_logger(cfg) train_model()
def train(): args = parse_args() # print(args) if args.config_file is not None: cfg_from_file(args.config_file) from lib.ssds_train import train_model train_model()
def train(): args = parse_args() if args.config_file is not None: cfg_from_file(args.config_file) train_model()
def train(): cfg_from_file('./experiments/cfgs_new/yolo_v3_small_inceptionv4_v4_8.15.yml') train_model()
def train(): args = parse_args() if args.config_file is not None: cfg_from_file(args.config_file) # os.environ["CUDA_LAUNCH_BLOCKING"] = "1" train_model()