def _get_current_parameter(args, config): def convert_to_info(config): class Info: pass ret = Info() ret.optimizers = OrderedDict() for name, opt in config.optimizers.items(): ret.optimizers[name] = opt.optimizer return ret best_error, best_epoch = callback.get_best_from_status(args) globname = os.path.join(args.outdir, 'results_current_*.nnp') exists = glob.glob(globname) if len(exists) > 0: ex_list = {} info = convert_to_info(config) for ex in exists: n = int(ex.rsplit('_', 1)[1].rsplit('.', 1)[0]) ex_list[n] = ex last_epoch = sorted(ex_list.keys(), reverse=True)[0] last_parameter = ex_list[last_epoch] logger.log( 99, "Load parameter from [{}]".format( os.path.basename(last_parameter))) #load.load([last_parameter], parameter_only=True) load_train_state(last_parameter, info) return last_epoch, best_epoch, best_error return 0, best_epoch, best_error
def _get_current_parameter(args): best_error, best_epoch = callback.get_best_from_status(args) globname = os.path.join(args.outdir, 'results_current_*.nnp') exists = glob.glob(globname) if len(exists) > 0: ex_list = {} for ex in exists: n = int(ex.rsplit('_', 1)[1].rsplit('.', 1)[0]) ex_list[n] = ex last_epoch = sorted(ex_list.keys(), reverse=True)[0] last_parameter = ex_list[last_epoch] logger.log(99, "Load parameter from [{}]".format( os.path.basename(last_parameter))) load.load([last_parameter], parameter_only=True) return last_epoch, best_epoch, best_error return 0, best_epoch, best_error