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
