i understand,but the reason why i use the torch.save() not the state_dict is that i hope to load the model and weight directly while don`t need to define the model first,because the my model structure may change many times,if i just save the state dict when i was training, i may not remember the exactly structure version when i evaluate the model,but load state dict need to define the model structure first which may cause the state dict between new model and loaded model do not match