motion_cnn.py 文件源码

def run(self):
        self.build_model()
        self.resume_and_evaluate()
        cudnn.benchmark = True

        for self.epoch in range(self.start_epoch, self.nb_epochs):
            self.train_1epoch()
            prec1, val_loss = self.validate_1epoch()
            is_best = prec1 > self.best_prec1
            #lr_scheduler
            self.scheduler.step(val_loss)
            # save model
            if is_best:
                self.best_prec1 = prec1
                with open('record/motion/motion_video_preds.pickle','wb') as f:
                    pickle.dump(self.dic_video_level_preds,f)
                f.close() 

            save_checkpoint({
                'epoch': self.epoch,
                'state_dict': self.model.state_dict(),
                'best_prec1': self.best_prec1,
                'optimizer' : self.optimizer.state_dict()
            },is_best,'record/motion/checkpoint.pth.tar','record/motion/model_best.pth.tar')