spatial_cnn.py 文件源码

def resume_and_evaluate(self):
        if self.resume:
            if os.path.isfile(self.resume):
                print("==> loading checkpoint '{}'".format(self.resume))
                checkpoint = torch.load(self.resume)
                self.start_epoch = checkpoint['epoch']
                self.best_prec1 = checkpoint['best_prec1']
                self.model.load_state_dict(checkpoint['state_dict'])
                self.optimizer.load_state_dict(checkpoint['optimizer'])
                print("==> loaded checkpoint '{}' (epoch {}) (best_prec1 {})"
                  .format(self.resume, checkpoint['epoch'], self.best_prec1))
            else:
                print("==> no checkpoint found at '{}'".format(self.resume))
        if self.evaluate:
            self.epoch = 0
            prec1, val_loss = self.validate_1epoch()
            return