Method load_model

model/RIFE.py:41–50

(self, path, rank=0)

        self.flownet.to(device)

    def load_model(self, path, rank=0):
        def convert(param):
            return {
            k.replace("module.", ""): v
                for k, v in param.items()
                if "module." in k
            }
            
        if rank <= 0:
            self.flownet.load_state_dict(convert(torch.load('{}/flownet.pkl'.format(path))))
        
    def save_model(self, path, rank=0):
        if rank == 0: