Method save_network

models/base_model.py:74–82

(self, network, network_label, iter_label)

        return str(network), sum(map(lambda x: x.numel(), network.parameters()))

    def save_network(self, network, network_label, iter_label):
        save_filename = '{}_{}.pth'.format(iter_label, network_label)
        save_path = os.path.join(self.opt['path']['models'], save_filename)
        if isinstance(network, nn.DataParallel) or isinstance(network, DistributedDataParallel):
            network = network.module
        state_dict = network.state_dict()
        for key, param in state_dict.items():
            state_dict[key] = param.cpu()
        torch.save(state_dict, save_path)

    def load_network(self, load_path, network, strict=True):
        if isinstance(network, nn.DataParallel) or isinstance(network, DistributedDataParallel):