def load_checkpoints(config_path, checkpoint_path, cpu=False): with open(config_path) as f: config = yaml.load(f) generator = OcclusionAwareGenerator( **config["model_params"]["generator_params"], **config["model_params"]["common_params"], ) if cpu: generator.cpu() else: generator.cuda() kp_detector = KPDetector( **config["model_params"]["kp_detector_params"], **config["model_params"]["common_params"], ) if cpu: kp_detector.cpu() else: kp_detector.cuda() checkpoint = torch.load(checkpoint_path, map_location="cpu" if cpu else None) generator.load_state_dict(checkpoint["generator"]) kp_detector.load_state_dict(checkpoint["kp_detector"]) generator = DataParallelWithCallback(generator) kp_detector = DataParallelWithCallback(kp_detector) generator.eval() kp_detector.eval() return generator, kp_detector
def load_checkpoints(config_path, checkpoint_path, cpu=False): with open(config_path) as f: config = yaml.load(f) generator = OcclusionAwareGenerator( **config['model_params']['generator_params'], **config['model_params']['common_params']) if not cpu: generator.cpu() kp_detector = KPDetector(**config['model_params']['kp_detector_params'], **config['model_params']['common_params']) if not cpu: kp_detector.cpu() if cpu: checkpoint = torch.load(checkpoint_path, map_location=torch.device('cpu')) else: checkpoint = torch.load(checkpoint_path, map_location=torch.device('cpu')) generator.load_state_dict(checkpoint['generator']) kp_detector.load_state_dict(checkpoint['kp_detector']) if not cpu: generator = DataParallelWithCallback(generator) kp_detector = DataParallelWithCallback(kp_detector) generator.eval() kp_detector.eval() return generator, kp_detector