def get_net(cfg, weight_path=None): """ 根据网络名称获取模型 :param net_name: 网络名称 :param weight_path: 与训练权重路径 :return: """ model = build_model(cfg) if cfg.model_path is not None: model.load_state_dict(torch.load(cfg.model_path)) return model
from inicls import build_model from mmcv import Config from tools.torch_utils import * cfg = Config.fromfile('./config_test.py') model = build_model(cfg=cfg) model = model.cuda() model.train() print('[i] Architecture is {}'.format(cfg.model)) print('[i] Total Params: %.2fM' % (calculate_parameters(model)))