def _load_pretrained_model(self):
    pretrain_dict = torch.load(os.path.join(os.path.dirname(os.path.abspath(__file__)), './mobilenet_VOC.pth'))
    model_dict = {}
    state_dict = self.state_dict()
    for (k, v) in pretrain_dict.items():
        if (k in state_dict):
            model_dict[k] = v
    state_dict.update(model_dict)
    self.load_state_dict(state_dict)
def _load_pretrained_model(self):
    pretrain_dict = torch.load(os.path.join(os.path.dirname(os.path.abspath(__file__)), './mobilenet_VOC.pth'))
    model_dict = {}
    state_dict = self.state_dict()
    for (k, v) in pretrain_dict.items():
        if (k in state_dict):
            model_dict[k] = v
    state_dict.update(model_dict)
    self.load_state_dict(state_dict)