def load_checkpoint()

in train/model.py [0:0]

• 16 lines of code
• 6 McCabe index (conditional complexity)

    def load_checkpoint(self, epoch, optimizer=None, suffix=''):

        load_path = self.get_checkpoint_path(epoch, suffix)
        assert os.path.exists(load_path), "Failed to load: {} (file not exist)".format(load_path)

        checkpoint = torch.load(load_path)

        all_params_matched = self.load_state(checkpoint['state_dict'], strict=False)

        if optimizer:
            if 'optimizer' in checkpoint.keys() and all_params_matched:
                optimizer.load_state_dict(checkpoint['optimizer'])
                logging.info("Model & Optimizer states are resumed from: `{}'".format(load_path))
            else:
                logging.warning(">> Failed to load optimizer state from: `{}'".format(load_path))
        else:
            logging.info("Only model state resumed from: `{}'".format(load_path))

        if 'epoch' in checkpoint.keys():
            if checkpoint['epoch'] != epoch:
                logging.warning(">> Epoch information inconsistant: {} vs {}".format(checkpoint['epoch'], epoch))