def METHOD_NAME(self, config: DictConfig, **kwargs: Any) -> None:
    config.lr, config.training_hyperparams.initial_lr = self._override_with_shortcut(config.lr, config.training_hyperparams.initial_lr)
    config.batch_size, config.dataset_params.train_dataloader_params.batch_size = self._override_with_shortcut(
        config.batch_size, config.dataset_params.train_dataloader_params.batch_size
    )
    config.val_batch_size, config.dataset_params.val_dataloader_params.batch_size = self._override_with_shortcut(
        config.val_batch_size, config.dataset_params.val_dataloader_params.batch_size
    )
    config.resume, config.training_hyperparams.resume = self._override_with_shortcut(config.resume, config.training_hyperparams.resume)
    config.epochs, config.training_hyperparams.max_epochs = self._override_with_shortcut(config.epochs, config.training_hyperparams.max_epochs)
    config.ema, config.training_hyperparams.ema = self._override_with_shortcut(config.ema, config.training_hyperparams.ema)
    config.num_workers, config.dataset_params.train_dataloader_params.num_workers = self._override_with_shortcut(
        config.num_workers, config.dataset_params.train_dataloader_params.num_workers
    )
    config.num_workers, config.dataset_params.val_dataloader_params.num_workers = self._override_with_shortcut(
        config.num_workers, config.dataset_params.val_dataloader_params.num_workers
    )