def prepare_pretrained_model() -> Path:
        """Download pre-trained models if they don't exist.

        Returns:
            Path: Path to the downloaded pre-trained model weights.

        Example:
            >>> model = Dsr()
            >>> weights_path = model.prepare_pretrained_model()
            >>> weights_path.name
            'vq_model_pretrained_128_4096.pckl'
        """
        pretrained_models_dir = Path("./pre_trained/")
        if not (pretrained_models_dir / "vq_model_pretrained_128_4096.pckl").is_file():
            download_and_extract(pretrained_models_dir, WEIGHTS_DOWNLOAD_INFO)
        return pretrained_models_dir / "vq_model_pretrained_128_4096.pckl"
Download pre-trained models if they don't exist.

        Returns:
            Path: Path to the downloaded pre-trained model weights.

        Example:
            >>> model = Dsr()
            >>> weights_path = model.prepare_pretrained_model()
            >>> weights_path.name
            'vq_model_pretrained_128_4096.pckl'
        
src/anomalib/models/image/dsr/lightning_model.py