def METHOD_NAME(
    self,
    transformation: Transformation,
    trained_network: nn.Module,
    device: torch.device,
) -> PTSPredictor:
    prediction_network = ARPredictionNetwork(
        prediction_length=self.prediction_length,
        context_length=self.context_length,
        num_parallel_samples=self.num_parallel_samples,
    ).to(device)
    copy_parameters(trained_network, prediction_network)
    return PTSPredictor(
        input_transform=transformation,
        prediction_net=prediction_network,
        batch_size=self.trainer.batch_size,
        freq=self.freq,
        prediction_length=self.prediction_length,
        device=device,
    )