def METHOD_NAME(config: TorchBenchModelConfig, metrics: List[str], dryrun: bool=False) -> Optional[TorchBenchModelMetrics]:
    """This function only handles NotImplementedError, all other errors will fail."""
    print(f"Running {config} ...", end='')
    if dryrun:
        return None
    # We do not allow RuntimeError in this test
    try:
        if "cpu_peak_mem" in metrics:
            # load the model instance within separate subprocess
            model = load_model_isolated(config)
        else:
            # load the model instance within current process
            model = load_model(config)
        # get the model test metrics
        result: TorchBenchModelMetrics = get_model_test_metrics(model, metrics=metrics)
    except NotImplementedError as e:
        print(" [NotImplemented]")
        return None
    print(" [Done]")
    return result