def METHOD_NAME(parameters):
    if not ("T_0" in parameters["scheduler"]):
        parameters["scheduler"]["T_0"] = 5
    if not ("T_mult" in parameters["scheduler"]):
        parameters["scheduler"]["T_mult"] = 1
    if not ("min_lr" in parameters["scheduler"]):
        parameters["scheduler"]["min_lr"] = parameters["learning_rate"] * 0.001
    return CosineAnnealingWarmRestarts(
        parameters["optimizer_object"],
        T_0=parameters["scheduler"]["T_0"],
        T_mult=parameters["scheduler"]["T_mult"],
        eta_min=parameters["scheduler"]["min_lr"],
    )