def check_warm_start(warm_start, from_unsupervised):
    """
    Gives a warning about ambiguous usage of the two parameters.
    """
    if warm_start and from_unsupervised is not None:
        warn_msg = "warm_start=True and from_unsupervised != None: "
        warn_msg = "warm_start will be ignore, training will start from unsupervised weights"
        warnings.warn(warn_msg)
    return

    Gives a warning about ambiguous usage of the two parameters.
    
pytorch_tabnet/utils.py