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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def levelize_smooth_or_improve_candidates(to_levelize, max_levels):
 """Turn parameter in to a list per level. Helper function to preprocess the smooth and improve_candidates parameters passed to smoothed_aggregation_solver and rootnode_solver. Parameters to_levelize : {string, tuple, list} Parameter to preprocess, i.e., levelize and convert to a level-by-level list such that entry i specifies the parameter at level i max_levels : int Defines the maximum number of levels considered Returns ------- to_levelize : list The parameter list such that entry i specifies the parameter choice at level i. Notes -------- This routine is needed because the user will pass in a parameter option such as smooth='jacobi', or smooth=['jacobi', None], and this option must be "levelized", or converted to a list of length max_levels such that entry [i] in that list is the parameter choice for level i. The parameter choice in to_levelize can be a string, tuple or list. If it is a string or tuple, then that option is assumed to be the parameter setting at every level. If to_levelize is inititally a list, if the length of the list is less than max_levels, the last entry in the list defines that parameter for all subsequent levels. Examples -------- ['gauss_seidel', None, None, None] """

    if isinstance(to_levelize, tuple) or isinstance(to_levelize, str):
        to_levelize = [to_levelize for i in range(max_levels)]
    elif isinstance(to_levelize, list):
        if len(to_levelize) < max_levels:
            mlz = max_levels - len(to_levelize)
            toext = [to_levelize[-1] for i in range(mlz)]
            to_levelize.extend(toext)
    elif to_levelize is None:
        to_levelize = [(None, {}) for i in range(max_levels)]

    return to_levelize