def METHOD_NAME(sch, args, take_log=False):
    """get features of iter vars
    Parameters
    ----------
    sch: tvm.te.schedule.Schedule
    args: Array of te.tensor.Tensor
        the buffer args for lower
    take_log: bool
        whether take log of numerical statics
    Returns
    -------
    features of every axis in the IR, see doc/features.md for detail
    """
    stmt = ana_lower(sch, args, simple_mode=True)
    feas = _get_itervar_feature(stmt, take_log)
    # convert tvm node to python type
    ret = []
    for row in feas:
        tmp = []
        tmp.append([row[0][0].value, row[0][1]])
        for item in row[1:]:
            tmp.append([item[0].value] + [x.value for x in item[1:]])
        ret.append(tmp)
    return ret