How to use the hls4ml.model.hls_model.CompressedType function in hls4ml

val = it[0]
            if not (val == 0 and extra_nzero_cnt < 1):
                if val == 0:
                    extra_nzero_cnt -= 1
                if it.multi_index[0] > max_idx:
                    max_idx = it.multi_index[0]
                if it.multi_index[1] > max_idx:
                    max_idx = it.multi_index[1]
                weights.append([it.multi_index[1], it.multi_index[0], val])
            it.iternext()
        weights.sort()

        index_precision = 32
        if max_idx > 0:
            index_precision = int(np.log2(max_idx) + 1)
        self.type = CompressedType(type_name, precision, 'ap_uint<{}>'.format(index_precision), **kwargs)

        self.data = weights

def __init__(self, name, precision, index_precision, **kwargs):
        super(CompressedType, self).__init__('compressed_type{index}', precision, **kwargs)
        self.index_precision = index_precision