How to use the gnomad.utils.gnomad_functions.logger.warn function in gnomad

filter_expr.append((mt.hwe.p_value > min_hardy_weinberg_threshold))
    if snv_only:
        filter_expr.append(hl.is_snp(mt.alleles[0], mt.alleles[1]))
    if bi_allelic_only:
        filter_expr.append(bi_allelic_expr(mt))

    if apply_hard_filters:
        if 'info' in mt.row_value:
            if 'QD' in mt.info:
                filter_expr.append((mt.info.QD >= 2))
            else:
                logger.warn("Could not apply QD hard filter, as `info.QD` not found in schema.")
            if 'FS' in mt.info:
                filter_expr.append((mt.info.FS <= 60))
            else:
                logger.warn("Could not apply FS hard filter, as `info.FS` not found in schema.")
            if 'MQ' in mt.info:
                filter_expr.append((mt.info.MQ >= 30))
            else:
                logger.warn("Could not apply MQ hard filter, as `info.MQ` not found in schema.")
        else:
            logger.warn("Could not apply hard filters as `info` not found in schema.")

    return mt.filter_rows(functools.reduce(operator.iand, filter_expr))

filter_expr.append(bi_allelic_expr(mt))

    if apply_hard_filters:
        if 'info' in mt.row_value:
            if 'QD' in mt.info:
                filter_expr.append((mt.info.QD >= 2))
            else:
                logger.warn("Could not apply QD hard filter, as `info.QD` not found in schema.")
            if 'FS' in mt.info:
                filter_expr.append((mt.info.FS <= 60))
            else:
                logger.warn("Could not apply FS hard filter, as `info.FS` not found in schema.")
            if 'MQ' in mt.info:
                filter_expr.append((mt.info.MQ >= 30))
            else:
                logger.warn("Could not apply MQ hard filter, as `info.MQ` not found in schema.")
        else:
            logger.warn("Could not apply hard filters as `info` not found in schema.")

    return mt.filter_rows(functools.reduce(operator.iand, filter_expr))

if apply_hard_filters:
        if 'info' in mt.row_value:
            if 'QD' in mt.info:
                filter_expr.append((mt.info.QD >= 2))
            else:
                logger.warn("Could not apply QD hard filter, as `info.QD` not found in schema.")
            if 'FS' in mt.info:
                filter_expr.append((mt.info.FS <= 60))
            else:
                logger.warn("Could not apply FS hard filter, as `info.FS` not found in schema.")
            if 'MQ' in mt.info:
                filter_expr.append((mt.info.MQ >= 30))
            else:
                logger.warn("Could not apply MQ hard filter, as `info.MQ` not found in schema.")
        else:
            logger.warn("Could not apply hard filters as `info` not found in schema.")

    return mt.filter_rows(functools.reduce(operator.iand, filter_expr))

The input interval HT should have a key of type Interval.
        The resulting table will have a key of the same type as the `intervals_ht` table and
        contain an `interval_info` field containing all non-key fields of the `intervals_ht`.

    :param mt: Input MT
    :param intervals_ht: Table containing the intervals. This table has to be keyed by locus.
    :param bi_allelic_only: If set, only bi-allelic sites are used for the computation
    :param autosomes_only: If set, only autosomal intervals are used.
    :param matches: If set, returns all intervals in intervals_ht that overlap the locus in the input MT.
    :return: Callrate MT
    """
    logger.info('Computing call rate MatrixTable')

    if len(intervals_ht.key) != 1 or not isinstance(intervals_ht.key[0], hl.expr.IntervalExpression):
        logger.warn(f'Call rate matrix computation expects `intervals_ht` with a key of type Interval. Found: {intervals_ht.key}')

    if autosomes_only:
        callrate_mt = filter_to_autosomes(mt)

    if bi_allelic_only:
        callrate_mt = callrate_mt.filter_rows(bi_allelic_expr(callrate_mt))

    intervals_ht = intervals_ht.annotate(_interval_key=intervals_ht.key)
    callrate_mt = callrate_mt.annotate_rows(_interval_key=intervals_ht.index(callrate_mt.locus, all_matches=match)._interval_key)

    if match:
        callrate_mt = callrate_mt.explode_rows('_interval_key')

    callrate_mt = callrate_mt.filter_rows(hl.is_defined(callrate_mt._interval_key.interval))
    callrate_mt = callrate_mt.select_entries(GT=hl.or_missing(hl.is_defined(callrate_mt.GT), hl.struct()))
    callrate_mt = callrate_mt.group_rows_by(**callrate_mt._interval_key).aggregate(callrate=hl.agg.fraction(hl.is_defined(callrate_mt.GT)))