objectives and metrics for multi-class multi-output (aka multi-label) xgboost classifier

This [tutorial](https://xgboost.readthedocs.io/en/stable/tutorials/multioutput.html) states that XGBoost 1.6 has experimental support for multi-output classification. However, it also states that there is limited support from objectives and metrics. In the multi-class _single-output_ scenario, I use `multi:softprob` as the objective and `mlogloss` as a metric. Could I use the same objective and metric for the multi-class _multi-output_ scenario? Or are there alternative objectives and metrics that I should use instead?