**Apache Airflow version**: 2.0.0

**Environment**:

- **Cloud provider or hardware configuration**: Docker container
- **OS** (e.g. from /etc/os-release): Debian Stretch

**What happened**:

When working on some custom DAG override logic, I noticed that invoking `DAG.partial_subset` does not properly update the corresponding `_task_group.used_group_ids` on the returned subset DAG, such that adding back a task which was excluded during the `partial_subset` operation fails.

**What you expected to happen**:

Tasks that had already been added to the original DAG can be added again to the subset DAG returned by `DAG.partial_subset`

**How to reproduce it**:
Create any DAG with a single task called, e.g. `my-task`, then invoke `dag.partial_subset(['not-my-task'], False, False)`

Note that the returned subset DAG's `_task_group.used_group_ids` still contains `my-task` even though it was not included in the subset DAG itself

**Anything else we need to know**:

I was able to work around this by adding logic to update the new partial subset DAG's `_task_group.used_group_ids` manually, but this should really be done as part of the `DAG.partial_subset` logic
airflow/models/dag.py
"""This method is deprecated in favor of bulk_write_to_db"""
        warnings.warn(
            "This method is deprecated and will be removed in a future version. Please use bulk_write_to_db",
            DeprecationWarning,
            stacklevel=2,
        )
        return cls.bulk_write_to_db(dags, session)
    @classmethod
    @provide_session
    def bulk_write_to_db(cls, dags: Collection["DAG"], session=None):
        """
        Ensure the DagModel rows for the given dags are up-to-date in the dag table in the DB, including
        calculated fields.
        Note that this method can be called for both DAGs and SubDAGs. A SubDag is actually a SubDagOperator.
        :param dags: the DAG objects to save to the DB
        :type dags: List[airflow.models.dag.DAG]
        :return: None
        """
        if not dags:
            return
        log.info("Sync %s DAGs", len(dags))
        dag_by_ids = {dag.dag_id: dag for dag in dags}
        dag_ids = set(dag_by_ids.keys())
        query = (
            session.query(DagModel)