**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
creating_job_id: Optional[int] = None,
    ):
        """
        Creates a dag run from this dag including the tasks associated with this dag.
        Returns the dag run.
        :param run_id: defines the run id for this dag run
        :type run_id: str
        :param run_type: type of DagRun
        :type run_type: airflow.utils.types.DagRunType
        :param execution_date: the execution date of this dag run
        :type execution_date: datetime.datetime
        :param state: the state of the dag run
        :type state: airflow.utils.state.State
        :param start_date: the date this dag run should be evaluated
        :type start_date: datetime
        :param external_trigger: whether this dag run is externally triggered
        :type external_trigger: bool
        :param conf: Dict containing configuration/parameters to pass to the DAG
        :type conf: dict
        :param creating_job_id: id of the job creating this DagRun
        :type creating_job_id: int
        :param session: database session
        :type session: sqlalchemy.orm.session.Session
        :param dag_hash: Hash of Serialized DAG
        :type dag_hash: str
        """
        if run_id and not run_type:
            if not isinstance(run_id, str):
                raise ValueError(f"`run_id` expected to be a str is {type(run_id)}")
            run_type: DagRunType = DagRunType.from_run_id(run_id)