**Apache Airflow version**:

2.0.1

**What happened**:

When clearing task across dags using `ExternalTaskMarker` the dag state of the external `DagRun` is not set to active. So cleared tasks in the external dag will not automatically start if the `DagRun` is a Failed or Succeeded state.

**What you expected to happen**:

The external `DagRun` run should also be set to Running state.

**How to reproduce it**:

Clear tasks in an external dag using an ExternalTaskMarker.


**Anything else we need to know**:

Looking at the code is has:

https://github.com/apache/airflow/blob/b23fc137812f5eabf7834e07e032915e2a504c17/airflow/models/dag.py#L1323-L1335

It seems like it intentionally calls the dag member method `set_dag_run_state` instead of letting the helper function `clear_task_insntances` set the `DagRun` state. But the member method will only change the state of `DagRun`s of dag where the original task is, while I believe `clear_task_instances` would correctly change the state of all involved `DagRun`s.

airflow/models/dag.py
return f"<DAG: {self.dag_id}>"
    def __eq__(self, other):
        if type(self) == type(other):
            
            
            return all(getattr(self, c, None) == getattr(other, c, None) for c in self._comps)
        return False
    def __ne__(self, other):
        return not self == other
    def __lt__(self, other):
        return self.dag_id < other.dag_id
    def __hash__(self):
        hash_components = [type(self)]
        for c in self._comps:
            
            if c == 'task_ids':
                val = tuple(self.task_dict.keys())
            else:
                val = getattr(self, c, None)
            try:
                hash(val)
                hash_components.append(val)
            except TypeError:
                hash_components.append(repr(val))
        return hash(tuple(hash_components))
    
    def __enter__(self):