**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/taskinstance.py
"""Prepare Task for Execution"""
        from airflow.models.renderedtifields import RenderedTaskInstanceFields
        task_copy = task.prepare_for_execution()
        self.task = task_copy
        def signal_handler(signum, frame):  
            self.log.error("Received SIGTERM. Terminating subprocesses.")
            task_copy.on_kill()
            raise AirflowException("Task received SIGTERM signal")
        signal.signal(signal.SIGTERM, signal_handler)
        
        self.clear_xcom_data()
        with Stats.timer(f'dag.{task_copy.dag_id}.{task_copy.task_id}.duration'):
            self.render_templates(context=context)
            RenderedTaskInstanceFields.write(RenderedTaskInstanceFields(ti=self, render_templates=False))
            RenderedTaskInstanceFields.delete_old_records(self.task_id, self.dag_id)
            
            airflow_context_vars = context_to_airflow_vars(context, in_env_var_format=True)
            self.log.info(
                "Exporting the following env vars:\n%s",
                '\n'.join(f"{k}={v}" for k, v in airflow_context_vars.items()),
            )
            os.environ.update(airflow_context_vars)
            
            task_copy.pre_execute(context=context)
            
            self._run_execute_callback(context, task)
            if task_copy.is_smart_sensor_compatible():