**Description**

For a DAG that looks like this:

```
A >> B
```

If A fails, B goes into "upstream_failed" state. If a user then marks A "success", B will remain in "upstream_failed" state. It will not automatically start running. This scenario often happens if the failure of A is dealt with outside of Airflow and the user does not want Airflow to run A again. But he usually expect Airflow to run B after A is marked "success".

**Use case / motivation**

After A is marked "success", its downstream tasks B should be cleared automatically and get ready to be scheduled. To avoid changing this behaviour completely, there can be a toggle button next to "Success" that lets the user decide if he wants Airflow to automatically clear downstream tasks that are in "upstream_failed" state.
airflow/models/dag.py
tis = tis.all()
        if dry_run:
            session.expunge_all()
            return tis
        
        
        count = len(tis)
        do_it = True
        if count == 0:
            return 0
        if confirm_prompt:
            ti_list = "\n".join(str(t) for t in tis)
            question = (
                "You are about to delete these {count} tasks:\n{ti_list}\n\nAre you sure? (yes/no): "
            ).format(count=count, ti_list=ti_list)
            do_it = utils.helpers.ask_yesno(question)
        if do_it:
            clear_task_instances(
                tis,
                session,
                dag=self,
                dag_run_state=dag_run_state,
            )
        else:
            count = 0
            print("Cancelled, nothing was cleared.")
        session.commit()
        return count
    @classmethod
    def clear_dags(