**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/www/views.py
@auth.has_access(
        [
            (permissions.ACTION_CAN_READ, permissions.RESOURCE_DAG),
            (permissions.ACTION_CAN_READ, permissions.RESOURCE_TASK_INSTANCE),
        ]
    )
    @action_logging
    def task(self):
        """Retrieve task."""
        dag_id = request.args.get('dag_id')
        task_id = request.args.get('task_id')
        
        
        execution_date = request.args.get('execution_date')
        dttm = timezone.parse(execution_date)
        form = DateTimeForm(data={'execution_date': dttm})
        root = request.args.get('root', '')
        dag = current_app.dag_bag.get_dag(dag_id)
        if not dag or task_id not in dag.task_ids:
            flash(f"Task [{dag_id}.{task_id}] doesn't seem to exist at the moment", "error")
            return redirect(url_for('Airflow.index'))
        task = copy.copy(dag.get_task(task_id))
        task.resolve_template_files()
        ti = TaskInstance(task=task, execution_date=dttm)
        ti.refresh_from_db()
        ti_attrs = []
        for attr_name in dir(ti):
            if not attr_name.startswith('_'):
                attr = getattr(ti, attr_name)
                if type(attr) != type(self.task):