**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
"""Set state to 'up_for_retry'"""
        self.set_task_instance_state(tis, State.UP_FOR_RETRY)
        self.update_redirect()
        return redirect(self.get_redirect())
class DagModelView(AirflowModelView):
    """View to show records from DAG table"""
    route_base = '/dagmodel'
    datamodel = AirflowModelView.CustomSQLAInterface(DagModel)  
    class_permission_name = permissions.RESOURCE_DAG
    method_permission_name = {
        'list': 'read',
        'show': 'read',
    }
    base_permissions = [
        permissions.ACTION_CAN_READ,
        permissions.ACTION_CAN_EDIT,
        permissions.ACTION_CAN_DELETE,
    ]
    list_columns = [
        'dag_id',
        'is_paused',
        'last_parsed_time',
        'last_expired',
        'scheduler_lock',
        'fileloc',
        'owners',
    ]
    formatters_columns = {'dag_id': wwwutils.dag_link}
    base_filters = [['dag_id', DagFilter, lambda: []]]
    def get_query(self):