**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
root=root,
        )
    @expose('/graph')
    @auth.has_access(
        [
            (permissions.ACTION_CAN_READ, permissions.RESOURCE_DAG),
            (permissions.ACTION_CAN_READ, permissions.RESOURCE_TASK_INSTANCE),
            (permissions.ACTION_CAN_READ, permissions.RESOURCE_TASK_LOG),
        ]
    )
    @gzipped
    @action_logging
    @provide_session
    def graph(self, session=None):
        """Get DAG as Graph."""
        dag_id = request.args.get('dag_id')
        dag = current_app.dag_bag.get_dag(dag_id)
        if not dag:
            flash(f'DAG "{dag_id}" seems to be missing.', "error")
            return redirect(url_for('Airflow.index'))
        root = request.args.get('root')
        if root:
            dag = dag.sub_dag(task_ids_or_regex=root, include_upstream=True, include_downstream=False)
        arrange = request.args.get('arrange', dag.orientation)
        nodes = task_group_to_dict(dag.task_group)
        edges = dag_edges(dag)
        dt_nr_dr_data = get_date_time_num_runs_dag_runs_form_data(request, session, dag)
        dt_nr_dr_data['arrange'] = arrange
        dttm = dt_nr_dr_data['dttm']
        class GraphForm(DateTimeWithNumRunsWithDagRunsForm):