**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
},
            }
        )
    if task_group.downstream_group_ids or task_group.downstream_task_ids:
        
        children.append(
            {
                'id': task_group.downstream_join_id,
                'value': {
                    'label': '',
                    'labelStyle': f"fill:{task_group.ui_fgcolor};",
                    'style': f"fill:{task_group.ui_color};",
                    'shape': 'circle',
                },
            }
        )
    return {
        "id": task_group.group_id,
        'value': {
            'label': task_group.label,
            'labelStyle': f"fill:{task_group.ui_fgcolor};",
            'style': f"fill:{task_group.ui_color}",
            'rx': 5,
            'ry': 5,
            'clusterLabelPos': 'top',
        },
        'tooltip': task_group.tooltip,
        'children': children,
    }
def dag_edges(dag):