**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
)
                else:
                    tis = tis.filter(TaskInstance.state.in_(state))
        tis = tis.order_by(TaskInstance.execution_date).all()
        return tis
    @property
    def roots(self) -> List[BaseOperator]:
        """Return nodes with no parents. These are first to execute and are called roots or root nodes."""
        return [task for task in self.tasks if not task.upstream_list]
    @property
    def leaves(self) -> List[BaseOperator]:
        """Return nodes with no children. These are last to execute and are called leaves or leaf nodes."""
        return [task for task in self.tasks if not task.downstream_list]
    def topological_sort(self, include_subdag_tasks: bool = False):
        """
        Sorts tasks in topographical order, such that a task comes after any of its
        upstream dependencies.
        Heavily inspired by:
        http://blog.jupo.org/2012/04/06/topological-sorting-acyclic-directed-graphs/
        :param include_subdag_tasks: whether to include tasks in subdags, default to False
        :return: list of tasks in topological order
        """
        from airflow.operators.subdag import SubDagOperator  
        
        graph_unsorted = OrderedDict((task.task_id, task) for task in self.tasks)
        graph_sorted = []  
        
        if len(self.tasks) == 0:
            return tuple(graph_sorted)