**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
super().__init__(**kwargs)
        if self.concurrency is None:
            self.concurrency = conf.getint('core', 'dag_concurrency')
        if self.has_task_concurrency_limits is None:
            
            self.has_task_concurrency_limits = True
    def __repr__(self):
        return f"<DAG: {self.dag_id}>"
    @property
    def timezone(self):
        return settings.TIMEZONE
    @staticmethod
    @provide_session
    def get_dagmodel(dag_id, session=None):