**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 task instance state."""
        try:
            count = len(tis)
            for ti in tis:
                ti.set_state(target_state, session)
            session.commit()
            flash(f"{count} task instances were set to '{target_state}'")
        except Exception:  
            flash('Failed to set state', 'error')
    @action('set_running', "Set state to 'running'", '', single=False)
    @auth.has_access(
        [
            (permissions.ACTION_CAN_EDIT, permissions.RESOURCE_DAG),
        ]
    )
    def action_set_running(self, tis):
        """Set state to 'running'"""
        self.set_task_instance_state(tis, State.RUNNING)
        self.update_redirect()
        return redirect(self.get_redirect())
    @action('set_failed', "Set state to 'failed'", '', single=False)
    @auth.has_access(
        [
            (permissions.ACTION_CAN_EDIT, permissions.RESOURCE_DAG),
        ]
    )
    def action_set_failed(self, tis):