**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
from airflow.decorators import task
        return functools.partial(task, dag=self)
    def add_task(self, task):
        """
        Add a task to the DAG
        :param task: the task you want to add
        :type task: task
        """
        if not self.start_date and not task.start_date:
            raise AirflowException("Task is missing the start_date parameter")
        
        elif not task.start_date:
            task.start_date = self.start_date
        
        
        elif self.start_date:
            task.start_date = max(task.start_date, self.start_date)
        
        if not task.end_date:
            task.end_date = self.end_date
        
        
        elif task.end_date and self.end_date:
            task.end_date = min(task.end_date, self.end_date)
        if (
            task.task_id in self.task_dict and self.task_dict[task.task_id] is not task
        ) or task.task_id in self._task_group.used_group_ids: