**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
Iterable,
    List,
    Optional,
    Set,
    Tuple,
    Type,
    Union,
    cast,
)
import jinja2
import pendulum
from croniter import croniter
from dateutil.relativedelta import relativedelta
from jinja2.nativetypes import NativeEnvironment
from sqlalchemy import Boolean, Column, ForeignKey, Index, Integer, String, Text, func, or_
from sqlalchemy.orm import backref, joinedload, relationship
from sqlalchemy.orm.session import Session
from sqlalchemy.sql import expression
import airflow.templates
from airflow import settings, utils
from airflow.configuration import conf
from airflow.exceptions import AirflowException, DuplicateTaskIdFound, TaskNotFound
from airflow.models.base import ID_LEN, Base
from airflow.models.baseoperator import BaseOperator
from airflow.models.dagbag import DagBag
from airflow.models.dagcode import DagCode
from airflow.models.dagparam import DagParam
from airflow.models.dagpickle import DagPickle
from airflow.models.dagrun import DagRun
from airflow.models.taskinstance import Context, TaskInstance, clear_task_instances