**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
from jinja2.utils import htmlsafe_json_dumps, pformat  
from pendulum.datetime import DateTime
from pygments import highlight, lexers
from pygments.formatters import HtmlFormatter  
from sqlalchemy import Date, and_, desc, func, or_, union_all
from sqlalchemy.orm import joinedload
from wtforms import SelectField, validators
from wtforms.validators import InputRequired
import airflow
from airflow import models, plugins_manager, settings
from airflow.api.common.experimental.mark_tasks import (
    set_dag_run_state_to_failed,
    set_dag_run_state_to_success,
)
from airflow.configuration import AIRFLOW_CONFIG, conf
from airflow.exceptions import AirflowException
from airflow.executors.executor_loader import ExecutorLoader
from airflow.jobs.base_job import BaseJob
from airflow.jobs.scheduler_job import SchedulerJob
from airflow.models import DAG, Connection, DagModel, DagTag, Log, SlaMiss, TaskFail, XCom, errors
from airflow.models.baseoperator import BaseOperator
from airflow.models.dagcode import DagCode
from airflow.models.dagrun import DagRun, DagRunType
from airflow.models.serialized_dag import SerializedDagModel
from airflow.models.taskinstance import TaskInstance
from airflow.providers_manager import ProvidersManager
from airflow.security import permissions
from airflow.ti_deps.dep_context import DepContext
from airflow.ti_deps.dependencies_deps import RUNNING_DEPS, SCHEDULER_QUEUED_DEPS
from airflow.utils import json as utils_json, timezone, yaml