**Apache Airflow version**: 2.0.0a1

**What happened**:

On my dev environment I have a lot of DAG runs with failed tasks, where the *downstream* task instances then have been set to `upstream_failed`. The scheduler is now refusing to schedule more instances for such DAGs.

The scheduler looks for such task instances that are not in the `State.finished` set:

https://github.com/apache/airflow/blob/db3fe0926bb75008311eed804052c90bfa912424/airflow/jobs/scheduler_job.py#L1482-L1488

However, `State.finished` is currently not a proper inverse of *running* states, it only includes success, failed, and skipped:

https://github.com/apache/airflow/blob/db3fe0926bb75008311eed804052c90bfa912424/airflow/utils/state.py#L110-L114

What is missing is the task instance `upstream_failed` state, so currently my log is being filled (very rapidly) with:

```
[2020-10-18 13:22:18,503] {{scheduler_job.py:1658}} INFO - DAG test_dag already has 26 active runs, not queuing any more tasks
```

Those 26 'active runs' are simply dag runs that failed and have 'upstream_failed' task instances.

Either `upstream_failed` should be added to `State.finished`, or the Scheduler task instance test should explicitly take that state into account.
tests/jobs/test_scheduler_job.py
state=State.RUNNING,
                                 execution_date=DEFAULT_DATE,
                                 start_date=DEFAULT_DATE,
                                 session=session)
        ti1a = dr1.get_task_instance(task_id='dummy', session=session)
        ti1a.state = State.SCHEDULED
        ti1b = dr1.get_task_instance(task_id='dummy_b', session=session)
        ti1b.state = State.SUCCESS
        session.commit()
        ti2 = dr2.get_task_instance(task_id='dummy', session=session)
        ti2.state = State.SCHEDULED
        session.commit()
        ti3 = TaskInstance(dag3.get_task('dummy'), DEFAULT_DATE)
        ti3.state = State.SCHEDULED
        session.merge(ti3)
        session.commit()
        with mock.patch.object(settings, "STORE_SERIALIZED_DAGS", True):
            dagbag = DagBag("/dev/null", include_examples=False)
            dagbag.bag_dag(dag1, root_dag=dag1)
            dagbag.bag_dag(dag2, root_dag=dag2)
            dagbag.bag_dag(dag3, root_dag=dag3)
            dagbag.sync_to_db(session)
        scheduler = SchedulerJob(num_runs=0)
        scheduler.dagbag.collect_dags_from_db()
        scheduler._change_state_for_tis_without_dagrun(
            old_states=[State.SCHEDULED, State.QUEUED],
            new_state=State.NONE,
            session=session)
        ti1a = dr1.get_task_instance(task_id='dummy', session=session)
        ti1a.refresh_from_db(session=session)