**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
with DAG(
        dag_id='test_task_with_upstream_skip_dag',
        start_date=DEFAULT_DATE,
        schedule_interval=None
    ) as dag:
        dummy1 = DummyOperator(task_id='dummy1')
        dummy2 = DummyOperator(task_id="dummy2")
        dummy3 = DummyOperator(task_id="dummy3")
        [dummy1, dummy2] >> dummy3
    
    dag.clear()
    dr = dag.create_dagrun(run_type=DagRunType.MANUAL,
                           state=State.RUNNING,
                           execution_date=DEFAULT_DATE)
    assert dr is not None
    with create_session() as session:
        tis = {ti.task_id: ti for ti in dr.get_task_instances(session=session)}
        
        tis[dummy1.task_id].state = State.SKIPPED
        tis[dummy2.task_id].state = State.SUCCESS
        assert tis[dummy3.task_id].state == State.NONE
    
    
    with create_session() as session:
        tis = {ti.task_id: ti for ti in dr.get_task_instances(session=session)}
        assert tis[dummy1.task_id].state == State.SKIPPED
        assert tis[dummy2.task_id].state == State.SUCCESS
        
        assert tis[dummy3.task_id].state == State.SKIPPED
class TestSchedulerJobQueriesCount(unittest.TestCase):