**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
dag = DAG(
            dag_id='dag_id',
            start_date=DEFAULT_DATE)
        task = DummyOperator(
            task_id='task_id',
            dag=dag,
            owner='airflow')
        dag = SerializedDAG.from_dict(SerializedDAG.to_dict(dag))
        
        session = settings.Session()
        scheduler_job = SchedulerJob()
        mock_logger = mock.MagicMock()
        test_executor = MockExecutor(do_update=False)
        scheduler_job.executor = test_executor
        scheduler_job._logger = mock_logger
        scheduler_job._change_state_for_tasks_failed_to_execute()  
        mock_logger.info.assert_not_called()
        
        session.query(TaskInstance).delete()
        session.commit()
        key = 'dag_id', 'task_id', DEFAULT_DATE, 1
        test_executor.queued_tasks[key] = 'value'
        ti = TaskInstance(task, DEFAULT_DATE)
        ti.state = State.QUEUED
        session.merge(ti)  
        session.commit()
        scheduler_job._change_state_for_tasks_failed_to_execute()  
        ti.refresh_from_db()
        self.assertEqual(State.SCHEDULED, ti.state)