**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
dr = dag.create_dagrun(
                run_type=DagRunType.SCHEDULED,
                execution_date=dag.following_schedule(dr.execution_date),
                state=State.RUNNING,
            )
        ex_date = dr.execution_date
        for tid, state in expected_task_states.items():
            if state != State.FAILED:
                continue
            self.null_exec.mock_task_fail(dag_id, tid, ex_date)
        try:
            dag = DagBag().get_dag(dag.dag_id)
            assert not isinstance(dag, SerializedDAG)
            
            dag.run(start_date=ex_date, end_date=ex_date, executor=self.null_exec, **run_kwargs)
        except AirflowException:
            pass
        
        for task_id, expected_state in expected_task_states.items():
            task = dag.get_task(task_id)
            ti = TaskInstance(task, ex_date)
            ti.refresh_from_db()
            self.assertEqual(ti.state, expected_state)
        
        dr = DagRun.find(dag_id=dag_id, execution_date=ex_date)
        dr = dr[0]
        dr.dag = dag
        self.assertEqual(dr.state, dagrun_state)
    def test_dagrun_fail(self):