**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 = drs[0]
        dag_version_1 = SerializedDagModel.get_latest_version_hash(dr.dag_id, session=session)
        assert dr.dag_hash == dag_version_1
        assert scheduler.dagbag.dags == {'test_verify_integrity_if_dag_changed': dag}
        assert len(scheduler.dagbag.dags.get("test_verify_integrity_if_dag_changed").tasks) == 1
        
        BashOperator(task_id='bash_task_1', dag=dag, bash_command='echo hi')
        SerializedDagModel.write_dag(dag=dag)
        dag_version_2 = SerializedDagModel.get_latest_version_hash(dr.dag_id, session=session)
        assert dag_version_2 != dag_version_1
        scheduled_tis = scheduler._schedule_dag_run(dr, 0, session)
        session.flush()
        assert scheduled_tis == 2
        drs = DagRun.find(dag_id=dag.dag_id, session=session)
        assert len(drs) == 1
        dr = drs[0]
        assert dr.dag_hash == dag_version_2
        assert scheduler.dagbag.dags == {'test_verify_integrity_if_dag_changed': dag}
        assert len(scheduler.dagbag.dags.get("test_verify_integrity_if_dag_changed").tasks) == 2
        tis_count = session.query(func.count(TaskInstance.task_id)).filter(
            TaskInstance.dag_id == dr.dag_id,
            TaskInstance.execution_date == dr.execution_date,
            TaskInstance.state == State.SCHEDULED
        ).scalar()
        assert tis_count == 2
        latest_dag_version = SerializedDagModel.get_latest_version_hash(dr.dag_id, session=session)
        assert dr.dag_hash == latest_dag_version
        session.rollback()
        session.close()
    def test_retry_still_in_executor(self):