**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
"""
        Checks if the scheduler does not put a task in limbo, when a task is retried
        but is still present in the executor.
        """
        executor = MockExecutor(do_update=False)
        dagbag = DagBag(dag_folder=os.path.join(settings.DAGS_FOLDER, "no_dags.py"), include_examples=False)
        dagbag.dags.clear()
        dag = DAG(
            dag_id='test_retry_still_in_executor',
            start_date=DEFAULT_DATE,
            schedule_interval="@once")
        dag_task1 = BashOperator(
            task_id='test_retry_handling_op',
            bash_command='exit 1',
            retries=1,
            dag=dag,
            owner='airflow')
        dag.clear()
        dag.is_subdag = False
        with create_session() as session:
            orm_dag = DagModel(dag_id=dag.dag_id)
            orm_dag.is_paused = False
            session.merge(orm_dag)
        dagbag.bag_dag(dag=dag, root_dag=dag)
        dagbag.sync_to_db()
        @mock.patch('airflow.jobs.scheduler_job.DagBag', return_value=dagbag)
        def do_schedule(mock_dagbag):