**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_ids = dagbag.dag_ids
            dagbag = DagBag(read_dags_from_db=True)
            for i, dag_id in enumerate(dag_ids):
                dag = dagbag.get_dag(dag_id)
                dr = dag.create_dagrun(
                    state=State.RUNNING,
                    run_id=f"{DagRunType.MANUAL.value}__{i}",
                    dag_hash=dagbag.dags_hash[dag.dag_id],
                )
                dagruns.append(dr)
                for ti in dr.get_task_instances():
                    ti.set_state(state=State.SCHEDULED)
            mock_agent = mock.MagicMock()
            job = SchedulerJob(subdir=PERF_DAGS_FOLDER, num_runs=1)
            job.executor = MockExecutor(do_update=False)
            job.heartbeat = mock.MagicMock()
            job.processor_agent = mock_agent
            with assert_queries_count(expected_query_count):
                with mock.patch.object(DagRun, 'next_dagruns_to_examine') as mock_dagruns:
                    mock_dagruns.return_value = dagruns
                    job._run_scheduler_loop()
    @parameterized.expand(
        [
            
            
            
            ([10,  10,  10, 10],  1,  1, "1d",  "None",  "no_structure"),  
            ([10,  10,  10, 10],  1,  1, "1d",  "None",        "linear"),  
            ([22,  14,  14, 14],  1,  1, "1d", "@once",  "no_structure"),  
            ([22,  14,  14, 14],  1,  1, "1d", "@once",        "linear"),