**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
"""
        Test that ignore_first_depends_on_past doesn't affect results
        (this is the same test as
        test_dagrun_deadlock_ignore_depends_on_past_advance_ex_date except
        that start_date == execution_date so depends_on_past is irrelevant).
        """
        self.evaluate_dagrun(
            dag_id='test_dagrun_states_deadlock',
            expected_task_states={
                'test_depends_on_past': State.SUCCESS,
                'test_depends_on_past_2': State.SUCCESS,
            },
            dagrun_state=State.SUCCESS,
            run_kwargs=dict(ignore_first_depends_on_past=True))
    def test_scheduler_start_date(self):