**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.
airflow/models/dagrun.py
self,
        scheduleable_tasks: List[TI],
        finished_tasks: List[TI],
        session: Session,
    ) -> Tuple[List[TI], bool]:
        old_states = {}
        ready_tis: List[TI] = []
        changed_tis = False
        if not scheduleable_tasks:
            return ready_tis, changed_tis
        
        for st in scheduleable_tasks:
            old_state = st.state
            if st.are_dependencies_met(
                dep_context=DepContext(
                    flag_upstream_failed=True,
                    finished_tasks=finished_tasks),
                    session=session):
                ready_tis.append(st)
            else:
                old_states[st.key] = old_state
        
        tis_filter = TI.filter_for_tis(old_states.keys())
        if tis_filter is not None:
            fresh_tis = session.query(TI).filter(tis_filter).all()
            changed_tis = any(ti.state != old_states[ti.key] for ti in fresh_tis)
        return ready_tis, changed_tis
    def _are_premature_tis(