**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
"""Generate Run ID based on Run Type and Execution Date"""
        return f"{run_type}__{execution_date.isoformat()}"
    @provide_session
    def get_task_instances(self, state=None, session=None):
        """Returns the task instances for this dag run"""
        tis = session.query(TI).filter(
            TI.dag_id == self.dag_id,
            TI.execution_date == self.execution_date,
        )
        if state:
            if isinstance(state, str):
                tis = tis.filter(TI.state == state)
            else:
                
                if None in state:
                    if all(x is None for x in state):
                        tis = tis.filter(TI.state.is_(None))
                    else:
                        not_none_state = [s for s in state if s]
                        tis = tis.filter(
                            or_(TI.state.in_(not_none_state),
                                TI.state.is_(None))
                        )
                else:
                    tis = tis.filter(TI.state.in_(state))
        if self.dag and self.dag.partial:
            tis = tis.filter(TI.task_id.in_(self.dag.task_ids))
        return tis.all()
    @provide_session
    def get_task_instance(self, task_id: str, session: Session = None):