**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
DR = DagRun
        qry = session.query(DR)
        dag_ids = [dag_id] if isinstance(dag_id, str) else dag_id
        if dag_ids:
            qry = qry.filter(DR.dag_id.in_(dag_ids))
        if run_id:
            qry = qry.filter(DR.run_id == run_id)
        if execution_date:
            if isinstance(execution_date, list):
                qry = qry.filter(DR.execution_date.in_(execution_date))
            else:
                qry = qry.filter(DR.execution_date == execution_date)
        if execution_start_date and execution_end_date:
            qry = qry.filter(DR.execution_date.between(execution_start_date, execution_end_date))
        elif execution_start_date:
            qry = qry.filter(DR.execution_date >= execution_start_date)
        elif execution_end_date:
            qry = qry.filter(DR.execution_date <= execution_end_date)
        if state:
            qry = qry.filter(DR.state == state)
        if external_trigger is not None:
            qry = qry.filter(DR.external_trigger == external_trigger)
        if run_type:
            qry = qry.filter(DR.run_type == run_type)
        if no_backfills:
            qry = qry.filter(DR.run_type != DagRunType.BACKFILL_JOB)
        dr = qry.order_by(DR.execution_date).all()
        return dr
    @staticmethod
    def generate_run_id(run_type: DagRunType, execution_date: datetime) -> str: