**Apache Airflow version**: 2.0.0, LocalExecutor

**Environment**: Docker on Win10 with WSL, official Python3.8 image

**What happened**:

When a DAG is running, and I delete task from the running DAG, the scheduler fails. When using Docker, upon automatic restart of the scheduler, the scheduler just fails again, perpetually.

![image](https://user-images.githubusercontent.com/46958547/103558919-a89f6e80-4eb5-11eb-8521-19b04ee3c690.png)

Note: I don't _know_ if the task itself was running at the time, but I would guess it was.

**What you expected to happen**:

The scheduler should understand that the task is not part of the DAG anymore and not fail.

**How to reproduce it**:

- Create a DAG with multiple tasks
- Let it run
- While running, delete one of the tasks from the source code
- See the scheduler break
airflow/models/dagrun.py
if unfinished_tasks and none_depends_on_past and none_task_concurrency:
                
                are_runnable_tasks = (
                    schedulable_tis
                    or self._are_premature_tis(unfinished_tasks, finished_tasks, session)
                    or changed_tis
                )
        leaf_task_ids = {t.task_id for t in dag.leaves}
        leaf_tis = [ti for ti in tis if ti.task_id in leaf_task_ids]
        
        if not unfinished_tasks and any(leaf_ti.state in State.failed_states for leaf_ti in leaf_tis):
            self.log.error('Marking run %s failed', self)
            self.set_state(State.FAILED)
            if execute_callbacks:
                dag.handle_callback(self, success=False, reason='task_failure', session=session)
            elif dag.has_on_failure_callback:
                callback = callback_requests.DagCallbackRequest(
                    full_filepath=dag.fileloc,
                    dag_id=self.dag_id,
                    execution_date=self.execution_date,
                    is_failure_callback=True,
                    msg='task_failure',
                )
        
        elif not unfinished_tasks and all(leaf_ti.state in State.success_states for leaf_ti in leaf_tis):
            self.log.info('Marking run %s successful', self)
            self.set_state(State.SUCCESS)
            if execute_callbacks:
                dag.handle_callback(self, success=True, reason='success', session=session)
            elif dag.has_on_success_callback: