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**Apache Airflow version**: 2.0.1


**Kubernetes version (if you are using kubernetes)** (use `kubectl version`): 1.18.15

**Environment**:

- **Cloud provider or hardware configuration**: AWS
- **OS** (e.g. from /etc/os-release): ubuntu 18.04
- **Kernel** (e.g. `uname -a`): Linux mlb-airflow-infra-workers-75f589bcd9-wtls8 4.9.0-9-amd64 #1 SMP Debian 4.9.168-1 (2019-04-12) x86_64 x86_64 x86_64 GNU/Linux
- **Install tools**:
- **Others**:

**What happened**:

<!-- (please include exact error messages if you can) -->
Scheduler is constantly restarting due to this error:
```
[2021-03-03 17:31:19,393] {scheduler_job.py:1298} ERROR - Exception when executing SchedulerJob._run_scheduler_loop
Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/airflow/jobs/scheduler_job.py", line 1280, in _execute
    self._run_scheduler_loop()
  File "/usr/local/lib/python3.6/dist-packages/airflow/jobs/scheduler_job.py", line 1384, in _run_scheduler_loop
    self.executor.heartbeat()
  File "/usr/local/lib/python3.6/dist-packages/airflow/executors/base_executor.py", line 162, in heartbeat
    self.sync()
  File "/usr/local/lib/python3.6/dist-packages/airflow/executors/celery_executor.py", line 340, in sync
    self.update_all_task_states()
  File "/usr/local/lib/python3.6/dist-packages/airflow/executors/celery_executor.py", line 399, in update_all_task_states
    state_and_info_by_celery_task_id = self.bulk_state_fetcher.get_many(self.tasks.values())
  File "/usr/local/lib/python3.6/dist-packages/airflow/executors/celery_executor.py", line 552, in get_many
    result = self._get_many_from_db_backend(async_results)
  File "/usr/local/lib/python3.6/dist-packages/airflow/executors/celery_executor.py", line 570, in _get_many_from_db_backend
    task_cls = app.backend.task_cls
AttributeError: 'DatabaseBackend' object has no attribute 'task_cls'
[2021-03-03 17:31:20,396] {process_utils.py:100} INFO - Sending Signals.SIGTERM to GPID 3852
[2021-03-03 17:31:20,529] {process_utils.py:66} INFO - Process psutil.Process(pid=3996, status='terminated', started='17:31:19') (3996) terminated with exit code None
[2021-03-03 17:31:20,533] {process_utils.py:66} INFO - Process psutil.Process(pid=3997, status='terminated', started='17:31:19') (3997) terminated with exit code None
[2021-03-03 17:31:20,533] {process_utils.py:206} INFO - Waiting up to 5 seconds for processes to exit...
[2021-03-03 17:31:20,540] {process_utils.py:66} INFO - Process psutil.Process(pid=3852, status='terminated', exitcode=0, started='17:31:13') (3852) terminated with exit code 0
[2021-03-03 17:31:20,540] {scheduler_job.py:1301} INFO - Exited execute loop
```

**What you expected to happen**: Scheduler running

<!-- What do you think went wrong? -->

**How to reproduce it**:

Install airflow  2.0.1 in an ubuntu 18.04 instance:

`pip install apache-airflow[celery,postgres,s3,crypto,jdbc,google_auth,redis,slack,ssh,sentry,kubernetes,statsd]==2.0.1`

Use the following variables:
```
AIRFLOW__CORE__SQL_ALCHEMY_CONN=postgresql+psycopg2://airflow:<pwd>@<DB>:<port>/airflow
AIRFLOW__CORE__DEFAULT_TIMEZONE=<TZ>
AIRFLOW__CORE__LOAD_DEFAULTS=false
AIRFLOW__CELERY__BROKER_URL=sqs://
AIRFLOW__CELERY__DEFAULT_QUEUE=<queue>
AIRFLOW__CORE__REMOTE_BASE_LOG_FOLDER=s3://<bucket>/<prefix>/
AIRFLOW__CORE__LOAD_EXAMPLES=false
AIRFLOW__CORE__REMOTE_LOGGING=True
AIRFLOW__CORE__FERNET_KEY=<fernet_key>
AIRFLOW__CORE__EXECUTOR=CeleryExecutor
AIRFLOW__CELERY__BROKER_TRANSPORT_OPTIONS__REGION=<region>
AIRFLOW__CELERY__RESULT_BACKEND=db+postgresql://airflow:<pwd>@<DB>:<port>/airflow
```

Start airflow components (webserver, celery workers, scheduler). With no DAGs running everything is stable and not failing but once a DAGs start running the scheduler starts getting the error and from then it constantly reboots until crash.

<!---

As minimally and precisely as possible. Keep in mind we do not have access to your cluster or dags.

If you are using kubernetes, please attempt to recreate the issue using minikube or kind.

## Install minikube/kind

- Minikube https://minikube.sigs.k8s.io/docs/start/
- Kind https://kind.sigs.k8s.io/docs/user/quick-start/

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--->


**Anything else we need to know**:

This happens every time and the scheduler keeps restarting

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airflow/executors/celery_executor.py
super().__init__()
        
        
        
        self._sync_parallelism = conf.getint('celery', 'SYNC_PARALLELISM')
        if self._sync_parallelism == 0:
            self._sync_parallelism = max(1, cpu_count() - 1)
        self.bulk_state_fetcher = BulkStateFetcher(self._sync_parallelism)
        self.tasks = {}
        
        self.adopted_task_timeouts: Dict[TaskInstanceKey, datetime.datetime] = OrderedDict()
        self.task_adoption_timeout = datetime.timedelta(
            seconds=conf.getint('celery', 'task_adoption_timeout', fallback=600)
        )
        self.task_publish_retries: Dict[TaskInstanceKey, int] = OrderedDict()
        self.task_publish_max_retries = conf.getint('celery', 'task_publish_max_retries', fallback=3)
    def start(self) -> None:
        self.log.debug('Starting Celery Executor using %s processes for syncing', self._sync_parallelism)
    def _num_tasks_per_send_process(self, to_send_count: int) -> int:
        """
        How many Celery tasks should each worker process send.
        :return: Number of tasks that should be sent per process
        :rtype: int
        """
        return max(1, int(math.ceil(1.0 * to_send_count / self._sync_parallelism)))
    def trigger_tasks(self, open_slots: int) -> None: