Currently, the celery executor imports the `Task` model for the Celery database backend directly:

https://github.com/apache/airflow/blob/2dd4e96045d4a7f45cc8c06df3d25c4f1479392c/airflow/executors/celery_executor.py#L38

However, Celery, being highly customisable, uses `self.task_cls` in the backend implementation; this defaults to either `Task` or `TaskExtended` depending on the Celery configuration, see [`celery.backends.database:66`](https://github.com/celery/celery/blob/406f04a082949ac42ec7a4af94fed896c515aaa4/celery/backends/database/__init__.py#L66):

> ```python
>     task_cls = Task
> ```

and [`celery.backends.database:76,77`](https://github.com/celery/celery/blob/406f04a082949ac42ec7a4af94fed896c515aaa4/celery/backends/database/__init__.py#L76-L77):

> ```python
>         if self.extended_result:
>             self.task_cls = TaskExtended
> ```

Airflow should support this flexibility, and instead of importing a fixed class just use `backend.task_cls`, so in `_get_many_from_db_backend` just use:

```python
        Task = app.backend.task_cls
        with session_cleanup(session):
            tasks = session.query(Task).filter(Task.task_id.in_(task_ids)).all()
```

I suppose there is one downside to this: `TaskExtended` fetches a few more columns per task, but given that the result of `task.to_dict()` is passed to `backend.meta_from_decoded()`, which could also have been customised to make use of information contained in a custom model, that's neither here nor there. It would be the price anyone using the `result_extended` option would need to pay elsewhere anyway.
airflow/executors/celery_executor.py
if key in self.task_publish_retries and (
                    self.task_publish_retries.get(key) <= self.task_publish_max_retries
                ):
                    Stats.incr("celery.task_timeout_error")
                    self.log.info(
                        "[Try %s of %s] Task Timeout Error for Task: (%s).",
                        self.task_publish_retries[key],
                        self.task_publish_max_retries,
                        key,
                    )
                    self.task_publish_retries[key] += 1
                    continue
            self.queued_tasks.pop(key)
            self.task_publish_retries.pop(key)
            if isinstance(result, ExceptionWithTraceback):
                self.log.error(  
                    CELERY_SEND_ERR_MSG_HEADER + ": %s\n%s\n", result.exception, result.traceback
                )
                self.event_buffer[key] = (State.FAILED, None)
            elif result is not None:
                result.backend = cached_celery_backend
                self.running.add(key)
                self.tasks[key] = result
                
                
                
                self.event_buffer[key] = (State.QUEUED, result.task_id)
                
                self.update_task_state(key, result.state, getattr(result, 'info', None))
    def _send_tasks_to_celery(self, task_tuples_to_send: List[TaskInstanceInCelery]):