**Description**

Allow custom executors subclassed from existing (CeleryExecutor, CeleryKubernetesExecutor, etc.) to use default CLI commands to start workers or flower monitoring.

**Use case / motivation**

Currently, users who decide to roll their own custom Celery-based executor cannot use default commands (i.e. `airflow celery worker`) even though it's built on top of existing CeleryExecutor. If they try to, they'll receive the following error: `airflow command error: argument GROUP_OR_COMMAND: celery subcommand works only with CeleryExecutor, your current executor: custom_package.CustomCeleryExecutor, see help above.`

One workaround for this is to create custom entrypoint script for worker/flower containers/processes that are still going to use the same Celery app as CeleryExecutor. This leads to unnecessary maintaining of this entrypoint script.

I'd suggest two ways of fixing that:

- Check if custom executor is subclassed from Celery executor (which might lead to errors, if custom executor is used to access other celery app, which might be a proper reason for rolling custom executor)
- Store `app` as attribute of Celery-based executors and match the one provided by custom executor with the default one

**Related Issues**

N/A
airflow/cli/cli_parser.py
ARG_ANONYMIZE,
            ARG_FILE_IO,
            ARG_VERBOSE,
            ARG_OUTPUT,
        ),
    ),
    ActionCommand(
        name='plugins',
        help='Dump information about loaded plugins',
        func=lazy_load_command('airflow.cli.commands.plugins_command.dump_plugins'),
        args=(ARG_OUTPUT, ARG_VERBOSE),
    ),
    GroupCommand(
        name="celery",
        help='Celery components',
        description=(
            'Start celery components. Works only when using CeleryExecutor. For more information, see '
            'https://airflow.apache.org/docs/apache-airflow/stable/executor/celery.html'
        ),
        subcommands=CELERY_COMMANDS,
    ),
    ActionCommand(
        name='standalone',
        help='Run an all-in-one copy of Airflow',
        func=lazy_load_command('airflow.cli.commands.standalone_command.standalone'),
        args=tuple(),
    ),
]
ALL_COMMANDS_DICT: Dict[str, CLICommand] = {sp.name: sp for sp in airflow_commands}
def _remove_dag_id_opt(command: ActionCommand):