### Apache Airflow version

2.6.1

### What happened

A number of Airflow CLI commands will fail with an error like the one below if a DAG uses a [custom Timetable](https://airflow.apache.org/docs/apache-airflow/stable/authoring-and-scheduling/timetable.html): 
```
Traceback (most recent call last):
  File "/opt/conda/envs/production-airflow-2.6.1/bin/airflow", line 11, in <module>
    sys.exit(main())
  File "/opt/conda/envs/production-airflow-2.6.1/lib/python3.9/site-packages/airflow/__main__.py", line 48, in main
    args.func(args)
  File "/opt/conda/envs/production-airflow-2.6.1/lib/python3.9/site-packages/airflow/cli/cli_config.py", line 51, in command
    return func(*args, **kwargs)
  File "/opt/conda/envs/production-airflow-2.6.1/lib/python3.9/site-packages/airflow/utils/cli.py", line 112, in wrapper
    return f(*args, **kwargs)
  File "/opt/conda/envs/production-airflow-2.6.1/lib/python3.9/site-packages/airflow/cli/commands/dag_command.py", line 139, in dag_backfill
    _run_dag_backfill(dags, args)
  File "/opt/conda/envs/production-airflow-2.6.1/lib/python3.9/site-packages/airflow/cli/commands/dag_command.py", line 79, in _run_dag_backfill
    ti.dry_run()
  File "/opt/conda/envs/production-airflow-2.6.1/lib/python3.9/site-packages/airflow/models/taskinstance.py", line 1730, in dry_run
    self.render_templates()
  File "/opt/conda/envs/production-airflow-2.6.1/lib/python3.9/site-packages/airflow/models/taskinstance.py", line 2172, in render_templates
    context = self.get_template_context()
  File "/opt/conda/envs/production-airflow-2.6.1/lib/python3.9/site-packages/airflow/models/taskinstance.py", line 1931, in get_template_context
    data_interval = dag.get_run_data_interval(dag_run)
  File "/opt/conda/envs/production-airflow-2.6.1/lib/python3.9/site-packages/airflow/models/dag.py", line 861, in get_run_data_interval
    return self.infer_automated_data_interval(run.execution_date)
  File "/opt/conda/envs/production-airflow-2.6.1/lib/python3.9/site-packages/airflow/models/dag.py", line 882, in infer_automated_data_interval
    raise ValueError(f"Not a valid timetable: {self.timetable!r}")
ValueError: Not a valid timetable: <workday.AfterWorkdayTimetable object at 0x7f50f9cd1700>
```

Some commands I have found that demonstrate this issue (though there may be more that I haven't found):
* `airflow dags backfill <dag_id> -s <date> -e <date> --dry-run` (works fine without `--dry-run`)
* `airflow dags test <dag_id> [date]`
* `airflow tasks render <dag_id> <task_id> <date>` (works fine if you pass a valid `run_id` instead of an `execution_date`)

### What you think should happen instead

Custom Timetables should work in all contexts that built-in timetables do.

### How to reproduce

Set up Airflow in a such a way that example plugins can be used (see comments below).  Add this DAG script:
```
#!/usr/bin/env python
from datetime import datetime

from airflow.decorators import dag, task

# copy airflow/example_dags/plugins/workday.py into your $PLUGINS_FOLDER
# OR update airflow.cfg to set core.plugins_folder = /path/to/airflow/example_dags/plugins
from workday import AfterWorkdayTimetable


@dag(
    start_date=datetime(2023, 5, 13),
    timetable=AfterWorkdayTimetable(),
    catchup=True,
)
def test_timetable():
    @task()
    def t():
        print('hello')

    t()


test_timetable()
```
To verify that the timetable is working correctly, you should be able to unpause the DAG and see tasks complete.  Then run one of the CLI commands that I mentioned above to see the error.

### Operating System

CentOS Stream 8

### Versions of Apache Airflow Providers

N/A

### Deployment

Other

### Deployment details

Self-hosted deployment/`standalone` mode
Postgres DB backend

### Anything else

Possibly related:
* #19578

### Are you willing to submit PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

"""Table containing DAG properties."""
    __tablename__ = "dag"
    """
    These items are stored in the database for state related information
    """
    dag_id = Column(StringID(), primary_key=True)
    root_dag_id = Column(StringID())
    
    
    is_paused_at_creation = airflow_conf.getboolean("core", "dags_are_paused_at_creation")
    is_paused = Column(Boolean, default=is_paused_at_creation)
    
    is_subdag = Column(Boolean, default=False)
    
    is_active = Column(Boolean, default=False)
    
    last_parsed_time = Column(UtcDateTime)
    
    last_pickled = Column(UtcDateTime)