### 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)

here and `'depends_on_past': False` in the operator's call
        `default_args`, the actual value will be `False`.
    :param params: a dictionary of DAG level parameters that are made
        accessible in templates, namespaced under `params`. These
        params can be overridden at the task level.
    :param max_active_tasks: the number of task instances allowed to run
        concurrently
    :param max_active_runs: maximum number of active DAG runs, beyond this
        number of DAG runs in a running state, the scheduler won't create
        new active DAG runs
    :param dagrun_timeout: specify how long a DagRun should be up before
        timing out / failing, so that new DagRuns can be created.
    :param sla_miss_callback: specify a function or list of functions to call when reporting SLA
        timeouts. See :ref:`sla_miss_callback<concepts:sla_miss_callback>` for
        more information about the function signature and parameters that are
        passed to the callback.
    :param default_view: Specify DAG default view (grid, graph, duration,
                                                   gantt, landing_times), default grid
    :param orientation: Specify DAG orientation in graph view (LR, TB, RL, BT), default LR
    :param catchup: Perform scheduler catchup (or only run latest)? Defaults to True
    :param on_failure_callback: A function or list of functions to be called when a DagRun of this dag fails.
        A context dictionary is passed as a single parameter to this function.
    :param on_success_callback: Much like the ``on_failure_callback`` except
        that it is executed when the dag succeeds.
    :param access_control: Specify optional DAG-level actions, e.g.,
        "{'role1': {'can_read'}, 'role2': {'can_read', 'can_edit', 'can_delete'}}"
    :param is_paused_upon_creation: Specifies if the dag is paused when created for the first time.
        If the dag exists already, this flag will be ignored. If this optional parameter
        is not specified, the global config setting will be used.
    :param jinja_environment_kwargs: additional configuration options to be passed to Jinja