### Apache Airflow version

2.2.0b2 (beta snapshot)

### Operating System

ubuntu 20.04

### Versions of Apache Airflow Providers

n/a

### Deployment

Virtualenv installation

### Deployment details

pip install /path/to/airflow/src

### What happened

Given any DAG initialized with: `schedule_interval=None`

Run `airflow dags test mydagname $(date +%Y-%m-%d)` and get an error:

```
INFO - No run dates were found for the given dates and dag interval.
```

This behavior changed in https://github.com/apache/airflow/pull/15397, it used to trigger a backfill dagrun at the given date.

### What you expected to happen

I expected a backfill dagrun with the given date, regardless of whether it fit into the `schedule_interval`.

If AIP-39 made that an unrealistic expectation, then I'd hope for some way to define unscheduled dags which can still be tested from the command line (which, so far as I know, is the fastest way to iterate on a DAG.).

As it is, I keep changing `schedule_interval` back and forth depending on whether I want to iterate via `astro dev start` (which tolerates `None` but does superfluous work if the dag is scheduled) or via `airflow dags test ...` (which doesn't tolerate `None`).

### How to reproduce

Initialize a DAG with: `schedule_interval=None` and run it via `airflow dags test mydagname $(date +%Y-%m-%d)`

### Anything else

_No response_

### 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)

airflow/models/dag.py
)
        most_recent_runs_iter = session.query(DagRun).filter(
            DagRun.dag_id == most_recent_subq.c.dag_id,
            DagRun.execution_date == most_recent_subq.c.max_execution_date,
        )
        most_recent_runs = {run.dag_id: run for run in most_recent_runs_iter}
        filelocs = []
        for orm_dag in sorted(orm_dags, key=lambda d: d.dag_id):
            dag = dag_by_ids[orm_dag.dag_id]
            filelocs.append(dag.fileloc)
            if dag.is_subdag:
                orm_dag.is_subdag = True
                orm_dag.fileloc = dag.parent_dag.fileloc  
                orm_dag.root_dag_id = dag.parent_dag.dag_id  
                orm_dag.owners = dag.parent_dag.owner  
            else:
                orm_dag.is_subdag = False
                orm_dag.fileloc = dag.fileloc
                orm_dag.owners = dag.owner
            orm_dag.is_active = True
            orm_dag.last_parsed_time = timezone.utcnow()
            orm_dag.default_view = dag.default_view
            orm_dag.description = dag.description
            orm_dag.schedule_interval = dag.schedule_interval
            orm_dag.max_active_tasks = dag.max_active_tasks
            orm_dag.max_active_runs = dag.max_active_runs
            orm_dag.has_task_concurrency_limits = any(t.max_active_tis_per_dag is not None for t in dag.tasks)
            run: Optional[DagRun] = most_recent_runs.get(dag.dag_id)
            if run is None:
                data_interval = None