### 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
self,
        state: DagRunState,
        execution_date: Optional[datetime] = None,
        run_id: Optional[str] = None,
        start_date: Optional[datetime] = None,
        external_trigger: Optional[bool] = False,
        conf: Optional[dict] = None,
        run_type: Optional[DagRunType] = None,
        session=None,
        dag_hash: Optional[str] = None,
        creating_job_id: Optional[int] = None,
        data_interval: Optional[Tuple[datetime, datetime]] = None,
    ):
        """
        Creates a dag run from this dag including the tasks associated with this dag.
        Returns the dag run.
        :param run_id: defines the run id for this dag run
        :type run_id: str
        :param run_type: type of DagRun
        :type run_type: airflow.utils.types.DagRunType
        :param execution_date: the execution date of this dag run
        :type execution_date: datetime.datetime
        :param state: the state of the dag run
        :type state: airflow.utils.state.DagRunState
        :param start_date: the date this dag run should be evaluated
        :type start_date: datetime
        :param external_trigger: whether this dag run is externally triggered
        :type external_trigger: bool
        :param conf: Dict containing configuration/parameters to pass to the DAG
        :type conf: dict