### 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/jobs/backfill_job.py
"""
        This function checks if there are any tasks in the dagrun (or all) that
        have a schedule or queued states but are not known by the executor. If
        it finds those it will reset the state to None so they will get picked
        up again.  The batch option is for performance reasons as the queries
        are made in sequence.
        :param filter_by_dag_run: the dag_run we want to process, None if all
        :type filter_by_dag_run: airflow.models.DagRun
        :return: the number of TIs reset
        :rtype: int
        """
        queued_tis = self.executor.queued_tasks
        
        running_tis = self.executor.running
        
        resettable_states = [State.SCHEDULED, State.QUEUED]
        if filter_by_dag_run is None:
            resettable_tis = (
                session.query(TaskInstance)
                .join(TaskInstance.dag_run)
                .filter(