### 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
) -> List[TaskInstance]:
        """
        Set the state of a TaskInstance to the given state, and clear its downstream tasks that are
        in failed or upstream_failed state.
        :param task_id: Task ID of the TaskInstance
        :type task_id: str
        :param execution_date: execution_date of the TaskInstance
        :type execution_date: datetime
        :param state: State to set the TaskInstance to
        :type state: State
        :param upstream: Include all upstream tasks of the given task_id
        :type upstream: bool
        :param downstream: Include all downstream tasks of the given task_id
        :type downstream: bool
        :param future: Include all future TaskInstances of the given task_id
        :type future: bool
        :param commit: Commit changes
        :type commit: bool
        :param past: Include all past TaskInstances of the given task_id
        :type past: bool
        """
        from airflow.api.common.experimental.mark_tasks import set_state
        task = self.get_task(task_id)
        task.dag = self
        altered = set_state(
            tasks=[task],
            execution_date=execution_date,
            upstream=upstream,
            downstream=downstream,
            future=future,