### 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/cli/commands/dag_command.py
"""
    Returns the state (and conf if exists) of a DagRun at the command line.
    >>> airflow dags state tutorial 2015-01-01T00:00:00.000000
    running
    >>> airflow dags state a_dag_with_conf_passed 2015-01-01T00:00:00.000000
    failed, {"name": "bob", "age": "42"}
    """
    if args.subdir:
        dag = get_dag(args.subdir, args.dag_id)
    else:
        dag = get_dag_by_file_location(args.dag_id)
    dr = DagRun.find(dag.dag_id, execution_date=args.execution_date)
    out = dr[0].state if dr else None
    conf_out = ''
    if out and dr[0].conf:
        conf_out = ', ' + json.dumps(dr[0].conf)
    print(str(out) + conf_out)
@cli_utils.action_logging
def dag_next_execution(args):
    """
    Returns the next execution datetime of a DAG at the command line.
    >>> airflow dags next-execution tutorial
    2018-08-31 10:38:00
    """
    dag = get_dag(args.subdir, args.dag_id)
    if dag.get_is_paused():
        print("[INFO] Please be reminded this DAG is PAUSED now.", file=sys.stderr)
    with create_session() as session:
        max_date_subq = (