### Apache Airflow version

main (development)

### What happened

Create a simple dag, allow it to completely run through. 

Next, when in grid view, on the left hand side click on the dag run at the top level. 

On the right hand side, then click on "Clear existing tasks". This will error with the following on the web server:

```
[2022-11-29 17:55:05,939] {app.py:1742} ERROR - Exception on /dagrun_clear [POST]
Traceback (most recent call last):
  File "/usr/local/lib/python3.7/site-packages/flask/app.py", line 2525, in wsgi_app
    response = self.full_dispatch_request()
  File "/usr/local/lib/python3.7/site-packages/flask/app.py", line 1822, in full_dispatch_request
    rv = self.handle_user_exception(e)
  File "/usr/local/lib/python3.7/site-packages/flask/app.py", line 1820, in full_dispatch_request
    rv = self.dispatch_request()
  File "/usr/local/lib/python3.7/site-packages/flask/app.py", line 1796, in dispatch_request
    return self.ensure_sync(self.view_functions[rule.endpoint])(**view_args)
  File "/opt/airflow/airflow/www/auth.py", line 47, in decorated
    return func(*args, **kwargs)
  File "/opt/airflow/airflow/www/decorators.py", line 83, in wrapper
    return f(*args, **kwargs)
  File "/opt/airflow/airflow/www/views.py", line 2184, in dagrun_clear
    confirmed=confirmed,
  File "/opt/airflow/airflow/www/views.py", line 2046, in _clear_dag_tis
    session=session,
  File "/opt/airflow/airflow/utils/session.py", line 72, in wrapper
    return func(*args, **kwargs)
  File "/opt/airflow/airflow/models/dag.py", line 2030, in clear
    exclude_task_ids=exclude_task_ids,
  File "/opt/airflow/airflow/models/dag.py", line 1619, in _get_task_instances
    tis = session.query(TaskInstance)
AttributeError: 'NoneType' object has no attribute 'query'
```
https://github.com/apache/airflow/blob/527fbce462429fc9836837378f801eed4e9d194f/airflow/models/dag.py#L1619

As per issue title, fails on main branch and `2.5.0rc2`. Works fine on `2.3.3` and `2.4.3`. 


### What you think should happen instead

Tasks within the dag should be cleared as expected. 

### How to reproduce

Run a dag, attempt to clear it within the UI at the top level of the dag. 

### Operating System

Ran via breeze

### Versions of Apache Airflow Providers

N/A

### Deployment

Other 3rd-party Helm chart

### Deployment details

Tested via breeze. 

### Anything else

Happens every time. 

### Are you willing to submit PR?

- [X] 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)

defines where jinja will look for your templates. Order matters.
        Note that jinja/airflow includes the path of your DAG file by
        default
    :param template_undefined: Template undefined type.
    :param user_defined_macros: a dictionary of macros that will be exposed
        in your jinja templates. For example, passing ``dict(foo='bar')``
        to this argument allows you to ``{{ foo }}`` in all jinja
        templates related to this DAG. Note that you can pass any
        type of object here.
    :param user_defined_filters: a dictionary of filters that will be exposed
        in your jinja templates. For example, passing
        ``dict(hello=lambda name: 'Hello %s' % name)`` to this argument allows
        you to ``{{ 'world' | hello }}`` in all jinja templates related to
        this DAG.
    :param default_args: A dictionary of default parameters to be used
        as constructor keyword parameters when initialising operators.
        Note that operators have the same hook, and precede those defined
        here, meaning that if your dict contains `'depends_on_past': True`
        here and `'depends_on_past': False` in the operator's call
        `default_args`, the actual value will be `False`.
    :param params: a dictionary of DAG level parameters that are made
        accessible in templates, namespaced under `params`. These
        params can be overridden at the task level.
    :param max_active_tasks: the number of task instances allowed to run
        concurrently
    :param max_active_runs: maximum number of active DAG runs, beyond this
        number of DAG runs in a running state, the scheduler won't create
        new active DAG runs
    :param dagrun_timeout: specify how long a DagRun should be up before
        timing out / failing, so that new DagRuns can be created. The timeout