### Apache Airflow version

main (development)

### What happened

Task failing with error "missing upstream values" when running a dag with dynamic task group mapping
error -
```
[2022-11-23, 15:50:07 UTC] {abstractoperator.py:456} ERROR - Cannot expand <Task(_PythonDecoratedOperator): increment_and_verify.hello_there> for run manual__2022-11-23T15:49:59.771915+00:00; missing upstream values: ['x']
```

### What you think should happen instead

It should succeed 

### How to reproduce

Run the below dag code 
```
from airflow import DAG
from airflow.models.taskinstance import TaskInstance
from airflow.operators.dummy import DummyOperator
from datetime import datetime, timedelta
from airflow.decorators import task, task_group
with DAG(
    dag_id="taskmap_taskgroup",
    tags=["AIP_42"],
    start_date=datetime(1970, 1, 1),
    schedule_interval=None,
) as dag:

    @task
    def onetwothree():
        return [1,2,3]

    @task
    def hello_there(arg):
        print(arg)

    @task_group
    def increment_and_verify(x):
        hello_there(x)

    increment_and_verify.expand(x=onetwothree())>>DummyOperator(task_id="done")
```

### Operating System

mac os

### Versions of Apache Airflow Providers

_No response_

### Deployment

Virtualenv installation

### Deployment details

_No response_

### 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)

session.commit()
            raise
        finally:
            Stats.incr(f"ti.finish.{self.dag_id}.{self.task_id}.{self.state}")
        
        self.clear_next_method_args()
        self.end_date = timezone.utcnow()
        self._log_state()
        self.set_duration()
        
        
        
        self._run_finished_callback(self.task.on_success_callback, context, "on_success")
        if not test_mode:
            session.add(Log(self.state, self))
            session.merge(self).task = self.task
            if self.state == TaskInstanceState.SUCCESS:
                self._register_dataset_changes(session=session)
            session.commit()
    def _register_dataset_changes(self, *, session: Session) -> None:
        for obj in self.task.outlets or []:
            self.log.debug("outlet obj %s", obj)
            
            if isinstance(obj, Dataset):
                dataset_manager.register_dataset_change(
                    task_instance=self,
                    dataset=obj,
                    session=session,
                )
    def _execute_task_with_callbacks(self, context, test_mode=False):