### 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)

run.conf = self.conf or {}
            
            run.start_date = timezone.utcnow()
        else:
            run = None
        
        
        if respect_dag_max_active_limit and current_active_dag_count >= dag.max_active_runs:
            return None
        run = run or dag.create_dagrun(
            execution_date=run_date,
            data_interval=dagrun_info.data_interval,
            start_date=timezone.utcnow(),
            state=DagRunState.RUNNING,
            external_trigger=False,
            session=session,
            conf=self.conf,
            run_type=DagRunType.BACKFILL_JOB,
            creating_job_id=self.id,
        )
        
        run.dag = dag
        
        run.state = DagRunState.RUNNING
        run.run_type = DagRunType.BACKFILL_JOB
        run.verify_integrity(session=session)
        run.notify_dagrun_state_changed(msg="started")
        return run
    @provide_session
    def _task_instances_for_dag_run(self, dag, dag_run, session=None):