### 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)

)
                
                
                if ti.are_dependencies_met(
                    dep_context=backfill_context, session=session, verbose=self.verbose
                ):
                    if executor.has_task(ti):
                        self.log.debug("Task Instance %s already in executor waiting for queue to clear", ti)
                    else:
                        self.log.debug("Sending %s to executor", ti)
                        
                        ti.state = TaskInstanceState.QUEUED
                        ti.queued_by_job_id = self.id
                        ti.queued_dttm = timezone.utcnow()
                        session.merge(ti)
                        try:
                            session.commit()
                        except OperationalError:
                            self.log.exception("Failed to commit task state change due to operational error")
                            session.rollback()
                            
                            return
                        cfg_path = None
                        if self.executor_class in (
                            executor_constants.LOCAL_EXECUTOR,
                            executor_constants.SEQUENTIAL_EXECUTOR,
                        ):
                            cfg_path = tmp_configuration_copy()
                        executor.queue_task_instance(
                            ti,