### Apache Airflow version

2.7.1

### What happened

Unable to retrieve logs for task inside task group inside mapped task group.
Got `404 "TaskInstance not found"` in network requests

### What you think should happen instead

_No response_

### How to reproduce

```
from datetime import datetime
from airflow import DAG
from airflow.decorators import task, task_group
from airflow.operators.bash import BashOperator
from airflow.utils.task_group import TaskGroup

with DAG("mapped_task_group_bug", schedule=None, start_date=datetime(1970, 1, 1)):
    @task
    def foo():
        return ["a", "b", "c"]


    @task_group
    def bar(x):
        with TaskGroup("baz"):
            # If child task group exists, logs 404
            #  "TaskInstance not found"
            # http://localhost:8080/api/v1/dags/mapped_task_group_bug/dagRuns/manual__2023-09-21T22:31:56.863704+00:00/taskInstances/bar.baz.bop/logs/2?full_content=false
            # if it is removed, logs appear
            BashOperator(task_id="bop", bash_command="echo hi $x", env={"x": x})


    bar.partial().expand(x=foo())
```

### Operating System

debian 11 / `astro dev start`

### Versions of Apache Airflow Providers

_No response_

### Deployment

Astronomer

### 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)

TaskFail.dag_id == dag.dag_id,
                DagRun.execution_date >= min_date,
                DagRun.execution_date <= base_date,
            )
        )
        if dag.partial:
            ti_fails = ti_fails.where(TaskFail.task_id.in_([t.task_id for t in dag.tasks]))
        ti_fails = session.scalars(ti_fails)
        fails_totals: dict[tuple[str, str, str], int] = defaultdict(int)
        for failed_task_instance in ti_fails:
            dict_key = (
                failed_task_instance.dag_id,
                failed_task_instance.task_id,
                failed_task_instance.run_id,
            )
            if failed_task_instance.duration:
                fails_totals[dict_key] += failed_task_instance.duration
        
        def grouping_key(ti: TaskInstance):
            return ti.dag_id, ti.task_id, ti.run_id
        mapped_tis = set()
        for _, group in itertools.groupby(sorted(task_instances, key=grouping_key), key=grouping_key):
            tis = list(group)
            duration = sum(x.duration for x in tis if x.duration)
            if duration:
                first_ti = tis[0]
                if first_ti.map_index >= 0:
                    mapped_tis.add(first_ti.task_id)
                date_time = wwwutils.epoch(first_ti.execution_date)
                x_points[first_ti.task_id].append(date_time)