PythonVirtualenvOperator: native template rendering breaks {{ ti }} / {{ task_instance }} pickling

### Description

The PythonVirtualenvOperator docs state that passing/serializing `ti / task_instance` is not supported. However, I’m seeing a confusing behavior difference depending on `render_template_as_native_obj`:

- With `render_template_as_native_obj=False`, templating `{{ ti }} / {{ task_instance }}` in `op_kwargs` appears to work (the task runs and prints values).

- With `render_template_as_native_obj=True`, the task fails while serializing arguments for the subprocess with a `PicklingError` (non-obvious error mentioning loggers/structlog).

**Minimal reproduction**
```
from pendulum import datetime

from airflow.sdk import dag
from airflow.providers.standard.operators.python import PythonVirtualenvOperator

def venv_callable(ti, task_instance):
print("ti =", ti)
print("task_instance =", task_instance)

@dag(
start_date=datetime(2026, 1, 1),
schedule=None,
catchup=False,
render_template_as_native_obj=False, # <-- changing only this flips behavior
)
def test_simple():
PythonVirtualenvOperator(
task_id="repro",
python_callable=venv_callable,
python_version="3.10",
serializer="cloudpickle",
op_kwargs={
"ti": "{{ ti }}",
"task_instance": "{{ task_instance }}",
},
requirements=["apache-airflow==3.1.6"],
system_site_packages=False,
)

test_simple()
```
**Steps to reproduce**

- Run the DAG above with `render_template_as_native_obj=False` → task succeeds.
- Change only `render_template_as_native_obj=True` → task fails during pickle/argument serialization.

**Error / traceback (render_template_as_native_obj=True)**
```
[2026-01-29 23:06:37] INFO - Use 'cloudpickle' as serializer.
[2026-01-29 23:06:37] ERROR - Task failed with exception
PicklingError: Only BytesLoggers to sys.stdout and sys.stderr can be pickled.
File "/home/airflow/.local/lib/python3.10/site-packages/airflow/sdk/execution_time/task_runner.py", line 1004 in run
...
File "/home/airflow/.local/lib/python3.10/site-packages/airflow/providers/standard/operators/python.py", line 529 in _write_args
File "/home/airflow/.local/lib/python3.10/site-packages/cloudpickle/cloudpickle.py", line 1537 in dumps
...
File "/home/airflow/.local/lib/python3.10/site-packages/structlog/_output.py", line 278 in __getstate__
```

### Use case/motivation

We use `PythonVirtualenvOperator` to run code in an isolated environment with separate dependencies, but we often still need basic task-instance context inside the callable (identifiers, try number, sometimes access to basic TI metadata / XCom).

Native template rendering (`render_template_as_native_obj=True`) is valuable for other templates because it renders lists/dicts/booleans as native Python types, so we don’t want to avoid it globally. The current behavior makes it easy to accidentally pass a “live” non-serializable object and then hit a confusing pickle error.

I understand that calling the Airflow REST API directly from the virtualenv is a valid workaround, but it would be very helpful to have an official/supported mechanism for isolated environments:

- a small supported serializable handle/proxy (e.g., `dag_id`, `run_id`, `task_id`, `try_number`, `map_index`, etc.),
- and a minimal supported helper/client (or a limited set of operations) to safely retrieve basic TaskInstance info from within the virtualenv without passing the full object.

Even if a full client is out of scope, UX would improve a lot with:
- explicit validation + a clearer error message when `TaskInstance/ti` ends up in `op_args/op_kwargs`, and/or
- documentation that this case behaves differently (and fails earlier) with native rendering enabled.

Environment
- Apache Airflow: 3.1.6
- Provider: apache-airflow-providers-standard (PythonVirtualenvOperator)
- Runner Python: 3.10
- Virtualenv Python: 3.10
- serializer: cloudpickle

### Related issues

https://github.com/apache/airflow/discussions/61231

### Are you willing to submit a 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)