### What do you see as an issue?


The [documentation for Dynamic Task Mapping](https://airflow.apache.org/docs/apache-airflow/stable/authoring-and-scheduling/dynamic-task-mapping.html#simple-mapping
) does not include an example of a "reduce" task (e.g. `sum_it` in the [examples](https://airflow.apache.org/docs/apache-airflow/stable/authoring-and-scheduling/dynamic-task-mapping.html#simple-mapping)) using the classic (or non-TaskFlow) operators. It only includes an example that uses the TaskFlow operators.

When I attempted to write a "reduce" task using classic operators for my DAG, I found that there wasn't an obvious approach.

### Solving the problem

We should add an example of a "reduce" task that uses the classic (non-TaskFlow) operators.

For example, for the given `sum_it` example:

```
"""Example DAG demonstrating the usage of dynamic task mapping reduce using classic
operators.
"""
from __future__ import annotations

from datetime import datetime

from airflow import DAG
from airflow.decorators import task
from airflow.operators.python import PythonOperator


def add_one(x: int):
    return x + 1

def sum_it(values):
    total = sum(values)
    print(f"Total was {total}")


with DAG(dag_id="example_dynamic_task_mapping_reduce", start_date=datetime(2022, 3, 4)):
    add_one_task = PythonOperator.partial(
        task_id="add_one",
        python_callable=add_one,
    ).expand(
        op_kwargs=[
            {"x": 1},
            {"x": 2},
            {"x": 3},
        ]
    )

    sum_it_task = PythonOperator(
        task_id="sum_it",
        python_callable=sum_it,
        op_kwargs={"values": add_one_task.output},
    )
```

### 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)

v == serialized_dag.default_args[k]
                    ), f"{dag.dag_id}.default_args[{k}] does not match"
        assert serialized_dag.timetable.summary == dag.timetable.summary
        assert serialized_dag.timetable.serialize() == dag.timetable.serialize()
        assert serialized_dag.timezone.name == dag.timezone.name
        for task_id in dag.task_ids:
            self.validate_deserialized_task(serialized_dag.get_task(task_id), dag.get_task(task_id))
    def validate_deserialized_task(
        self,
        serialized_task,
        task,
    ):
        """Verify non-Airflow operators are casted to BaseOperator or MappedOperator."""
        assert not isinstance(task, SerializedBaseOperator)
        assert isinstance(task, (BaseOperator, MappedOperator))
        
        assert serialized_task.task_group
        if isinstance(task, BaseOperator):
            assert isinstance(serialized_task, SerializedBaseOperator)
            fields_to_check = task.get_serialized_fields() - {
                
                "_task_type",
                "_operator_name",
                "subdag",
                
                "_log",
                
                "template_ext",
                "template_fields",