**Apache Airflow version**:
2.0 / master

**Environment**:

breeze

**What happened**:

Using this DAG:

```py
from airflow.operators.bash import BashOperator
from airflow.operators.python import task
from airflow.models import DAG
from airflow.utils.task_group import TaskGroup

@task
def show():
    print("Cats are awesome!")

with DAG(
    "using_task_group",
    default_args={'owner': 'airflow'},
    start_date=days_ago(2),
    schedule_interval=None,
) as dag3:
    start_task = BashOperator(
        task_id="start_task",
        bash_command="echo start",
    )

    end_task = BashOperator(
        task_id="end_task",
        bash_command="echo end",
    )

    with TaskGroup(group_id="show_tasks") as tg1:
        previous_show = show()
        for _ in range(100):
            next_show = show()
            previous_show >> next_show
            previous_show = next_show
```
I get:
```
Broken DAG: [/files/dags/test.py] Traceback (most recent call last):
  File "/opt/airflow/airflow/models/baseoperator.py", line 410, in __init__
    task_group.add(self)
  File "/opt/airflow/airflow/utils/task_group.py", line 140, in add
    raise DuplicateTaskIdFound(f"Task id '{key}' has already been added to the DAG")
airflow.exceptions.DuplicateTaskIdFound: Task id 'show_tasks.show' has already been added to the DAG
```

If I remove the task group the task are generated as expected.

**What you expected to happen**:

I expect to be able to generate tasks dynamically using TaskGroup and task decoratos.

**How to reproduce it**:

Use the DAG from above.

**Anything else we need to know**:

N/A

airflow/operators/python.py
"""
        Python wrapper to generate PythonDecoratedOperator out of simple python functions.
        Used for Airflow Decorated interface
        """
        _PythonDecoratedOperator.validate_python_callable(f)
        kwargs.setdefault('task_id', f.__name__)
        @functools.wraps(f)
        def factory(*args, **f_kwargs):
            op = _PythonDecoratedOperator(
                python_callable=f,
                op_args=args,
                op_kwargs=f_kwargs,
                multiple_outputs=multiple_outputs,
                **kwargs,
            )
            if f.__doc__:
                op.doc_md = f.__doc__
            return XComArg(op)
        return cast(T, factory)
    if callable(python_callable):
        return wrapper(python_callable)
    elif python_callable is not None:
        raise AirflowException('No args allowed while using @task, use kwargs instead')
    return wrapper
class BranchPythonOperator(PythonOperator, SkipMixin):