**Apache Airflow version**:  1.10.10


**Kubernetes version (if you are using kubernetes)**: 1.14.10

**Environment**:

- **Cloud provider or hardware configuration**: Any, GCP 
- **OS** (e.g. from /etc/os-release): Ubuntu 1.10.10
- **Kernel** (e.g. `uname -a`): Any
- **Install tools**: Any
- **Others**: NA

**What happened**:
DAGs with ExternalTaskMarker don't clean external task after second usage of clean on whole DAG


**What you expected to happen**:

All external task should be cleaned

**How to reproduce it**:
enable serialization `store_serialized_dags = True`

create example DAGs:

```
default_args = {'owner': 'airflow',
                'start_date': datetime(2018, 1, 1)}

def hello_world_py(*args):
    print('Hello World')
    print('This is DAG is dep}')

schedule = '@daily'
dag_id = 'dep_dag'
with DAG(dag_id=dag_id,
         schedule_interval=schedule,
         default_args=default_args) as dag:
    t1 = PythonOperator(task_id='hello_world',
                        python_callable=hello_world_py,)
    dep_1 = ExternalTaskSensor(task_id='child_task1',
                               external_dag_id='hello_world_2',
                               external_task_id='parent_task',
                               mode='reschedule')
    dep_1 >> t1

def create_dag(dag_id, schedule, dag_number, default_args):
    dag = DAG(dag_id, schedule_interval=schedule,
              default_args=default_args)
    with dag:
        t1 = PythonOperator(task_id='hello_world',
                            python_callable=hello_world_py,
                            dag_number=dag_number)
        parent_task = SerializableExternalTaskMarker(task_id='parent_task',
                                         external_dag_id='dep_dag',
                                         external_task_id='child_task1')
        t1 >> parent_task
    return dag

for n in range(1, 4):
    dag_id = 'hello_world_{}'.format(str(n))
    default_args = {'owner': 'airflow',
                    'start_date': datetime(2018, 1, 1)}
    schedule = '@daily'
    dag_number = n
    globals()[dag_id] = create_dag(dag_id, schedule, dag_number, default_args)
```

1. Run both DAGs
2. Wait until first few dagruns where completed
3. Clean first dugrun in DAG with marker
4. Check external dug was cleaned on this date
5. Mark success this date in each DAGs or wait until complete
6. Clean DAG with marker second time on same date
7. ExternalTaskMarker don't work

**Anything else we need to know**:
I think ExternalTaskMarker don't work because of serialization, after serialization each task instance get operator field equal 'SerializedBaseOperator' and markers logic dot' work [here](https://github.com/apache/airflow/blob/master/airflow/models/dag.py#L1072) 

To test ExternalTaskMarker with serialization you can use:

<details>

```
from airflow.sensors.external_task_sensor import ExternalTaskMarker
class FakeName(type):

    def __new__(metacls, name, bases, namespace, **kw):
         name = namespace.get("__name__", name)
         return super().__new__(metacls, name, bases, namespace, **kw)
class SerializableExternalTaskMarker(ExternalTaskMarker, metaclass=FakeName):

    # The _serialized_fields are lazily loaded when get_serialized_fields() method is called
    __serialized_fields = None  # type: Optional[FrozenSet[str]]
    __name__ = "ExternalTaskMarker"

    @classmethod
    def get_serialized_fields(cls):
        """Serialized BigQueryOperator contain exactly these fields."""
        if not cls.__serialized_fields:
            cls.__serialized_fields = frozenset(
                ExternalTaskMarker.get_serialized_fields() | {
                    "recursion_depth", "external_dag_id", "external_taskid", "execution_date"
                }
            )
        return cls.__serialized_fields
```

</details>

@kaxil 
tests/models/test_taskinstance.py
"""
        Test that task retries are handled properly
        """
        with patch("airflow.models.taskinstance.STORE_SERIALIZED_DAGS", dag_serialization):
            dag = models.DAG(dag_id='test_retry_handling')
            task = BashOperator(
                task_id='test_retry_handling_op',
                bash_command='echo {{dag.dag_id}}; exit 1',
                retries=1,
                retry_delay=datetime.timedelta(seconds=0),
                dag=dag,
                owner='test_pool',
                start_date=timezone.datetime(2016, 2, 1, 0, 0, 0))
            def run_with_error(ti):
                try:
                    ti.run()
                except AirflowException: