**Apache Airflow version**:
v2.0.0

**What happened**:

Custom operators inheriting from DummyOperator are go in to a scheduled state, where as DummyOperator itself is set straight to success.

**What you expected to happen**:

All operators should be successfully executed.

**How to reproduce it**:

```py
from datetime import datetime
from airflow import DAG
from airflow.operators.dummy_operator import DummyOperator

class MyJob(DummyOperator):
    template_fields_renderers = {
        "body": "json"
    }
    template_fields = ("body",)

    def __init__(self, body, *args, **kwargs):
        super().__init__(*args, **kwargs)
        self.body = body

with DAG(
    dag_id="test",
    schedule_interval=None,
    start_date=datetime(2020, 8, 13),
) as dag:
    MyJob(task_id="aaaa", body={"aaa": "bbb"})

```

**Anything else we need to know**:
This is a known problem that we will fix, see: https://github.com/apache/airflow/pull/10956#discussion_r502492775
airflow/serialization/serialized_objects.py
from kubernetes.client import models as k8s
    from airflow.kubernetes.pod_generator import PodGenerator
    
    HAS_KUBERNETES = True
except ImportError:
    HAS_KUBERNETES = False
log = logging.getLogger(__name__)
FAILED = 'serialization_failed'
BUILTIN_OPERATOR_EXTRA_LINKS: List[str] = [
    "airflow.providers.google.cloud.operators.bigquery.BigQueryConsoleLink",
    "airflow.providers.google.cloud.operators.bigquery.BigQueryConsoleIndexableLink",
    "airflow.providers.google.cloud.operators.mlengine.AIPlatformConsoleLink",
    "airflow.providers.qubole.operators.qubole.QDSLink",
    "airflow.operators.dagrun_operator.TriggerDagRunLink",
    "airflow.sensors.external_task_sensor.ExternalTaskSensorLink",
]
class BaseSerialization:
    """BaseSerialization provides utils for serialization."""
    
    _primitive_types = (int, bool, float, str)
    
    
    _datetime_types = (datetime.datetime,)
    
    _excluded_types = (logging.Logger, Connection, type)
    _json_schema: Optional[Validator] = None
    _CONSTRUCTOR_PARAMS: Dict[str, Parameter] = {}
    SERIALIZER_VERSION = 1
    @classmethod
    def to_json(cls, var: Union[DAG, BaseOperator, dict, list, set, tuple]) -> str: