**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/models/baseoperator.py
wait_for_downstream: bool = False,
        dag=None,
        params: Optional[Dict] = None,
        default_args: Optional[Dict] = None,  
        priority_weight: int = 1,
        weight_rule: str = WeightRule.DOWNSTREAM,
        queue: str = conf.get('celery', 'default_queue'),
        pool: Optional[str] = None,
        pool_slots: int = 1,
        sla: Optional[timedelta] = None,
        execution_timeout: Optional[timedelta] = None,
        on_execute_callback: Optional[TaskStateChangeCallback] = None,
        on_failure_callback: Optional[TaskStateChangeCallback] = None,
        on_success_callback: Optional[TaskStateChangeCallback] = None,
        on_retry_callback: Optional[TaskStateChangeCallback] = None,
        trigger_rule: str = TriggerRule.ALL_SUCCESS,
        resources: Optional[Dict] = None,
        run_as_user: Optional[str] = None,
        task_concurrency: Optional[int] = None,
        executor_config: Optional[Dict] = None,
        do_xcom_push: bool = True,
        inlets: Optional[Any] = None,
        outlets: Optional[Any] = None,
        task_group: Optional["TaskGroup"] = None,
        **kwargs,
    ):
        from airflow.models.dag import DagContext
        from airflow.utils.task_group import TaskGroupContext
        super().__init__()
        if kwargs: