**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/dagrun.py
cls,
        session: Session,
        max_number: Optional[int] = None,
    ):
        """
        Return the next DagRuns that the scheduler should attempt to schedule.
        This will return zero or more DagRun rows that are row-level-locked with a "SELECT ... FOR UPDATE"
        query, you should ensure that any scheduling decisions are made in a single transaction -- as soon as
        the transaction is committed it will be unlocked.
        :rtype: list[airflow.models.DagRun]
        """
        from airflow.models.dag import DagModel