### Body

Currently `start_date` is mandatory parameter.
For DAGs with `schedule=None` we can relax this requirement as no scheduling calculation needed so the `start_date` parameter isn't used.

### Committer

- [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.
return num
            assert isinstance(value, DagParam)
            xcom_arg = return_num(value)
            self.operator = xcom_arg.operator
        dag = xcom_pass_to_op()
        new_value = 52
        dr = dag.create_dagrun(
            run_id=DagRunType.MANUAL.value,
            start_date=timezone.utcnow(),
            execution_date=self.DEFAULT_DATE,
            data_interval=(self.DEFAULT_DATE, self.DEFAULT_DATE),
            state=State.RUNNING,
            conf={"value": new_value},
        )
        self.operator.run(start_date=self.DEFAULT_DATE, end_date=self.DEFAULT_DATE)
        ti = dr.get_task_instances()[0]
        assert ti.xcom_pull() == new_value
    @pytest.mark.parametrize("value", [VALUE, 0])
    def test_set_params_for_dag(self, value):
        """Test that dag param is correctly set when using dag decorator"""
        @dag_decorator(default_args=self.DEFAULT_ARGS)
        def xcom_pass_to_op(value=value):
            @task_decorator
            def return_num(num):
                return num
            xcom_arg = return_num(value)
            self.operator = xcom_arg.operator
        dag = xcom_pass_to_op()
        assert dag.params["value"] == value
    def test_warning_location(self):