**Description**
The `airflow.models.baseoperator.chain()` is a very useful and convenient way to add sequential task dependencies in DAGs but the function only supports tasks of a `BaseOperator` type.

**Use case / motivation**
Users who create tasks via the `@task` decorator will not be able to use the `chain()` function to apply sequential dependencies that do not share an `XComArg` implicit dependency.

**Are you willing to submit a PR?**
Absolutely. 🚀 

**Related Issues**
None

airflow/models/baseoperator.py
self,
        start_date: Optional[datetime] = None,
        end_date: Optional[datetime] = None,
        upstream: bool = False,
        downstream: bool = False,
        session: Session = None,
    ):
        """
        Clears the state of task instances associated with the task, following
        the parameters specified.
        """
        qry = session.query(TaskInstance).filter(TaskInstance.dag_id == self.dag_id)
        if start_date:
            qry = qry.filter(TaskInstance.execution_date >= start_date)
        if end_date:
            qry = qry.filter(TaskInstance.execution_date <= end_date)
        tasks = [self.task_id]
        if upstream:
            tasks += [t.task_id for t in self.get_flat_relatives(upstream=True)]
        if downstream:
            tasks += [t.task_id for t in self.get_flat_relatives(upstream=False)]
        qry = qry.filter(TaskInstance.task_id.in_(tasks))
        results = qry.all()
        count = len(results)
        clear_task_instances(results, session, dag=self.dag)
        session.commit()
        return count
    @provide_session
    def get_task_instances(