**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
MyOperator(...,
                executor_config={
                    "KubernetesExecutor":
                        {"image": "myCustomDockerImage"}
                }
            )
    :type executor_config: dict
    :param do_xcom_push: if True, an XCom is pushed containing the Operator's
        result
    :type do_xcom_push: bool
    :param doc: Add documentation or notes to your Task objects that is visible in
        Task Instance details View in the Webserver
    :type doc: str
    :param doc_md: Add documentation (in Markdown format) or notes to your Task objects
        that is visible in Task Instance details View in the Webserver
    :type doc_md: str
    :param doc_rst: Add documentation (in RST format) or notes to your Task objects
        that is visible in Task Instance details View in the Webserver
    :type doc_rst: str
    :param doc_json: Add documentation (in JSON format) or notes to your Task objects
        that is visible in Task Instance details View in the Webserver
    :type doc_json: str
    :param doc_yaml: Add documentation (in YAML format) or notes to your Task objects
        that is visible in Task Instance details View in the Webserver
    :type doc_yaml: str
    """
    
    template_fields: Iterable[str] = ()
    
    template_ext: Iterable[str] = ()