**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
which ultimately becomes a node in DAG objects. Task dependencies should
    be set by using the set_upstream and/or set_downstream methods.
    :param task_id: a unique, meaningful id for the task
    :type task_id: str
    :param owner: the owner of the task, using the unix username is recommended
    :type owner: str
    :param email: the 'to' email address(es) used in email alerts. This can be a
        single email or multiple ones. Multiple addresses can be specified as a
        comma or semi-colon separated string or by passing a list of strings.
    :type email: str or list[str]
    :param email_on_retry: Indicates whether email alerts should be sent when a
        task is retried
    :type email_on_retry: bool
    :param email_on_failure: Indicates whether email alerts should be sent when
        a task failed
    :type email_on_failure: bool
    :param retries: the number of retries that should be performed before
        failing the task
    :type retries: int
    :param retry_delay: delay between retries
    :type retry_delay: datetime.timedelta
    :param retry_exponential_backoff: allow progressive longer waits between
        retries by using exponential backoff algorithm on retry delay (delay
        will be converted into seconds)
    :type retry_exponential_backoff: bool
    :param max_retry_delay: maximum delay interval between retries
    :type max_retry_delay: datetime.timedelta
    :param start_date: The ``start_date`` for the task, determines
        the ``execution_date`` for the first task instance. The best practice
        is to have the start_date rounded