**Description**

The operator is arguably unnecessarily limited to AI Platform’s standard images. The only change that is required to lift this constraint is making `package_uris` and `training_python_module` optional with default values `[]` and `None`, respectively. Then, using `master_config`, one can supply `imageUri` and run any image of choice.

**Use case / motivation**

This will open up for running arbitrary images on AI Platform.

**Are you willing to submit a PR?**

If the above sounds reasonable, I can open pull requests.
airflow/providers/google/cloud/operators/mlengine.py
"""
    Operator for launching a MLEngine training job.
    .. seealso::
        For more information on how to use this operator, take a look at the guide:
        :ref:`howto/operator:MLEngineStartTrainingJobOperator`
    :param job_id: A unique templated id for the submitted Google MLEngine
        training job. (templated)
    :type job_id: str
    :param package_uris: A list of package locations for MLEngine training job,
        which should include the main training program + any additional
        dependencies. (templated)
    :type package_uris: List[str]
    :param training_python_module: The Python module name to run within MLEngine
        training job after installing 'package_uris' packages. (templated)
    :type training_python_module: str
    :param training_args: A list of templated command line arguments to pass to
        the MLEngine training program. (templated)
    :type training_args: List[str]
    :param region: The Google Compute Engine region to run the MLEngine training
        job in (templated).
    :type region: str
    :param scale_tier: Resource tier for MLEngine training job. (templated)
    :type scale_tier: str
    :param master_type: Cloud ML Engine machine name.
        Must be set when scale_tier is CUSTOM. (templated)
    :type master_type: str
    :param master_config: Cloud ML Engine master config.
        master_type must be set if master_config is provided. (templated)
    :type master_type: dict
    :param runtime_version: The Google Cloud ML runtime version to use for