**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
Should not be None if version_name is provided.
        Should be None if uri is provided. (templated)
    :type model_name: str
    :param version_name: The Google Cloud ML Engine model version to use for
        prediction.
        Should be None if uri is provided. (templated)
    :type version_name: str
    :param uri: The GCS path of the saved model to use for prediction.
        Should be None if model_name is provided.
        It should be a GCS path pointing to a tensorflow SavedModel. (templated)
    :type uri: str
    :param max_worker_count: The maximum number of workers to be used
        for parallel processing. Defaults to 10 if not specified. Should be a
        string representing the worker count ("10" instead of 10, "50" instead
        of 50, etc.)
    :type max_worker_count: str
    :param runtime_version: The Google Cloud ML Engine runtime version to use
        for batch prediction.
    :type runtime_version: str
    :param signature_name: The name of the signature defined in the SavedModel
        to use for this job.
    :type signature_name: str
    :param project_id: The Google Cloud project name where the prediction job is submitted.
        If set to None or missing, the default project_id from the Google Cloud connection is used.
        (templated)
    :type project_id: str
    :param gcp_conn_id: The connection ID used for connection to Google
        Cloud Platform.
    :type gcp_conn_id: str
    :param delegate_to: The account to impersonate using domain-wide delegation of authority,