**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
template_fields = [
        '_project_id',
        '_model_name',
        '_impersonation_chain',
    ]
    @apply_defaults
    def __init__(
        self,
        *,
        model_name: str,
        project_id: Optional[str] = None,
        gcp_conn_id: str = 'google_cloud_default',
        delegate_to: Optional[str] = None,
        impersonation_chain: Optional[Union[str, Sequence[str]]] = None,
        **kwargs,
    ) -> None:
        super().__init__(**kwargs)
        self._project_id = project_id
        self._model_name = model_name
        self._gcp_conn_id = gcp_conn_id
        self._delegate_to = delegate_to
        self._impersonation_chain = impersonation_chain
    def execute(self, context):
        hook = MLEngineHook(
            gcp_conn_id=self._gcp_conn_id,
            delegate_to=self._delegate_to,
            impersonation_chain=self._impersonation_chain,
        )
        return hook.get_model(project_id=self._project_id, model_name=self._model_name)
class MLEngineDeleteModelOperator(BaseOperator):