**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
self._region = region
        self._scale_tier = scale_tier
        self._master_type = master_type
        self._master_config = master_config
        self._runtime_version = runtime_version
        self._python_version = python_version
        self._job_dir = job_dir
        self._service_account = service_account
        self._gcp_conn_id = gcp_conn_id
        self._delegate_to = delegate_to
        self._mode = mode
        self._labels = labels
        self._impersonation_chain = impersonation_chain
        if not self._project_id:
            raise AirflowException('Google Cloud project id is required.')
        if not self._job_id:
            raise AirflowException('An unique job id is required for Google MLEngine training job.')
        if not package_uris:
            raise AirflowException('At least one python package is required for MLEngine Training job.')
        if not training_python_module:
            raise AirflowException(
                'Python module name to run after installing required packages is required.'
            )
        if not self._region:
            raise AirflowException('Google Compute Engine region is required.')
        if self._scale_tier is not None and self._scale_tier.upper() == "CUSTOM" and not self._master_type:
            raise AirflowException('master_type must be set when scale_tier is CUSTOM')
        if self._master_config and not self._master_type:
            raise AirflowException('master_type must be set when master_config is provided')
    def execute(self, context):