Return a dict created by ``sagemaker.container_def()`` for deploying this model to a specified instance type.

        Subclasses can override this to provide custom container definitions for
        deployment to a specific instance type. Called by ``deploy()``.

        Args:
            instance_type (str): The EC2 instance type to deploy this Model to. For example, 'ml.p2.xlarge'.
            accelerator_type (str): The Elastic Inference accelerator type to deploy to the instance for loading and
                making inferences to the model. For example, 'ml.eia1.medium'.

        Returns:
            dict: A container definition object usable with the CreateModel API.

def prepare_container_def(self, instance_type, accelerator_type=None):  # pylint: disable=unused-argument
        """Return a dict created by ``sagemaker.container_def()`` for deploying this model to a specified instance type.

        Subclasses can override this to provide custom container definitions for
        deployment to a specific instance type. Called by ``deploy()``.

        Args:
            instance_type (str): The EC2 instance type to deploy this Model to. For example, 'ml.p2.xlarge'.
            accelerator_type (str): The Elastic Inference accelerator type to deploy to the instance for loading and
                making inferences to the model. For example, 'ml.eia1.medium'.

        Returns:
            dict: A container definition object usable with the CreateModel API.
        """
        return sagemaker.container_def(self.image, self.model_data, self.env)