src/sagemaker/mxnet/model.py [201:244]:
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            content_types,
            response_types,
            inference_instances,
            transform_instances,
            model_package_name,
            model_package_group_name,
            image_uri,
            model_metrics,
            metadata_properties,
            marketplace_cert,
            approval_status,
            description,
            drift_check_baselines=drift_check_baselines,
        )

    def prepare_container_def(self, instance_type=None, accelerator_type=None):
        """Return a container definition with framework configuration.

        Framework configuration is set in model environment variables.

        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[str, str]: A container definition object usable with the
            CreateModel API.
        """
        deploy_image = self.image_uri
        if not deploy_image:
            if instance_type is None:
                raise ValueError(
                    "Must supply either an instance type (for choosing CPU vs GPU) or an image URI."
                )

            region_name = self.sagemaker_session.boto_session.region_name
            deploy_image = self.serving_image_uri(
                region_name, instance_type, accelerator_type=accelerator_type
            )

        deploy_key_prefix = model_code_key_prefix(self.key_prefix, self.name, deploy_image)
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src/sagemaker/pytorch/model.py [200:241]:
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            content_types,
            response_types,
            inference_instances,
            transform_instances,
            model_package_name,
            model_package_group_name,
            image_uri,
            model_metrics,
            metadata_properties,
            marketplace_cert,
            approval_status,
            description,
            drift_check_baselines=drift_check_baselines,
        )

    def prepare_container_def(self, instance_type=None, accelerator_type=None):
        """A container definition with framework configuration set in model environment variables.

        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.

        Returns:
            dict[str, str]: A container definition object usable with the
            CreateModel API.
        """
        deploy_image = self.image_uri
        if not deploy_image:
            if instance_type is None:
                raise ValueError(
                    "Must supply either an instance type (for choosing CPU vs GPU) or an image URI."
                )

            region_name = self.sagemaker_session.boto_session.region_name
            deploy_image = self.serving_image_uri(
                region_name, instance_type, accelerator_type=accelerator_type
            )

        deploy_key_prefix = model_code_key_prefix(self.key_prefix, self.name, deploy_image)
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