code: def test_model_register(
      sagemaker_session,
      mxnet_inference_version,
      mxnet_inference_py_version,
      skip_if_mms_version,
  ):
      model = MXNetModel(
          MODEL_DATA,
          role=ROLE,
          entry_point=SCRIPT_PATH,
          framework_version=mxnet_inference_version,
          py_version=mxnet_inference_py_version,
          sagemaker_session=sagemaker_session,
      )
      predictor = model.deploy(1, GPU)
      assert isinstance(predictor, MXNetPredictor)
  
      model_package_name = "test-mxnet-register-model"
      content_types = ["application/json"]
      response_types = ["application/json"]
      inference_instances = ["ml.m4.xlarge"]
      transform_instances = ["ml.m4.xlarget"]
      model.register(
          content_types,
          response_types,
          inference_instances,
          transform_instances,
          model_package_name=model_package_name,
      )
      sagemaker_session.create_model_package_from_containers.assert_called()
  
imports: from __future__ import absolute_import
  import logging
  import json
  import os
  import pytest
  from mock import MagicMock, Mock, ANY
  from mock import patch
  from pkg_resources import parse_version
  from sagemaker.fw_utils import UploadedCode
  from sagemaker.drift_check_baselines import DriftCheckBaselines
  from sagemaker.metadata_properties import MetadataProperties
  from sagemaker.model_metrics import FileSource, MetricsSource, ModelMetrics
  from sagemaker.mxnet import defaults
  from sagemaker.mxnet import MXNet
  from sagemaker.mxnet import MXNetPredictor, MXNetModel
  from sagemaker.session_settings import SessionSettings
label_desc: Use image node_id 15 for calling a global function with example usage: test_model_register(sagemaker_session, mxnet_inference_version, mxnet_inference_py_version, skip_if_mms_version) without return types