code: def test_mms_model(
      repack_model, sagemaker_session, gpu_pytorch_instance_type
  ):
      PyTorchModel(
          MODEL_DATA,
          role=ROLE,
          entry_point=SCRIPT_PATH,
          sagemaker_session=sagemaker_session,
          framework_version="1.2",
          py_version="py3",
      ).deploy(1, gpu_pytorch_instance_type)
  
      repack_model.assert_called_with(
          dependencies=[],
          inference_script=SCRIPT_PATH,
          kms_key=None,
          model_uri="s3://some/data.tar.gz",
          repacked_model_uri=ANY,
          sagemaker_session=sagemaker_session,
          source_directory=None,
      )
  
imports: from __future__ import absolute_import
  import logging
  import json
  import os
  import pytest
  from mock import ANY, MagicMock, Mock, patch
  from packaging.version import Version
  from sagemaker import image_uris
  from sagemaker.pytorch import defaults
  from sagemaker.pytorch import PyTorch, PyTorchPredictor, PyTorchModel
  from sagemaker.instance_group import InstanceGroup
  from sagemaker.session_settings import SessionSettings
label_desc: Use image node_id 12 for calling a global function with example usage: test_mms_model(repack_model, sagemaker_session, gpu_pytorch_instance_type) without return types