code: def test_register_calls_model_package_args(
      get_model_package_args, sagemaker_session
  ):
      """model.register() should pass the ValidationSpecification to get_model_package_args()"""
  
      source_dir = "s3://blah/blah/blah"
      t = Model(
          entry_point=ENTRY_POINT_INFERENCE,
          role=ROLE,
          sagemaker_session=sagemaker_session,
          source_dir=source_dir,
          image_uri=IMAGE_URI,
          model_data=MODEL_DATA,
      )
  
      t.register(
          SUPPORTED_CONTENT_TYPES,
          SUPPORTED_RESPONSE_MIME_TYPES,
          SUPPORTED_REALTIME_INFERENCE_INSTANCE_TYPES,
          SUPPORTED_BATCH_TRANSFORM_INSTANCE_TYPES,
          marketplace_cert=True,
          description=MODEL_DESCRIPTION,
          model_package_name=MODEL_NAME,
          validation_specification=VALIDATION_SPECIFICATION,
      )
  
      # check that the kwarg validation_specification was passed to the internal method 'get_model_package_args'
      assert (
          "validation_specification"
          in get_model_package_args.call_args_list[0][1]
      ), "validation_specification kwarg was not passed to get_model_package_args"
  
      # check that the kwarg validation_specification is identical to the one passed into the method 'register'
      assert (
          VALIDATION_SPECIFICATION
          == get_model_package_args.call_args_list[0][1][
              "validation_specification"
          ]
      ), """ValidationSpecification from model.register method is not identical to validation_spec from
           get_model_package_args"""
  
imports: from __future__ import absolute_import
  import random
  from unittest.mock import MagicMock
  import pytest
  from mock import Mock, patch
  import sagemaker
  from sagemaker.async_inference import AsyncInferenceConfig
  from sagemaker.model import FrameworkModel, Model
  from sagemaker.huggingface.model import HuggingFaceModel
  from sagemaker.jumpstart.constants import JUMPSTART_GATED_AND_PUBLIC_BUCKET_NAME_SET, JUMPSTART_RESOURCE_BASE_NAME
  from sagemaker.jumpstart.enums import JumpStartTag
  from sagemaker.mxnet.model import MXNetModel
  from sagemaker.pytorch.model import PyTorchModel
  from sagemaker.session_settings import SessionSettings
  from sagemaker.sklearn.model import SKLearnModel
  from sagemaker.tensorflow.model import TensorFlowModel
  from sagemaker.xgboost.model import XGBoostModel
  from sagemaker.enums import EndpointType
  from sagemaker.compute_resource_requirements.resource_requirements import ResourceRequirements
  from sagemaker.workflow.properties import Properties
  from tests.unit import _test_default_bucket_and_prefix_combinations, DEFAULT_S3_BUCKET_NAME, DEFAULT_S3_OBJECT_KEY_PREFIX_NAME, SAGEMAKER_CONFIG_EDGE_PACKAGING_JOB
label_desc: Use image node_id 39 for calling a global function with example usage: test_register_calls_model_package_args(get_model_package_args, sagemaker_session) without return types