code: def fixture_model_package_example():
      """Example ModelPackage instance"""
      test_example = ModelPackage(
          model_package_arn=MODEL_PACKAGE_ARN,
          model_package_description=MODEL_PACKAGE_DESCRIPTION,
          model_package_group_name=MODEL_PACKAGE_GROUP_NAME,
          model_package_name=MODEL_PACKAGE_NAME,
          model_approval_status=MODEL_APPROVAL_STATUS,
          model_package_status=MODEL_PACKAGE_STATUS,
          model_package_version=MODEL_PACKAGE_VERSION,
          approval_description=APPROVAL_DESCRIPTION,
          domain=DOMAIN,
          task=TASK,
          created_by=CREATED_BY,
          source_algorithms=SOURCE_ALGORITHMS,
          inference_specification=INFERENCE_SPECIFICATION,
      )
      return test_example
  
imports: from __future__ import absolute_import
  import io
  import os
  import json
  import datetime
  import re
  import logging
  import pytest
  from mock import patch, Mock
  from botocore.exceptions import ClientError
  import botocore.response
  from sagemaker.model_card import schema_constraints
  from sagemaker.model_card import Environment, ModelOverview, IntendedUses, BusinessDetails, ObjectiveFunction, TrainingMetric, HyperParameter, Metric, TrainingDetails, MetricGroup, EvaluationJob, AdditionalInformation, ModelCard, Function, TrainingJobDetails, ModelPackage
  from sagemaker.model_card.model_card import ModelCardExportJob, ModelPackageCreator, SourceAlgorithm, Container, InferenceSpecification
  from sagemaker.model_card.helpers import _MaxSizeArray, _IsList, _OneOf, _IsModelCardObject, _JSONEncoder, _hash_content_str, _DefaultToRequestDict, _SkipEncodingDecoding
  from sagemaker.model_card.evaluation_metric_parsers import EvaluationMetricTypeEnum, EVALUATION_METRIC_PARSERS
label_desc: Use image node_id 2 for calling a global function with example usage: fixture_model_package_example() and returns: test_example