code: def fixture_fixture_training_details_example():
      """Example training details instance."""
      test_example = TrainingDetails(
          objective_function=ObjectiveFunction(
              function=Function(
                  function=OBJECITVE_FUNCTION_FUNC,
                  facet=OBJECTIVE_FUNCTION_FACET,
                  condition=OBJECTIVE_FUNCTION_CONDITION,
              ),
              notes=OBJECTIVE_FUNCTION_NOTES,
          ),
          training_observations=TRAINING_OBSERVATIONS,
          training_job_details=TrainingJobDetails(
              training_arn=TRAINING_ARN,
              training_datasets=TRAINING_DATASETS,
              training_environment=TRAINING_ENVIRONMENT,
              training_metrics=TRAINING_METRICS,
              hyper_parameters=HYPER_PARAMETER,
          ),
      )
      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 5 for calling a global function with example usage: fixture_fixture_training_details_example() and returns: test_example