code: def test_add_user_provided_training_metrics(training_details_example):
      assert (
          len(
              training_details_example.training_job_details.user_provided_training_metrics
          )
          == 0
      )
      training_details_example.add_metric(USER_METRIC)
      assert (
          len(
              training_details_example.training_job_details.user_provided_training_metrics
          )
          == 1
      )
      assert (
          training_details_example.training_job_details.user_provided_training_metrics[
              0
          ].name
          == USER_METRIC_NAME
      )
  
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 35 for calling a global function with example usage: test_add_user_provided_training_metrics(training_details_example) without return types