text: # Copyright 2021 The Kubeflow Authors
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #      http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  import kfp_server_api
  import unittest
  from pprint import pprint
  from .metrics_visualization_v1 import metrics_visualization_v1_pipeline
  from .util import KfpMlmdClient, run_pipeline_func, TestCase
  
  import kfp
  import kfp_server_api
  
  
  def verify(run: kfp_server_api.ApiRun, mlmd_connection_config,
             argo_workflow_name: str, **kwargs):
      t = unittest.TestCase()
      t.maxDiff = None  # we always want to see full diff
      t.assertEqual(run.status, 'Succeeded')
      client = KfpMlmdClient(mlmd_connection_config=mlmd_connection_config)
      tasks = client.get_tasks(argo_workflow_name=argo_workflow_name)
      pprint(tasks)
  
      table_visualization = tasks['table-visualization']
      markdown_visualization = tasks['markdown-visualization']
      roc_visualization = tasks['roc-visualization']
      html_visualization = tasks['html-visualization']
      confusion_visualization = tasks['confusion-visualization']
  
      t.assertEqual(
          table_visualization.get_dict()['outputs']['artifacts'][0]['name'],
          'mlpipeline_ui_metadata')
      t.assertEqual(
          markdown_visualization.get_dict()['outputs']['artifacts'][0]['name'],
          'mlpipeline_ui_metadata')
      t.assertEqual(
          roc_visualization.get_dict()['outputs']['artifacts'][0]['name'],
          'mlpipeline_ui_metadata')
      t.assertEqual(
          html_visualization.get_dict()['outputs']['artifacts'][0]['name'],
          'mlpipeline_ui_metadata')
      t.assertEqual(
          confusion_visualization.get_dict()['outputs']['artifacts'][0]['name'],
          'mlpipeline_ui_metadata')
  
  
  run_pipeline_func([])
  