50 lines
1.6 KiB
Python
50 lines
1.6 KiB
Python
# Copyright 2021 The Kubeflow Authors
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import kfp_server_api
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import unittest
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from pprint import pprint
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from .table import table_pipeline
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from kfp.samples.test.utils import KfpMlmdClient, run_pipeline_func, TestCase
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import kfp.deprecated as kfp
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def verify(run: kfp_server_api.ApiRun, mlmd_connection_config,
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argo_workflow_name: str, **kwargs):
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t = unittest.TestCase()
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t.maxDiff = None # we always want to see full diff
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t.assertEqual(run.status, 'Succeeded')
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client = KfpMlmdClient(mlmd_connection_config=mlmd_connection_config)
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tasks = client.get_tasks(argo_workflow_name=argo_workflow_name)
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pprint(tasks)
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table_visualization = tasks['table-visualization']
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output = [
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a for a in table_visualization.outputs.artifacts
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if a.name == 'mlpipeline_ui_metadata'
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][0]
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pprint(output)
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t.assertEqual(
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table_visualization.get_dict()['outputs']['artifacts'][0]['name'],
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'mlpipeline_ui_metadata')
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run_pipeline_func([
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TestCase(
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pipeline_func=table_pipeline,
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mode=kfp.dsl.PipelineExecutionMode.V1_LEGACY)
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])
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