90 lines
2.9 KiB
Python
90 lines
2.9 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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"""Two step v2-compatible pipeline with URI placeholders."""
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import unittest
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from pprint import pprint
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from typing import Dict
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import kfp.deprecated as kfp
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import kfp_server_api
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from .two_step_with_uri_placeholder import two_step_with_uri_placeholder
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from kfp.samples.test.utils import run_pipeline_func, TestCase, KfpMlmdClient, KfpTask
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from ml_metadata.proto import Execution
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def verify_tasks(t: unittest.TestCase, tasks: Dict[str, KfpTask]):
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t.assertCountEqual(tasks.keys(), ['read-from-gcs', 'write-to-gcs'],
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'task names')
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write_task = tasks['write-to-gcs']
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read_task = tasks['read-from-gcs']
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t.assertEqual(
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{
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'name': 'write-to-gcs',
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'inputs': {
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'parameters': {
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'msg': 'Hello world!',
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}
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},
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'outputs': {
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'artifacts': [{
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'metadata': {
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'display_name': 'artifact'
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},
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'name': 'artifact',
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'type': 'system.Artifact'
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}],
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},
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'type': 'system.ContainerExecution',
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'state': Execution.State.COMPLETE,
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}, write_task.get_dict())
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t.assertEqual(
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{
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'name': 'read-from-gcs',
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'inputs': {
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'artifacts': [{
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'metadata': {
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'display_name': 'artifact'
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},
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'name': 'artifact',
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'type': 'system.Artifact',
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}],
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},
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'outputs': {},
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'type': 'system.ContainerExecution',
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'state': Execution.State.COMPLETE,
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}, read_task.get_dict())
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def verify(run: kfp_server_api.ApiRun, mlmd_connection_config, **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(run_id=run.id)
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verify_tasks(t, tasks)
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if __name__ == '__main__':
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run_pipeline_func([
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TestCase(
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pipeline_func=two_step_with_uri_placeholder,
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verify_func=verify,
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mode=kfp.dsl.PipelineExecutionMode.V2_ENGINE,
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),
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])
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