pipelines/samples/test/two_step_with_uri_placehold...

90 lines
2.9 KiB
Python

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