87 lines
2.7 KiB
Python
87 lines
2.7 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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"""Lightweight functions v2 with outputs."""
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from typing import NamedTuple
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import os
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from kfp import compiler, dsl
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from kfp.dsl import Input, Dataset, Model, Metrics, component
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# In tests, we install a KFP package from the PR under test. Users should not
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# normally need to specify `kfp_package_path` in their component definitions.
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_KFP_PACKAGE_PATH = os.getenv('KFP_PACKAGE_PATH')
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@component(kfp_package_path=_KFP_PACKAGE_PATH)
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def concat_message(first: str, second: str) -> str:
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return first + second
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@component(kfp_package_path=_KFP_PACKAGE_PATH)
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def add_numbers(first: int, second: int) -> int:
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return first + second
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@component(kfp_package_path=_KFP_PACKAGE_PATH)
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def output_artifact(number: int, message: str) -> Dataset:
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result = [message for _ in range(number)]
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return '\n'.join(result)
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@component(kfp_package_path=_KFP_PACKAGE_PATH)
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def output_named_tuple(
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artifact: Input[Dataset]
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) -> NamedTuple('Outputs', [
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('scalar', str),
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('metrics', Metrics),
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('model', Model),
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]):
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scalar = "123"
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import json
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metrics = json.dumps({
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'metrics': [{
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'name': 'accuracy',
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'numberValue': 0.9,
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'format': "PERCENTAGE",
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}]
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})
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with open(artifact.path, 'r') as f:
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artifact_contents = f.read()
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model = "Model contents: " + artifact_contents
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from collections import namedtuple
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output = namedtuple('Outputs', ['scalar', 'metrics', 'model'])
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return output(scalar, metrics, model)
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@dsl.pipeline(name='functions-with-outputs')
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def pipeline(
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first_message: str = 'first',
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second_message: str = 'second',
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first_number: int = 1,
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second_number: int = 2,
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):
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concat_task = concat_message(first=first_message, second=second_message)
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add_numbers_task = add_numbers(first=first_number, second=second_number)
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output_artifact_task = output_artifact(
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number=add_numbers_task.output, message=concat_task.output)
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output_name_tuple = output_named_tuple(artifact=output_artifact_task.output)
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if __name__ == '__main__':
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compiler.Compiler().compile(
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pipeline_func=pipeline, package_path=__file__ + '.yaml')
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