59 lines
1.9 KiB
Python
59 lines
1.9 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."""
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from kfp.deprecated import components, dsl
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from kfp.deprecated.components import InputPath, OutputPath
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def preprocess(
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uri: str, some_int: int, output_parameter_one: OutputPath(int),
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output_dataset_one: OutputPath('Dataset')
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):
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with open(output_dataset_one, 'w') as f:
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f.write(uri)
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with open(output_parameter_one, 'w') as f:
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f.write("{}".format(some_int))
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preprocess_op = components.create_component_from_func(
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preprocess, base_image='python:3.9'
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)
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@components.create_component_from_func
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def train_op(
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dataset: InputPath('Dataset'),
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model: OutputPath('Model'),
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num_steps: int = 100
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):
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'''Dummy Training Step.'''
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with open(dataset, 'r') as input_file:
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input_string = input_file.read()
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with open(model, 'w') as output_file:
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for i in range(num_steps):
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output_file.write(
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"Step {}\n{}\n=====\n".format(i, input_string)
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)
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@dsl.pipeline(name='two-step-pipeline')
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def two_step_pipeline(uri: str = 'uri-to-import', some_int: int = 1234):
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preprocess_task = preprocess_op(uri=uri, some_int=some_int)
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train_task = train_op(
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num_steps=preprocess_task.outputs['output_parameter_one'],
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dataset=preprocess_task.outputs['output_dataset_one']
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)
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