pipelines/sdk/python/tests/compiler/testdata/two_step.py

55 lines
1.9 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."""
from kfp.deprecated import components
from kfp.deprecated import dsl
from kfp.deprecated.components import InputPath
from kfp.deprecated.components import OutputPath
def preprocess(uri: str, some_int: int, output_parameter_one: OutputPath(int),
output_dataset_one: OutputPath('Dataset')):
"""Dummy Preprocess Step."""
with open(output_dataset_one, 'w') as f:
f.write('Output dataset')
with open(output_parameter_one, 'w') as f:
f.write("{}".format(1234))
preprocess_op = components.create_component_from_func(
preprocess, base_image='python:3.9')
@components.create_component_from_func
def train_op(dataset: InputPath('Dataset'),
model: OutputPath('Model'),
num_steps: int = 100):
"""Dummy Training Step."""
with open(dataset, 'r') as input_file:
input_string = input_file.read()
with open(model, 'w') as output_file:
for i in range(num_steps):
output_file.write("Step {}\n{}\n=====\n".format(
i, input_string))
@dsl.pipeline(name='two_step_pipeline')
def two_step_pipeline():
preprocess_task = preprocess_op(uri='uri-to-import', some_int=12)
train_task = train_op(
num_steps=preprocess_task.outputs['output_parameter_one'],
dataset=preprocess_task.outputs['output_dataset_one'])