pipelines/sdk/python/tests/compiler/testdata/testpackage/mypipeline/compose.py

102 lines
3.6 KiB
Python

# Copyright 2018 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.
import kfp.deprecated.dsl as dsl
class GetFrequentWordOp(dsl.ContainerOp):
"""A get frequent word class representing a component in ML Pipelines.
The class provides a nice interface to users by hiding details such
as container, command, arguments.
"""
def __init__(self, name, message):
"""Args:
name: An identifier of the step which needs to be unique within a pipeline.
message: a dsl.PipelineParam object representing an input message.
"""
super(GetFrequentWordOp, self).__init__(
name=name,
image='python:3.5-jessie',
command=['sh', '-c'],
arguments=[
'python -c "from collections import Counter; '
'words = Counter(\'%s\'.split()); print(max(words, key=words.get))" '
'| tee /tmp/message.txt' % message
],
file_outputs={'word': '/tmp/message.txt'})
class SaveMessageOp(dsl.ContainerOp):
"""A class representing a component in ML Pipelines.
It saves a message to a given output_path.
"""
def __init__(self, name, message, output_path):
"""Args:
name: An identifier of the step which needs to be unique within a pipeline.
message: a dsl.PipelineParam object representing the message to be saved.
output_path: a dsl.PipelineParam object representing the GCS path for output file.
"""
super(SaveMessageOp, self).__init__(
name=name,
image='google/cloud-sdk',
command=['sh', '-c'],
arguments=[
'echo %s | tee /tmp/results.txt | gsutil cp /tmp/results.txt %s'
% (message, output_path)
])
@dsl.pipeline(
name='Save Most Frequent',
description='Get Most Frequent Word and Save to GCS')
def save_most_frequent_word(message: dsl.PipelineParam,
outputpath: dsl.PipelineParam):
"""A pipeline function describing the orchestration of the workflow."""
counter = GetFrequentWordOp(name='get-Frequent', message=message)
saver = SaveMessageOp(
name='save', message=counter.output, output_path=outputpath)
class DownloadMessageOp(dsl.ContainerOp):
"""A class representing a component in ML Pipelines.
It downloads a message and outputs it.
"""
def __init__(self, name, url):
"""Args:
name: An identifier of the step which needs to be unique within a pipeline.
usl: the gcs url to download the message from.
"""
super(DownloadMessageOp, self).__init__(
name=name,
image='google/cloud-sdk',
command=['sh', '-c'],
arguments=['gsutil cat %s | tee /tmp/results.txt' % url],
file_outputs={'downloaded': '/tmp/results.txt'})
@dsl.pipeline(
name='Download and Save Most Frequent',
description='Download and Get Most Frequent Word and Save to GCS')
def download_save_most_frequent_word(url: str, outputpath: str):
downloader = DownloadMessageOp('download', url)
save_most_frequent_word(downloader.output, outputpath)