95 lines
3.4 KiB
Python
95 lines
3.4 KiB
Python
# Copyright 2018 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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import kfp.dsl as dsl
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import kfp.gcp as gcp
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class GetFrequentWordOp(dsl.ContainerOp):
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"""A get frequent word class representing a component in ML Pipelines.
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The class provides a nice interface to users by hiding details such
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as container, command, arguments.
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"""
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def __init__(self, name, message):
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"""Args:
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name: An identifier of the step which needs to be unique within a pipeline.
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message: a dsl.PipelineParam object representing an input message.
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"""
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super(GetFrequentWordOp, self).__init__(
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name=name,
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image='python:3.5-jessie',
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command=['sh', '-c'],
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arguments=[
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'python -c "from collections import Counter; '
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'words = Counter(\'%s\'.split()); print(max(words, key=words.get))" '
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'| tee /tmp/message.txt' % message
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],
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file_outputs={'word': '/tmp/message.txt'})
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class SaveMessageOp(dsl.ContainerOp):
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"""A class representing a component in ML Pipelines.
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It saves a message to a given output_path.
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"""
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def __init__(self, name, message, output_path):
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"""Args:
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name: An identifier of the step which needs to be unique within a pipeline.
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message: a dsl.PipelineParam object representing the message to be saved.
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output_path: a dsl.PipelineParam object representing the GCS path for output file.
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"""
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super(SaveMessageOp, self).__init__(
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name=name,
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image='google/cloud-sdk',
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command=['sh', '-c'],
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arguments=[
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'echo %s | tee /tmp/results.txt | gsutil cp /tmp/results.txt %s'
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% (message, output_path)
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])
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class ExitHandlerOp(dsl.ContainerOp):
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"""A class representing a component in ML Pipelines."""
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def __init__(self, name):
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super(ExitHandlerOp, self).__init__(
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name=name,
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image='python:3.5-jessie',
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command=['sh', '-c'],
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arguments=['echo exit!'])
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@dsl.pipeline(
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name='Save Most Frequent',
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description='Get Most Frequent Word and Save to GCS')
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def save_most_frequent_word(message: str, outputpath: str):
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"""A pipeline function describing the orchestration of the workflow."""
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exit_op = ExitHandlerOp('exiting')
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with dsl.ExitHandler(exit_op):
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counter = GetFrequentWordOp(name='get-Frequent', message=message)
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counter.container.set_memory_request('200M')
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saver = SaveMessageOp(
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name='save', message=counter.output, output_path=outputpath)
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saver.container.set_cpu_limit('0.5')
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saver.container.set_gpu_limit('2')
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saver.add_node_selector_constraint('cloud.google.com/gke-accelerator',
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'nvidia-tesla-k80')
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saver.apply(
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gcp.use_tpu(tpu_cores=8, tpu_resource='v2', tf_version='1.12'))
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