153 lines
5.3 KiB
Python
153 lines
5.3 KiB
Python
# Copyright 2019 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 json
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import kfp.dsl as dsl
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from string import Template
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@dsl.pipeline(
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name="Deploy example MAB",
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description="Multi-armed bandit example"
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)
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def mabdeploy_seldon(docker_image1='seldonio/mock_classifier:1.0',
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docker_image2='seldonio/mock_classifier:1.0',
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mab_router_image='seldonio/mab_epsilon_greedy:1.1'):
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#serve two models load balanced as bandit as per https://github.com/SeldonIO/seldon-core/blob/master/notebooks/helm_examples.ipynb
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#in this example no volumes or buckets required as the models are baked into images
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#seldon can also be used with volumes - see seldon tf mnist example
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mabjson_template = Template("""
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{
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"apiVersion": "machinelearning.seldon.io/v1alpha2",
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"kind": "SeldonDeployment",
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"metadata": {
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"labels": {
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"app": "seldon"
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},
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"name": "mnist-classifier-mab"
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},
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"spec": {
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"name": "mnist-classifier-mab",
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"predictors": [
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{
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"name": "abtest",
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"replicas": 1,
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"componentSpecs": [{
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"spec": {
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"containers": [
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{
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"image": "$image1",
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"imagePullPolicy": "IfNotPresent",
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"name": "classifier-1",
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"resources": {
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"requests": {
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"memory": "1Mi"
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}
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}
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}],
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"terminationGracePeriodSeconds": 20
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}},
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{
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"metadata":{
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"labels":{
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"version":"v2"
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}
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},
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"spec":{
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"containers":[
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{
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"image": "$image2",
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"imagePullPolicy": "IfNotPresent",
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"name": "classifier-2",
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"resources": {
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"requests": {
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"memory": "1Mi"
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}
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}
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}
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],
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"terminationGracePeriodSeconds": 20
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}
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},
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{
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"spec":{
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"containers": [{
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"image": "$router",
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"name": "eg-router"
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}],
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"terminationGracePeriodSeconds": 20
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}}
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],
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"graph": {
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"name": "eg-router",
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"type":"ROUTER",
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"parameters": [
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{
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"name": "n_branches",
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"value": "2",
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"type": "INT"
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},
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{
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"name": "epsilon",
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"value": "0.2",
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"type": "FLOAT"
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},
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{
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"name": "verbose",
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"value": "1",
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"type": "BOOL"
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}
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],
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"children": [
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{
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"name": "classifier-1",
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"endpoint":{
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"type":"REST"
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},
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"type":"MODEL",
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"children":[]
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},
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{
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"name": "classifier-2",
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"endpoint":{
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"type":"REST"
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},
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"type":"MODEL",
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"children":[]
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}
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]
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}
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}
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]
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}
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}
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""")
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mabjson = mabjson_template.substitute({ 'image1': str(docker_image1),'image2': str(docker_image2),'router': str(mab_router_image)})
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mabdeployment = json.loads(mabjson)
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deploy = dsl.ResourceOp(
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name="deploy",
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k8s_resource=mabdeployment,
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action="apply",
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success_condition='status.state == Available'
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)
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if __name__ == "__main__":
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import kfp.compiler as compiler
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compiler.Compiler().compile(mabdeploy_seldon, __file__ + ".tar.gz")
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