mirror of https://github.com/kubeflow/examples.git
52 lines
1.6 KiB
Python
52 lines
1.6 KiB
Python
# Copyright 2018 Google LLC
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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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# from kfp.dsl.types import String
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@dsl.pipeline(
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name='Github issue summarization',
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description='Demonstrate Tensor2Tensor-based training and TF-Serving'
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)
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def gh_summ_serveonly(
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github_token: str = 'YOUR_GITHUB_TOKEN_HERE',
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):
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serve = dsl.ContainerOp(
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name='serve',
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image='gcr.io/google-samples/ml-pipeline-kubeflow-tfserve:v2',
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arguments=["--model_name", 'ghsumm-%s' % (dsl.RUN_ID_PLACEHOLDER,),
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"--model_path",
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'gs://aju-dev-demos-codelabs/kubecon/example_t2t_model/model_output/export'
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]
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).apply(gcp.use_gcp_secret('user-gcp-sa'))
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webapp = dsl.ContainerOp(
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name='webapp',
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image='gcr.io/google-samples/ml-pipeline-webapp-launcher:v3ap',
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arguments=["--model_name", 'ghsumm-%s' % (dsl.RUN_ID_PLACEHOLDER,),
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"--github_token", github_token]
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)
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webapp.after(serve)
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if __name__ == '__main__':
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import kfp.compiler as compiler
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compiler.Compiler().compile(gh_summ_serveonly, __file__ + '.tar.gz')
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