examples/github_issue_summarization/pipelines/example_pipelines/gh_summ_serve.py

52 lines
1.6 KiB
Python

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