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v0.2.1-rc.1 Latest Latest
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Published: Jul 12, 2018 License: Apache-2.0

README

Building images

The Dockerfiles in each component should be parameterized, with parameters stored in a versions folder. This allows us to use build_image.py to build all images.

For example

python build_image.py --tf_version=1.6 --platform=gpu tf_serving
python build_image.py --tf_version=1.4.1 tf_notebook

See build_image.py for details.

Supported versions

TF Serving
  • CPU: 1.4, 1.5, 1.6, 1.7, 1.8
  • GPU: 1.6, 1.7
TF notebook
  • CPU: 1.4.1, 1.5.1, 1.6.0, 1.7.0, 1.8.0
  • GPU: 1.4.1, 1.5.1, 1.6.0, 1.7.0, 1.8.0

Releasing images

image-releaser is the ksonnet app of releasing workflows.

JOB_NAME="tf-serving-workflow" # For tensorflow serving image

# For tensorflow notebook, set JOB_NAME="tf-notebook-workflow"

cd ${GIT_KUBEFLOW}/components/image-releaser
COMMIT=0da89b8a4af6c314287196b79d9a5f01d279b596 # Commit for the release
git checkout ${COMMIT}
PULL_BASE_SHA=${COMMIT:0:8}
DATE=`date +%Y%m%d`
VERSION_TAG="v${DATE}-${PULL_BASE_SHA}"
JOB_TYPE=postsubmit
BUILD_NUMBER=$(uuidgen)
BUILD_NUMBER=${BUILD_NUMBER:0:4}
REPO_OWNER=kubeflow
REPO_NAME=kubeflow
ENV=releasing

ks param set --env=${ENV} ${JOB_NAME} name "${JOB_NAME}-${VERSION_TAG}"
ks param set --env=${ENV} ${JOB_NAME} versionTag "${VERSION_TAG}"
ks param set --env=${ENV} ${JOB_NAME} prow_env  \
  "JOB_NAME=${JOB_NAME},JOB_TYPE=${JOB_TYPE},PULL_BASE_SHA=${PULL_BASE_SHA},REPO_NAME=${REPO_NAME},REPO_OWNER=${REPO_OWNER},BUILD_NUMBER=${BUILD_NUMBER}"
ks apply ${ENV} -c "${JOB_NAME}"

Directories

Path Synopsis
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