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Releasing TensorFlow Java

The TensorFlow Java API is available on Maven Central and JCenter through artifacts uploaded to OSS Sonatype. This document describes the process of updating the release artifacts. It does not describe how to use the artifacts, for which the reader is referred to the TensorFlow for Java installation instructions.

Background

TensorFlow source (which is primarily in C++) is built using bazel and not maven. TensorFlow Java wraps over this native code and thus depends on platform (OS, architecture) specific native code.

Hence, the process for building and uploading release artifacts is not a single mvn deploy command.

Release process overview

The process of releasing TensorFlow Java is split in two major steps:

  • Building and deploying the native artifacts
  • Building and deploying all artifacts consolidated

The first step is executed on different build servers, each responsible to build the native artifact for a specific architecture and platform. The second step is conducted locally in a Docker container for a hermetic release process.

It is important to note that any change pushed to a release branch (i.e. a branch prefixed by r) will start a new release workflow. Therefore, these changes should always increment the version number.

Pre-requisites

Preparing a release

Major or minor release

  1. Get a clean version of the source code by cloning the TensorFlow Java GitHub repository

    git clone https://github.com/tensorflow/java

  2. Create a new branch for the release named r<MajorVersion>.<MinorVersion>

    git checkout -b r1.0

  3. Update the version of the Maven artifacts to the full version of the release

    mvn versions:set -DnewVersion=1.0.0

  4. Update the TensorFlow Java version to reflect the new release at the following locations:

  5. Commit the changes and push the new branch to the GitHub repository

    git add .
git commit -m "Releasing 1.0.0"
git push --set-upstream origin r1.0

Patch release

  1. Get a clean version of the source code by cloning the TensorFlow Java GitHub repository

    git clone https://github.com/tensorflow/java

  2. Switch to the release branch of the version to patch

    git checkout r1.0

  3. Patch the code with your changes. For example, changes could be merged from another branch you were working on or be applied directly to this branch when the required changes are minimal.

  4. Update the version of the Maven artifacts to the full version of the release

    mvn versions:set -DnewVersion=1.0.1

  5. Update the TensorFlow Java version to reflect the new release at the following locations:

  6. Commit the changes and push the branch to the GitHub repository

    git add .
git commit -m "Releasing 1.0.1"
git push

Building native artifacts

Any change pushed to a release branch will trigger a new release workflow. GitHub Actions builds the native artifacts for all supported architures/platforms and deploy them temporarily on OSSRH for staging.

There is no user action required for this step other than watching the progress of the GitHub Actions workflow and making sure that all steps have been completed successfully.

Build native artifacts manually

Some platforms cannot be build successfully on GitHub Actions, due to some limits to their resources (e.g. max 6 hours for a job). For this reasons, we need to build manually some of our artifacts on private servers.

To do so, follow the same steps as the CI build for the same platform and make sure to checkout the release branch and to provide your Sonatype credentials for temporary staging.

Performing the release

  1. At the root of your TensorFlow Java copy, create a Maven settings.xml file with your OSSRH credentials and your GPG key passphrase:

    SONATYPE_USERNAME="your_sonatype.org_username_here"
SONATYPE_PASSWORD="your_sonatype.org_password_here"
GPG_PASSPHRASE="your_gpg_passphrase_here"
cat > settings.xml <<EOF
<settings>
  <servers>
    <server>
      <id>ossrh</id>
      <username>${SONATYPE_USERNAME}</username>
      <password>${SONATYPE_PASSWORD}</password>
    </server>
    <server>
      <id>ossrh-staging</id>
      <username>${SONATYPE_USERNAME}</username>
      <password>${SONATYPE_PASSWORD}</password>
    </server>
  </servers>
  <profiles>
    <profile>
      <activation>
        <activeByDefault>true</activeByDefault>
      </activation>
      <properties>
        <gpg.executable>gpg2</gpg.executable>
        <gpg.passphrase>${GPG_PASSPHRASE}</gpg.passphrase>
      </properties>
    </profile>
  <profiles>
</settings>
EOF

  2. Execute the release.sh script. This will deploy artifacts on OSS Sonatype. All native artifacts previously temporarily staged by GitHub Actions will be fetched, signed and redeployed as well.

    The script takes in a parameter the sequence number of the staging repository created in OSSRH by the GitHub Actions workflow. You can retrieve this ID by looking in the staging repositories in OSSRH console directly, or check at the output of the step Create Staging Repository of the prepare job in the workflow execution, where the ID is printed.

    # Staging repository created: orgtensorflow-1100
sh release.sh 1100

  3. If the script above succeeds then the artifacts would have been uploaded to the private staging repository in Sonatype. After verifying the release, you should finalize or abort the release. Visit https://oss.sonatype.org/#stagingRepositories, find the orgtensorflow-* of your release and click Close and Release to finalize the release. You always have the option to Drop it to abort and restart if something went wrong.

  4. Go to GitHub and create a release tag on the release branch with a summary of what the version includes.

Some things of note: - For details, look at the Sonatype guide. - Syncing with Maven Central can take 10 minutes to 2 hours (as per the OSSRH guide).

Finishing a release

Major or minor release

  1. Checkout the master branch and merge back changes from the released branch

    git checkout master
git merge r1.0

  2. In your local copy, checkout the master branch and increase the next snapshot version.

    mvn versions:set -DnewVersion=1.1.0-SNAPSHOT

  3. Update the TensorFlow Java version to reflect the new snapshot at the following locations:

  4. Commit your changes and push the master branch to the GitHub repository

    git add .
git commit -m "Increase version for next iteration"
git push

Patch release

  1. Checkout the master branch and merge back changes from the released branch 
    git checkout master
git merge r1.0
  2. Commit the changes and push the master branch to the GitHub repository 
    git add .
git commit -m "Merge release 1.0.1"
git push

References