val DslContext.uuidPrefix: String
    get() = settingsRoot.id.toString().substringAfter("Gradle")

data class VersionedSettingsBranch(val branchName: String) {
    /**
     * 0~23.
     * To avoid nightly promotion jobs running at the same time,
     * we run each branch on different hours.
     * master - 0:00
     * release - 1:00
     * release6x - 2:00
     * release7x - 3:00
     * ...
     * releaseNx - (N-4):00

import gradlebuild.basics.capitalize
import com.google.gson.Gson
import java.net.URI

wrapperUpdateTask("nightly", "nightly")
wrapperUpdateTask("rc", "release-candidate")
wrapperUpdateTask("current", "current")

tasks.withType<Wrapper>().configureEach {
    val jvmOpts = "-Dfile.encoding=UTF-8"
    inputs.property("jvmOpts", jvmOpts)
    doLast {
        val optsEnvVar = "DEFAULT_JVM_OPTS"

  python --version
fi

# TFCI Mac VM images do not have twine installed by default so we need to
# install it manually. We use Twine in nightly builds to upload Python packages
# to PyPI.
if [[ "$TFCI_MACOS_TWINE_INSTALL_ENABLE" == 1 ]]; then
  pip install twine==3.6.0
fi

# Scheduled nightly and release builds upload build artifacts (Pip packages,
# Libtensorflow archives) to GCS buckets. TFCI Mac VMs need to authenticate as

      - name: Checkout repository for nightly (skipped for releases)
        if: ${{ github.event_name == 'schedule' }}
        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
        with:
          ref: 'nightly'
      - name: Checkout repository
        if: ${{ github.event_name == 'push' }}

# If building installer wheels, set the required environment variables that are
# read by setup.py.
if [[ "$TFCI_INSTALLER_WHL_ENABLE" == 1 ]]; then
  export collaborator_build=True
  # If building nightly installer wheels, set the project name to
  # nightly equivalent.
  if [[ "$TFCI_NIGHTLY_UPDATE_VERSION_ENABLE" == 1 ]]; then
    export TFCI_INSTALLER_WHL_PROJECT_NAME="$TFCI_INSTALLER_WHL_NIGHTLY_PROJECT_NAME"
  fi

    )
}

tasks.register<UpdateReleasedVersions>("updateReleasedVersionsToLatestNightly") {
    currentReleasedVersion = project.provider {
        val jsonText = URI("https://services.gradle.org/versions/nightly").toURL().readText()
        println(jsonText)
        val versionInfo = Gson().fromJson(jsonText, VersionBuildTimeInfo::class.java)
        ReleasedVersion(versionInfo.version, versionInfo.buildTime)
    }
}

    prepTask = branch.prepNightlyTaskName(),
    triggerName = "QuickFeedback",
    vcsRootId = gradlePromotionBranches
) {
    init {
        id("Promotion_SnapshotFromQuickFeedbackStepUpload")
        name = "Nightly Snapshot (from QuickFeedback) - Upload"
        description = "Builds and uploads the latest successful changes on '${branch.branchName}' from Quick Feedback as a new distribution"

        steps {
            buildStep(

        |           |--------- QuickFeedback
        |           |--------- ...
        |           |--------- ReadyForRelease
        |
        |---------- Promotion
        |           |--------- Publish Nightly Snapshot
        |           |--------- Publish Branch Snapshot
        |           |--------- ...
        |
        |---------- Util
                    |--------- ...

# tensorflow/core/public/version.h and tools/pip_package/setup.py.
#
# These variables aren't available by default. Scripts must source this file
# explicitly, *after* checking if update_version.py needs to be run for a
# nightly job. update_version.py affects TF_VER_SUFFIX, TF_VER_PYTHON, and
# TF_VER_FULL.

# Note: in awk, the command '/search/ {commands}' applies the commands to any line that

    ```

    This will run it using your installed version of TensorFlow. To be sure
    you're running the same code that you're testing:

    *   Use an up to date [tf-nightly](https://pypi.org/project/tf-nightly/)
        `pip install -U tf-nightly`
    *   Rebase your pull request onto a recent pull from
        [TensorFlow's](https://github.com/tensorflow/tensorflow) master branch.