fi
# Import tf nightly wheel built with numpy2 from PyPI in numpy1 env for testing.
# This aims to maintain TF compatibility with NumPy 1.x until 2025 b/361369076.
if [[ "$TFCI_WHL_NUMPY_VERSION" == 1 ]]; then
  # Uninstall tf nightly wheel built with numpy1.
  "$python" -m pip uninstall -y tf_nightly_numpy1
  # Install tf nightly cpu wheel built with numpy2.x from PyPI in numpy1.x env.

# Update the version numbers for Nightly only, then fetch the version numbers
# for choosing the final directory name. This adds "-devYYYYMMDD" to the end of
# the version string (.devYYYYMMDD for Python; see pypi.org/project/tf-nightly)
if [[ "$TFCI_NIGHTLY_UPDATE_VERSION_ENABLE" == 1 ]]; then
  tfrun python3 tensorflow/tools/ci_build/update_version.py --nightly
fi
source ci/official/utilities/get_versions.sh

 |        |---- QuickFeedback
 |        |---- ...
 |        |---- ReadyForRelease
 |
 |----- Promotion (buildTypeId: Gradle_Master_Promotion)
 |        |----- Nightly Snapshot
 |        |----- ...
 |
 |----- Util
         |----- WarmupEc2Agent
         |----- AdHocPerformanceTest

Release (buildTypeId: Gradle_Release)
 |----- Check (buildTypeId: Gradle_Release_Check)

# Record GPU count and CUDA version status
if [[ "$TFCI_NVIDIA_SMI_ENABLE" == 1 ]]; then
  tfrun nvidia-smi
fi

# Update the version numbers for Nightly only
if [[ "$TFCI_NIGHTLY_UPDATE_VERSION_ENABLE" == 1 ]]; then
  tfrun python3 tensorflow/tools/ci_build/update_version.py --nightly
fi

tfrun bazel $TFCI_BAZEL_BAZELRC_ARGS test $TFCI_BAZEL_COMMON_ARGS --config=linux_libtensorflow_test

      - 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 for releases (skipped for nightly)
        if: ${{ github.event_name == 'push' }}

# ==============================================================================
source "${BASH_SOURCE%/*}/utilities/setup.sh"

# Update the version numbers for Nightly only
if [[ "$TFCI_NIGHTLY_UPDATE_VERSION_ENABLE" == 1 ]]; then
  python3 tensorflow/tools/ci_build/update_version.py --nightly
fi

# This generates a pure python wheel of the format "*-py3-none-any.whl"

    cleanCheckout = false
) {
    init {
        id("Promotion_SnapshotFromQuickFeedbackStepPromote")
        name = "Nightly Snapshot (from QuickFeedback) - Promote"
        description = "Promotes a previously built distribution on this agent on '${branch.branchName}' from Quick Feedback as a new nightly snapshot. This build checks out gradle-promote, so don't be misled by the 'master' branch."

        steps {
            buildStep(

  - type: dropdown
    id: tf-nightly
    attributes:
      label: Have you reproduced the bug with TensorFlow Nightly?
      description: It is strongly suggested that you reproduce the bug with [TensorFlow Nightly](https://www.tensorflow.org/install/pip#nightly)
      options:
        - "Yes"
        - "No"
    validations:
      required: true

# Record GPU count and CUDA version status
if [[ "$TFCI_NVIDIA_SMI_ENABLE" == 1 ]]; then
  tfrun nvidia-smi
fi

# Update the version numbers for Nightly only
if [[ "$TFCI_NIGHTLY_UPDATE_VERSION_ENABLE" == 1 ]]; then
  tfrun python3 tensorflow/tools/ci_build/update_version.py --nightly
  # replace tensorflow to tf_nightly in the wheel name
  export TFCI_BUILD_PIP_PACKAGE_ARGS="$(echo $TFCI_BUILD_PIP_PACKAGE_ARGS | sed 's/tensorflow/tf_nightly/')"

system, Kokoro, schedules our CI jobs by combining a build script with a file
from the `envs` directory that is filled with configuration options:

-   Nightly jobs (Run nightly on the `nightly` branch)
    -   Uses `wheel.sh`, `libtensorflow.sh`, `code_check_full.sh`
-   Continuous jobs (Run on every GitHub commit)
    -   Uses `pycpp.sh`
-   Presubmit jobs (Run on every GitHub PR)