# Run any CI script and env configuration to bisect a failing target in some
# build configuration. You must set the following variables to control this
# script:
#
#   TF_BISECT_GOOD: Last known good commit (e.g. commit from the last passing job)
#   TF_BISECT_BAD: First bad commit (e.g. commit from the first failing job)
#   TF_BISECT_SCRIPT: The build script path relative to the TF root dir, e.g.

      - name: Create a new Github Issue
        uses: actions/github-script@d556feaca394842dc55e4734bf3bb9f685482fa0 # v6.3.3
        with:
          github-token: ${{secrets.GITHUB_TOKEN}}
          script: |
            const script = require('./.github/workflows/create_issue.js')

    ```
    cd ci/official/wheel_test
    ```
2.  Run a script for creating requirements file:
    ```
    bash update_requirements.sh <path_to_tensorflow_wheel> <python_version>
    e.g.:
    bash update_requirements.sh /tmp/tensorflow-2.14.0-cp311-cp311-linux_x86_64.whl 3_11
    ```

#### Requirements Updater Script
This script automates the process of updating TensorFlow requirements for a
specific Python version.

# This env is only valid when RBE is available on the selected platform, since
# it enables a derived --config setting.  If RBE is not available (i.e. there
# is no --config setting), bazel would fail and quit. This script does a quick
# check This script checks for such errors early
if ! grep "rbe_$TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX" .bazelrc; then
  cat <<EOF
ERROR: RBE was enabled via the 'rbe' env in the 'TFCI' variable.
       TFCI: $TFCI

# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
# This script dumps some information about the environment. It's most useful
# for verifying changes to the TFCI scripts system, and most users won't need
# to interact with it at all.
source "${BASH_SOURCE%/*}/utilities/setup.sh"

# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================

# script to run pip-compile for each requirement.
# if there is a change in requirements.in then all lock files will be updated
# accordingly

# All commands run relative to this directory
cd "$(dirname "${BASH_SOURCE[0]}")"

  python3 \
    "$TFCI_GIT_DIR/ci/official/utilities/extract_resultstore_links.py" \
    "$TFCI_OUTPUT_DIR/script.log" \
    --print \
    --xml-out-path "$XML_PATH" || resultstore_extract_fallback
}

if grep -q "Streaming build results to" "$TFCI_OUTPUT_DIR/script.log"; then
  resultstore_extract || resultstore_extract_fallback

against a pending change. Search for "MLCI" internally to find it.

You may invoke a CI script of your choice by following these instructions:

```bash
cd tensorflow-git-dir

# Here is a single-line example of running a script on Linux to build the
# GPU version of TensorFlow for Python 3.12, using the public TF bazel cache and
# a local build cache:

# limitations under the License.
# ==============================================================================

# script to run pip-compile for keras, tensorboard, estimator deps.
# if there is a change in requirements.in then all lock files will be updated
# accordingly.

# -e: abort script if one command fails
# -u: error if undefined variable used
# -o pipefail: entire command fails if pipe fails. watch out for yes | ...

   `release_updater.sh`

5) Run the `updater.sh` shell script. \
   If the base requirements file hasn't yet been updated to account for the new
   Python version, which will require different versions for at least some
   dependencies, it will need to be updated now, for the script to run
   successfully.

6) A new `requirements_lock_3_11.txt` file should appear under the root of the