// to the macros in tensorflow/core/framework/op_requires.h. This is provided
// for plugin OpKernel developer's convenience.

#define C_OPKERNELCONTEXT_REQUIRES_OK(CTX, C_STATUS, __VA_ARGS__) \
  do {                                                            \
    ::tensorflow::Status _s(__VA_ARGS__);                         \
    if (!TF_PREDICT_TRUE(_s.ok())) {                              \

name: ARM CI

on:
  push:
    branches:
      - master
      - r2.**
permissions:
  contents: read

jobs:
  build:
    # Don't do this in forks, and if labeled, only for 'kokoro:force-run'
    if: github.repository == 'tensorflow/tensorflow' && (github.event.action != 'labeled' || (github.event.action == 'labeled' && github.event.label.name == 'kokoro:force-run'))

# "pip tests" run a similar suite of tests the "nonpip" tests, but do something
# odd to attempt to validate the quality of the pip package. The wheel is
# installed into a virtual environment, and then that venv is used to run all

// https://github.com/tensorflow/community/blob/master/rfcs/20200612-stream-executor-c-api/C_API_versioning_strategy.md
#define TF_VALIDATE_STRUCT_SIZE(STRUCT_NAME, STRUCT_OBJ, SIZE_VALUE_NAME) \
  do {                                                                    \
    if (STRUCT_OBJ.struct_size == 0) {                                    \
      return tensorflow::Status(absl::StatusCode::kFailedPrecondition,    \

  # Install the necessary Python, unless it's already present
  pyenv install -s "$TFCI_PYTHON_VERSION"
  pyenv local "$TFCI_PYTHON_VERSION"
  # Do a sanity check to make sure that we using the correct Python version
  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.

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

mv BUILD.bazel BUILD

SUPPORTED_VERSIONS=("3_9" "3_10" "3_11" "3_12")

for VERSION in "${SUPPORTED_VERSIONS[@]}"
do
  touch "requirements_lock_$VERSION.txt"
  bazel run \
    --experimental_convenience_symlinks=ignore \
    --enable_bzlmod=false \
    //:requirements_"$VERSION".update
  sed -i '/^#/d' requirements_lock_"$VERSION".txt

  schedule:
    - cron: 0 4 * * *  # 4am UTC is 9pm PDT and 8pm PST
name: Set nightly branch to master HEAD

permissions: {}

jobs:
  master-to-nightly:
    if: github.repository == 'tensorflow/tensorflow' # Don't do this in forks
    runs-on: ubuntu-latest
    permissions:
      contents: write
    steps:
    - uses: zofrex/mirror-branch@a8809f0b42f9dfe9b2c5c2162a46327c23d15266 # v1.0.3
      name: Set nightly branch to master HEAD

      - '!tensorflow/tools/tf_sig_build_dockerfiles/README.md'

permissions:
  contents: read

jobs:
  docker:
    if: github.repository == 'tensorflow/tensorflow' # Don't do this in forks
    runs-on: ubuntu-latest
    strategy:
      matrix:
        python-version: [python3.9, python3.10, python3.11, python3.12]
    permissions:
      contents: read
      pull-requests: write

# limitations under the License.
# ==============================================================================
# Release jobs are very basic. They don't use any caching or RBE,
# but they do upload logs to resultstore.
# IMPORTANT: trailing slash is required on GCS URIs, as it tells gcloud to
# pretend the path is a directory.
TFCI_ARTIFACT_FINAL_GCS_ENABLE=1

    - cron: '44 15 * * 5'
  push:
    branches: [ master ]

# Declare default permissions as read only.
permissions: read-all

jobs:
  analysis:
    if: github.repository == 'tensorflow/tensorflow' # Don't do this in forks
    name: Scorecards analysis
    runs-on: ubuntu-latest
    permissions:
      # Needed to upload the results to code-scanning dashboard.
      security-events: write
      id-token: write

    steps: