bool_flag(
    name = "enable_registration_v2",
    build_setting_default = False,
    visibility = ["//visibility:public"],
)

config_setting(
    name = "registration_v1",
    flag_values = {":enable_registration_v2": "False"},
    visibility = ["//visibility:public"],
)

config_setting(
    name = "registration_v2",
    flag_values = {":enable_registration_v2": "True"},

      -
        name: Set up Docker Buildx
        uses: docker/setup-buildx-action@8c0edbc76e98fa90f69d9a2c020dcb50019dc325 # v2.2.1
      -
        name: Login to DockerHub
        uses: docker/login-action@f4ef78c080cd8ba55a85445d5b36e214a81df20a # v2.1.0
        with:
          username: ${{ secrets.DOCKERHUB_USERNAME }}
          password: ${{ secrets.DOCKERHUB_TOKEN }}
      -
        name: Login to GCR

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

name: ARM CI Extended

on:
  push:
    tags:
      - v2.**
  schedule:
    - cron: '0 4 * * *'

permissions:
  contents: read

jobs:
  build:
    if: github.repository == 'tensorflow/tensorflow' # Don't do this in forks
    runs-on: [self-hosted, linux, ARM64]

      -
        name: Set up Docker Buildx
        uses: docker/setup-buildx-action@8c0edbc76e98fa90f69d9a2c020dcb50019dc325 # v2.2.1
      -
        name: Login to DockerHub
        uses: docker/login-action@f4ef78c080cd8ba55a85445d5b36e214a81df20a # v2.1.0
        with:
          username: ${{ secrets.DOCKERHUB_USERNAME }}
          password: ${{ secrets.DOCKERHUB_TOKEN }}
      -
        name: Login to GCR

build --action_env=CACHEBUSTER=20220325

# Use Python 3.X as installed in container image
build --action_env PYTHON_BIN_PATH="/usr/local/bin/python3"
build --python_path="/usr/local/bin/python3"

# Build TensorFlow v2
build --define=tf_api_version=2 --action_env=TF2_BEHAVIOR=1

# Use lld as the linker
build --linkopt="-fuse-ld=lld"
build --linkopt="-lm"
build --linkopt="-Wl,--undefined-version"

      - name: Check whether the citation metadata from CITATION.cff is valid
        uses: citation-file-format/cffconvert-github-action@4cf11baa70a673bfdf9dad0acc7ee33b3f4b6084 # v2.0.0
        with:

# Hook external TensorFlow modules.
# Import compat before trying to import summary from tensorboard, so that
# reexport_tf_summary can get compat from sys.modules. Only needed if using
# lazy loading.
_current_module.compat.v2  # pylint: disable=pointless-statement

# Load tensorflow-io-gcs-filesystem if enabled
if (_os.getenv("TF_USE_MODULAR_FILESYSTEM", "0") == "true" or
    _os.getenv("TF_USE_MODULAR_FILESYSTEM", "0") == "1"):

        *   (since v2.7) `tf.math.segment_mean`
        *   (since v2.7) `tf.math.segment_prod`
        *   (since v2.7) `tf.math.segment_sum`
        *   (since v2.7) `tf.math.unsorted_segment_mean`
        *   (since v2.7) `tf.math.unsorted_segment_prod`
        *   (since v2.7) `tf.math.unsorted_segment_sum`
        *   (since v2.7) `tf.math.unsorted_segment_sqrt`

                absl::Span<AbstractTensorHandle*> outputs) {
  return ops::Mul(ctx, inputs[0], inputs[1], &outputs[0], "Mul");
}

// TODO(vnvo2409): Add more tests from `python/ops/gradient_checker_v2_test.py`.
// These tests should not be confused with `[*]_grad_test` which compare the
// result of `gradient_checker` and `[*]_grad`. The tests here test the
// functionality of `gradient_checker` by comparing the result with expected

and follow the sandboxing guideline above to protect against these types of
vulnerabilities.

## Security properties of execution modes

TensorFlow has several execution modes, with Eager-mode being the default in v2.
Eager mode lets users write imperative-style statements that can be easily
inspected and debugged and it is intended to be used during the development
phase.