# limitations under the License.
# ==============================================================================
TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config release_arm64_linux"
TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_arm64
# Note: this is not set to "--cpu", because that changes the package name
# to tensorflow_cpu. These ARM builds are supposed to have the name "tensorflow"
# despite lacking Nvidia CUDA support.

  std::unordered_map<int64_t, TapeTensor> sources_that_are_targets;
  for (int i = 0; i < target_tensor_ids.size(); ++i) {
    int64_t target_id = target_tensor_ids[i];
    if (sources_set.find(target_id) != sources_set.end()) {
      auto tensor = targets[i];
      sources_that_are_targets.insert(
          std::make_pair(target_id, TapeTensor(tensor)));
    }
  }

  | sort -u
}

# Verify that, given a build target and a license-list generator target, all of
# the dependencies of that target which include a license notice file are then
# included when generating that license. Necessary because the license targets
# in TensorFlow are manually enumerated rather than generated automatically.
do_external_licenses_check(){
  BUILD_TARGET="$1"
  LICENSES_TARGET="$2"

source ci/official/envs/linux_arm64
TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config  cross_compile_linux_arm64"

   tfrun bazel build $TFCI_BAZEL_COMMON_ARGS --profile "$TFCI_OUTPUT_DIR/profile.json.gz" --config="${TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX}_pycpp_test"
else
   tfrun bazel test $TFCI_BAZEL_COMMON_ARGS --profile "$TFCI_OUTPUT_DIR/profile.json.gz" --config="${TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX}_pycpp_test"
fi

# Note: the profile can be viewed by visiting chrome://tracing in a Chrome browser.

# > TF's gen_api_init_files has a genrule to run the core TensorFlow code
# > on the host machine. If we don't have --distinct_host_configuration=false,
# > the core TensorFlow code will be built once for the host and once for the
# > target platform.
# See also https://docs.bazel.build/versions/master/guide.html#build-configurations-and-cross-compilation
build --distinct_host_configuration=false

    permissions:
      contents: write
    steps:
    - uses: zofrex/mirror-branch@a8809f0b42f9dfe9b2c5c2162a46327c23d15266 # v1.0.3
      name: Set nightly branch to master HEAD
      with:

# ==============================================================================
source ci/official/envs/macos_x86
TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION  --config cross_compile_macos_x86"
TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=cross_compile_macos_x86
TFCI_MACOS_CROSS_COMPILE_ENABLE=1
TFCI_MACOS_CROSS_COMPILE_SDK_DEST="tensorflow/tools/toolchains/cross_compile/cc/MacOSX.sdk"

  in_grads.reserve(input_tensors.size());
  for (int target_index = 0; target_index < input_tensors.size();
       ++target_index) {
    const auto current_grad =
        accumulated_gradients_.find(input_tensors[target_index].GetID());
    if (current_grad == accumulated_gradients_.end()) {
      if (IsDtypeTrainable(input_tensors[target_index].GetDType())) {

  # and don't print duplicates
  awk '/Streaming build results to/ {print $NF}' "$TFCI_OUTPUT_DIR/script.log" | uniq
}

# Print out any ResultStore URLs for Bazel invocations' results.
# Each failed target there will have its own representation, making failures
# easier to find and read.
function resultstore_extract {
  local \
    XML_PATH="$TFCI_OUTPUT_DIR/Bazel_Test_and_Build_Results/sponge_log.xml"

  python3 \