| 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"

  for (int i = 0; i < noutputs; ++i) {
    output_names[i] = c_output_names[i];
  }
  std::vector<string> target_oper_names(ntargets);
  for (int i = 0; i < ntargets; ++i) {
    target_oper_names[i] = c_target_oper_names[i];
  }
  TF_Run_Helper(s->session, nullptr, run_options, input_pairs, output_names,
                c_outputs, target_oper_names, run_metadata, status);
}

void TF_PRunSetup(TF_DeprecatedSession* s,

# 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.

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

# > 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

  ;;
esac

mkdir -p "${TARGET}"

mkdir -p ${TARGET}/usr/include

# Put the current kernel headers from ubuntu in place.
ln -s "/usr/include/linux" "${TARGET}/usr/include/linux"
ln -s "/usr/include/asm-generic" "${TARGET}/usr/include/asm-generic"
ln -s "/usr/include/aarch64-linux-gnu/asm" "${TARGET}/usr/include/asm"

# Download glibc's shared and development libraries based on the value of the
# `VERSION` parameter.

    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)));
    }
  }

  TF_RETURN_IF_ERROR(GradientTape::ComputeGradient(
      vspace, target_tensor_ids, source_tensor_ids, sources_that_are_targets,
      output_gradients, result, /*build_default_zeros_grads*/ 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"

  # 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 \