TFCI_DOCKER_PULL_ENABLE=1
TFCI_DOCKER_REBUILD_ARGS="--target=tf ci/official/containers/linux_arm64"
TFCI_INDEX_HTML_ENABLE=1
TFCI_LIB_SUFFIX="-cpu-linux-arm64"
TFCI_OUTPUT_DIR=build_output
TFCI_WHL_AUDIT_ENABLE=1
TFCI_WHL_AUDIT_PLAT=manylinux2014_aarch64
TFCI_WHL_BAZEL_TEST_ENABLE=1
TFCI_WHL_SIZE_LIMIT=240M

  template <typename G>
  Cleanup(Cleanup<G>&& src)  // NOLINT
      : released_(src.is_released()), f_(src.release()) {}

  // Assignment to a Cleanup object behaves like destroying it
  // and making a new one in its place, analogous to unique_ptr
  // semantics.
  Cleanup& operator=(Cleanup&& src) {  // NOLINT
    if (!released_) f_();
    released_ = src.released_;
    f_ = src.release();
    return *this;
  }

  ~Cleanup() {

`tf` instead of `tensorflow`, following the common practice of importing
TensorFlow via the command `import tensorflow as tf`.

The primary function of this module is to import all of the public TensorFlow
interfaces into a single place. The interfaces themselves are located in
sub-modules, as described below.

Note that the file `__init__.py` in the TensorFlow source code tree is actually

> effort to improve the structure of CI and build related files within the
> TensorFlow repo. This warning will be removed when the contents of this
> directory are stable and appropriate documentation around its usage is in
> place.

Maintainer: TensorFlow DevInfra

********************************************************************************

The CI folder contains the configuration files and scripts used to build, test,

TFCI_INDEX_HTML_ENABLE=1
TFCI_LIB_SUFFIX="-cpu-linux-x86_64"
TFCI_OUTPUT_DIR=build_output
TFCI_WHL_AUDIT_ENABLE=1
TFCI_WHL_AUDIT_PLAT=manylinux2014_x86_64
TFCI_WHL_BAZEL_TEST_ENABLE=1
TFCI_WHL_SIZE_LIMIT=240M

    TAG=$(head -n 1 "$KOKORO_PIPER_DIR/presubmit_request.txt" | cut -d" " -f2)
  else
    TAG="pr-${KOKORO_GITHUB_PULL_REQUEST_NUMBER}"
  fi
fi

# Build for both JAX and TF usage.  We do these in one place because they share
# almost all of the same cache layers
export DOCKER_BUILDKIT=1
for target in jax tf; do
  IMAGE="gcr.io/tensorflow-sigs/build-arm64:$target-$TAG"
  docker pull "$IMAGE" || true

// loading a library. The rules for determining the exact location of the
// library are platform-specific and are not documented here.
//
// On success, place OK in status and return the newly created library handle.
// Otherwise returns nullptr and set error status.
TF_CAPI_EXPORT extern void* TF_LoadSharedLibrary(const char* library_filename,

TFCI_NIGHTLY_UPDATE_VERSION_ENABLE=
TFCI_NVIDIA_SMI_ENABLE=
TFCI_OUTPUT_DIR=
TFCI_PYCPP_SWAP_TO_BUILD_ENABLE=
TFCI_PYTHON_VERIFY_PIP_INSTALL_ARGS=
TFCI_PYTHON_VERSION=
TFCI_WHL_AUDIT_ENABLE=
TFCI_WHL_AUDIT_PLAT=
TFCI_WHL_BAZEL_TEST_ENABLE=
TFCI_WHL_IMPORT_TEST_ENABLE=1
TFCI_WHL_SIZE_LIMIT=

fi

# Create and expand to the full path of TFCI_OUTPUT_DIR
export TFCI_OUTPUT_DIR=$(realpath "$TFCI_OUTPUT_DIR")
mkdir -p "$TFCI_OUTPUT_DIR"

# In addition to dumping all script output to the terminal, place it into
# $TFCI_OUTPUT_DIR/script.log
exec > >(tee "$TFCI_OUTPUT_DIR/script.log") 2>&1

# Setup tfrun, a helper function for executing steps that can either be run

      if (iter == input_nodes.end()) {
        // This node is not referenced in inputs. Add it to the body.
        body_nodes->push_back(node);
      } else {
        // This node is referenced in inputs. Currently, we place an
        // artificial restriction and require that when num_opers=-1, such
        // nodes must have a single output.
        if (node->num_outputs() != 1) {
          return InvalidArgument(