}

// Helper functions which delegate to `AbstractOperation`, update
// the state of the ForwardOperation and call the tape as appropriate.
// These APIs are mainly to facilitate testing and are subject to change.
namespace internal {
Status Reset(AbstractOperation* op_, const char* op,
             const char* raw_device_name, ForwardOperation* forward_op_) {
  forward_op_->op_name = op;
  forward_op_->attrs.Reset(op);

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

# script to run pip-compile for keras, tensorboard, estimator deps.
# if there is a change in requirements.in then all lock files will be updated
# accordingly.

mv BUILD.bazel BUILD

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

for VERSION in "${SUPPORTED_VERSIONS[@]}"
do

if [[ "$TFCI_WHL_SIZE_LIMIT_ENABLE" == "1" ]] && [[ -n "$(find . -iname "*.whl" -size "+$TFCI_WHL_SIZE_LIMIT")" ]]; then
  echo "Error: Generated wheel is too big! Limit is $TFCI_WHL_SIZE_LIMIT"
  echo '(search for TFCI_WHL_SIZE_LIMIT to change it)'
  ls -sh *.whl
  exit 2
fi

# Quick install checks
venv=$(mktemp -d)
"python${TFCI_PYTHON_VERSION}" -m venv "$venv"
python="$venv/bin/python3"

# support through e.g. `--config=cuda` (or `--config=cuda_clang` in OSS).
alias(
    name = "is_cuda_enabled",
    actual = if_oss(
        "@local_config_cuda//:is_cuda_enabled",
        "@local_config_cuda//cuda:using_clang",
    ),
)

# Config setting that is satisfied when CUDA device code should be compiled
# with clang. It does not imply that CUDA support has been enabled.
alias(

build:avx_win --copt=/arch:AVX

# Use Clang-cl compiler on Windows
build:win_clang --copt=/clang:-Weverything
build:win_clang --extra_toolchains=@local_config_cc//:cc-toolchain-x64_windows-clang-cl
build:win_clang --extra_execution_platforms=//tensorflow/tools/toolchains/win:x64_windows-clang-cl
build:win_clang --host_platform=//tensorflow/tools/toolchains/win:x64_windows-clang-cl
build:win_clang --compiler=clang-cl

        # TF 2.12 + Clang (containers are the same, but env vars in configs.bzl are different)
        map sigbuild-r2.12-clang 2.12-python3.9
        map sigbuild-r2.12-clang-python3.8 2.12-python3.8
        map sigbuild-r2.12-clang-python3.9 2.12-python3.9
        map sigbuild-r2.12-clang-python3.10 2.12-python3.10
        map sigbuild-r2.12-clang-python3.11 2.12-python3.11
        # TF 2.13

  return val


def set_clang_cuda_compiler_path(environ_cp):
  """Set CLANG_CUDA_COMPILER_PATH."""
  default_clang_path = '/usr/lib/llvm-17/bin/clang'
  if not os.path.exists(default_clang_path):
    default_clang_path = '/usr/lib/llvm-16/bin/clang'
    if not os.path.exists(default_clang_path):
      default_clang_path = which('clang') or ''

  clang_cuda_compiler_path = prompt_loop_or_load_from_env(

One or more test dependencies are not in the pip package.
If these test dependencies need to be in the TensorFlow pip package, please
add them to //tensorflow/tools/pip_package/BUILD. Otherwise, add the no_pip tag
to the test, or change code_check_full.bats in the SIG Build repository. That's
https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/tf_sig_build_dockerfiles/devel.usertools/code_check_full.bats
Here are the affected tests:
EOF

# Other build-related tools
autoconf
automake
build-essential
ca-certificates
llvm-17
clang-17
clang-format-12
lld-17
colordiff
curl
ffmpeg
gdb
git
jq
less
libcurl3-dev
libcurl4-openssl-dev
libfreetype6-dev
libhdf5-serial-dev
libomp-17-dev
libssl-dev
libtool
libxml2-dev
libxslt1-dev
libzmq3-dev
mlocate
moreutils
openjdk-11-jdk
openjdk-11-jre-headless
openssl
patchelf

# set in the shell environment, those variables will be restored after the
# TFCI env has been loaded. This is useful for e.g. on-demand "generic" jobs
# where the user may wish to change just one option.
if [[ -z "${TFCI:-}" ]]; then
  echo '==TFCI==: The $TFCI variable is not set. This is fine as long as you'
  echo 'already sourced a TFCI env file with "set -a; source <path>; set +a".'