--experimental_cc_shared_library \
    --@local_config_cuda//:enable_cuda \
    --@local_config_cuda//cuda:include_cuda_libs=false \
    --repo_env=HERMETIC_CUDA_VERSION="12.3.2" \
    --repo_env=HERMETIC_CUDNN_VERSION="8.9.7.29" \
    --repo_env=HERMETIC_NCCL_VERSION="2.27.7" \
    "somepath(//tensorflow/tools/pip_package:wheel, " \
    "@local_config_cuda//cuda:cudart + "\
    "@local_config_cuda//cuda:cudart + "\

  tfrun bazel $TFCI_BAZEL_BAZELRC_ARGS build $TFCI_BAZEL_COMMON_ARGS --profile "$PROFILE_JSON_PATH" --@local_config_cuda//cuda:override_include_cuda_libs=true --config=hermetic_cuda_umd --config="${TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX}_pycpp_test"
else

    actual = if_oss(
        "@local_config_cuda//:is_cuda_enabled",
        "@local_config_cuda//cuda:using_config_cuda",
    ),
)

# 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(
    name = "is_cuda_compiler_clang",
    actual = if_oss(
        "@local_config_cuda//:is_cuda_compiler_clang",

    cudnn_redistributions = CUDNN_REDISTRIBUTIONS,
)

load(
    "@rules_ml_toolchain//third_party/gpus/cuda/hermetic:cuda_configure.bzl",
    "cuda_configure",
)

cuda_configure(name = "local_config_cuda")

load(
    "@rules_ml_toolchain//third_party/nccl/hermetic:nccl_redist_init_repository.bzl",
    "nccl_redist_init_repository",
)

nccl_redist_init_repository()

load(

common:cuda --repo_env TF_NEED_CUDA=1
common:cuda --@local_config_cuda//:enable_cuda
common:cuda --config=cuda_version
# This flag is needed to include CUDA libraries.
common:cuda --@local_config_cuda//cuda:include_cuda_libs=true

# This configuration is used for building the wheels.
common:cuda_wheel --@local_config_cuda//cuda:include_cuda_libs=false