package(default_visibility = ["//visibility:public"])

filegroup(
    name = "gcc",
    srcs = glob(["bin/*-gcc"]),
)

filegroup(
    name = "ar",
    srcs = glob(["bin/*-ar"]),
)

filegroup(
    name = "ld",
    srcs = glob(["bin/*-ld"]),
)

filegroup(
    name = "nm",
    srcs = glob(["bin/*-nm"]),
)

filegroup(
    name = "objcopy",
    srcs = glob(["bin/*-objcopy"]),
)

filegroup(

-   type: input id: Bazel attributes: label: Bazel version description: if
    compiling from source placeholder: validations: required: false

-   type: input id: Compiler attributes: label: GCC/Compiler version
    description: if compiling from source placeholder: validations: required:
    false

-   type: input id: Cuda attributes: label: CUDA/cuDNN version description:
    placeholder: validations: required: false

# The profile can be viewed by visiting chrome://tracing in a Chrome browser.
# See https://docs.bazel.build/versions/main/skylark/performance.html#performance-profiling
build --profile=/tf/pkg/profile.json.gz

# Use the rebuilt gcc toolchain to compile for manylinux2014
build --crosstool_top="@ml2014_clang_aarch64_config_aarch64//crosstool:toolchain"

build --copt="-mtune=generic" --copt="-march=armv8-a" --copt="-O3"

# The profile can be viewed by visiting chrome://tracing in a Chrome browser.
# See https://docs.bazel.build/versions/main/skylark/performance.html#performance-profiling
build --profile=/tf/pkg/profile.json.gz

# Use the rebuilt gcc toolchain to compile for manylinux2014
build --crosstool_top="@ml2014_aarch64_config_aarch64//crosstool:toolchain"
test --crosstool_top="@ml2014_aarch64_config_aarch64//crosstool:toolchain"

        vmhc("Health Check")
        vmar("Auto Registration")
    end
    subgraph Gateway
        twc("Tag Watcher")
        gdc("Gateway Deployment")
        gcc("Gateway Class")
        twc--Depends-->gdc
        gdc-.-gcc
    end
    subgraph Ingress
        ic("Ingress Controller")
        isc("Ingress Status Controller")
        ic-.-isc
    end
    mcsc("Multicluster Secret")

build:cuda_clang_official --action_env=TF_CUDNN_VERSION="8"
build:cuda_clang_official --action_env=CUDA_TOOLKIT_PATH="/usr/local/cuda-12.3"
build:cuda_clang_official --action_env=GCC_HOST_COMPILER_PATH="/dt9/usr/bin/gcc"
build:cuda_clang_official --action_env=CLANG_CUDA_COMPILER_PATH="/usr/lib/llvm-17/bin/clang"
build:cuda_clang_official --action_env=LD_LIBRARY_PATH="/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64"

    msys ' '; \
    msys 'pacman --noconfirm -Syy bsdcpio bsdtar bzip2'; \
    msys 'pacman --noconfirm -Syy coreutils curl dash file filesystem findutils'; \
    msys 'pacman --noconfirm -Syy flex gawk gcc-libs grep gzip inetutils info'; \
    msys 'pacman --noconfirm -Syy less lndir mintty ncurses pactoys-git patch'; \
    msys 'pacman --noconfirm -Syy pax-git pkgfile rebase sed tar tftp-hpa time tzcode util-linux which'; \

    * TensorFlow is now compiled with `_GLIBCXX_USE_CXX11_ABI=1`. Downstream projects that encounter `std::__cxx11` or `[abi:cxx11]` linker errors will need to adopt this compiler option. See [the GNU C++ Library docs on Dual ABI](https://gcc.gnu.org/onlinedocs/libstdc++/manual/using_dual_abi.html).