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

cuda_json_init_repository()

load(
    "@cuda_redist_json//:distributions.bzl",
    "CUDA_REDISTRIBUTIONS",
    "CUDNN_REDISTRIBUTIONS",
)
load(
    "@rules_ml_toolchain//third_party/gpus/cuda/hermetic:cuda_redist_init_repositories.bzl",

#     release_cpu_linux:               Toolchain and CUDA options for Linux CPU builds.
#     release_gpu_linux:               Toolchain and CUDA options for Linux GPU builds.
#     release_cpu_macos:               Toolchain and CUDA options for MacOS CPU builds.
#     release_cpu_windows:             Toolchain and CUDA options for Windows CPU builds.
# LINT.IfChange

    done < $BATS_TEST_TMPDIR/missing_deps
    exit 1
  fi
}

# The Python package is not allowed to depend on any CUDA packages.
@test "Pip package doesn't depend on CUDA" {
  bazel cquery \
    --experimental_cc_shared_library \
    --@local_config_cuda//:enable_cuda \
    --@local_config_cuda//cuda:include_cuda_libs=false \

RUN ln -sf /usr/bin/python3.12 /usr/bin/python
RUN ln -sf /usr/lib/python3.12 /usr/lib/tf_python

# Link the compat driver to the location if available.
RUN if [ -e "/usr/local/cuda/compat/libcuda.so.1" ]; then ln -s /usr/local/cuda/compat/libcuda.so.1 /usr/lib/x86_64-linux-gnu/libcuda.so.1; fi

# Install various tools.
# - bats: bash unit testing framework
# - bazelisk: always use the correct bazel version

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.
TFCI_BUILD_PIP_PACKAGE_WHEEL_NAME_ARG="--repo_env=WHEEL_NAME=tensorflow"
TFCI_DOCKER_ENABLE=1
TFCI_DOCKER_IMAGE=us-docker.pkg.dev/ml-oss-artifacts-published/ml-public-container/ml-build-arm64:latest

    #   -r ci/official/requirements_updater/nvidia-constraints.txt
    #   -r ci/official/requirements_updater/nvidia-requirements.txt
    #   nvidia-cudnn-cu12
    #   nvidia-cusolver-cu12
nvidia-cuda-cupti-cu12==12.5.82 \
    --hash=sha256:4f835281cf492e2bedd153f5c3de9da8f1d775a419468305e64ce73b3b0c6dc3 \
    --hash=sha256:bde77a5feb66752ec61db2adfe47f56b941842825b4c7e2068aff27c9d107953 \

    #   -r ci/official/requirements_updater/nvidia-constraints.txt
    #   -r ci/official/requirements_updater/nvidia-requirements.txt
    #   nvidia-cudnn-cu12
    #   nvidia-cusolver-cu12
nvidia-cuda-cupti-cu12==12.5.82 \
    --hash=sha256:4f835281cf492e2bedd153f5c3de9da8f1d775a419468305e64ce73b3b0c6dc3 \
    --hash=sha256:bde77a5feb66752ec61db2adfe47f56b941842825b4c7e2068aff27c9d107953 \

    #   -r ci/official/requirements_updater/nvidia-constraints.txt
    #   -r ci/official/requirements_updater/nvidia-requirements.txt
    #   nvidia-cudnn-cu12
    #   nvidia-cusolver-cu12
nvidia-cuda-cupti-cu12==12.5.82 \
    --hash=sha256:4f835281cf492e2bedd153f5c3de9da8f1d775a419468305e64ce73b3b0c6dc3 \
    --hash=sha256:bde77a5feb66752ec61db2adfe47f56b941842825b4c7e2068aff27c9d107953 \

    #   -r ci/official/requirements_updater/nvidia-constraints.txt
    #   -r ci/official/requirements_updater/nvidia-requirements.txt
    #   nvidia-cudnn-cu12
    #   nvidia-cusolver-cu12
nvidia-cuda-cupti-cu12==12.5.82 \
    --hash=sha256:4f835281cf492e2bedd153f5c3de9da8f1d775a419468305e64ce73b3b0c6dc3 \
    --hash=sha256:bde77a5feb66752ec61db2adfe47f56b941842825b4c7e2068aff27c9d107953 \

    #   -r ci/official/requirements_updater/nvidia-constraints.txt
    #   -r ci/official/requirements_updater/nvidia-requirements.txt
    #   nvidia-cudnn-cu12
    #   nvidia-cusolver-cu12
nvidia-cuda-cupti-cu12==12.5.82 \
    --hash=sha256:4f835281cf492e2bedd153f5c3de9da8f1d775a419468305e64ce73b3b0c6dc3 \
    --hash=sha256:bde77a5feb66752ec61db2adfe47f56b941842825b4c7e2068aff27c9d107953 \