RUN wget https://github.com/NixOS/patchelf/releases/download/0.18.0/patchelf-0.18.0-x86_64.tar.gz && tar -zxvf patchelf-0.18.0-x86_64.tar.gz -C /usr && rm -rf patchelf-0.18.0-x86_64.tar.gz

# Don't use the bazel cache when a new docker image is created.
RUN echo build --action_env=DOCKER_CACHEBUSTER=$(date +%s%N)$RANDOM >> /etc/bazel.bazelrc

TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_tpu
TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow_tpu"
TFCI_LIB_SUFFIX="-tpu-linux-x86_64"
TFCI_WHL_BAZEL_TEST_ENABLE=0
TFCI_WHL_IMPORT_TEST_ENABLE=0
TFCI_WHL_SIZE_LIMIT=580M

TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_cuda
TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow"
TFCI_DOCKER_ARGS="--gpus all"
TFCI_LIB_SUFFIX="-gpu-linux-x86_64"

build:android_arm64 --fat_apk_cpu=arm64-v8a
build:android_x86 --config=android
build:android_x86 --cpu=x86
build:android_x86 --fat_apk_cpu=x86
build:android_x86_64 --config=android
build:android_x86_64 --cpu=x86_64
build:android_x86_64 --fat_apk_cpu=x86_64

# Build everything statically for Android since all static libs are later
# bundled together into a single .so for deployment.
build:android --dynamic_mode=off

REPO_ROOT="$(dirname "$(dirname "${SCRIPT_DIR}")")"

LOCAL_ARCH=$(uname -m)

# Pass environment set target architecture to build system
if [[ ${TARGET_ARCH} ]]; then
    # Target explicitly set
    :
elif [[ ${LOCAL_ARCH} == x86_64 ]]; then
    TARGET_ARCH=amd64
elif [[ ${LOCAL_ARCH} == armv8* ]]; then
    TARGET_ARCH=arm64
elif [[ ${LOCAL_ARCH} == arm64* ]]; then
    TARGET_ARCH=arm64
elif [[ ${LOCAL_ARCH} == aarch64* ]]; then

        instead of 2.15, or users could receive an installation error due to
        those missing dependencies.
*   TensorFlow 2.15.0.post1 is being released for Linux x86_64 to resolve this
    issue as quickly as possible.
    *   This version removes the `tensorrt` Python package dependencies from the
        tensorflow[and-cuda] installation method to ensure `pip install