/settings.gradle*                           @gradle/bt-developer-productivity
gradle/shared-with-buildSrc/                @gradle/bt-developer-productivity
packaging/internal-build-reports/           @gradle/bt-developer-productivity
testing/distributions-basics/               @gradle/bt-developer-productivity
testing/distributions-core/                 @gradle/bt-developer-productivity

export DEBIAN_FRONTEND=noninteractive

# Fetch the NVIDIA key.
apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/3bf863cc.pub;

# Set up sources for NVIDIA CUDNN.
cat >/etc/apt/sources.list.d/nvidia.list <<SOURCES
# NVIDIA
deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/ /

		<name>CodeLibs</name>
		<url>https://fess.codelibs.org/</url>
	</organization>
	<developers>
		<developer>
			<id>shinsuke</id>
			<name>Shinsuke Sugaya</name>
			<email>******@****.***</email>
			<organization>CodeLibs Inc.</organization>
			<organizationUrl>https://codelibs.co</organizationUrl>
		</developer>
	</developers>
	<issueManagement>
		<system>GitHub</system>

		<name>CodeLibs</name>
		<url>https://fess.codelibs.org/</url>
	</organization>
	<developers>
		<developer>
			<id>shinsuke</id>
			<name>Shinsuke Sugaya</name>
			<email>******@****.***</email>
			<organization>CodeLibs Inc.</organization>
			<organizationUrl>https://codelibs.co</organizationUrl>
		</developer>
	</developers>
	<scm>
		<connection>scm:git:******@****.***:codelibs/fess-suggest.git</connection>

nvidia-cuda-nvcc-cu12>=12.5.82,<13.0
nvidia-cuda-nvrtc-cu12>=12.5.82,<13.0
nvidia-cuda-runtime-cu12>=12.5.82,<13.0
# The upper bound is set for the CUDNN API compatibility.
# See
# https://docs.nvidia.com/deeplearning/cudnn/backend/latest/developer/forward-compatibility.html#cudnn-api-compatibility
nvidia-cudnn-cu12>=9.3.0.75,<10.0
nvidia-cufft-cu12>=11.2.3.61,<12.0
nvidia-curand-cu12>=10.3.6.82,<11.0
nvidia-cusolver-cu12>=11.6.3.83,<12.0

1.  Using tools and libraries installed directly on your system.

    Refer to the
    [CPU-only developer Dockerfile](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/dockerfiles/dockerfiles/devel-cpu.Dockerfile)
    and
    [GPU developer Dockerfile](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/dockerfiles/dockerfiles/devel-gpu.Dockerfile)

build:cuda_clang --@local_config_cuda//:cuda_compiler=clang
build:cuda_clang --copt=-Qunused-arguments
# Select supported compute capabilities (supported graphics cards).
# This is the same as the official TensorFlow builds.
# See https://developer.nvidia.com/cuda-gpus#compute
# `compute_XY` enables PTX embedding in addition to SASS. PTX
# is forward compatible beyond the current compute capability major
# release while SASS is only forward compatible inside the current

    <root-XML localName="document" namespaceURI="http://developer.apple.com/namespaces/sl" />
    <sub-class-of type="application/vnd.apple.iwork" />
    <glob pattern="*.pages"/>
  </mime-type>
  <mime-type type="application/vnd.apple.numbers">
    <root-XML localName="document" namespaceURI="http://developer.apple.com/namespaces/ls" />
    <sub-class-of type="application/vnd.apple.iwork" />

        `tf.distribute.experimental.MultiWorkerMirroredStrategy`
    *   Update NVIDIA `NCCL` to `2.5.7-1` for better performance and performance
        tuning. Please see
        [nccl developer guide](https://docs.nvidia.com/deeplearning/sdk/nccl-developer-guide/docs/env.html)
        for more information on this.
    *   Support gradient `allreduce` in `float16`. See this

    ask_cuda_compute_capabilities = (
        'Please specify a list of comma-separated CUDA compute capabilities '
        'you want to build with.\nYou can find the compute capability of your '
        'device at: https://developer.nvidia.com/cuda-gpus. Each capability '
        'can be specified as "x.y" or "compute_xy" to include both virtual and'
        ' binary GPU code, or as "sm_xy" to only include the binary '