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Base DLC (#4822)
base dlc code changes
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‎base/x86_64/gpu/buildspec.yml‎

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account_id: &ACCOUNT_ID <set-$ACCOUNT_ID-in-environment>
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prod_account_id: &PROD_ACCOUNT_ID 763104351884
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region: &REGION <set-$REGION-in-environment>
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framework: &FRAMEWORK base
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version: &VERSION 12.8.1
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short_version: &SHORT_VERSION "12.8"
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arch_type: &ARCH_TYPE x86_64
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autopatch_build: "False"
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repository_info:
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base_repository: &BASE_REPOSITORY
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image_type: &IMAGE_TYPE gpu
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root: .
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repository_name: &REPOSITORY_NAME !join [ pr, "-", *FRAMEWORK ]
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repository: &REPOSITORY !join [ *ACCOUNT_ID, .dkr.ecr., *REGION, .amazonaws.com/, *REPOSITORY_NAME ]
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release_repository_name: &RELEASE_REPOSITORY_NAME !join [ *FRAMEWORK ]
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release_repository: &RELEASE_REPOSITORY !join [ *PROD_ACCOUNT_ID, .dkr.ecr., *REGION, .amazonaws.com/, *RELEASE_REPOSITORY_NAME ]
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context:
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base_context: &BASE_CONTEXT
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deep_learning_container:
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source: src/deep_learning_container.py
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target: deep_learning_container.py
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install_python:
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source: scripts/install_python.sh
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target: install_python.sh
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install_cuda:
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source: scripts/install_cuda.sh
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target: install_cuda.sh
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install_efa:
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source: scripts/install_efa.sh
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target: install_efa.sh
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images:
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base_x86_64_gpu_cuda128:
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<<: *BASE_REPOSITORY
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context:
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<<: *BASE_CONTEXT
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image_size_baseline: 11000
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device_type: &DEVICE_TYPE gpu
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cuda_version: &CUDA_VERSION cu128
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python_version: &DOCKER_PYTHON_VERSION py3
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tag_python_version: &TAG_PYTHON_VERSION py312
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os_version: &OS_VERSION ubuntu24.04
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tag: !join [ *DEVICE_TYPE, "-", *CUDA_VERSION, "-", *TAG_PYTHON_VERSION, "-", *OS_VERSION, "-", *ARCH_TYPE, "-ec2" ]
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latest_release_tag: !join [ *DEVICE_TYPE, "-", *CUDA_VERSION, "-", *TAG_PYTHON_VERSION, "-", *OS_VERSION, "-", *ARCH_TYPE, "-ec2" ]
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docker_file: !join [ *FRAMEWORK, /, *ARCH_TYPE, /, *DEVICE_TYPE, /, *CUDA_VERSION, /Dockerfile ]
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target: final
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build: true
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enable_common_stage_build: false
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test_configs:
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test_platforms:
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- sanity
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- security

‎base/x86_64/gpu/cu128/Dockerfile‎

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ARG PYTHON="python3"
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ARG PYTHON_VERSION="3.12.10"
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ARG PYTHON_SHORT_VERSION="3.12"
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ARG CUDA_MAJOR="12"
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ARG CUDA_MINOR="8"
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ARG EFA_VERSION="1.40.0"
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FROM nvidia/cuda:12.8.1-base-ubuntu24.04 AS base-builder
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RUN apt-get update \
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&& apt-get -y upgrade --only-upgrade systemd \
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&& apt-get install -y --allow-change-held-packages --no-install-recommends \
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automake \
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build-essential \
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ca-certificates \
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cmake \
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curl \
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emacs \
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git \
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jq \
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libcurl4-openssl-dev \
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libglib2.0-0 \
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libegl1 \
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libgl1 \
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libsm6 \
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libssl-dev \
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libxext6 \
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libxrender-dev \
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zlib1g-dev \
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unzip \
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vim \
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wget \
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libhwloc-dev \
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libgomp1 \
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libibverbs-dev \
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libnuma1 \
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libnuma-dev \
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libtool \
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openssl \
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python3-dev \
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autoconf \
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pkg-config \
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check \
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libsubunit0 \
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libsubunit-dev \
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libffi-dev \
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&& apt-get autoremove -y \
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&& apt-get clean \
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&& rm -rf /var/lib/apt/lists/*
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##############################################################################
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FROM base-builder AS python-builder
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ARG PYTHON_VERSION
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COPY install_python.sh install_python.sh
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RUN bash install_python.sh ${PYTHON_VERSION} && rm install_python.sh
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##############################################################################
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FROM base-builder AS cuda-builder
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ARG CUDA_MAJOR
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ARG CUDA_MINOR
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COPY install_cuda.sh install_cuda.sh
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RUN bash install_cuda.sh "${CUDA_MAJOR}.${CUDA_MINOR}" && rm install_cuda.sh
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##############################################################################
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FROM nvidia/cuda:12.8.1-base-ubuntu24.04 AS final
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ARG PYTHON
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ARG PYTHON_SHORT_VERSION
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ARG CUDA_MAJOR
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ARG CUDA_MINOR
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ARG EFA_VERSION
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LABEL maintainer="Amazon AI"
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LABEL dlc_major_version="1"
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ENV DEBIAN_FRONTEND=noninteractive \
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LANG=C.UTF-8 \
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LC_ALL=C.UTF-8 \
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DLC_CONTAINER_TYPE=base \
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# Python won’t try to write .pyc or .pyo files on the import of source modules
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# Force stdin, stdout and stderr to be totally unbuffered. Good for logging
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PYTHONDONTWRITEBYTECODE=1 \
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PYTHONUNBUFFERED=1 \
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PYTHONIOENCODING=UTF-8 \
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CUDA_HOME="/usr/local/cuda" \
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PATH="/opt/amazon/openmpi/bin:/opt/amazon/efa/bin:/usr/local/cuda/bin:${PATH}" \
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LD_LIBRARY_PATH="/usr/local/lib:/usr/local/cuda/lib64:/opt/amazon/ofi-nccl/lib:/opt/amazon/efa/lib:/opt/amazon/openmpi/lib:${LD_LIBRARY_PATH}"
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WORKDIR /
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# + python and pip packages (awscli, boto3, requests)
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COPY --from=python-builder /usr/local/lib/python${PYTHON_SHORT_VERSION} /usr/local/lib/python${PYTHON_SHORT_VERSION}
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COPY --from=python-builder /usr/local/include/python${PYTHON_SHORT_VERSION} /usr/local/include/python${PYTHON_SHORT_VERSION}
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COPY --from=python-builder /usr/local/bin /usr/local/bin
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# + cuda-toolkit, cudnn, nccl
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COPY --from=cuda-builder /usr/local/cuda-${CUDA_MAJOR}.${CUDA_MINOR} /usr/local/cuda-${CUDA_MAJOR}.${CUDA_MINOR}
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COPY install_efa.sh install_efa.sh
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COPY deep_learning_container.py /usr/local/bin/deep_learning_container.py
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COPY sitecustomize.py /usr/local/lib/python${PYTHON_SHORT_VERSION}/sitecustomize.py
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RUN chmod +x /usr/local/bin/deep_learning_container.py && \
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# Install EFA
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bash install_efa.sh ${EFA_VERSION} && \
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rm install_efa.sh && \
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# OSS compliance
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apt-get update && \
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apt-get install -y --allow-change-held-packages --no-install-recommends unzip && \
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HOME_DIR=/root && \
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curl -o ${HOME_DIR}/oss_compliance.zip https://aws-dlinfra-utilities.s3.amazonaws.com/oss_compliance.zip && \
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unzip ${HOME_DIR}/oss_compliance.zip -d ${HOME_DIR}/ && \
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cp ${HOME_DIR}/oss_compliance/test/testOSSCompliance /usr/local/bin/testOSSCompliance && \
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chmod +x /usr/local/bin/testOSSCompliance && \
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chmod +x ${HOME_DIR}/oss_compliance/generate_oss_compliance.sh && \
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${HOME_DIR}/oss_compliance/generate_oss_compliance.sh ${HOME_DIR} ${PYTHON} && \
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rm -rf ${HOME_DIR}/oss_compliance* && \
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rm -rf /tmp/tmp* && \
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rm -rf /root/.cache | true
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CMD ["/bin/bash"]

‎dlc_developer_config.toml‎

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[build]
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# Add in frameworks you would like to build. By default, builds are disabled unless you specify building an image.
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# available frameworks - ["autogluon", "huggingface_tensorflow", "huggingface_pytorch", "huggingface_tensorflow_trcomp", "huggingface_pytorch_trcomp", "pytorch_trcomp", "tensorflow", "pytorch", "stabilityai_pytorch"]
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# available frameworks - ["base", "autogluon", "huggingface_tensorflow", "huggingface_pytorch", "huggingface_tensorflow_trcomp", "huggingface_pytorch_trcomp", "pytorch_trcomp", "tensorflow", "pytorch", "stabilityai_pytorch"]
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build_frameworks = []
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‎scripts/install_cuda.sh‎

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#!/bin/bash
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set -ex
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# https://raw.githubusercontent.com/pytorch/pytorch/842d51500be144d53f4d046d31169e8f46c063f6/.ci/docker/common/install_cuda.sh
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function prune_cuda {
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# Remove non-essential CUDA components to reduce image size:
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# - Documentation and manual pages
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# - Sample code, demos, and example projects
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# - IDE integration (Nsight Eclipse Edition)
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# - Debugging tools (compute-sanitizer, debugger)
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# - Profiling tools (Nsight Compute, Nsight Systems)
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# - Legacy tools (Visual Profiler)
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# This keeps only the essential runtime libraries, headers and development tools
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rm -rf /usr/local/cuda/compute-sanitizer/docs \
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/usr/local/cuda/nsight-compute-****.*.*/docs \
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/usr/local/cuda/nsight-systems-****.*.*/documentation \
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/usr/local/cuda/extras/demo_suite \
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/usr/local/cuda/extras/CUPTI/samples \
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/usr/local/cuda/nsight-compute-****.*.*/extras/samples \
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/usr/local/cuda/libnvvp \
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/usr/local/cuda/nsightee_plugins \
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/usr/local/cuda/compute-sanitizer \
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/usr/local/cuda/extras/Debugger \
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/usr/local/cuda/nsight-compute-****.*.* \
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/usr/local/cuda/nsight-systems-****.*.*
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rm -rf /usr/local/cuda/doc
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rm -rf /usr/local/cuda/samples
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rm -rf /usr/local/cuda/share/doc
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}
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function install_cuda118_stack {
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CUDNN_VERSION=9.1.0.70
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NCCL_VERSION=v2.21.5-1
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CUDA_HOME="/usr/local/cuda"
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# move cuda-compt and remove existing cuda dir from nvidia/cuda:**.*.*-base-*
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mv /usr/local/cuda/compat /usr/local
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rm -rf /usr/local/cuda-*
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rm -rf /usr/local/cuda
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# install cuda
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cd /tmp
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wget -q https://developer.download.nvidia.com/compute/cuda/11.8.0/local_installers/cuda_11.8.0_520.61.05_linux.run
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chmod +x cuda_11.8.0_520.61.05_linux.run
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./cuda_11.8.0_520.61.05_linux.run --toolkit --silent
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rm -f cuda_11.8.0_520.61.05_linux.run
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ln -s /usr/local/cuda-11.8 /usr/local/cuda
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# bring back cuda-compat
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mv /usr/local/compat /usr/local/cuda/compat
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# install cudnn
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mkdir -p /tmp/cudnn
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cd /tmp/cudnn
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wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive.tar.xz -O cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive.tar.xz
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tar xf cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive.tar.xz
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cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive/include/* /usr/local/cuda/include/
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cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive/lib/* /usr/local/cuda/lib64/
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# install nccl
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mkdir -p /tmp/nccl
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cd /tmp/nccl
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git clone -b $NCCL_VERSION --depth 1 https://github.com/NVIDIA/nccl.git
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cd nccl
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make -j src.build
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cp -a build/include/* /usr/local/cuda/include/
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cp -a build/lib/* /usr/local/cuda/lib64/
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prune_cuda
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ldconfig
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}
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function install_cuda124_stack {
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CUDNN_VERSION="9.1.0.70"
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NCCL_VERSION="v2.23.4-1"
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CUDA_HOME="/usr/local/cuda"
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# move cuda-compt and remove existing cuda dir from nvidia/cuda:**.*.*-base-*
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mv /usr/local/cuda/compat /usr/local
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rm -rf /usr/local/cuda-*
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rm -rf /usr/local/cuda
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# install cuda
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cd /tmp
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wget -q https://developer.download.nvidia.com/compute/cuda/12.4.1/local_installers/cuda_12.4.1_550.54.15_linux.run
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chmod +x cuda_12.4.1_550.54.15_linux.run
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./cuda_12.4.1_550.54.15_linux.run --toolkit --silent
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rm -f cuda_12.4.1_550.54.15_linux.run
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ln -s /usr/local/cuda-12.4 /usr/local/cuda
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# bring back cuda-compat
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mv /usr/local/compat /usr/local/cuda/compat
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# install cudnn
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mkdir -p /tmp/cudnn
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cd /tmp/cudnn
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wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz -O cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
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tar xf cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
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cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/include/* /usr/local/cuda/include/
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cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/lib/* /usr/local/cuda/lib64/
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# install nccl
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mkdir -p /tmp/nccl
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cd /tmp/nccl
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git clone -b $NCCL_VERSION --depth 1 https://github.com/NVIDIA/nccl.git
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cd nccl
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make -j src.build
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cp -a build/include/* /usr/local/cuda/include/
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cp -a build/lib/* /usr/local/cuda/lib64/
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prune_cuda
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ldconfig
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}
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function install_cuda126_stack {
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CUDNN_VERSION="9.7.0.66"
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NCCL_VERSION="v2.23.4-1"
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CUDA_HOME="/usr/local/cuda"
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# move cuda-compt and remove existing cuda dir from nvidia/cuda:**.*.*-base-*
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mv /usr/local/cuda/compat /usr/local
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rm -rf /usr/local/cuda-*
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rm -rf /usr/local/cuda
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# install CUDA
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wget -q https://developer.download.nvidia.com/compute/cuda/12.6.3/local_installers/cuda_12.6.3_560.35.05_linux.run
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chmod +x cuda_12.6.3_560.35.05_linux.run
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./cuda_12.6.3_560.35.05_linux.run --toolkit --silent
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rm -f cuda_12.6.3_560.35.05_linux.run
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ln -s /usr/local/cuda-12.6 /usr/local/cuda
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# bring back cuda-compat
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mv /usr/local/compat /usr/local/cuda/compat
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# install cudnn
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mkdir -p /tmp/cudnn
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cd /tmp/cudnn
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wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz -O cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
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tar xf cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
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cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/include/* /usr/local/cuda/include/
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cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/lib/* /usr/local/cuda/lib64/
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# install nccl
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mkdir -p /tmp/nccl
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cd /tmp/nccl
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git clone -b $NCCL_VERSION --depth 1 https://github.com/NVIDIA/nccl.git
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cd nccl
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make -j src.build
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cp -a build/include/* /usr/local/cuda/include/
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cp -a build/lib/* /usr/local/cuda/lib64/
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prune_cuda
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ldconfig
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}
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function install_cuda128_stack {
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CUDNN_VERSION="9.8.0.87"
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NCCL_VERSION="v2.26.2-1"
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CUDA_HOME="/usr/local/cuda"
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# move cuda-compt and remove existing cuda dir from nvidia/cuda:**.*.*-base-*
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mv /usr/local/cuda/compat /usr/local
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rm -rf /usr/local/cuda-*
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rm -rf /usr/local/cuda
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# install CUDA
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wget -q https://developer.download.nvidia.com/compute/cuda/12.8.1/local_installers/cuda_12.8.1_570.124.06_linux.run
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chmod +x cuda_12.8.1_570.124.06_linux.run
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./cuda_12.8.1_570.124.06_linux.run --toolkit --silent
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rm -f cuda_12.8.1_570.124.06_linux.run
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ln -s /usr/local/cuda-12.8 /usr/local/cuda
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# bring back cuda-compat
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mv /usr/local/compat /usr/local/cuda/compat
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# install cudnn
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mkdir -p /tmp/cudnn
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cd /tmp/cudnn
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wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz -O cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
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tar xf cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
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cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/include/* /usr/local/cuda/include/
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cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/lib/* /usr/local/cuda/lib64/
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# install nccl
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mkdir -p /tmp/nccl
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cd /tmp/nccl
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git clone -b $NCCL_VERSION --depth 1 https://github.com/NVIDIA/nccl.git
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cd nccl
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make -j src.build
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cp -a build/include/* /usr/local/cuda/include/
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cp -a build/lib/* /usr/local/cuda/lib64/
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prune_cuda
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ldconfig
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}
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# idiomatic parameter and option handling in sh
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while test $# -gt 0
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do
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case "$1" in
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11.8) install_cuda118_stack;
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;;
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12.4) install_cuda124_stack;
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;;
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12.6) install_cuda126_stack;
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;;
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12.8) install_cuda128_stack;
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;;
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*) echo "bad argument $1"; exit 1
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;;
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esac
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shift
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done

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