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bhanutejagkBhanu Teja Goshikonda
bhanutejagk
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Bhanu Teja Goshikonda
authored
Build cu130 base image with Python 3.13.11, CUDA 13.0.2, and EFA 1.47.0 (#5621)
* Update cu130 base image to Python 3.13.11, CUDA 13.0.2, and EFA 1.46.0 - Update Python version from 3.12.10 to 3.13.11 - Update CUDA version from 13.0.0 to 13.0.2 with driver 580.95.05 - Update EFA version from 1.44.0 to 1.46.0 - Update image tag from py312 to py313 - New image tag: 13.0.2-gpu-py313-cu130-ubuntu22.04-ec2 * Enable base image build for cu130 in developer config - Add 'base' to build_frameworks list - Set dlc-pr-base buildspec to base/buildspec-cu130-ubuntu22.yml * Fix pip symlink for Python installations Add symlinks for 'pip' and 'pip3' to point to version-specific pip. This fixes the test_pip_check failure where pip was not found in PATH. The 'make altinstall' command only creates version-specific binaries (e.g., pip3.13) and does not create generic pip/pip3 symlinks. The script was already creating symlinks for python/python3, but was missing the corresponding pip symlinks. * Revert developer config to default state Reset build_frameworks to empty array and dlc-pr-base buildspec to empty string. This reverts the temporary changes made for testing the base image build. * Add CUDA 13.0.2 base image with updated versions New cu1302 base image configuration: - CUDA: 13.0.2 - Python: 3.13.11 - cuDNN: 9.15.1.9 - NCCL: v2.28.9-1 - EFA: 1.46.0 Changes: - Add new Dockerfile at base/x86_64/gpu/cu1302/ubuntu22.04/ - Add new buildspec base/buildspec-cu1302-ubuntu22.yml - Add install_cuda1302_stack_ul22 function in install_cuda.sh - Revert cu130 Dockerfile to upstream (CUDA 13.0.0) * Enable cu1302 base image build in developer config * Revert buildspec-cu130-ubuntu22.yml to upstream * fix: remove pip symlink lines as pip upgrade already creates them * Reverted toml file to its original state * Reverted back install_python.sh file and building image * Reverted back toml file to its original * Updated EFA version to 1.47 * refactor: reorganize cu130 dockerfiles into py312/py313 subdirectories * Building cu13.0.2 base image * Reverted back toml file * Building cu 13.0.2 image * Reverted back toml file --------- Co-authored-by: Bhanu Teja Goshikonda <bhanugk@amazon.com>
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‎base/buildspec-cu130-ubuntu22.yml‎

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os_version: &OS_VERSION ubuntu22.04
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tag: !join [ *VERSION, "-", *DEVICE_TYPE, "-", *TAG_PYTHON_VERSION, "-", *CUDA_VERSION, "-", *OS_VERSION, "-ec2" ]
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latest_release_tag: !join [ *VERSION, "-", *DEVICE_TYPE, "-", *TAG_PYTHON_VERSION, "-", *CUDA_VERSION, "-", *OS_VERSION, "-ec2" ]
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docker_file: !join [ *FRAMEWORK, /, *ARCH_TYPE, /, *DEVICE_TYPE, /, *CUDA_VERSION, /, *OS_VERSION, /Dockerfile ]
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docker_file: !join [ *FRAMEWORK, /, *ARCH_TYPE, /, *DEVICE_TYPE, /, *CUDA_VERSION, /, *OS_VERSION, /, *TAG_PYTHON_VERSION, /Dockerfile ]
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target: final
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build: true
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enable_common_stage_build: false

‎base/buildspec-cu1302-ubuntu22.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 13.0.2
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short_version: &SHORT_VERSION "13.0"
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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_cuda1302_ubuntu22:
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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 cu130
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python_version: &DOCKER_PYTHON_VERSION py3
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tag_python_version: &TAG_PYTHON_VERSION py313
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os_version: &OS_VERSION ubuntu22.04
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tag: !join [ *VERSION, "-", *DEVICE_TYPE, "-", *TAG_PYTHON_VERSION, "-", *CUDA_VERSION, "-", *OS_VERSION, "-ec2" ]
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latest_release_tag: !join [ *VERSION, "-", *DEVICE_TYPE, "-", *TAG_PYTHON_VERSION, "-", *CUDA_VERSION, "-", *OS_VERSION, "-ec2" ]
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docker_file: !join [ *FRAMEWORK, /, *ARCH_TYPE, /, *DEVICE_TYPE, /, *CUDA_VERSION, /, *OS_VERSION, /, *TAG_PYTHON_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/buildspec.yml‎

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buildspec_pointer: buildspec-cu130-ubuntu22.yml
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buildspec_pointer: buildspec-cu1302-ubuntu22.yml

base/x86_64/gpu/cu130/ubuntu22.04/Dockerfile renamed to base/x86_64/gpu/cu130/ubuntu22.04/py312/Dockerfile

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‎base/x86_64/gpu/cu130/ubuntu22.04/py313/Dockerfile‎

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ARG PYTHON="python3"
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ARG PYTHON_VERSION="3.13.11"
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ARG PYTHON_SHORT_VERSION="3.13"
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ARG CUDA_MAJOR="13"
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ARG CUDA_MINOR="0"
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ARG CUDA_PATCH="2"
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ARG EFA_VERSION="1.47.0"
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ARG OS_VERSION="ubuntu22.04"
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FROM nvidia/cuda:${CUDA_MAJOR}.${CUDA_MINOR}.${CUDA_PATCH}-base-${OS_VERSION} AS base-builder
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RUN mv /usr/local/cuda/compat /usr/local \
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&& 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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libbz2-dev \
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liblzma-dev \
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libsqlite3-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 ${PYTHON_VERSION} && rm install_python.sh
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##############################################################################
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FROM base-builder AS cuda-builder
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ARG CUDA_MAJOR
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ARG CUDA_MINOR
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ARG CUDA_PATCH
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ARG OS_VERSION
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COPY install_cuda.sh install_cuda.sh
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RUN bash install_cuda.sh "${CUDA_MAJOR}.${CUDA_MINOR}.${CUDA_PATCH}" "${OS_VERSION}" && rm install_cuda.sh
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##############################################################################
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FROM nvidia/cuda:${CUDA_MAJOR}.${CUDA_MINOR}.${CUDA_PATCH}-base-${OS_VERSION} AS final
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ARG PYTHON
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ARG PYTHON_SHORT_VERSION
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ARG CUDA_MAJOR
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ARG CUDA_MINOR
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ARG EFA_VERSION
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LABEL maintainer="Amazon AI"
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LABEL dlc_major_version="1"
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ENV DEBIAN_FRONTEND=noninteractive \
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LANG=C.UTF-8 \
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LC_ALL=C.UTF-8 \
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DLC_CONTAINER_TYPE=base \
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# Python won't try to write .pyc or .pyo files on the import of source modules
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# Force stdin, stdout and stderr to be totally unbuffered. Good for logging
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PYTHONDONTWRITEBYTECODE=1 \
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PYTHONUNBUFFERED=1 \
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PYTHONIOENCODING=UTF-8 \
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CUDA_HOME="/usr/local/cuda" \
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PATH="/opt/amazon/openmpi/bin:/opt/amazon/efa/bin:/usr/local/cuda/bin:${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 bash_telemetry.sh /usr/local/bin/bash_telemetry.sh
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RUN chmod +x /usr/local/bin/deep_learning_container.py && \
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chmod +x /usr/local/bin/bash_telemetry.sh && \
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echo 'source /usr/local/bin/bash_telemetry.sh' >> /etc/bash.bashrc && \
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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 upgrade -y && \
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apt-get install -y --allow-change-held-packages --no-install-recommends \
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unzip \
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wget && \
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apt-get clean && \
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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 /var/lib/apt/lists/* && \
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rm -rf /root/.cache | true
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CMD ["/bin/bash"]

‎scripts/install_cuda.sh‎

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ldconfig
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}
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function install_cuda1302_stack_ul22 {
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CUDNN_VERSION="9.15.1.9"
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NCCL_VERSION="v2.28.9-1"
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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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rm -rf /usr/local/cuda-*
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rm -rf /usr/local/cuda
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# install CUDA 13.0.2
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wget -q https://developer.download.nvidia.com/compute/cuda/13.0.2/local_installers/cuda_13.0.2_580.95.05_linux.run
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chmod +x cuda_13.0.2_580.95.05_linux.run
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./cuda_13.0.2_580.95.05_linux.run --toolkit --silent
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rm -f cuda_13.0.2_580.95.05_linux.run
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ln -s /usr/local/cuda-13.0 /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-${CUDNN_VERSION}_cuda13-archive.tar.xz -O cudnn-linux-x86_64-${CUDNN_VERSION}_cuda13-archive.tar.xz
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tar xf cudnn-linux-x86_64-${CUDNN_VERSION}_cuda13-archive.tar.xz
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cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda13-archive/include/* /usr/local/cuda/include/
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cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda13-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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*) echo "bad OS version $2"; exit 1 ;;
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esac
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;;
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13.0.2)
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case "$2" in
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"ubuntu22.04") install_cuda1302_stack_ul22 ;;
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*) echo "bad OS version $2"; exit 1 ;;
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esac
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;;
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*) echo "bad CUDA version $1"; exit 1 ;;
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esac
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shift 2 # Skip both arguments at once

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