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https://github.com/saymrwulf/onnxruntime.git
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### Description * Add a few arguments CUDA_VERSION, CUDNN_VERSION, OS, GIT_COMMIT, GIT_BRANCH and ONNXRUNTIME_VERSION to the Dockerfile.cuda to allow for more flexibility in the build process. * Update README.md to include the new arguments and their usage. * Output labels to image so that it is easy to inspect the image. Available CUDA versions for ubuntu 24.04 can be found [here](https://hub.docker.com/r/nvidia/cuda/tags), and available CUDNN versions can be found [here](https://pypi.org/project/nvidia-cudnn-cu12/#history). Example command line to build docker image: ``` docker build -t onnxruntime-cuda --build-arg CUDA_VERSION=12.6.1 \ --build-arg CUDNN_VERSION=9.5.0.50 \ --build-arg GIT_BRANCH=$(git rev-parse --abbrev-ref HEAD) \ --build-arg GIT_COMMIT=$(git rev-parse HEAD) \ --build-arg ONNXRUNTIME_VERSION=$(cat ../VERSION_NUMBER) \ -f Dockerfile.cuda .. ``` Example labels from `docker inspect onnxruntime-cuda`: ``` "Labels": { "CUDA_VERSION": "12.6.1", "CUDNN_VERSION": "9.5.0.50", "maintainer": "Changming Sun <chasun@microsoft.com>", "onnxruntime_git_branch": "main", "onnxruntime_git_commit": "bc84958dcef5c6017ae58085f55b669efd74f4a5", "onnxruntime_version": "1.20.0", "org.opencontainers.image.ref.name": "ubuntu", "org.opencontainers.image.version": "24.04" } ``` ### Motivation and Context https://github.com/microsoft/onnxruntime/pull/22339 has hard-coded the cuda and cudnn versions. User might want to choose specified cuda and cudnn version during building docker image.
111 lines
4.1 KiB
Text
111 lines
4.1 KiB
Text
# --------------------------------------------------------------
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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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# --------------------------------------------------------------
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# Build onnxruntime-gpu python package with CUDA 12.x & CUDNN 9.x for python 3.12 in Ubuntu 24.04.
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# If memory is less than 64GB, you may change "--parallel" to "--parallel 4" to avoid out-of-memory error.
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ARG CUDA_VERSION=12.6.1
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ARG CUDNN_VERSION=9.5.0.50
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ARG OS=ubuntu24.04
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FROM nvcr.io/nvidia/cuda:${CUDA_VERSION}-devel-${OS}
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ARG CUDA_VERSION
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ARG CUDNN_VERSION
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ARG CMAKE_CUDA_ARCHITECTURES="61;70;75;80;86;90"
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ENV DEBIAN_FRONTEND=noninteractive
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# Add source code to /code
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ADD . /code
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ENV PATH=/usr/local/cuda/bin:${PATH}
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# Install required packages
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RUN apt-get update && apt-get install -y --no-install-recommends \
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ca-certificates \
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g++ \
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gcc \
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make \
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git \
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cmake \
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wget \
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ninja-build \
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python3-pip \
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python3.12-dev \
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python3.12-venv \
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&& rm -rf /var/lib/apt/lists/*
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# Install CUDNN 9.4.0.58 for building ONNX Runtime with CUDA.
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RUN cudnn_tar="cudnn-linux-x86_64-${CUDNN_VERSION}_cuda${CUDA_VERSION%%.*}-archive.tar.xz" \
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&& wget "https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/${cudnn_tar}" \
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&& mkdir -p /code/build/cudnn \
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&& tar -Jxvf ${cudnn_tar} -C /code/build/cudnn --strip=1 \
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&& rm -f ${cudnn_tar}
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# Create a virtual environment and install dependencies, then build ONNX Runtime with CUDA support.
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RUN cd /code \
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&& python3 -m venv /code/env \
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&& . /code/env/bin/activate \
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&& pip install --upgrade psutil setuptools wheel packaging \
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&& pip install -r tools/ci_build/github/linux/docker/inference/x86_64/python/cpu/scripts/requirements.txt \
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&& python /code/tools/ci_build/build.py --build_dir /code/build/Linux \
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--allow_running_as_root --skip_submodule_sync \
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--use_cuda --cuda_home /usr/local/cuda \
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--cudnn_home /code/build/cudnn \
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--build_shared_lib --skip_tests \
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--config Release --build_wheel --update --build --parallel \
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--cmake_generator Ninja \
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--enable_cuda_nhwc_ops \
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--cmake_extra_defines ONNXRUNTIME_VERSION=$(cat ./VERSION_NUMBER) "CMAKE_CUDA_ARCHITECTURES=${CMAKE_CUDA_ARCHITECTURES}" onnxruntime_BUILD_UNIT_TESTS=OFF
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# Start second stage to copy the build artifacts
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FROM nvcr.io/nvidia/cuda:${CUDA_VERSION}-runtime-${OS}
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ARG CUDA_VERSION
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ARG CUDNN_VERSION
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ARG GIT_COMMIT
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ARG GIT_BRANCH
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ARG ONNXRUNTIME_VERSION
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# Make sure the required build arguments are set. See README.md for more information.
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RUN test -n ${GIT_COMMIT:?}
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RUN test -n ${GIT_BRANCH:?}
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RUN test -n ${ONNXRUNTIME_VERSION:?}
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LABEL CUDA_VERSION="${CUDA_VERSION}"
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LABEL CUDNN_VERSION="${CUDNN_VERSION}"
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LABEL maintainer="Changming Sun <chasun@microsoft.com>"
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LABEL onnxruntime_version="${ONNXRUNTIME_VERSION}"
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LABEL onnxruntime_git_branch="${GIT_BRANCH}"
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LABEL onnxruntime_git_commit="${GIT_COMMIT}"
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# Copy built wheel and license
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COPY --from=0 /code/build/Linux/Release/dist /ort
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COPY --from=0 /code/dockerfiles/LICENSE-IMAGE.txt /code/LICENSE-IMAGE.txt
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# Set environment variables
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ENV DEBIAN_FRONTEND=noninteractive
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ENV CUDNN_VERSION=$CUDNN_VERSION
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ENV ONNXRUNTIME_VERSION=$ONNXRUNTIME_VERSION
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# CUDNN from nvidia-cudnn-cu12 python package is located in the site-packages directory of python virtual environment.
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ENV LD_LIBRARY_PATH="/ort/env/lib/python3.12/site-packages/nvidia/cudnn/lib:/usr/local/cuda/lib64"
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# Install runtime dependencies
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RUN apt-get update && apt-get install -y --no-install-recommends \
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libstdc++6 \
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ca-certificates \
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python3-pip \
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python3.12-venv \
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&& python3 -m venv /ort/env \
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&& . /ort/env/bin/activate \
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&& pip install /ort/*.whl \
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&& pip install nvidia-cudnn-cu${CUDA_VERSION%%.*}==${CUDNN_VERSION} \
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&& python -c 'import onnxruntime; print(onnxruntime.get_available_providers())' \
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&& rm -rf /ort/*.whl \
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&& rm -rf /var/lib/apt/lists/*
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# Ensure the virtual environment is always activated when running commands in the container.
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RUN echo ". /ort/env/bin/activate" >> ~/.bashrc
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# Set the default command to start an interactive bash shell
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CMD [ "/bin/bash" ]
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