mirror of
https://github.com/andreinechaev/nvcc4jupyter.git
synced 2026-06-15 19:50:50 +05:30
Cosmin Ștefan Ciocan
34 lines
1.1 KiB
Docker
34 lines
1.1 KiB
Docker
FROM ubuntu:22.04
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ARG VENV_PATH=/opt/dev-venv
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ENV VENV_ACTIVATE=${VENV_PATH}/bin/activate
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ENV DEBIAN_FRONTEND="noninteractive"
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# install the latest CUDA toolkit (https://developer.nvidia.com/cuda-downloads)
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RUN apt update
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RUN apt install -y wget
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RUN wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
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RUN dpkg -i cuda-keyring_1.1-1_all.deb
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RUN apt update
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RUN apt -y install cuda-toolkit-12-3
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RUN echo "PATH=\"\$PATH:/usr/local/cuda/bin\"" >> ~/.bashrc
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# install OpenCV to test compilation with external libraries
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RUN apt install -y libopencv-dev pkg-config
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# make & language-pack-en are for documentation
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RUN apt install -y \
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gcc \
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git \
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language-pack-en \
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make \
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python3.10-venv \
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vim
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# we create the virtualenv here so that the devcontainer.json setting
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# python.defaultInterpreterPath can be used to find it; if we do it in the
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# post_create.sh script, the virtualenv will not be loaded and features like
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# pylance, black, isort, etc. will not work
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RUN python3.10 -m venv ${VENV_PATH}
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RUN echo "source ${VENV_ACTIVATE}" >> ~/.bashrc
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