mirror of
https://github.com/pytorch/pytorch.git
synced 2025-10-20 21:14:14 +08:00
474fe7d976
Summary: We no longer build binaries for CUDA 11.0 so let's ensure that we have build for CUDA 11.1 by default instead Signed-off-by: Eli Uriegas <eliuriegas@fb.com> Pull Request resolved: https://github.com/pytorch/pytorch/pull/53299 Reviewed By: anjali411 Differential Revision: D26857194 Pulled By: seemethere fbshipit-source-id: 6094913922c0da832b96e5e49a67369d69d0b8ad
82 lines
2.9 KiB
Docker
82 lines
2.9 KiB
Docker
# syntax = docker/dockerfile:experimental
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#
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# NOTE: To build this you will need a docker version > 18.06 with
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# experimental enabled and DOCKER_BUILDKIT=1
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#
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# If you do not use buildkit you are not going to have a good time
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#
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# For reference:
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# https://docs.docker.com/develop/develop-images/build_enhancements/
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ARG BASE_IMAGE=ubuntu:18.04
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ARG PYTHON_VERSION=3.8
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FROM ${BASE_IMAGE} as dev-base
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RUN --mount=type=cache,id=apt-dev,target=/var/cache/apt \
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apt-get update && apt-get install -y --no-install-recommends \
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build-essential \
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ca-certificates \
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ccache \
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cmake \
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curl \
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git \
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libjpeg-dev \
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libpng-dev && \
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rm -rf /var/lib/apt/lists/*
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RUN /usr/sbin/update-ccache-symlinks
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RUN mkdir /opt/ccache && ccache --set-config=cache_dir=/opt/ccache
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ENV PATH /opt/conda/bin:$PATH
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FROM dev-base as conda
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ARG PYTHON_VERSION=3.8
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RUN curl -fsSL -v -o ~/miniconda.sh -O https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh && \
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chmod +x ~/miniconda.sh && \
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~/miniconda.sh -b -p /opt/conda && \
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rm ~/miniconda.sh && \
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/opt/conda/bin/conda install -y python=${PYTHON_VERSION} conda-build pyyaml numpy ipython&& \
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/opt/conda/bin/conda clean -ya
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FROM dev-base as submodule-update
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WORKDIR /opt/pytorch
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COPY . .
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RUN git submodule update --init --recursive
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FROM conda as build
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WORKDIR /opt/pytorch
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COPY --from=conda /opt/conda /opt/conda
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COPY --from=submodule-update /opt/pytorch /opt/pytorch
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RUN --mount=type=cache,target=/opt/ccache \
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TORCH_CUDA_ARCH_LIST="3.5 5.2 6.0 6.1 7.0+PTX 8.0" TORCH_NVCC_FLAGS="-Xfatbin -compress-all" \
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CMAKE_PREFIX_PATH="$(dirname $(which conda))/../" \
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python setup.py install
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FROM conda as conda-installs
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ARG PYTHON_VERSION=3.8
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ARG CUDA_VERSION=11.1
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ARG CUDA_CHANNEL=nvidia
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ARG INSTALL_CHANNEL=pytorch-nightly
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ENV CONDA_OVERRIDE_CUDA=${CUDA_VERSION}
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RUN /opt/conda/bin/conda install -c "${INSTALL_CHANNEL}" -c "${CUDA_CHANNEL}" -y python=${PYTHON_VERSION} pytorch torchvision torchtext "cudatoolkit=${CUDA_VERSION}" && \
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/opt/conda/bin/conda clean -ya
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RUN /opt/conda/bin/pip install torchelastic
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FROM ${BASE_IMAGE} as official
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ARG PYTORCH_VERSION
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LABEL com.nvidia.volumes.needed="nvidia_driver"
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RUN --mount=type=cache,id=apt-final,target=/var/cache/apt \
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apt-get update && apt-get install -y --no-install-recommends \
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ca-certificates \
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libjpeg-dev \
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libpng-dev && \
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rm -rf /var/lib/apt/lists/*
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COPY --from=conda-installs /opt/conda /opt/conda
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ENV PATH /opt/conda/bin:$PATH
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ENV NVIDIA_VISIBLE_DEVICES all
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ENV NVIDIA_DRIVER_CAPABILITIES compute,utility
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ENV LD_LIBRARY_PATH /usr/local/nvidia/lib:/usr/local/nvidia/lib64
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ENV PYTORCH_VERSION ${PYTORCH_VERSION}
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WORKDIR /workspace
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FROM official as dev
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# Should override the already installed version from the official-image stage
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COPY --from=build /opt/conda /opt/conda
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