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Dockerfile
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# syntax = docker/dockerfile:experimental
#
# NOTE: To build this you will need a docker version > 18.06 with
# experimental enabled and DOCKER_BUILDKIT=1
#
# If you do not use buildkit you are not going to have a good time
#
# For reference:
# https://docs.docker.com/develop/develop-images/build_enhancements/
ARG BASE_IMAGE=ubuntu:20.04
ARG PYTHON_VERSION=3.8
FROM ${BASE_IMAGE} as dev-base
RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
build-essential \
ca-certificates \
ccache \
cmake \
curl \
git \
libjpeg-dev \
libpng-dev && \
rm -rf /var/lib/apt/lists/*
RUN /usr/sbin/update-ccache-symlinks
RUN mkdir /opt/ccache && ccache --set-config=cache_dir=/opt/ccache
ENV PATH /opt/conda/bin:$PATH
FROM dev-base as conda
ARG PYTHON_VERSION=3.8
# Automatically set by buildx
ARG TARGETPLATFORM
# translating Docker's TARGETPLATFORM into miniconda arches
RUN case ${TARGETPLATFORM} in \
"linux/arm64") MINICONDA_ARCH=aarch64 ;; \
*) MINICONDA_ARCH=x86_64 ;; \
esac && \
curl -fsSL -v -o ~/miniconda.sh -O "https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-${MINICONDA_ARCH}.sh"
COPY requirements.txt .
# Manually invoke bash on miniconda script per https://github.com/conda/conda/issues/10431
RUN chmod +x ~/miniconda.sh && \
bash ~/miniconda.sh -b -p /opt/conda && \
rm ~/miniconda.sh && \
/opt/conda/bin/conda install -y python=${PYTHON_VERSION} cmake conda-build pyyaml numpy ipython && \
/opt/conda/bin/python -mpip install -r requirements.txt && \
/opt/conda/bin/conda clean -ya
FROM dev-base as submodule-update
WORKDIR /opt/pytorch
COPY . .
RUN git submodule update --init --recursive
FROM conda as build
ARG CMAKE_VARS
WORKDIR /opt/pytorch
COPY --from=conda /opt/conda /opt/conda
COPY --from=submodule-update /opt/pytorch /opt/pytorch
RUN make triton
RUN --mount=type=cache,target=/opt/ccache \
export eval ${CMAKE_VARS} && \
TORCH_CUDA_ARCH_LIST="3.5 5.2 6.0 6.1 7.0+PTX 8.0" TORCH_NVCC_FLAGS="-Xfatbin -compress-all" \
CMAKE_PREFIX_PATH="$(dirname $(which conda))/../" \
python setup.py install
FROM conda as conda-installs
ARG PYTHON_VERSION=3.8
ARG CUDA_VERSION=12.1
ARG CUDA_CHANNEL=nvidia
ARG INSTALL_CHANNEL=pytorch-nightly
# Automatically set by buildx
# Note conda needs to be pinned to 23.5.2 see: https://github.com/pytorch/pytorch/issues/106470
RUN /opt/conda/bin/conda install -c "${INSTALL_CHANNEL}" -y python=${PYTHON_VERSION} conda=23.5.2
ARG TARGETPLATFORM
# On arm64 we can only install wheel packages.
RUN case ${TARGETPLATFORM} in \
"linux/arm64") pip install --extra-index-url https://download.pytorch.org/whl/cpu/ torch torchvision torchaudio ;; \
*) /opt/conda/bin/conda install -c "${INSTALL_CHANNEL}" -c "${CUDA_CHANNEL}" -y "python=${PYTHON_VERSION}" pytorch torchvision torchaudio "pytorch-cuda=$(echo $CUDA_VERSION | cut -d'.' -f 1-2)" ;; \
esac && \
/opt/conda/bin/conda clean -ya
RUN /opt/conda/bin/pip install torchelastic
FROM ${BASE_IMAGE} as official
ARG PYTORCH_VERSION
ARG TRITON_VERSION
ARG TARGETPLATFORM
ARG CUDA_VERSION
LABEL com.nvidia.volumes.needed="nvidia_driver"
RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
ca-certificates \
libjpeg-dev \
libpng-dev \
&& rm -rf /var/lib/apt/lists/*
COPY --from=conda-installs /opt/conda /opt/conda
RUN if test -n "${TRITON_VERSION}" -a "${TARGETPLATFORM}" != "linux/arm64"; then \
DEBIAN_FRONTEND=noninteractive apt install -y --no-install-recommends gcc; \
rm -rf /var/lib/apt/lists/*; \
fi
ENV PATH /opt/conda/bin:$PATH
ENV NVIDIA_VISIBLE_DEVICES all
ENV NVIDIA_DRIVER_CAPABILITIES compute,utility
ENV LD_LIBRARY_PATH /usr/local/nvidia/lib:/usr/local/nvidia/lib64
ENV PYTORCH_VERSION ${PYTORCH_VERSION}
WORKDIR /workspace
FROM official as dev
# Should override the already installed version from the official-image stage
COPY --from=build /opt/conda /opt/conda