# syntax=docker/dockerfile:1 # NOTE: Building this image require's docker version >= 23.0. # # For reference: # - https://docs.docker.com/build/dockerfile/frontend/#stable-channel ARG BASE_IMAGE=ubuntu:22.04 ARG PYTHON_VERSION=3.11 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=3.11 # Automatically set by buildx ARG TARGETPLATFORM # translating Docker's TARGETPLATFORM into miniconda arches RUN case ${TARGETPLATFORM} in \ "linux/arm64") MINICONDA_ARCH=aarch64 ;; \ *) MINICONDA_ARCH=x86_64 ;; \ esac && \ curl -fsSL -v -o ~/miniconda.sh -O "https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Linux-${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 ${CMAKE_VARS} && \ TORCH_CUDA_ARCH_LIST="7.0 7.2 7.5 8.0 8.6 8.7 8.9 9.0 9.0a" TORCH_NVCC_FLAGS="-Xfatbin -compress-all" \ CMAKE_PREFIX_PATH="$(dirname $(which conda))/../" \ python setup.py install FROM conda as conda-installs ARG PYTHON_VERSION=3.11 ARG CUDA_PATH=cu121 ARG CUDA_CHANNEL=nvidia ARG INSTALL_CHANNEL=whl/nightly # Automatically set by buildx RUN /opt/conda/bin/conda update -y -n base -c defaults conda RUN /opt/conda/bin/conda install -y python=${PYTHON_VERSION} ARG TARGETPLATFORM # INSTALL_CHANNEL whl - release, whl/nightly - nightly, whle/test - test channels RUN case ${TARGETPLATFORM} in \ "linux/arm64") pip install --extra-index-url https://download.pytorch.org/whl/cpu/ torch torchvision torchaudio ;; \ *) pip install --index-url https://download.pytorch.org/${INSTALL_CHANNEL}/${CUDA_PATH#.}/ torch torchvision torchaudio ;; \ esac && \ /opt/conda/bin/conda clean -ya RUN /opt/conda/bin/pip install torchelastic RUN IS_CUDA=$(python -c 'import torch ; print(torch.cuda._is_compiled())'); \ echo "Is torch compiled with cuda: ${IS_CUDA}"; \ if test "${IS_CUDA}" != "True" -a ! -z "${CUDA_VERSION}"; then \ exit 1; \ fi 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 PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:$PATH 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