331 lines
15 KiB
Docker
331 lines
15 KiB
Docker
# syntax=docker/dockerfile:1
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# NOTE: Building this image require's docker version >= 23.0.
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#
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# For reference:
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# - https://docs.docker.com/build/dockerfile/frontend/#stable-channel
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ARG CUDA_VERSION=12.1.0
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FROM nvidia/cuda:${CUDA_VERSION}-cudnn8-devel-ubuntu22.04
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ARG HTTP_PROXY
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ARG HTTPS_PROXY
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ENV http_proxy=${HTTP_PROXY}
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ENV https_proxy=${HTTPS_PROXY}
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ARG DEBIAN_FRONTEND="noninteractive"
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ENV DEBIAN_FRONTEND=${DEBIAN_FRONTEND}
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ENV MAMBA_ROOT_PREFIX=~/micromamba
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ARG ROOT_PASSWD="root"
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ENV ROOT_PASSWD=${ROOT_PASSWD}
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WORKDIR /root
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SHELL ["/bin/bash", "-c"]
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COPY id_rsa.pub /root/.ssh/id_rsa.pub
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# base tools
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RUN apt-get update && \
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apt-get install -y rdma-core ibverbs-utils perftest libibverbs-dev infiniband-diags && \
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apt-get install -y wget curl htop jq vim bash libaio-dev build-essential openssh-server python3 python3-pip bzip2 && \
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apt-get install -y --no-install-recommends software-properties-common build-essential autotools-dev nfs-common pdsh cmake g++ gcc curl wget vim tmux emacs less unzip htop iftop iotop ca-certificates openssh-client openssh-server rsync iputils-ping net-tools sudo llvm-dev re2c && \
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add-apt-repository ppa:git-core/ppa -y && \
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apt-get install -y git libnuma-dev wget && \
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wget -O - https://apt.kitware.com/keys/kitware-archive-latest.asc | sudo apt-key add - && \
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sudo apt-add-repository "deb https://apt.kitware.com/ubuntu/ $(lsb_release -cs) main" && \
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sudo apt-get update && \
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sudo apt-get install -y cmake && \
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sed -i 's/#PermitRootLogin prohibit-password/PermitRootLogin yes/' /etc/ssh/sshd_config && \
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sed -i 's/#PasswordAuthentication yes/PasswordAuthentication yes/' /etc/ssh/sshd_config && \
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sed -i 's/PubkeyAuthentication no/PubkeyAuthentication yes/' /etc/ssh/sshd_config && \
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sed -i 's/^#Port 22/Port 22/' /etc/ssh/sshd_config && \
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mkdir /var/run/sshd && \
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echo "root:${ROOT_PASSWD}" | chpasswd && \
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mkdir -p ~/.pip && \
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wget -qO- https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/miniconda.sh && \
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bash /tmp/miniconda.sh -b -p /opt/conda && \
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rm /tmp/miniconda.sh && \
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conda init bash && \
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ln -s /opt/conda/etc/profile.d/conda.sh /etc/profile.d/conda.sh && \
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echo ". /opt/conda/etc/profile.d/conda.sh" >> ~/.bashrc && \
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cat <<EOF > ~/.condarc
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channels:
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- conda-forge
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- bioconda
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- pytorch
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- pytorch-nightly
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- nvidia
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- defaults
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show_channel_urls: true
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EOF
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# reference: https://github.com/huggingface/transformers/blob/main/docker/transformers-pytorch-deepspeed-latest-gpu/Dockerfile
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# PyTorch
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ARG CONDA_ENV_NAME="deepspeed"
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ENV CONDA_ENV_NAME=${CONDA_ENV_NAME}
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ARG PYTHON_VERSION=3.10
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ENV PYTHON_VERSION=${PYTHON_VERSION}
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ENV PATH=/opt/conda/envs/${CONDA_ENV_NAME}/bin:/usr/bin:/opt/conda/bin:$PATH
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ENV DEEPSPEED_PYTHON="/opt/conda/envs/${CONDA_ENV_NAME}/bin/python3"
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ENV REF='main'
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ENV STAGE_DIR=/tmp
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ENV OPENMPI_BASEVERSION=4.1
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ENV OPENMPI_VERSION=${OPENMPI_BASEVERSION}.6
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ARG CUDA='cu121'
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ENV CUDA=${CUDA}
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ARG PYTORCH_VERSION=2.3.1
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ENV PYTORCH_VERSION=${PYTORCH_VERSION}
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ARG TORCHVISION_VERSION=0.18.1
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ENV TORCHVISION_VERSION=${TORCHVISION_VERSION}
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ARG TORCHAUDIO_VERSION=2.3.1
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ENV TORCHAUDIO_VERSION=${TORCHAUDIO_VERSION}
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ARG PYTORCH_CUDA_VERSION=12.1
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ENV PYTORCH_CUDA_VERSION=${PYTORCH_CUDA_VERSION}
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ARG SETUPTOOLS_VERSION=69.5.1
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ENV SETUPTOOLS_VERSION=${SETUPTOOLS_VERSION}
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ARG USE_CUDA=1
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ENV USE_CUDA=${USE_CUDA}
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ARG USE_ROCM=0
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ENV USE_ROCM=${USE_ROCM}
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ARG USE_XPU=0
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ENV USE_XPU=${USE_XPU}
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ARG _GLIBCXX_USE_CXX11_ABI=1
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ENV _GLIBCXX_USE_CXX11_ABI=${_GLIBCXX_USE_CXX11_ABI}
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RUN source /opt/conda/etc/profile.d/conda.sh && \
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conda create -n ${CONDA_ENV_NAME} python=${PYTHON_VERSION} -c conda-forge -y && \
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echo "conda activate ${CONDA_ENV_NAME}" >> ~/.bashrc && \
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which python > ~/python_path.txt && \
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conda activate ${CONDA_ENV_NAME} && \
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git clone https://github.com/ninja-build/ninja.git ${STAGE_DIR}/ninja && \
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cd ${STAGE_DIR}/ninja && \
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git clone https://github.com/google/googletest.git && \
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python ./configure.py --bootstrap && \
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conda run -n ${CONDA_ENV_NAME} bash -c "CXXFLAGS='-pthread' LDFLAGS='-pthread' python ./configure.py --bootstrap --gtest-source-dir=$(pwd)/googletest" && \
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./ninja all && \
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./ninja_test && \
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python3 -m pip install --no-cache-dir --upgrade pip && \
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python3 -m pip install open_clip_torch nvidia-ml-py3 opencv-contrib-python && \
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conda clean -afy && \
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git clone https://github.com/huggingface/transformers && cd transformers && git checkout $REF && cd .. && \
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python -m pip install setuptools==${SETUPTOOLS_VERSION} && \
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python3 -m pip install --no-cache-dir ./transformers[deepspeed-testing] && \
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python3 -m pip uninstall -y torch torchvision torchaudio && \
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python3 -m pip install torch==${PYTORCH_VERSION}+${CUDA} torchvision==${TORCHVISION_VERSION}+${CUDA} torchaudio==${TORCHAUDIO_VERSION} xformers --extra-index-url https://download.pytorch.org/whl/${CUDA} && \
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python3 -m pip install --no-cache-dir git+https://github.com/huggingface/accelerate@main#egg=accelerate && \
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python3 -m pip uninstall -y transformer-engine && \
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python3 -m pip uninstall -y torch-tensorrt && \
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python3 -m pip uninstall -y apex
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# install apex
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RUN source /opt/conda/etc/profile.d/conda.sh && \
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conda activate ${CONDA_ENV_NAME} && \
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git clone https://github.com/NVIDIA/apex ${STAGE_DIR}/apex && \
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cd apex && \
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MAX_JOBS=1 python3 -m pip install -v --disable-pip-version-check --no-cache-dir --no-build-isolation --config-settings "--build-option=--cpp_ext" --config-settings "--build-option=--cuda_ext" ./ && \
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python -c "import apex.amp; print('Apex is installed and the amp module is available.')" && \
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cd .. && \
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rm -rf ${STAGE_DIR}/apex
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ENV MLNX_OFED_VERSION=5.8-4.1.5.0
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RUN source /opt/conda/etc/profile.d/conda.sh && \
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conda activate ${CONDA_ENV_NAME} && \
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mkdir -p ${STAGE_DIR} && \
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wget -q -O - http://www.mellanox.com/downloads/ofed/MLNX_OFED-${MLNX_OFED_VERSION}/MLNX_OFED_LINUX-${MLNX_OFED_VERSION}-ubuntu22.04-x86_64.tgz | tar xzf - && \
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cd MLNX_OFED_LINUX-${MLNX_OFED_VERSION}-ubuntu22.04-x86_64 && \
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./mlnxofedinstall --user-space-only --without-fw-update --all -q && \
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cd ${STAGE_DIR} && \
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rm -rf ${STAGE_DIR}/MLNX_OFED_LINUX-${MLNX_OFED_VERSION}-ubuntu22.04-x86_64*
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ENV NV_PEER_MEM_VERSION=1.2
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ENV NV_PEER_MEM_TAG=${NV_PEER_MEM_VERSION}-0
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RUN source /opt/conda/etc/profile.d/conda.sh && \
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conda activate ${CONDA_ENV_NAME} && \
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rm -rf ${STAGE_DIR} && \
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mkdir -p ${STAGE_DIR} && \
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git clone https://github.com/Mellanox/nv_peer_memory.git --branch ${NV_PEER_MEM_TAG} ${STAGE_DIR}/nv_peer_memory && \
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cd ${STAGE_DIR}/nv_peer_memory && \
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./build_module.sh && \
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cd ${STAGE_DIR} && \
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tar xzf ${STAGE_DIR}/nvidia-peer-memory_${NV_PEER_MEM_VERSION}.orig.tar.gz && \
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cd ${STAGE_DIR}/nvidia-peer-memory-${NV_PEER_MEM_VERSION} && \
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apt-get update && \
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apt --fix-broken install -y && \
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apt-get install -y dkms && \
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dpkg-buildpackage -us -uc && \
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dpkg -i ${STAGE_DIR}/nvidia-peer-memory_${NV_PEER_MEM_TAG}_all.deb
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# install mpi
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ENV PATH=/usr/local/mpi/bin:${PATH}
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ENV LD_LIBRARY_PATH=/usr/local/lib:/usr/local/mpi/lib:/usr/local/mpi/lib64:${LD_LIBRARY_PATH}
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RUN source /opt/conda/etc/profile.d/conda.sh && \
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conda activate ${CONDA_ENV_NAME} && \
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rm -rf ${STAGE_DIR} && \
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mkdir -p ${STAGE_DIR} && \
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cd ${STAGE_DIR} && \
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wget -q -O - https://download.open-mpi.org/release/open-mpi/v${OPENMPI_BASEVERSION}/openmpi-${OPENMPI_VERSION}.tar.gz | tar xzf - && \
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cd openmpi-${OPENMPI_VERSION} && \
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./configure --prefix=/usr/local/openmpi-${OPENMPI_VERSION} && \
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make -j"$(nproc)" install && \
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ln -s /usr/local/openmpi-${OPENMPI_VERSION} /usr/local/mpi && \
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test -f /usr/local/mpi/bin/mpic++ && \
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cd ${STAGE_DIR} && \
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rm -r ${STAGE_DIR}/openmpi-${OPENMPI_VERSION} && \
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mv /usr/local/mpi/bin/mpirun /usr/local/mpi/bin/mpirun.real && \
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echo '#!/bin/bash' > /usr/local/mpi/bin/mpirun && \
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echo 'mpirun.real --allow-run-as-root --prefix /usr/local/mpi "$@"' >> /usr/local/mpi/bin/mpirun && \
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chmod a+x /usr/local/mpi/bin/mpirun
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# SSH daemon port inside container cannot conflict with host OS port
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# ENV SSH_PORT=2222
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# RUN source /opt/conda/etc/profile.d/conda.sh && \
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# conda activate ${CONDA_ENV_NAME} && \
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# cat /etc/ssh/sshd_config > ${STAGE_DIR}/sshd_config && \
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# sed "0,/^Port 22/s//Port ${SSH_PORT}/" ${STAGE_DIR}/sshd_config > /etc/ssh/sshd_config
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RUN source /opt/conda/etc/profile.d/conda.sh && \
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conda activate ${CONDA_ENV_NAME} && \
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useradd --create-home --uid 1000 --shell /bin/bash deepspeed && \
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usermod -aG sudo deepspeed && \
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echo "deepspeed ALL=(ALL) NOPASSWD: ALL" >> /etc/sudoers
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# install cutlass https://github.com/NVIDIA/cutlass
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# H100: architecture is Hopper (cutlass need add : cmake .. -DCUTLASS_NVCC_ARCHS="90a" )
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# A100: architecture is Ampere
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# V100: architecture is Volta
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# T4: architecture is Turing
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# ENV CUDACXX=${CUDA_INSTALL_PATH}/bin/nvcc
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# 70：适用于 NVIDIA Volta 架构（如 Tesla V100）。
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# 75：适用于 NVIDIA Turing 架构（如 Tesla T4）。
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# 80：适用于 NVIDIA Ampere 架构（如 A100）。
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# 90a：适用于 NVIDIA Hopper 架构（如 H100）。
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# 89:GeForce RTX 4090
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ARG DCUTLASS_NVCC_ARCHS="80;89;90a"
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ENV DCUTLASS_NVCC_ARCHS=${DCUTLASS_NVCC_ARCHS}
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RUN source /opt/conda/etc/profile.d/conda.sh && \
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conda activate ${CONDA_ENV_NAME} && \
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git clone https://github.com/NVIDIA/cutlass /opt/cutlass && \
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cd /opt/cutlass && \
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git checkout . && \
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git checkout master && \
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mkdir build && \
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cd build && \
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cmake .. -DCUTLASS_NVCC_ARCHS=${DCUTLASS_NVCC_ARCHS} -DCUTLASS_ENABLE_TESTS=OFF -DCUTLASS_UNITY_BUILD_ENABLED=ON && \
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make -j"$(nproc)" install && \
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cd ..
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# Some Packages from https://github.com/microsoft/DeepSpeed/blob/master/docker/Dockerfile
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# RUN source /opt/conda/etc/profile.d/conda.sh && \
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# conda activate ${CONDA_ENV_NAME} && \
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# apt-get update && \
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# apt-get install -y --no-install-recommends libsndfile-dev libcupti-dev libjpeg-dev libpng-dev screen libaio-dev && \
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# python -m pip install pipdeptree psutil yappi cffi ipdb pandas matplotlib py3nvml pyarrow graphviz astor boto3 tqdm sentencepiece msgpack requests pandas sphinx sphinx_rtd_theme scipy numpy scikit-learn nvidia-ml-py3 mpi4py
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# install deepspeed step 1
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RUN source /opt/conda/etc/profile.d/conda.sh && \
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conda activate ${CONDA_ENV_NAME} && \
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/opt/conda/envs/${CONDA_ENV_NAME}/bin/python -m pip install setuptools==${SETUPTOOLS_VERSION} && \
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git clone https://github.com/oneapi-src/oneCCL.git ${STAGE_DIR}/oneCCL && \
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cd ${STAGE_DIR}/oneCCL && \
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git checkout . && \
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git checkout master && \
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mkdir build && \
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cd build && \
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cmake .. -DCMAKE_INSTALL_PREFIX=/usr/local && \
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make -j"$(nproc)" install
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# install deepspeed step 2
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ARG CUDA_ARCH_LIST="80;86;89;90"
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ENV CUDA_ARCH_LIST=${CUDA_ARCH_LIST}
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RUN source /opt/conda/etc/profile.d/conda.sh && \
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conda activate ${CONDA_ENV_NAME} && \
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git clone https://github.com/microsoft/DeepSpeed-Kernels.git ${STAGE_DIR}/DeepSpeed-Kernels && \
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cd ${STAGE_DIR}/DeepSpeed-Kernels && \
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CUDA_ARCH_LIST=${CUDA_ARCH_LIST} python -m pip install -v .
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ARG DEEPSPEED_VERSION="v0.14.3"
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ENV DEEPSPEED_VERSION=${DEEPSPEED_VERSION}
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ARG DEEPSPEED_INSTALL_FLAGS="--allow_sudo --pip_sudo --verbose"
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ENV DEEPSPEED_INSTALL_FLAGS=${DEEPSPEED_INSTALL_FLAGS}
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ARG DS_BUILD_SPARSE_ATTN=0
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ENV DS_BUILD_SPARSE_ATTN=${DS_BUILD_SPARSE_ATTN}
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ARG DS_BUILD_FUSED_ADAM=1
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ENV DS_BUILD_FUSED_ADAM=${DS_BUILD_FUSED_ADAM}
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ARG DS_BUILD_CPU_ADAM=1
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ENV DS_BUILD_CPU_ADAM=${DS_BUILD_CPU_ADAM}
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ARG DS_BUILD_OPS=1
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ENV DS_BUILD_OPS=${DS_BUILD_OPS}
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ARG HOSTFILE_CONTENT=""
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ENV HOSTFILE_CONTENT=${HOSTFILE_CONTENT}
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ENV CUTLASS_PATH='/opt/cutlass'
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ENV CUDA_HOME='/usr/local/cuda'
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ENV LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
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ENV PATH=${CUDA_HOME}/bin:${PATH}
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# install deepspeed step 3
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RUN source /opt/conda/etc/profile.d/conda.sh && \
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conda activate ${CONDA_ENV_NAME} && \
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git clone https://github.com/microsoft/DeepSpeed.git ${STAGE_DIR}/DeepSpeed && \
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cd ${STAGE_DIR}/DeepSpeed && \
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git checkout ${DEEPSPEED_VERSION} && \
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sed 's/pip install/python -m pip install/' install.sh > install_modified.sh && \
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chmod +x ./install_modified.sh && \
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if [ -n "${HOSTFILE_CONTENT}" ]; then \
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echo "${HOSTFILE_CONTENT}" > /tmp/hostfile && \
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INSTALL_CMD="./install_modified.sh ${DEEPSPEED_INSTALL_FLAGS} --hostfile /tmp/hostfile"; \
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else \
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INSTALL_CMD="./install_modified.sh ${DEEPSPEED_INSTALL_FLAGS}"; \
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fi && \
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eval $INSTALL_CMD && \
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cat <<EOF > ~/compile_deepspeed_ops.py
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import deepspeed
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def compile_ops():
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builders = [
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deepspeed.ops.op_builder.AsyncIOBuilder,
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deepspeed.ops.op_builder.FusedAdamBuilder,
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deepspeed.ops.op_builder.CPUAdamBuilder,
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deepspeed.ops.op_builder.CPUAdagradBuilder,
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deepspeed.ops.op_builder.CPULionBuilder,
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deepspeed.ops.op_builder.EvoformerAttnBuilder,
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deepspeed.ops.op_builder.FPQuantizerBuilder,
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deepspeed.ops.op_builder.FusedLambBuilder,
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deepspeed.ops.op_builder.FusedLionBuilder,
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deepspeed.ops.op_builder.QuantizerBuilder,
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deepspeed.ops.op_builder.RaggedOpsBuilder,
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deepspeed.ops.op_builder.RandomLTDBuilder,
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deepspeed.ops.op_builder.SparseAttnBuilder,
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deepspeed.ops.op_builder.SpatialInferenceBuilder,
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deepspeed.ops.op_builder.TransformerBuilder,
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deepspeed.ops.op_builder.StochasticTransformerBuilder,
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]
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for builder in builders:
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print(f"Compiling {builder.__name__}")
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builder().load()
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if __name__ == "__main__":
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compile_ops()
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EOF && \
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python compile_deepspeed_ops.py && \
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ds_report
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# install transformers and flash-attn
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RUN source /opt/conda/etc/profile.d/conda.sh && \
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conda activate ${CONDA_ENV_NAME} && \
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git clone https://github.com/huggingface/transformers ${STAGE_DIR}/transformers && \
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cd ${STAGE_DIR}/transformers && \
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python3 ./setup.py develop && \
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python3 -m pip install -U --no-cache-dir "pydantic<2" && \
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pip install flash-attn --no-build-isolation -i https://pypi.org/simple/ --trusted-host pypi.org
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# other packages
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ENV TORCH_CUDA_ARCH_LIST="80;86;89;90"
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RUN source /opt/conda/etc/profile.d/conda.sh && \
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conda activate ${CONDA_ENV_NAME} && \
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pip3 install optimum && \
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pip3 install peft tiktoken tqdm matplotlib seaborn numpy pandas scikit-learn diffusers huggingface_hub spacy blobfile pycocotools open_clip_torch zstandard -i https://pypi.org/simple/ --trusted-host pypi.org
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ARG DEEPSPEED_TRAIN='/data/train_data'
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ENV DEEPSPEED_TRAIN=DEEPSPEED_TRAIN
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ARG DEEPSPEED_VALIDATION='/data/validation_data'
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ENV DEEPSPEED_VALIDATION=DEEPSPEED_VALIDATION
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ARG NCCL_SOCKET_IFNAME='eth0'
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CMD ["/usr/sbin/sshd", "-D"]
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# CMD ["/bin/bash", "-c", "/usr/sbin/sshd -D & while true; do sleep 1000; done"]
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