544 lines
20 KiB
Docker
544 lines
20 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 TAG_VERSION="12.4.1"
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FROM nvidia/cuda:${TAG_VERSION}-cudnn-devel-ubuntu22.04 as apptainerbuilder
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ARG HTTP_PROXY
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ARG HTTPS_PROXY
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ENV http_proxy=${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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# 安装必需的包
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RUN apt-get update && apt-get install -y \
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wget \
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gcc \
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git \
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libc-dev \
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make \
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bash \
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linux-headers-generic \
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libseccomp-dev \
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libssl-dev \
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libuuid1 \
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uuid-dev \
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pkg-config \
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&& rm -rf /var/lib/apt/lists/*
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# 安装 Go
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ARG GO_VERSION="1.21.13"
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RUN wget https://golang.org/dl/go${GO_VERSION}.linux-amd64.tar.gz && \
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tar -C /usr/local -xzf go${GO_VERSION}.linux-amd64.tar.gz && \
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rm go${GO_VERSION}.linux-amd64.tar.gz
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# 设置 Go 环境变量
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ENV PATH="/usr/local/go/bin:${PATH}"
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# 构建 Apptainer
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ARG APPTAINER_COMMITISH="main"
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ARG MCONFIG_OPTIONS="--with-suid"
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WORKDIR /go/src/github.com/apptainer
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RUN git clone https://github.com/apptainer/apptainer.git \
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&& cd apptainer \
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&& git checkout "$APPTAINER_COMMITISH" \
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&& ./mconfig $MCONFIG_OPTIONS -p /usr/local/apptainer \
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&& cd builddir \
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&& make \
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&& make install
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# 清理
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RUN apt-get remove -y wget gcc git && \
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apt-get autoremove -y && \
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apt-get clean
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FROM nvidia/cuda:${TAG_VERSION}-cudnn-devel-ubuntu22.04
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COPY --from=apptainerbuilder /usr/local/apptainer /usr/local/apptainer
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ENV PATH="/usr/local/apptainer/bin:$PATH"
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ENV APPTAINER_TMPDIR="/tmp/tmp-apptainer"
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ARG HTTP_PROXY
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ARG HTTPS_PROXY
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ENV http_proxy=${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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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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# base tools
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RUN <<EOT
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#!/bin/bash
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apt-get update
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apt-get install -y libgl1-mesa-glx bash-completion wget curl htop jq vim bash libaio-dev build-essential openssh-server openssh-client python3 python3-pip python3-venv 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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pip install pipx
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pipx install nvitop
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pipx ensurepath
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. ~/.bashrc
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# Configure SSH for password and public key authentication
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mkdir ~/.ssh
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# 创建或覆盖 SSH 配置文件 ~/.ssh/config
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# - Host *: 针对所有主机的通用配置
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# - ForwardAgent yes: 启用 SSH 代理转发，允许通过本地的 SSH 代理进行身份验证
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# - StrictHostKeyChecking no: 禁用主机密钥检查，自动接受新的主机密钥（适用于自动化环境）
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printf "Host * \n ForwardAgent yes\nHost *\n StrictHostKeyChecking no" > ~/.ssh/config
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cp /etc/ssh/sshd_config /etc/ssh/sshd_config.bak
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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 yes/PubkeyAuthentication yes/' /etc/ssh/sshd_config
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sed -i 's/^\(\s*\)GSSAPIAuthentication yes/\1GSSAPIAuthentication no/' /etc/ssh/ssh_config
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sed -i "s/^#Port 22/Port ${SSH_PORT}/" /etc/ssh/sshd_config
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sudo sed -i "s/# Port 22/Port ${SSH_PORT}/" /etc/ssh/ssh_config
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ssh-keygen -t rsa -b 4096 -f /root/.ssh/id_rsa -N "" <<< y
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cat ~/.ssh/id_rsa.pub >> ~/.ssh/auth
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cat /root/.ssh/id_rsa.pub >> /root/.ssh/authorized_keys
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cat /root/.ssh/id_rsa.pub >> /root/.ssh/authorized_keys2
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chmod 600 /root/.ssh/authorized_keys
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chmod 600 /root/.ssh/authorized_keys2
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mkdir /var/run/sshd
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echo "root:${ROOT_PASSWD}" | chpasswd
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mkdir -p ~/.pip
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# install miniconda
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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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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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. /opt/conda/etc/profile.d/conda.sh
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conda init bash
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conda config --set show_channel_urls true
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# 配置 .condarc 文件
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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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# install pixi
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curl -fsSL https://pixi.sh/install.sh | bash
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EOT
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# install NVIDIA DOCA 2.7
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# RUN <<EOT
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# #!/bin/bash
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# wget https://www.mellanox.com/downloads/DOCA/DOCA_v2.7.0/host/doca-host_2.7.0-209000-24.04-ubuntu2204_amd64.deb
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# sudo dpkg -i doca-host_2.7.0-209000-24.04-ubuntu2204_amd64.deb
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# sudo apt-get update
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# sudo apt-get -y install doca-all
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# EOT
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ARG NV_DRIVER_VERSION="535"
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RUN apt-get update && \
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DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends tzdata && \
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apt-get install -y \
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apt-file \
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automake \
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default-jdk \
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dh-make \
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g++ \
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git \
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openjdk-8-jdk \
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libcap2 \
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libnuma-dev \
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libtool \
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# Provide CUDA dependencies by libnvidia-compute*
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libnvidia-compute-${NV_DRIVER_VERSION} \
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make \
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maven \
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pkg-config \
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udev \
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wget \
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environment-modules \
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# Remove cuda-compat* from nvidia/cuda:x86_64 images, provide CUDA dependencies by libnvidia-compute* instead
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&& apt-get remove -y openjdk-11-* cuda-compat* || apt-get autoremove -y
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# reference: https://github.com/huggingface/transformers/blob/main/docker/transformers-pytorch-deepspeed-latest-gpu/Dockerfile
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# PyTorch
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ARG CONDA_ENV_NAME="deepspeed"
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ENV CONDA_ENV_NAME=${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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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 <<EOT
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#!/bin/bash
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source /opt/conda/etc/profile.d/conda.sh
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conda create -n ${CONDA_ENV_NAME} python=${PYTHON_VERSION} ninja cmake mpich mpi4py ucx ucx-py cuda-cudart cuda-version=12 -y -c rapidsai-nightly -c conda-forge
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echo "conda activate ${CONDA_ENV_NAME}" >> ~/.bashrc
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conda activate ${CONDA_ENV_NAME}
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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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# # (PyTorch must be installed before pre-compiling any DeepSpeed c++/cuda ops.)
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# # (https://www.deepspeed.ai/tutorials/advanced-install/#pre-install-deepspeed-ops)
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python3 -m pip uninstall -y torch torchvision torchaudio
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# # install pytorch create conda env aleay exists
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# 直接将 PyTorch 安装指引 中的 https://download.pytorch.org/whl 替换为 https://mirror.sjtu.edu.cn/pytorch-wheels 即可。
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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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EOT
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# install apex TORCH_CUDA_ARCH_LIST all "6.0;6.1;6.2;7.0;7.5;8.0;8.6;8.9;9.0"
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ARG TORCH_CUDA_ARCH_LIST="8.0;8.6;8.9;9.0"
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ENV TORCH_CUDA_ARCH_LIST=${TORCH_CUDA_ARCH_LIST}
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RUN <<EOT
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#!/bin/bash
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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 ${STAGE_DIR}/apex
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# if pip >= 23.1 (ref: https://pip.pypa.io/en/stable/news/#v23-1) which supports multiple `--config-settings` with the same key...
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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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EOT
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# install colossalai
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ARG VERSION=main
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RUN <<EOT
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#!/bin/bash
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source /opt/conda/etc/profile.d/conda.sh
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conda activate ${CONDA_ENV_NAME}
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git clone -b ${VERSION} https://github.com/hpcaitech/ColossalAI.git
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cd ./ColossalAI
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BUILD_EXT=1 pip install -v .
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rm -rf colossalai
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EOT
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# install tensornvme
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RUN <<EOT
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#!/bin/bash
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apt update -y
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apt install -y libaio-dev
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pip install -v git+https://github.com/hpcaitech/TensorNVMe.git
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EOT
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# https://network.nvidia.com/products/infiniband-drivers/linux/mlnx_ofed/
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ENV MLNX_OFED_VERSION=23.10-3.2.2.0
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RUN <<EOT
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#!/bin/bash
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source /opt/conda/etc/profile.d/conda.sh
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conda activate ${CONDA_ENV_NAME}
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# Pre-build **latest** DeepSpeed, so it would be ready for testing (otherwise, the 1st deepspeed test will timeout)
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python3 -m pip uninstall -y deepspeed
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# This has to be run (again) inside the GPU VMs running the tests.
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# The installation works here, but some tests fail, if we do not pre-build deepspeed again in the VMs running the tests.
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# TODO: Find out why test fail. install deepspeed
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# DS_BUILD_CPU_ADAM=${DS_BUILD_CPU_ADAM} DS_BUILD_FUSED_ADAM={DS_BUILD_FUSED_ADAM} python3 -m pip install "deepspeed<=0.14.0" --global-option="build_ext" --global-option="-j8" --no-cache -v --disable-pip-version-check 2>&1
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# from https://github.com/huggingface/transformers/blob/main/docker/transformers-pytorch-deepspeed-latest-gpu/Dockerfile install deepspeed fail
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# reference deepspeed install from https://github.com/microsoft/DeepSpeed/blob/master/docker/Dockerfile
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# install deepspeed prepare
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# install Mellanox OFED
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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 --skip-distro-check --without-ucx --without-hcoll --without-openmpi --without-sharp --all --force -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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EOT
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ARG NV_PEER_MEM_VERSION="1.2"
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ENV NV_PEER_MEM_VERSION=${NV_PEER_MEM_VERSION}
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ENV NV_PEER_MEM_TAG=${NV_PEER_MEM_VERSION}-0
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RUN <<EOT
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#!/bin/bash
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source /opt/conda/etc/profile.d/conda.sh
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conda activate ${CONDA_ENV_NAME}
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# install nv_peer_mem
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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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EOT
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# # install mpi
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# ENV OPENMPI_BASEVERSION=4.1
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# ENV OPENMPI_VERSION=${OPENMPI_BASEVERSION}.6
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# ENV PATH=/usr/local/mpi/bin:${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 <<EOT
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# #!/bin/bash
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# source /opt/conda/etc/profile.d/conda.sh
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# conda activate ${CONDA_ENV_NAME}
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# # OPENMPI
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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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# # Sanity check:
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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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# # Create a wrapper for OpenMPI to allow running as root by default
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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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# EOT
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# 29.78 Usage: install.sh [options...]
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# 29.78
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# 29.78 By default will install deepspeed and all third party dependencies across all machines listed in
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# 29.78 hostfile (hostfile: /job/hostfile). If no hostfile exists, will only install locally
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# 29.78
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# 29.78 [optional]
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# 29.78 -l, --local_only Install only on local machine
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# 29.78 -s, --pip_sudo Run pip install with sudo (default: no sudo)
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# 29.78 -r, --allow_sudo Allow script to be run by root (probably don't want this, instead use --pip_sudo)
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# 29.78 -n, --no_clean Do not clean prior build state, by default prior build files are removed before building wheels
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# 29.78 -m, --pip_mirror Use the specified pip mirror (default: the default pip mirror)
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# 29.78 -H, --hostfile Path to MPI-style hostfile (default: /job/hostfile)
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# 29.78 -e, --examples Checkout deepspeed example submodule (no install)
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# 29.78 -v, --verbose Verbose logging
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# 29.78 -h, --help This help text
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RUN <<EOT
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#!/bin/bash
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source /opt/conda/etc/profile.d/conda.sh
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conda activate ${CONDA_ENV_NAME}
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useradd --create-home --uid 1000 --shell /bin/bash deepspeed
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usermod -aG sudo deepspeed
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echo "deepspeed ALL=(ALL) NOPASSWD: ALL" >> /etc/sudoers
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EOT
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# install cutlass https://github.com/NVIDIA/cutlass
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# H100: architecture is Hopper (cutlass need add : cmake .. -DCUTLASS_NVCC_ARCHS="90a" )
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# A100: architecture is Ampere
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# V100: architecture is Volta
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# T4: architecture is Turing
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# ENV CUDACXX=${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
|
||
# DCUTLASS_NVCC_ARCHS 架构参考：
|
||
# https://github.com/NVIDIA/cutlass/blob/main/media/docs/quickstart.md#building-for-multiple-architectures
|
||
ARG DCUTLASS_NVCC_ARCHS="80;89;90a"
|
||
ENV DCUTLASS_NVCC_ARCHS=${DCUTLASS_NVCC_ARCHS}
|
||
RUN <<EOT
|
||
#!/bin/bash
|
||
source /opt/conda/etc/profile.d/conda.sh
|
||
conda activate ${CONDA_ENV_NAME}
|
||
git clone https://github.com/NVIDIA/cutlass /opt/cutlass
|
||
cd /opt/cutlass
|
||
git checkout .
|
||
git checkout master
|
||
mkdir build
|
||
cd build
|
||
cmake .. -DCUTLASS_NVCC_ARCHS=${DCUTLASS_NVCC_ARCHS} -DCUTLASS_ENABLE_TESTS=OFF -DCUTLASS_UNITY_BUILD_ENABLED=ON # compiles for NVIDIA Hopper GPU architecture, like H100
|
||
make -j"$(nproc)" install
|
||
cd ..
|
||
# make test_unit -j"$(nproc)"
|
||
# make test_unit_gemm_warp -j"$(nproc)"
|
||
EOT
|
||
|
||
# Some Packages from https://github.com/microsoft/DeepSpeed/blob/master/docker/Dockerfile
|
||
# RUN <<EOT
|
||
# source /opt/conda/etc/profile.d/conda.sh
|
||
# conda activate ${CONDA_ENV_NAME}
|
||
# apt-get update
|
||
# apt-get install -y --no-install-recommends libsndfile-dev libcupti-dev libjpeg-dev libpng-dev screen libaio-dev
|
||
# 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
|
||
# EOT
|
||
|
||
# install deepspeed step 1
|
||
RUN <<EOT
|
||
#!/bin/bash
|
||
source /opt/conda/etc/profile.d/conda.sh
|
||
conda activate ${CONDA_ENV_NAME}
|
||
/opt/conda/envs/${CONDA_ENV_NAME}/bin/python -m pip install setuptools==${SETUPTOOLS_VERSION}
|
||
# install oneapi for deepspeed
|
||
git clone https://github.com/oneapi-src/oneCCL.git ${STAGE_DIR}/oneCCL
|
||
cd ${STAGE_DIR}/oneCCL
|
||
git checkout .
|
||
git checkout master
|
||
mkdir build
|
||
cd build
|
||
cmake .. -DCMAKE_INSTALL_PREFIX=/usr/local
|
||
make -j"$(nproc)" install
|
||
EOT
|
||
|
||
# install deepspeed step 2
|
||
ARG CUDA_ARCH_LIST="80;86;89;90"
|
||
ENV CUDA_ARCH_LIST=${CUDA_ARCH_LIST}
|
||
RUN <<EOT
|
||
#!/bin/bash
|
||
source /opt/conda/etc/profile.d/conda.sh
|
||
conda activate ${CONDA_ENV_NAME}
|
||
git clone https://github.com/microsoft/DeepSpeed-Kernels.git ${STAGE_DIR}/DeepSpeed-Kernels
|
||
cd ${STAGE_DIR}/DeepSpeed-Kernels
|
||
# CUDA_ARCH_LIST=${CUDA_ARCH_LIST} python setup.py bdist_wheel
|
||
# pip install dist/deepspeed_kernels-*.whl
|
||
CUDA_ARCH_LIST=${CUDA_ARCH_LIST} python -m pip install -v .
|
||
EOT
|
||
|
||
ARG DEEPSPEED_VERSION="v0.14.3"
|
||
ENV DEEPSPEED_VERSION=${DEEPSPEED_VERSION}
|
||
ARG DEEPSPEED_INSTALL_FLAGS="--allow_sudo --pip_sudo --verbose"
|
||
ENV DEEPSPEED_INSTALL_FLAGS=${DEEPSPEED_INSTALL_FLAGS}
|
||
ARG DS_BUILD_SPARSE_ATTN=0
|
||
ENV DS_BUILD_SPARSE_ATTN=${DS_BUILD_SPARSE_ATTN}
|
||
ARG DS_BUILD_FUSED_ADAM=1
|
||
ENV DS_BUILD_FUSED_ADAM=${DS_BUILD_FUSED_ADAM}
|
||
ARG DS_BUILD_CPU_ADAM=1
|
||
ENV DS_BUILD_CPU_ADAM=${DS_BUILD_CPU_ADAM}
|
||
ARG DS_BUILD_OPS=1
|
||
ENV DS_BUILD_OPS=${DS_BUILD_OPS}
|
||
ARG HOSTFILE_CONTENT=""
|
||
ENV HOSTFILE_CONTENT=${HOSTFILE_CONTENT}
|
||
ENV CUTLASS_PATH='/opt/cutlass'
|
||
ENV CUDA_HOME='/usr/local/cuda'
|
||
ENV LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
|
||
ENV PATH=${CUDA_HOME}/bin:${PATH}
|
||
# install deepspeed step 3
|
||
RUN <<EOT
|
||
#!/bin/bash
|
||
source /opt/conda/etc/profile.d/conda.sh
|
||
conda activate ${CONDA_ENV_NAME}
|
||
git clone https://github.com/microsoft/DeepSpeed.git ${STAGE_DIR}/DeepSpeed
|
||
cd ${STAGE_DIR}/DeepSpeed
|
||
git checkout ${DEEPSPEED_VERSION}
|
||
sed 's/pip install/python -m pip install/' install.sh > install_modified.sh
|
||
chmod +x ./install_modified.sh
|
||
# 检查 HOSTFILE_CONTENT 并写入文件
|
||
if [ -n "${HOSTFILE_CONTENT}" ]; then
|
||
echo "${HOSTFILE_CONTENT}" > /tmp/hostfile
|
||
INSTALL_CMD="./install_modified.sh ${DEEPSPEED_INSTALL_FLAGS} --hostfile /tmp/hostfile"
|
||
else
|
||
INSTALL_CMD="./install_modified.sh ${DEEPSPEED_INSTALL_FLAGS}"
|
||
fi
|
||
eval $INSTALL_CMD
|
||
# compile deepspeed ops
|
||
ds_report
|
||
# clean up
|
||
# rm -f deepspeed/git_version_info_installed.py
|
||
# rm -rf dist build deepspeed.egg-info
|
||
# python setup.py bdist_wheel
|
||
# DS_BUILD_OPS=${DS_BUILD_OPS} pip install -v dist/deepspeed*.whl
|
||
# DS_BUILD_OPS=${DS_BUILD_OPS} pip install -v -r requirements/requirements.txt
|
||
# pip install numpy==1.22.4 # ImportError: cannot import name 'BUFSIZE' from 'numpy' (/opt/conda/envs/deepspeed/lib/python3.10/site-packages/numpy/__init__.py) wait for fix in numpy=2.0.0
|
||
EOT
|
||
|
||
# install transformers and flash-attn
|
||
RUN <<EOT
|
||
#!/bin/bash
|
||
source /opt/conda/etc/profile.d/conda.sh
|
||
conda activate ${CONDA_ENV_NAME}
|
||
# install transformers
|
||
git clone https://github.com/huggingface/transformers ${STAGE_DIR}/transformers
|
||
cd ${STAGE_DIR}/transformers
|
||
python3 ./setup.py develop
|
||
python3 -m pip install -U --no-cache-dir "pydantic<2"
|
||
# install flash-attn
|
||
# pip install packaging -i https://pypi.org/simple/ --trusted-host pypi.org
|
||
pip install flash-attn --no-build-isolation -i https://pypi.org/simple/ --trusted-host pypi.org
|
||
EOT
|
||
|
||
# other packages
|
||
RUN <<EOT
|
||
#!/bin/bash
|
||
source /opt/conda/etc/profile.d/conda.sh
|
||
conda activate ${CONDA_ENV_NAME}
|
||
pip3 install optimum
|
||
pip3 install peft tiktoken \
|
||
tqdm matplotlib seaborn numpy pandas scikit-learn diffusers \
|
||
huggingface_hub spacy blobfile pycocotools \
|
||
open_clip_torch \
|
||
zstandard mpi4py -i https://pypi.org/simple/ --trusted-host pypi.org
|
||
EOT
|
||
|
||
ARG NCCL_IB_DISABLE="1"
|
||
ARG NCCL_SOCKET_IFNAME="eth0"
|
||
ENV NCCL_IB_DISABLE=${NCCL_IB_DISABLE}
|
||
ENV NCCL_SOCKET_IFNAME=${NCCL_SOCKET_IFNAME}
|
||
# deepspeed env
|
||
RUN <<EOT
|
||
#!/bin/bash
|
||
cat <<EOF > ~/.deepspeed_env
|
||
NCCL_IB_DISABLE=${NCCL_IB_DISABLE}
|
||
NCCL_SOCKET_IFNAME=${NCCL_SOCKET_IFNAME}
|
||
NCCL_DEBUG=INFO
|
||
CUTLASS_PATH=${CUTLASS_PATH}
|
||
CUDA_HOME=${CUDA_HOME}
|
||
EOF
|
||
#CUDA_VISIBLE_DEVICES=0,1,2,3
|
||
#OMP_NUM_THREADS=8
|
||
#MASTER_ADDR=192.168.1.1
|
||
#MASTER_PORT=12345
|
||
EOT
|
||
|
||
CMD ["/usr/sbin/sshd", "-D"]
|