464 lines
18 KiB
Docker
464 lines
18 KiB
Docker
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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:${CUDA_VERSION}-cudnn8-devel-ubuntu22.04
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ARG DEBIAN_FRONTEND="noninteractive"
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ENV DEBIAN_FRONTEND=${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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# 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 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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# install latest cmake
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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/ $(lsb_release -cs) main"
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sudo apt-get update
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sudo apt-get install -y cmake
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# Configure SSH for password and public key authentication
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sed -i 's/#PermitRootLogin prohibit-password/PermitRootLogin yes/' /etc/ssh/sshd_config
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sed -i 's/#PasswordAuthentication yes/PasswordAuthentication yes/' /etc/ssh/sshd_config
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sed -i 's/PubkeyAuthentication no/PubkeyAuthentication yes/' /etc/ssh/sshd_config
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sed -i 's/^#Port 22/Port 22/' /etc/ssh/sshd_config
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sed -i 's/^Port [0-9]*/Port 22/' /etc/ssh/sshd_config
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mkdir /var/run/sshd
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echo "root:${ROOT_PASSWD}" | chpasswd
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mkdir -p ~/.pip
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# 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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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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# 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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# 安装 micromamba
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# echo 1 | bash <(curl -s https://cdn.jsdelivr.net/gh/hotwa/MicroMamba_Installer@main/install.sh)
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# micromamba shell init -s bash -p ~/micromamba
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# cat <<'EOF' >> ~/.bashrc
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# source ~/micromamba/etc/profile.d/micromamba.sh
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# EOF
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# # 配置 .mambarc 文件
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# cat <<EOF > ~/.mambarc
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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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EOT
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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/${CONDA_ENV_NAME}/bin/python3"
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ENV REF='main'
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ENV STAGE_DIR=/tmp
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ENV NV_PEER_MEM_VERSION=1.2
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ENV NV_PEER_MEM_TAG=${NV_PEER_MEM_VERSION}-0
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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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ENV MLNX_OFED_VERSION=4.9-7.1.0.0
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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} -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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# 克隆 ninja 源码并编译
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git clone https://github.com/ninja-build/ninja.git ${STAGE_DIR}/ninja
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cd ${STAGE_DIR}/ninja
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# 克隆 GoogleTest 源码
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git clone https://github.com/google/googletest.git
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python ./configure.py --bootstrap
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# 配置并构建 Ninja 测试，添加 pthread 链接选项
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# CXXFLAGS="-pthread" LDFLAGS="-pthread" ./configure.py --bootstrap --gtest-source-dir=$(pwd)/googletest
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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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# 运行 Ninja 单元测试
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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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# # (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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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
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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 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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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-${MLNX_OFED_VERSION}-ubuntu20.04-x86_64.tgz | tar xzf -
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cd MLNX_OFED_LINUX-${MLNX_OFED_VERSION}-ubuntu20.04-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}-ubuntu20.04-x86_64*
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cd ..
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# install nv_peer_mem
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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-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 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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# SSH daemon port inside container cannot conflict with host OS port
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ENV SSH_PORT=2222
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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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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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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
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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 <<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 ${CONDA_ENV_NAME}
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git clone https://github.com/NVIDIA/cutlass /opt/cutlass
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cd /opt/cutlass
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git checkout .
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git checkout master
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mkdir build
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cd build
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cmake .. -DCUTLASS_NVCC_ARCHS=${DCUTLASS_NVCC_ARCHS} -DCUTLASS_ENABLE_TESTS=OFF -DCUTLASS_UNITY_BUILD_ENABLED=ON # compiles for NVIDIA Hopper GPU architecture, like H100
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make -j"$(nproc)" install
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cd ..
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# make test_unit -j"$(nproc)"
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# make test_unit_gemm_warp -j"$(nproc)"
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EOT
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# Some Packages from https://github.com/microsoft/DeepSpeed/blob/master/docker/Dockerfile
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# RUN <<EOT
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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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# 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 \
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# psutil \
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# yappi \
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# cffi \
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# ipdb \
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# pandas \
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# matplotlib \
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# py3nvml \
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# pyarrow \
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# graphviz \
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# astor \
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# boto3 \
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# tqdm \
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# sentencepiece \
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# msgpack \
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# requests \
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# pandas \
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# sphinx \
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# sphinx_rtd_theme \
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# scipy \
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# numpy \
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# scikit-learn \
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# nvidia-ml-py3 \
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# mpi4py
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# EOT
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# install deepspeed step 1
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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 ${CONDA_ENV_NAME}
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/opt/conda/envs/${CONDA_ENV_NAME}/bin/python -m pip install setuptools==${SETUPTOOLS_VERSION}
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# install oneapi for deepspeed
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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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EOT
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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 <<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/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 setup.py bdist_wheel
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# pip install dist/deepspeed_kernels-*.whl
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CUDA_ARCH_LIST=${CUDA_ARCH_LIST} python -m pip install -v .
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EOT
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ARG DEEPSPEED_VERSION="v0.14.3"
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ENV DEEPSPEED_VERSION=${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 <<EOT
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#!/bin/bash
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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 $INSTALL_CMD
|
||
# compile deepspeed ops
|
||
cat <<'EOF' >> ~/.bashrc
|
||
source ~/micromamba/etc/profile.d/micromamba.sh
|
||
echo "alias mamba=micromamba" >> ~/.bashrc
|
||
echo "alias mba=mamba" >> ~/.bashrc
|
||
EOF
|
||
# 配置 .mambarc 文件
|
||
cat <<EOF > ~/compile_deepspeed_ops.py
|
||
import deepspeed
|
||
|
||
def compile_ops():
|
||
builders = [
|
||
deepspeed.ops.op_builder.AsyncIOBuilder,
|
||
deepspeed.ops.op_builder.FusedAdamBuilder,
|
||
deepspeed.ops.op_builder.CPUAdamBuilder,
|
||
deepspeed.ops.op_builder.CPUAdagradBuilder,
|
||
deepspeed.ops.op_builder.CPULionBuilder,
|
||
deepspeed.ops.op_builder.EvoformerAttnBuilder,
|
||
deepspeed.ops.op_builder.FPQuantizerBuilder,
|
||
deepspeed.ops.op_builder.FusedLambBuilder,
|
||
deepspeed.ops.op_builder.FusedLionBuilder,
|
||
deepspeed.ops.op_builder.QuantizerBuilder,
|
||
deepspeed.ops.op_builder.RaggedOpsBuilder,
|
||
deepspeed.ops.op_builder.RandomLTDBuilder,
|
||
deepspeed.ops.op_builder.SparseAttnBuilder,
|
||
deepspeed.ops.op_builder.SpatialInferenceBuilder,
|
||
deepspeed.ops.op_builder.TransformerBuilder,
|
||
deepspeed.ops.op_builder.StochasticTransformerBuilder,
|
||
]
|
||
|
||
for builder in builders:
|
||
print(f"Compiling {builder.__name__}")
|
||
builder().load()
|
||
|
||
if __name__ == "__main__":
|
||
compile_ops()
|
||
EOF
|
||
python compile_deepspeed_ops.py
|
||
ds_report
|
||
# clean up
|
||
# rm -f deepspeed/git_version_info_installed.py
|
||
# rm -rf dist build deepspeed.egg-info
|
||
# python setup.py bdist_wheel
|
||
# DS_BUILD_OPS=${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
|
||
ENV TORCH_CUDA_ARCH_LIST="80;86;89;90"
|
||
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 -i https://pypi.org/simple/ --trusted-host pypi.org
|
||
EOT
|
||
|
||
CMD ["/usr/sbin/sshd", "-D"]
|