update version
This commit is contained in:
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finetune/Dockerfile.update
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460
finetune/Dockerfile.update
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@@ -0,0 +1,460 @@
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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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ARG ROOT_PASSWD="root"
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ENV ROOT_PASSWD=${ROOT_PASSWD}
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WORKDIR /root
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SHELL ["/bin/bash", "-c"]
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# base tools
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RUN <<EOT
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#!/bin/bash
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apt-get update
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apt-get install -y wget curl htop jq vim bash libaio-dev build-essential openssh-server python3 python3-pip bzip2
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apt-get install -y --no-install-recommends software-properties-common build-essential autotools-dev nfs-common pdsh cmake g++ gcc curl wget vim tmux emacs less unzip htop iftop iotop ca-certificates openssh-client openssh-server rsync iputils-ping net-tools sudo llvm-dev re2c
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add-apt-repository ppa:git-core/ppa -y
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apt-get install -y git libnuma-dev wget
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# Configure SSH for password and public key authentication
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sed -i 's/#PermitRootLogin prohibit-password/PermitRootLogin yes/' /etc/ssh/sshd_config
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sed -i 's/#PasswordAuthentication yes/PasswordAuthentication yes/' /etc/ssh/sshd_config
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sed -i 's/PubkeyAuthentication no/PubkeyAuthentication yes/' /etc/ssh/sshd_config
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sed -i 's/^#Port 22/Port 22/' /etc/ssh/sshd_config
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sed -i 's/^Port [0-9]*/Port 22/' /etc/ssh/sshd_config
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mkdir /var/run/sshd
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echo "root:${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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# install pixi
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curl -fsSL https://pixi.sh/install.sh | bash
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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/${CONDA_ENV_NAME}/bin/python3"
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ENV REF='main'
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ENV STAGE_DIR=/tmp
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ARG CUDA='cu121'
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ENV CUDA=${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 -c conda-forge -y
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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==${TORCHAUDIO_VERSION} xformers --extra-index-url https://mirror.sjtu.edu.cn/pytorch-wheels/${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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# 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 --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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EOT
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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 <<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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apt-get install -y --no-install-recommends dkms gcc-12 dctrl-tools fakeroot linux-headers-generic libnvidia-ml1
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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 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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# 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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||||
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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
|
||||
# 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 \
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||||
# yappi \
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||||
# cffi \
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||||
# 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}
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||||
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 $INSTALL_CMD
|
||||
# compile deepspeed ops
|
||||
cat <<'EOF' >> ~/.bashrc
|
||||
source ~/micromamba/etc/profile.d/micromamba.sh
|
||||
echo "alias mamba=micromamba" >> ~/.bashrc
|
||||
echo "alias mba=mamba" >> ~/.bashrc
|
||||
EOF
|
||||
# 配置 .mambarc 文件
|
||||
cat <<EOF > ~/compile_deepspeed_ops.py
|
||||
import deepspeed
|
||||
|
||||
def compile_ops():
|
||||
builders = [
|
||||
deepspeed.ops.op_builder.AsyncIOBuilder,
|
||||
deepspeed.ops.op_builder.FusedAdamBuilder,
|
||||
deepspeed.ops.op_builder.CPUAdamBuilder,
|
||||
deepspeed.ops.op_builder.CPUAdagradBuilder,
|
||||
deepspeed.ops.op_builder.CPULionBuilder,
|
||||
deepspeed.ops.op_builder.EvoformerAttnBuilder,
|
||||
deepspeed.ops.op_builder.FPQuantizerBuilder,
|
||||
deepspeed.ops.op_builder.FusedLambBuilder,
|
||||
deepspeed.ops.op_builder.FusedLionBuilder,
|
||||
deepspeed.ops.op_builder.QuantizerBuilder,
|
||||
deepspeed.ops.op_builder.RaggedOpsBuilder,
|
||||
deepspeed.ops.op_builder.RandomLTDBuilder,
|
||||
deepspeed.ops.op_builder.SparseAttnBuilder,
|
||||
deepspeed.ops.op_builder.SpatialInferenceBuilder,
|
||||
deepspeed.ops.op_builder.TransformerBuilder,
|
||||
deepspeed.ops.op_builder.StochasticTransformerBuilder,
|
||||
]
|
||||
|
||||
for builder in builders:
|
||||
print(f"Compiling {builder.__name__}")
|
||||
builder().load()
|
||||
|
||||
if __name__ == "__main__":
|
||||
compile_ops()
|
||||
EOF
|
||||
python compile_deepspeed_ops.py
|
||||
ds_report
|
||||
# clean up
|
||||
# rm -f deepspeed/git_version_info_installed.py
|
||||
# rm -rf dist build deepspeed.egg-info
|
||||
# python setup.py bdist_wheel
|
||||
# DS_BUILD_OPS=${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 ${CONDA_ENV_NAME}
|
||||
pip3 install optimum
|
||||
pip3 install peft tiktoken \
|
||||
tqdm matplotlib seaborn numpy pandas scikit-learn diffusers \
|
||||
huggingface_hub spacy blobfile pycocotools \
|
||||
open_clip_torch \
|
||||
zstandard mpi4py -i https://pypi.org/simple/ --trusted-host pypi.org
|
||||
EOT
|
||||
|
||||
ARG NCCL_IB_DISABLE="1"
|
||||
ARG NCCL_SOCKET_IFNAME="eth0"
|
||||
ENV NCCL_IB_DISABLE=${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"]
|
||||
67
finetune/docker-compose_update.yml
Normal file
67
finetune/docker-compose_update.yml
Normal file
@@ -0,0 +1,67 @@
|
||||
version: '3.8'
|
||||
|
||||
# DeepSpeed支持多种C++/CUDA扩展（ops），这些ops旨在优化深度学习的训练和推理过程。以下是一些主要的DeepSpeed ops及其功能：
|
||||
|
||||
# FusedAdam - 提供融合优化的Adam优化器，适用于GPU。
|
||||
# FusedLamb - 类似FusedAdam，针对LAMB优化器，适用于大规模分布式训练。
|
||||
# SparseAttention - 用于高效计算稀疏注意力机制。
|
||||
# Transformer - 提供Transformer模型的高效实现。
|
||||
# TransformerInference - 专门用于Transformer模型的推理优化。
|
||||
# CPUAdam - 针对CPU优化的Adam优化器。
|
||||
# CPULion - 针对CPU的Lion优化器。
|
||||
# Quantizer - 提供量化支持，以减少模型大小和提高推理速度。
|
||||
# RandomLTD - 用于随机层裁剪的优化器。
|
||||
# StochasticTransformer - 支持随机Transformer模型的训练和推理。
|
||||
|
||||
services:
|
||||
ubuntu-finetune:
|
||||
build:
|
||||
context: .
|
||||
dockerfile: Dockerfile.update
|
||||
args: # PyTorch版本、Python版本与pytorch_lightning版本的对应关系表 https://blog.csdn.net/qq_41813454/article/details/137421822
|
||||
PYTHON_VERSION: "3.10"
|
||||
CUDA_VERSION: "12.1.0"
|
||||
PYTORCH_VERSION: "2.3.0"
|
||||
TORCHVISION_VERSION: "0.18.0"
|
||||
TORCHAUDIO_VERSION: "2.3.0"
|
||||
DS_BUILD_OPS: 1
|
||||
USE_CUDA: 1
|
||||
USE_ROCM: 0
|
||||
USE_XPU: 0
|
||||
CUDA: cu121
|
||||
CUDA_ARCH_LIST: "80;86;89;90" # for RTX 4090, all : "80;86;89;90"
|
||||
SETUPTOOLS_VERSION: "69.5.1"
|
||||
DCUTLASS_NVCC_ARCHS: "80;86;89;90;90a" # 90a for H100 GPU 89:GeForce RTX 4090
|
||||
DEEPSPEED_VERSION: "master"
|
||||
DEEPSPEED_INSTALL_FLAGS: "--allow_sudo"
|
||||
HTTP_PROXY: "http://127.0.0.1:15777"
|
||||
HTTPS_PROXY: "http://127.0.0.1:15777"
|
||||
CACHEBUST: 1
|
||||
volumes:
|
||||
- ./src:/bbtft
|
||||
- /tmp:/tmp
|
||||
container_name: ubuntu-finetune
|
||||
pull_policy: if_not_present
|
||||
# tty: true
|
||||
restart: unless-stopped
|
||||
image: hotwa/deepspeed:pt23_update
|
||||
shm_size: '32gb'
|
||||
ports:
|
||||
- 3228:22
|
||||
environment:
|
||||
- NVIDIA_VISIBLE_DEVICES=all
|
||||
- NVIDIA_DRIVER_CAPABILITIES=compute,utility
|
||||
- TMPDIR=/var/tmp
|
||||
networks:
|
||||
- network_finetune
|
||||
deploy:
|
||||
resources:
|
||||
reservations:
|
||||
devices:
|
||||
- driver: nvidia
|
||||
count: all
|
||||
capabilities: [gpu]
|
||||
|
||||
networks:
|
||||
network_finetune:
|
||||
name: network_finetune
|
||||
Reference in New Issue
Block a user