Merged specific files from main branch into devgpu
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161
spawnerdockerfile/Dockerfile.ngc
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161
spawnerdockerfile/Dockerfile.ngc
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ARG REGISTRY=quay.io
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ARG OWNER=jupyter
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ARG LABEL=notebook
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ARG VERSION
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ARG BASE_CONTAINER=$REGISTRY/$OWNER/$LABEL:$VERSION
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FROM $BASE_CONTAINER
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ARG HTTP_PROXY
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ARG HTTPS_PROXY
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ENV http_proxy=${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=${ROOT_PASSWD}
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WORKDIR /root
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SHELL ["/bin/bash", "-c"]
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# https://network.nvidia.com/products/infiniband-drivers/linux/mlnx_ofed/
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ENV MLNX_OFED_VERSION=23.10-3.2.2.0
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RUN <<EOT
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#!/bin/bash
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# SYSTEM_NAME=$(lsb_release -cs) # 查看发行版本
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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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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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# 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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# 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 bash-completion wget curl htop jq vim bash libaio-dev build-essential openssh-server python3 python3-pip bzip2 sudo
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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:${ROOT_PASSWD}" | chpasswd
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mkdir -p ~/.pip
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eval "$(curl https://get.x-cmd.com)"
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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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RUN <<EOT
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#!/bin/bash
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pip install -v -U git+https://github.com/facebookresearch/xformers.git@main#egg=xformers
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pip install git+https://github.com/huggingface/transformers
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EOT
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ENV STAGE_DIR=/tmp
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RUN <<EOT
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#!/bin/bash
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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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python -m pip install -v .
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EOT
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RUN <<EOT
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#!/bin/bash
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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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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=${HOSTFILE_CONTENT}
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ENV CUTLASS_PATH="/opt/pytorch/pytorch/third_party/cutlass"
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ENV CUDA_HOME="/usr/local/cuda"
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ENV LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
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ENV PATH=${CUDA_HOME}/bin:${PATH}
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RUN <<EOT
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#!/bin/bash
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git clone https://github.com/microsoft/DeepSpeed.git ${STAGE_DIR}/DeepSpeed
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cd ${STAGE_DIR}/DeepSpeed
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git checkout ${DEEPSPEED_VERSION}
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./install.sh ${DEEPSPEED_INSTALL_FLAGS}
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ds_report
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EOT
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RUN <<EOT
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#!/bin/bash
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python -m pip install --upgrade pip
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python -m pip install peft tiktoken seaborn blobfile open_clip_torch zstandard mpi4py
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# optimum 手动解决依赖
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python -m pip install black~=23.1 ruff==0.1.5 diffusers>=0.17.0
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python -m pip install --no-deps git+https://github.com/huggingface/optimum.git#egg=optimum[diffusers,quality]
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EOT
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RUN <<EOT
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#!/bin/bash
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# 项目目录中的定义通常会覆盖用户家目录中的定义
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# 配置 .deepspeed_env 文件
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cat <<EOF > ~/.deepspeed_env
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TORCH_USE_CUDA_DSA=1
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DEEPSPEED_VERBOSE=1
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DEEPSPEED_LOG_LEVEL=DEBUG
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CUTLASS_PATH=${CUTLASS_PATH}
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TORCH_CUDA_ARCH_LIST=${TORCH_CUDA_ARCH_LIST}
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CUDA_HOME=${CUDA_HOME}
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LD_LIBRARY_PATH=${LD_LIBRARY_PATH}
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EOF
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unset https_proxy http_proxy
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EOT
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CMD ["/usr/sbin/sshd", "-D"]
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72
spawnerdockerfile/docker-compose_ngc.yml
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72
spawnerdockerfile/docker-compose_ngc.yml
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version: '3.9'
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# DeepSpeed支持多种C++/CUDA扩展（ops），这些ops旨在优化深度学习的训练和推理过程。以下是一些主要的DeepSpeed ops及其功能：
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# FusedAdam - 提供融合优化的Adam优化器，适用于GPU。
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# FusedLamb - 类似FusedAdam，针对LAMB优化器，适用于大规模分布式训练。
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# SparseAttention - 用于高效计算稀疏注意力机制。
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# Transformer - 提供Transformer模型的高效实现。
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# TransformerInference - 专门用于Transformer模型的推理优化。
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# CPUAdam - 针对CPU优化的Adam优化器。
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# CPULion - 针对CPU的Lion优化器。
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# Quantizer - 提供量化支持，以减少模型大小和提高推理速度。
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# RandomLTD - 用于随机层裁剪的优化器。
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# StochasticTransformer - 支持随机Transformer模型的训练和推理。
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# 检测系统总内存（以GB为单位）
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# TOTAL_MEM=$(awk '/MemTotal/ {printf "%.0f\n", $2/1024/1024}' /proc/meminfo)
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# echo "Docker Compose 文件已生成，shm_size 设置为 ${TOTAL_MEM}GB。"
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services:
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ubuntu-finetune:
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build:
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context: .
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dockerfile: Dockerfile.ngc
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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
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REGISTRY: "nvcr.io"
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OWNER: "nvidia" # nvcr.io/nvidia/pytorch:24.06-py3
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LABEL: "pytorch"
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VERSION: "24.06-py3"
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DS_BUILD_OPS: 1
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DEEPSPEED_VERSION: "master"
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DEEPSPEED_INSTALL_FLAGS: "--allow_sudo"
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HTTP_PROXY: "http://127.0.0.1:15777"
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HTTPS_PROXY: "http://127.0.0.1:15777"
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CACHEBUST: 1
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# volumes:
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# - ./workspace:/workspace
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# - /tmp:/tmp
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container_name: ubuntu-ngc
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pull_policy: if_not_present
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ulimits:
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memlock:
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soft: -1
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hard: -1
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# tty: true
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# stdin_open: true
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restart: unless-stopped
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image: hotwa/notebook:ngc
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privileged: true
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ipc: host
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network_mode: host
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shm_size: '128gb'
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# ports:
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# - 3228:2222
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environment:
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- NVIDIA_VISIBLE_DEVICES=all
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- NVIDIA_DRIVER_CAPABILITIES=compute,utility
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- TMPDIR=/var/tmp
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# networks:
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# - network_finetune
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# command: ["/usr/sbin/sshd", "-D"]
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deploy:
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resources:
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reservations:
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devices:
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- driver: nvidia
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count: all
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capabilities: [gpu]
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# networks:
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# network_finetune:
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# name: network_finetune
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20
spawnerdockerfile/install_conda.sh
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spawnerdockerfile/install_conda.sh
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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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