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data-infradata-infra
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升级20240801版本
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‎images/jupyter-notebook/Dockerfile-ubuntu-conda

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@@ -4,11 +4,13 @@ FROM $FROM_IMAGES
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ARG PYTHONVERSION
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ARG CONDAENV
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ARG CUDAVERSION=cu118
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ARG TARGETARCH=amd64
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RUN apt update
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ENV TZ Asia/Shanghai
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ENV DEBIAN_FRONTEND noninteractive
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RUN apt update -y
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# 安装运维工具
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RUN apt install -y -f --no-install-recommends vim apt-transport-https gnupg2 ca-certificates-java rsync jq wget git dnsutils iputils-ping net-tools curl mysql-client locales zip unzip nginx lsof
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@@ -24,10 +26,18 @@ RUN echo "alias ll='ls -alF'" >> /root/.bashrc && \
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echo "alias vi='vim'" >> /root/.bashrc && \
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/bin/bash -c "source /root/.bashrc"
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# 安装anaconda
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RUN wget https://mirrors.tuna.tsinghua.edu.cn/anaconda/miniconda/Miniconda3-latest-Linux-x86_64.sh && \
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mkdir /root/.conda && bash Miniconda3-latest-Linux-x86_64.sh -b && \
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rm -f Miniconda3-latest-Linux-x86_64.sh
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# 安装amd64的conda
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RUN if [ "$TARGETARCH" = "amd64" ]; then \
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wget https://mirrors.tuna.tsinghua.edu.cn/anaconda/miniconda/Miniconda3-latest-Linux-x86_64.sh; \
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mkdir /root/.conda && bash Miniconda3-latest-Linux-x86_64.sh -b ; \
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rm -f Miniconda3-latest-Linux-x86_64.sh ; \
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fi
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# 安装arm64的conda
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RUN if [ "$TARGETARCH" = "arm64" ]; then \
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wget https://mirrors.tuna.tsinghua.edu.cn/anaconda/miniconda/Miniconda3-latest-Linux-aarch64.sh ; \
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mkdir /root/.conda && bash Miniconda3-latest-Linux-aarch64.sh -b ; \
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rm -f Miniconda3-latest-Linux-aarch64.sh ; \
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fi
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# 激活python3
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ENV PATH "/root/miniconda3/bin":$PATH
@@ -45,10 +55,11 @@ RUN apt install -y openssh-server openssh-client
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# 安装
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RUN apt install -y -f python3-opencv ffmpeg
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COPY pip.conf /root/.pip/pip.conf
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RUN pip3 install celery redis pyarrow requests_toolbelt cryptography tqdm fsspec aiohttp librosa flask werkzeug requests tornado Pillow pysnooper opencv-python numpy scipy matplotlib scikit-image ipython pyyaml visualdl filelock && rm -rf ~/.cache
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RUN pip install --upgrade pip && pip install tornado==6.2 gsutil simplejson sqlalchemy joblib scikit-learn jinja2 requests numpy pandas flask pymysql pysnooper pyyaml jupyterlab==3.4.8 voila notebook==6.4.12 && rm -rf /tmp/* /var/tmp/* /root/.cache \
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RUN pip install --upgrade pip && pip install tornado==6.2 gsutil simplejson sqlalchemy joblib scikit-learn jinja2 requests numpy pandas flask pymysql pysnooper pyyaml jupyterlab==3.4.8 voila notebook==6.4.12 && rm -rf /tmp/* /var/tmp/* /root/.cache
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RUN pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/${CUDAVERSION} && rm -rf /tmp/* /var/tmp/* /root/.cache
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#RUN jupyter labextension install @jupyter-widgets/jupyterlab-manager
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#RUN pip install --upgrade jupyterlab-git jupyterlab_tensorboard_pro && jupyter lab build && jupyter labextension install jupyterlab_tensorboard_pro && jupyter serverextension enable jupyterlab_tensorboard_pro --sys-prefix
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‎images/jupyter-notebook/build.sh

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set -ex
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TARGETARCH=amd64
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hubhost=ccr.ccs.tencentyun.com/cube-studio
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base_image=ubuntu:22.04
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docker build -t $hubhost/notebook:jupyter-ubuntu22.04 --build-arg FROM_IMAGES=$base_image --build-arg PYTHONVERSION=3.8 --build-arg CONDAENV=python38 -f Dockerfile-ubuntu-conda .
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docker push $hubhost/notebook:jupyter-ubuntu22.04
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base_image=nvidia/cuda:11.8.0-cudnn8-devel-ubuntu22.04
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docker build -t $hubhost/notebook:jupyter-ubuntu22.04-cuda11.8.0-cudnn8 --build-arg FROM_IMAGES=$base_image --build-arg PYTHONVERSION=3.8 --build-arg CONDAENV=python38 -f Dockerfile-ubuntu-conda .
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docker push $hubhost/notebook:jupyter-ubuntu22.04-cuda11.8.0-cudnn8
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base_image=ubuntu:20.04
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docker build --network=host -t $hubhost/notebook-enterprise:jupyter-ubuntu-cpu-conda-$TARGETARCH --build-arg FROM_IMAGES=$base_image --build-arg PYTHONVERSION=3.9 --build-arg CONDAENV=python39 --build-arg TARGETARCH=$TARGETARCH -f Dockerfile-ubuntu-conda .
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docker push $hubhost/notebook-enterprise:jupyter-ubuntu-cpu-conda-$TARGETARCH
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base_image=nvidia/cuda:11.8.0-cudnn8-devel-ubuntu20.04
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docker build --network=host -t $hubhost/notebook-enterprise:jupyter-ubuntu-gpu-conda-$TARGETARCH --build-arg FROM_IMAGES=$base_image --build-arg PYTHONVERSION=3.9 --build-arg CONDAENV=python39 --build-arg TARGETARCH=$TARGETARCH --build-arg CUDAVERSION=cu118 -f Dockerfile-ubuntu-conda .
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docker push $hubhost/notebook-enterprise:jupyter-ubuntu-gpu-conda-$TARGETARCH
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base_image=nvidia/cuda:12.1.0-cudnn8-devel-ubuntu20.04
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docker build --network=host -t $hubhost/notebook-enterprise:jupyter-ubuntu-gpu-conda-12.1.0-cudnn8-$TARGETARCH --build-arg FROM_IMAGES=$base_image --build-arg PYTHONVERSION=3.9 --build-arg CONDAENV=python39 --build-arg TARGETARCH=$TARGETARCH --build-arg CUDAVERSION=cu121 -f Dockerfile-ubuntu-conda .
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docker push $hubhost/notebook-enterprise:jupyter-ubuntu-gpu-conda-12.1.0-cudnn8-$TARGETARCH
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‎images/jupyter-notebook/init.sh

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@@ -9,8 +9,10 @@ echo root:cube-studio | chpasswd
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service ssh restart
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# 客户端连接命令， ssh -p ${SSH_PORT} root@${SERVICE_EXTERNAL_IP}
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#sed -i "s/Host cube-studio/Host ${NOTEBOOK_NAME}/g" /examples/ssh连接
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sed -i "s/localhost/${SERVICE_EXTERNAL_IP}/g" /examples/ssh连接
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sed -i "s/localport/${SSH_PORT}/g" /examples/ssh连接
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sed -i "s/hostname/cube-studio-${NOTEBOOK_NAME}/g" /examples/ssh连接
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# 配置example
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ln -s /examples /mnt/${USERNAME}/

‎images/jupyter-notebook/pip.conf

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[global]
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index-url = https://mirrors.aliyun.com/pypi/simple

‎images/jupyter-notebook/readme.md

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@@ -22,8 +22,8 @@ vscode镜像的构建在：https://github.com/tencentmusic/cube-studio/tree/mast
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NOTEBOOK_IMAGES=[
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['ccr.ccs.tencentyun.com/cube-studio/notebook:vscode-ubuntu-cpu-base', 'vscode（cpu）'],
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['ccr.ccs.tencentyun.com/cube-studio/notebook:vscode-ubuntu-gpu-base', 'vscode（gpu）'],
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['ccr.ccs.tencentyun.com/cube-studio/notebook:jupyter-ubuntu22.04', 'jupyter（cpu）'],
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['ccr.ccs.tencentyun.com/cube-studio/notebook:jupyter-ubuntu22.04-cuda11.8.0-cudnn8','jupyter（gpu）'],
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['ccr.ccs.tencentyun.com/cube-studio/notebook:jupyter-ubuntu-cpu-base', 'jupyter（cpu）'],
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['ccr.ccs.tencentyun.com/cube-studio/notebook:jupyter-ubuntu-gpu-base','jupyter（gpu）'],
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['ccr.ccs.tencentyun.com/cube-studio/notebook:jupyter-ubuntu-bigdata', 'jupyter（bigdata）'],
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['ccr.ccs.tencentyun.com/cube-studio/notebook:jupyter-ubuntu-machinelearning', 'jupyter（machinelearning）'],
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['ccr.ccs.tencentyun.com/cube-studio/notebook:jupyter-ubuntu-deeplearning', 'jupyter（deeplearning）'],
@@ -34,7 +34,7 @@ NOTEBOOK_IMAGES=[
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也可以直接run一个容器，然后安装插件后将容器commmit成镜像。
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```
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# 启动jupyter
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docker run --name jupyter -p 3000:3000 -d ccr.ccs.tencentyun.com/cube-studio/notebook:jupyter-ubuntu22.04 jupyter lab --notebook-dir=/ --ip=0.0.0.0 --no-browser --allow-root --port=3000 --NotebookApp.token='' --NotebookApp.password='' --NotebookApp.allow_origin='*'
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docker run --name jupyter -p 3000:3000 -d ccr.ccs.tencentyun.com/cube-studio/notebook:jupyter-ubuntu-cpu-base jupyter lab --notebook-dir=/ --ip=0.0.0.0 --no-browser --allow-root --port=3000 --NotebookApp.token='' --NotebookApp.password='' --NotebookApp.allow_origin='*'
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# 启动vscode
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docker run --name vscode -p 3000:3000 -d ccr.ccs.tencentyun.com/cube-studio/notebook:vscode-ubuntu-cpu-base node /home/theia/src-gen/backend/main.js /home/project --hostname=0.0.0.0 --port=3000

‎images/mul-cuda/ubuntu/Dockerfile

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# docker build -t ccr.ccs.tencentyun.com/cube-studio/gpu:ubuntu18.04-python3.6-cuda10.1-cuda10.0-cuda9.0-cudnn7.6 .
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# docker build --network=host -t ccr.ccs.tencentyun.com/cube-studio/gpu:ubuntu18.04-python3.6-cuda10.1-cuda10.0-cuda9.0-cudnn7.6 .
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FROM ccr.ccs.tencentyun.com/cube-studio/gpu:ubuntu18.04-python3.6-cuda10.1-cuda10.0-cuda9.0-cudnn7.6-base
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WORKDIR /

‎images/mul-cuda/ubuntu/Dockerfile-base

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# docker build -t ccr.ccs.tencentyun.com/cube-studio/gpu:ubuntu18.04-python3.6-cuda10.1-cuda10.0-cuda9.0-cudnn7.6-base .
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# docker build --network=host -t ccr.ccs.tencentyun.com/cube-studio/gpu:ubuntu18.04-python3.6-cuda10.1-cuda10.0-cuda9.0-cudnn7.6-base .
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# 手动安装了各种cuda
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# https://developer.nvidia.com/cuda-toolkit-archive 安装不上

‎images/ubuntu-gpu/cuda/python/Dockerfile

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@@ -10,6 +10,6 @@ RUN set -x; rm -rf /usr/bin/python /usr/bin/python3; apt install -y --fix-missin
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RUN bash -c "wget https://bootstrap.pypa.io/get-pip.py && python get-pip.py --ignore-installed" \
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&& rm -rf /usr/bin/pip && ln -s /usr/bin/pip3 /usr/bin/pip
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RUN pip install -U pip && pip install flask requests kubernetes numpy pandas tornado pysnooper
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RUN pip install -U pip && pip install flask requests kubernetes numpy pandas tornado pysnooper redis
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‎install/docker/Dockerfile

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# docker build -t ccr.ccs.tencentyun.com/cube-studio/kubeflow-dashboard:2024.07.01 -f install/docker/Dockerfile .
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# docker build -t ccr.ccs.tencentyun.com/cube-studio/kubeflow-dashboard:2024.08.01 -f install/docker/Dockerfile .
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FROM ccr.ccs.tencentyun.com/cube-studio/kubeflow-dashboard:base-python3.9-amd64-20231001
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‎install/docker/Dockerfile-base

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ENV LANGUAGE zh_CN.UTF-8
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# 便捷操作
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RUN echo "alias ll='ls -alF'" >> /etc/profile && \
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echo "alias la='ls -A'" >> /etc/profile && \
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echo "alias vi='vim'" >> /etc/profile
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RUN echo "alias ll='ls -alF'" >> ~/.bashrc && \
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echo "alias la='ls -A'" >> ~/.bashrc && \
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echo "alias vi='vim'" >> ~/.bashrc
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COPY install/docker/requirements.txt /requirements.txt
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