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BigJohhn
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add docker support
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‎docker/10_nvidia.json

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{
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"file_format_version" : "1.0.0",
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"ICD" : {
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"library_path" : "libEGL_nvidia.so.0"
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}
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}
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‎docker/Dockerfile

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# 1stly, to build zeroth-bot-sim:v0
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# FROM nvidia/cuda:12.1.0-cudnn8-devel-ubuntu20.04
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# COPY sources.list /etc/apt/sources.list
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# RUN mkdir /root/.pip
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# COPY pip.conf /root/.pip/pip.conf
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# RUN apt install -y wget zlib1g-dev libssl-dev libncurses5-dev libsqlite3-dev libreadline-dev libtk8.6 libgdm-dev libdb4o-cil-dev libpcap-dev
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# RUN wget https://mirrors.huaweicloud.com/python/3.8.19/Python-3.8.19.tar.xz && tar -xvf Python-3.8.19.tar.xz
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# WORKDIR /root/Python-3.8.19
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# RUN ./configure --prefix=/usr/local && make && make install
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# WORKDIR /usr/local/bin/
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# RUN ln -s pip3 pip
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# WORKDIR /app/sim/
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# RUN make install-dev
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# RUN wget https://developer.nvidia.com/isaac-gym-preview-4
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# # RUN tar -xvf
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# RUN make install-third-party-external
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FROM zeroth-bot-sim:v0
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WORKDIR /root
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RUN apt update
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# on vnc client use <your docker ip>:5901
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RUN apt update && apt install -y \
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--no-install-recommends \
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libxcursor-dev \
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libxrandr-dev \
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libxinerama-dev \
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libxi-dev \
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mesa-common-dev \
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zip \
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unzip \
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make \
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vulkan-utils \
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mesa-vulkan-drivers \
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pigz \
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git \
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libegl1
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# WAR for eglReleaseThread shutdown crash in libEGL_mesa.so.0 (ensure it's never detected/loaded)
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# Can't remove package libegl-mesa0 directly (because of libegl1 which we need)
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RUN rm /usr/lib/x86_64-linux-gnu/libEGL_mesa.so.0 /usr/lib/x86_64-linux-gnu/libEGL_mesa.so.0.0.0 /usr/share/glvnd/egl_vendor.d/50_mesa.json
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COPY ./nvidia_icd.json /usr/share/vulkan/icd.d/nvidia_icd.json
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COPY ./10_nvidia.json /usr/share/glvnd/egl_vendor.d/10_nvidia.json
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WORKDIR /app/sim
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RUN useradd --create-home gymuser
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USER gymuser
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# copy gym repo to docker
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COPY --chown=gymuser . .
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# install gym modules
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ENV PATH="/home/gymuser/.local/bin:$PATH"
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RUN export MODEL_DIR=sim/resources/stompymicro
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ENV NVIDIA_VISIBLE_DEVICES=all NVIDIA_DRIVER_CAPABILITIES=all
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CMD ["tail","-f", "/dev/null"]
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# CMD ["python3", "sim/train.py", "--task=stompymicro", "--num_envs=4"]
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# python3 sim/train.py --task=stompymicro --num_envs=4
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‎docker/README.md

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Preliminaries
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```
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Ensure nvidia-smi is work on your host machine.
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```
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There is a prebuilt docker image, tested on a amd64 machine, with Ubuntu 24.04 LTS.
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```
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docker pull ghcr.io/bigjohnn/zeroth-bot-sim:v1
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```
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But if that not work, maybe you can build it by yourself.
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Make some changes in your Dockerfile && docker-compose.yml.
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```
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PREBUILD a docker image that have external dependencies
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# 1stly, to build zeroth-bot-sim:v0
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# FROM nvidia/cuda:12.1.0-cudnn8-devel-ubuntu20.04
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# COPY sources.list /etc/apt/sources.list
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# RUN mkdir /root/.pip
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# COPY pip.conf /root/.pip/pip.conf
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# RUN apt install -y wget zlib1g-dev libssl-dev libncurses5-dev libsqlite3-dev libreadline-dev libtk8.6 libgdm-dev libdb4o-cil-dev libpcap-dev
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# RUN wget https://mirrors.huaweicloud.com/python/3.8.19/Python-3.8.19.tar.xz && tar -xvf Python-3.8.19.tar.xz
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# WORKDIR /root/Python-3.8.19
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# RUN ./configure --prefix=/usr/local && make && make install
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# WORKDIR /usr/local/bin/
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# RUN ln -s pip3 pip
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# WORKDIR /app/sim/
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# RUN make install-dev
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# RUN wget https://developer.nvidia.com/isaac-gym-preview-4
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# # RUN tar -xvf
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# RUN make install-third-party-external
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```
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Then,
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Terminal1:
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```
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docker-compose up --build
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```
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```
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ARNING: Found orphan containers (a55a8ae7a762_docker_my_cuda_service_1) for this project. If you removed or renamed this service in your compose file, you can run this command with the --remove-orphans flag to clean it up.
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Building my-service
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[+] Building 1.6s (10/10) FINISHED docker:default
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=> [internal] load build definition from Dockerfile 0.2s
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=> => transferring dockerfile: 348B 0.0s
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=> [internal] load metadata for docker.io/nvidia/cuda:12.1.0-cudnn8-devel-ubuntu20.04 0.0s
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=> [internal] load .dockerignore 0.2s
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=> => transferring context: 2B 0.0s
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=> [1/5] FROM docker.io/nvidia/cuda:12.1.0-cudnn8-devel-ubuntu20.04 0.0s
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=> [internal] load build context 0.2s
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=> => transferring context: 34B 0.0s
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=> CACHED [2/5] WORKDIR /app 0.0s
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=> CACHED [3/5] COPY sources.list /etc/apt/sources.list 0.0s
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=> CACHED [4/5] RUN apt update 0.0s
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=> CACHED [5/5] WORKDIR /app/sim/ 0.0s
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=> exporting to image 0.2s
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=> => exporting layers 0.0s
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=> => writing image sha256:8e9c02e6c8b50dcbf7d6d1962d51de926126f132b65b65952ad8dfc74634f8c6 0.0s
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=> => naming to docker.io/library/docker_my-service 0.1s
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WARNING: Image for service my-service was built because it did not already exist. To rebuild this image you must use `docker-compose build` or `docker-compose up --build`.
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Creating docker_my-service_1 ... done
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Attaching to docker_my-service_1
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my-service_1 |
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my-service_1 | ==========
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my-service_1 | == CUDA ==
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my-service_1 | ==========
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my-service_1 |
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my-service_1 | CUDA Version 12.1.0
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my-service_1 |
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my-service_1 | Container image Copyright (c) 2016-2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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my-service_1 |
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my-service_1 | This container image and its contents are governed by the NVIDIA Deep Learning Container License.
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my-service_1 | By pulling and using the container, you accept the terms and conditions of this license:
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my-service_1 | https://developer.nvidia.com/ngc/nvidia-deep-learning-container-license
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my-service_1 |
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my-service_1 | A copy of this license is made available in this container at /NGC-DL-CONTAINER-LICENSE for your convenience.
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my-service_1 |
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my-service_1 | *************************
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my-service_1 | ** DEPRECATION NOTICE! **
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my-service_1 | *************************
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my-service_1 | THIS IMAGE IS DEPRECATED and is scheduled for DELETION.
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my-service_1 | https://gitlab.com/nvidia/container-images/cuda/blob/master/doc/support-policy.md
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my-service_1 |
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```
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Terminal2:
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```
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docker exec -it docker_zeroth-sim_1 /bin/bash
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```
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```
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gymuser@06aac36e0751:/app/sim# python3 sim/train.py --task=stompymicro --num_envs=4
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```

‎docker/docker-compose.yml

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# version: '3.8'
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services:
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zeroth-sim:
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build:
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context: . # Assuming the Dockerfile is in the current directory
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dockerfile: Dockerfile
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volumes:
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- /home/hph/Codes/zeroth-bot:/app # Must have absolute path
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- /tmp/.X11-unix:/tmp/.X11-unix
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environment:
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- DISPLAY=$DISPLAY
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privileged: true
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cap_add:
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- SYS_PTRACE
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shm_size: 6g
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tty: true
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stdin_open: true
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deploy:
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resources:
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reservations:
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devices:
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- capabilities: [gpu]
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count: all

‎docker/nvidia_icd.json

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{
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"file_format_version" : "1.0.0",
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"ICD": {
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"library_path": "libGLX_nvidia.so.0",
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"api_version" : "1.1.95"
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}
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}

‎docker/pip.conf

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[global]
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trusted-host=mirrors.aliyun.com
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index-url=http://mirrors.aliyun.com/pypi/simple/

‎docker/sources.list

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deb http://mirrors.ustc.edu.cn/ubuntu/ focal main restricted universe multiverse
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deb http://mirrors.ustc.edu.cn/ubuntu/ focal-updates main restricted universe multiverse
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deb http://mirrors.ustc.edu.cn/ubuntu/ focal-backports main restricted universe multiverse
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deb http://mirrors.ustc.edu.cn/ubuntu/ focal-security main restricted universe multiverse

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