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【Python】深度强化学习配置安装

【Python】深度强化学习配置安装

作者: 乞力马扎罗的雪人 | 来源:发表于2020-02-23 21:11 被阅读0次

    深度强化学习环境几次在不同环境中迁移,特此写博客以便记录下次配置安装。

    Anaconda 3

    wget https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/Anaconda3-5.1.0-Linux-x86_64.sh
    bash Anaconda3-5.1.0-Linux-x86.sh
    

    之后在 运行 bashrc更改 source .bashrc
    该安装包会自动安装所有包,加环境变量,以及安装VSCODE。

    conda 导入environment.xml

    name: pytorch1.0
    channels:
      - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
      - https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge/
      - https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/msys2/
      - https://mirrors.ustc.edu.cn/anaconda/pkgs/free/
      - defaults
    dependencies:
      - ca-certificates=2019.1.23=0
      - certifi=2018.11.29=py36_0
      - libedit=3.1.20181209=hc058e9b_0
      - libffi=3.2.1=hd88cf55_4
      - libgcc-ng=8.2.0=hdf63c60_1
      - libstdcxx-ng=8.2.0=hdf63c60_1
      - ncurses=6.1=he6710b0_1
      - openssl=1.0.2r=h7b6447c_0
      - pip=19.0.3=py36_0
      - python=3.6.5=hc3d631a_2
      - readline=7.0=h7b6447c_5
      - setuptools=40.8.0=py36_0
      - sqlite=3.26.0=h7b6447c_0
      - tk=8.6.8=hbc83047_0
      - wheel=0.33.1=py36_0
      - xz=5.2.4=h14c3975_4
      - zlib=1.2.11=h7b6447c_3
      - pip:
        - atari-py==0.1.7
        - atomicwrites==1.3.0
        - attrs==19.1.0
        - cffi==1.12.3
        - chardet==3.0.4
        - click==7.0
        - colorama==0.4.1
        - cycler==0.10.0
        - cython==0.29.13
        - decorator==4.4.0
        - docopt==0.6.2
        - filelock==3.0.12
        - flask==1.1.1
        - flatbuffers==1.11
        - funcsigs==1.0.2
        - future==0.17.1
        - glfw==1.8.2
        - gym==0.12.1
        - idna==2.8
        - imageio==2.5.0
        - importlib-metadata==0.18
        - itsdangerous==1.1.0
        - jinja2==2.10.1
        - kiwisolver==1.1.0
        - lockfile==0.12.2
        - markupsafe==1.1.1
        - matplotlib==3.1.1
        - more-itertools==7.1.0
        - mujoco-py==2.0.2.4
        - networkx==2.3
        - numpy==1.16.3
        - opencv-python==4.1.1.26
        - packaging==19.0
        - pandas==0.24.2
        - pillow==6.0.0
        - pluggy==0.12.0
        - pqi==2.0.6
        - protobuf==3.9.1
        - psutil==5.6.3
        - py==1.8.0
        - py-spy==0.1.11
        - pycparser==2.19
        - pyglet==1.3.2
        - pyopengl==3.1.0
        - pyparsing==2.4.0
        - pytest==5.0.0
        - python-dateutil==2.8.0
        - pytz==2019.1
        - pywavelets==1.0.3
        - pyyaml==5.1.1
        - ray==0.7.3
        - redis==3.2.1
        - requests==2.21.0
        - scikit-image==0.15.0
        - scipy==1.2.1
        - selectivesearch==0.4
        - setproctitle==1.1.10
        - six==1.12.0
        - torch==1.0.1.post2
        - torchvision==0.2.2.post3
        - typing==3.7.4
        - urllib3==1.24.2
        - wcwidth==0.1.7
        - werkzeug==0.15.5
        - zipp==0.5.1
    

    分布式安装库horovod

    一个支持tensorflow,pytorch,keras的分布式库,基于mpirun,github地址https://github.com/horovod/horovod

    $ git clone --recursive https://github.com/horovod/horovod
    $ cd horovod
    $ python setup.py sdist
    $ HOROVOD_GPU_ALLREDUCE=NCCL HOROVOD_WITH_TENSORFLOW=1 /data6/yizhou/tool/miniconda3/bin/pip install --no-cache-dir
    

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