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linux服務器強化學習平台搭建(sumo安裝)

本文轉載自   查看原文   2020-09-22 17:26   1102 

Anaconda環境遷移

anaconda base 3.7.4

mujoco-py環境還沒有配置安裝mujoco-py因為注冊表的原因

flow環境安裝還有問題：已解決


tf-keras-rl

pip安裝所需包時，出現錯誤

好像是pillow的問題，已解決。更換了一下安裝順序，把pillow最后安裝

遷移方法與步驟

  • 安裝Jetbrain toolbox，然后更改安裝位置，安裝pycharm

  • 安裝anaconda，下載anaconda的包，bash安裝

    • 原環境備份導出：

      # 激活將導出的環境
conda activate environment
# 將原有服務器上面的環境導出
conda env export > environment.yaml
# 導出pip安裝的包
pip freeze > requirement.txt

    • 目標機執行導入環境操作：

      conda env create -f environment.yaml
# 進入新建的環境
conda activate environment
pip install -r requirement.txt

    • 檢查tensorflow環境，pytorch環境，GPU，cuda等是否安裝

      python
import tensorflow as tf
tf.test.is_built_with_cuda()
tf.test.is_gpu_available() # 目前返回False說明還存在問題

  • SUMO安裝

  • 安裝下載Flow

  • 使用google Chrome，並且配置FQ插件

  • 搜狗輸入法安裝，記得把搜狗輸入法置於第二位，不會顯示亂碼

SUMO安裝

目前進展：

  • 根據flow的安裝教程安裝flow與sumo：https://github.com/flow-project/flow/blob/master/docs/source/flow_setup.rst#optional-direct-install-of-sumo-from-github

  • sumo安裝出現問題：

    (base) ubuntu@host-192-168-96-5:~/data/sumo$ sudo apt-get install proj  libtool libgdal1-dev libxerces-c2-dev libfox-1.6-0 libfox-1.6-dev
sudo: unable to resolve host host-192-168-96-5
Reading package lists... Done
Building dependency tree       
Reading state information... Done
Package libxerces-c2-dev is not available, but is referred to by another package.
This may mean that the package is missing, has been obsoleted, or
is only available from another source

Package proj is not available, but is referred to by another package.
This may mean that the package is missing, has been obsoleted, or
is only available from another source

E: Package 'proj' has no installation candidate
E: Package 'libxerces-c2-dev' has no installation candidate

    (Optional) Direct install of SUMO from GitHub

    The below commands walk you through installing and building SUMO locally. Note that if this does not work, you are recommended to point an issue on the flow-dev message board or refer to SUMO's documentation regarding installing their software.

    We begin by downloading SUMO's github directory:

    cd ~
git clone https://github.com/eclipse/sumo.git
cd sumo
git checkout 2147d155b1
make -f Makefile.cvs

    If you have Ubuntu 14.04+, run the following command

    ./configure
make -j$nproc
echo 'export SUMO_HOME="$HOME/sumo"' >> ~/.bashrc
echo 'export PATH="$HOME/sumo/bin:$PATH"' >> ~/.bashrc
echo 'export PYTHONPATH="$HOME/sumo/tools:$PYTHONPATH"' >> ~/.bashrc
source ~/.bashrc

    按照上面教程走到./configure之后出現錯誤：

    Optional features summary
-------------------------
Enabled: PROJ GDAL GUI
Disabled: Debug Profiling Coverage PIC UnitTests Python OSG ffmpeg

    不用去管上述的錯誤，直接進行。要注意的是安裝apt-get依賴的時候要根據第四個教程的ubuntu14.04的，而不是12.04的.。然后后續安裝按照flow的教程

    主要根據第四份的教程

    1553240002264

    git checkout 2147d155b1
297  make -f Makefile.cvs
298  ./configure
299  sudo apt-get install autoconf
300  sudo apt-get install proj  libtool libgdal1-dev libxerces-c2-dev libfox-1.6-0 libfox-1.6-dev
301  sudo ./configure --with-fox-includes=/usr/include/fox-1.6 --with-gdal-includes=/usr/include/gdal --with-proj-libraries=/usr/lib --with-gdal-libraries=/usr --with-proj-gdal
302  sudo apt-get install autoconf
303  sudo apt-get install libproj-dev proj-bin proj-data  libtool libgdal1-dev libxerces-c3-dev libfox-1.6-0 libfox-1.6-dev
304  cd /usr/lib
305  sudo ln -s libgdal1.7.0.so libgdal.so
306  sudo ln -s libproj.so.0.7.0 proj-lib.so
309  cd ~
310  cd sumo
311  cd data
312  cd sumo
313  sudo aclocal
314  sudo automake
315  sudo automake --add-missing
316  sudo ./configure --with-fox-includes=/usr/include/fox-1.6 --with-gdal-includes=/usr/include/gdal --with-proj-libraries=/usr/lib --with-gdal-libraries=/usr --with-proj-gdal
317  sudo make -j$nproc
318  echo 'export SUMO_HOME="/home/ubuntu/data/sumo"' >> ~/.bashrc
319  echo 'export PATH="/home/ubuntu/data/sumo/bin:$PATH"' >> ~/.bashrc
320  echo 'export PYTHONPATH="/home/ubuntu/data/sumo/tools:$PYTHONPATH"' >> ~/.bashrc
321  source ~/.bashrc
322  sumo-gui
323  sumo
324  echo $SUMO_HOME
325 (base) ubuntu@host-192-168-96-5:~/data/sumo$

    用上述方法就不需要移動sumo文件到處都是，就在data/sumo下面，這樣就比較清晰
    要使用pycharm還要設置環境變量SUMO_HOME和添加tools:
    安裝完成后：確保sumo-*下有四個文件夾--未必
    而且在終端命令行輸入sumo或者sumo-gui都可以執行
    最后更改環境變量gedit ~/.bashrc source ~/.bashrc

  • 如果使用的是pycharm編譯器，需要更改edit Configurations與Project Structure
    Edit Configurations：RUN下面，是添加SUMO_HOME環境變量，即sumo-*所在的位置

    Project Structure：添加sumo下的tools文件夾路徑。file ->settings ->project ->project structure ->Add Content Root ->選擇sumo的tools文件夾路徑 ->ok

  • 或者從終端啟用Pycharm
    具體原因來自於PyCharm ignoring LD_LIBRARY_PATH from .bashrc

升級至sumo-1.6.0

sumo 1.1.0之后的版本不支持上述方式安裝了，只能使用https://sumo.dlr.de/docs/Installing/Linux_Build.html安裝，但是不能與其他版本共存，於是先不升級。sumo1.1之后的版本更好安裝了。

按照教程來吧，網址如下喲：

https://sumo.dlr.de/docs/Installing/Linux_Build.html#Building_the_SUMO_binaries_with_cmakesumo.dlr.de

讓我們開始吧~

hold on，如果你已經安裝過sumo，需要先卸載舊的版本哦。如果你從未裝過sumo，跳過卸載的步驟。

卸載sumo，分兩種類型

1）若是apt-get 安裝，則直接apt-get remove

sudo apt-get remove sumo
sudo apt-get remove sumo-tools
sudo apt-get remove sumo-docs

2）若是make install編譯安裝，則

參考: https://stackoverflow.com/questions/36256049/uninstall-sumo-0-22

試試下面三種方法

i）在sudo make install的目錄下執行：sudo make uninstall

ii）如果你找不到安裝目錄啦，去/usr/local/bin刪除下面的文件

cd /usr/local/bin
sudo rm activitygen dfrouter emissionsDrivingCycle jtrrouter marouter od2trips sumo-gui TraCITestClient duarouter emissionsMap netconvert netgenerate polyconvert sumo

iii）如果你還能找到安裝目錄，進入sumo的bin文件目錄，刪除下面的文件

sudo rm activitygen dfrouter emissionsDrivingCycle jtrrouter marouter od2trips sumo-gui TraCITestClient duarouter emissionsMap netconvert netgenerate polyconvert sumo

最后，記得刪除整個sumo文件夾，sudo rm -r+你的SUMO版本

下面進入正題，參考官方教程[https://sumo.dlr.de/docs/Installing/Linux_Build.html#Building_the_SUMO_binaries_with_cmake] 安裝sumo-1.5.0啦

  1. 首先，安裝需要的庫和依賴

    sudo apt-get install cmake python g++ libxerces-c-dev libfox-1.6-dev libgdal-dev libproj-dev libgl2ps-dev swig

  2. 下載安裝包
    去這里下載安裝包：https://sourceforge.net/projects/sumo/files/sumo/
    我下載的是sumo-src-1.5.0.tar.gz

  3. 在home下解壓，然后

    tar xzf sumo-src-1.5.0.tar.gz
cd sumo-1.5.0
pwd

  4. 修改SUMO_HOME路徑

    export SUMO_HOME="/home/<user>/sumo-1.5.0"
echo $SUMO_HOME

    結果應該顯示：/home/<用戶名>/sumo-1.5.0

  5. 用到cmake開始build

    mkdir build/cmake-build
cd build/cmake-build
cmake ../..

  6. make

    make -j $(nproc)

    或者

    make -j $(grep -c ^processor /proc/cpuinfo)

可能的問題：

  1. 終端輸入sumo-gui不能打開sumo仿真界面？
    試試下面的方法呢
    首先打開bashrc：

    sudo gedit ~/.bashrc

    添加：

    export PATH=/home/[我的用戶名]/sumo-1.5.0/bin:$PATH

    記得讓修改的路徑生效：

    source ~/.bashrc

升級至sumo-1.7.0

  1. 可以不用卸載原來的包data/sumo
  2. 下載安裝包到任意位置，包名通常為sumo-x.x.x
  3. 步驟如上
  4. 編譯成功后將sumo-x.x.x移動到data並重命名為data/sumo這樣就可以不用更改~/.bashrc文件

本次安裝出現問題：

//usr/lib/x86_64-linux-gnu/libpoppler.so.58: undefined reference to `TIFFDefaultStripSize@LIBTIFF_4.0' //usr/lib/x86_64-linux-gnu/libpoppler.so.58: undefined reference to `TIFFFdOpen@LIBTIFF_4.0'
//usr/lib/x86_64-linux-gnu/libpoppler.so.58: undefined reference to `TIFFWriteScanline@LIBTIFF_4.0' //usr/lib/x86_64-linux-gnu/libpoppler.so.58: undefined reference to `TIFFClose@LIBTIFF_4.0'
//usr/lib/x86_64-linux-gnu/libpoppler.so.58: undefined reference to `TIFFSetField@LIBTIFF_4.0' collect2: error: ld returned 1 exit status src/polyconvert/CMakeFiles/polyconvert.dir/build.make:346: recipe for target '../../bin/polyconvertD' failed make[2]: *** [../../bin/polyconvertD] Error 1 CMakeFiles/Makefile2:2711: recipe for target 'src/polyconvert/CMakeFiles/polyconvert.dir/all' failed make[1]: *** [src/polyconvert/CMakeFiles/polyconvert.dir/all] Error 2 make[1]: *** Waiting for unfinished jobs.... //usr/lib/x86_64-linux-gnu/libpoppler.so.58: undefined reference to `TIFFDefaultStripSize@LIBTIFF_4.0'
//usr/lib/x86_64-linux-gnu/libpoppler.so.58: undefined reference to `TIFFFdOpen@LIBTIFF_4.0' //usr/lib/x86_64-linux-gnu/libpoppler.so.58: undefined reference to `TIFFWriteScanline@LIBTIFF_4.0'
//usr/lib/x86_64-linux-gnu/libpoppler.so.58: undefined reference to `TIFFClose@LIBTIFF_4.0' //usr/lib/x86_64-linux-gnu/libpoppler.so.58: undefined reference to `TIFFSetField@LIBTIFF_4.0'
collect2: error: ld returned 1 exit status
src/netgen/CMakeFiles/netgenerate.dir/build.make:241: recipe for target '../../bin/netgenerateD' failed
make[2]: *** [../../bin/netgenerateD] Error 1
CMakeFiles/Makefile2:2199: recipe for target 'src/netgen/CMakeFiles/netgenerate.dir/all' failed
make[1]: *** [src/netgen/CMakeFiles/netgenerate.dir/all] Error 2
//usr/lib/x86_64-linux-gnu/libpoppler.so.58: undefined reference to `TIFFDefaultStripSize@LIBTIFF_4.0' //usr/lib/x86_64-linux-gnu/libpoppler.so.58: undefined reference to `TIFFFdOpen@LIBTIFF_4.0'
//usr/lib/x86_64-linux-gnu/libpoppler.so.58: undefined reference to `TIFFWriteScanline@LIBTIFF_4.0' //usr/lib/x86_64-linux-gnu/libpoppler.so.58: undefined reference to `TIFFClose@LIBTIFF_4.0'
//usr/lib/x86_64-linux-gnu/libpoppler.so.58: undefined reference to `TIFFSetField@LIBTIFF_4.0' collect2: error: ld returned 1 exit status src/CMakeFiles/netconvert.dir/build.make:115: recipe for target '../../bin/netconvertD' failed make[2]: *** [../../bin/netconvertD] Error 1 CMakeFiles/Makefile2:614: recipe for target 'src/CMakeFiles/netconvert.dir/all' failed make[1]: *** [src/CMakeFiles/netconvert.dir/all] Error 2 Makefile:138: recipe for target 'all' failed make: *** [all] Error 2

make -j $(nproc)之后出現上述問題，分析后是因為libtiff包在anaconda3里面產生沖突

locate libtiff.so
/home/ubuntu/data/anacond3/envs/node33-base/lib/libtiff.so
/home/ubuntu/data/anacond3/envs/node33-base/lib/libtiff.so.5
/home/ubuntu/data/anacond3/envs/node33-base/lib/libtiff.so.5.4.0
/home/ubuntu/data/anacond3/envs/tf-keras-rl/lib/libtiff.so
/home/ubuntu/data/anacond3/envs/tf-keras-rl/lib/libtiff.so.5
/home/ubuntu/data/anacond3/envs/tf-keras-rl/lib/libtiff.so.5.4.0
/home/ubuntu/data/anacond3/envs/tf_gpu_env/lib/libtiff.so
/home/ubuntu/data/anacond3/envs/tf_gpu_env/lib/libtiff.so.5
/home/ubuntu/data/anacond3/envs/tf_gpu_env/lib/libtiff.so.5.2.4
/home/ubuntu/data/anacond3/lib/libtiff.so
/home/ubuntu/data/anacond3/lib/libtiff.so.5
/home/ubuntu/data/anacond3/lib/libtiff.so.5.5.0
/home/ubuntu/data/anacond3/pkgs/libtiff-4.0.10-h2733197_2/lib/libtiff.so
/home/ubuntu/data/anacond3/pkgs/libtiff-4.0.10-h2733197_2/lib/libtiff.so.5
/home/ubuntu/data/anacond3/pkgs/libtiff-4.0.10-h2733197_2/lib/libtiff.so.5.4.0
/home/ubuntu/data/anacond3/pkgs/libtiff-4.0.10-hfc65ed5_1004/lib/libtiff.so
/home/ubuntu/data/anacond3/pkgs/libtiff-4.0.10-hfc65ed5_1004/lib/libtiff.so.5
/home/ubuntu/data/anacond3/pkgs/libtiff-4.0.10-hfc65ed5_1004/lib/libtiff.so.5.4.0
/home/ubuntu/data/anacond3/pkgs/libtiff-4.0.6-3/lib/libtiff.so
/home/ubuntu/data/anacond3/pkgs/libtiff-4.0.6-3/lib/libtiff.so.5
/home/ubuntu/data/anacond3/pkgs/libtiff-4.0.6-3/lib/libtiff.so.5.2.4
/home/ubuntu/data/anacond3/pkgs/libtiff-4.1.0-h2733197_1/lib/libtiff.so
/home/ubuntu/data/anacond3/pkgs/libtiff-4.1.0-h2733197_1/lib/libtiff.so.5
/home/ubuntu/data/anacond3/pkgs/libtiff-4.1.0-h2733197_1/lib/libtiff.so.5.5.0
/usr/lib/x86_64-linux-gnu/libtiff.so
/usr/lib/x86_64-linux-gnu/libtiff.so.5
/usr/lib/x86_64-linux-gnu/libtiff.so.5.2.4

然后把 anaconda3下面的 libtiff.so移走

mkdir /home/ubuntu/data/bak
mv /home/ubuntu/data/anacond3/lib/libtiff.so* ~/data/bak/

重新編譯后成功

tf_gpu_env下安裝mujoco的情況：

按照教程已安裝好mujoco150，運行：

./simulate ../model/humanoid.xml

結果：


出現無法顯示的問題，先暫且到這兒。


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