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真实机下 ubuntu 18.04 安装anaconda+cuDNN+pytorch以及其版本选择（亲测非常实用）_anaconda哪个版本适合ubuntu18.04
作者：Gausst松鼠会 | 2024-02-29 12:06:08
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anaconda哪个版本适合ubuntu18.04
推荐这个博客：有版本对应关系查询：
https://blog.csdn.net/qq_18483627/article/details/105885483?utm_medium=distribute.pc_relevant.none-task-blog-BlogCommendFromMachineLearnPai2-22.nonecase&depth_1-utm_source=distribute.pc_relevant.none-task-blog-BlogCommendFromMachineLearnPai2-22.nonecase版本对应查询
一、安装Anaconda
使用镜像下载：https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/
zhenghan@zhenghan:~$ cd Software/
zhenghan@zhenghan:~/Software$ ls
Anaconda3-5.0.1-Linux-x86_64.sh pycharm-2019.2.6
cuda_10.1.105_418.39_linux.run 永久激活
google-chrome-stable_current_amd64.deb
zhenghan@zhenghan:~/Software$ sh Anaconda3-5.0.1-Linux-x86_64.sh
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Welcome to Anaconda3 5.0.1 In order to continue the installation process, please review the license agreement. Please, press ENTER to continue >>> 按回车 #然后一直按回车到协议完毕 #出现： Do you accept the license terms? [yes|no] >>>输入yes #下面就是问你安装目录，建议就是默认的安装路径，直接按回车 Anaconda3 will now be installed into this location: /home/mayunteng/anaconda3 - Press ENTER to confirm the location - Press CTRL-C to abort the installation - Or specify a different location below [/home/mayunteng/anaconda3] >>> 按回车 #接下来就是等待安装完成 #注意安装完成以后会询问你是否把anaconda3的路径加到环境变量里去，一定要选yes,一定要选yes,一定要选yes。
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安装完成以后，重启终端，依次输入下面的指令，如果显示的是anaconda版本的python,代表安装成功。
henghan@zhenghan:~/Software$ source ~/.bashrc
zhenghan@zhenghan:~/Software$ python
Python 3.6.3 |Anaconda, Inc.| (default, Oct 13 2017, 12:02:49)
[GCC 7.2.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>>
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也可以通过 conda list 查看
zhenghan@zhenghan:~/Software$ conda list # packages in environment at /home/zhenghan/anaconda3: # _ipyw_jlab_nb_ext_conf 0.1.0 py36he11e457_0 alabaster 0.7.10 py36h306e16b_0 anaconda 5.0.1 py36hd30a520_1 anaconda-client 1.6.5 py36h19c0dcd_0 anaconda-navigator 1.6.9 py36h11ddaaa_0 anaconda-project 0.8.0 py36h29abdf5_0 asn1crypto 0.22.0 py36h265ca7c_1 astroid 1.5.3 py36hbdb9df2_0 astropy 2.0.2 py36ha51211e_4 babel 2.5.0 py36h7d14adf_0 backports 1.0 py36hfa02d7e_1 backports.shutil_get_terminal_size 1.0.0 py36hfea85ff_2 beautifulsoup4 4.6.0 py36h49b8c8c_1 bitarray 0.8.1 py36h5834eb8_0 bkcharts 0.2 py36h735825a_0 blaze 0.11.3 py36h4e06776_0 bleach 2.0.0 py36h688b259_0 bokeh 0.12.10 py36hbb0e44a_0 boto 2.48.0 py36h6e4cd66_1 bottleneck 1.2.1 py36haac1ea0_0 bzip2 1.0.6 h0376d23_1 ca-certificates 2017.08.26 h1d4fec5_0 cairo 1.14.10 haa5651f_5 certifi 2017.7.27.1 py36h8b7b77e_0 cffi 1.10.0 py36had8d393_1 chardet 3.0.4 py36h0f667ec_1 click 6.7 py36h5253387_0 cloudpickle 0.4.0 py36h30f8c20_0 clyent 1.2.2 py36h7e57e65_1 colorama 0.3.9 py36h489cec4_0 conda 4.3.30 py36h5d9f9f4_0 conda-build 3.0.27 py36h940a66d_0 conda-env 2.6.0 h36134e3_1 conda-verify 2.0.0 py36h98955d8_0 contextlib2 0.5.5 py36h6c84a62_0 cryptography 2.0.3 py36ha225213_1 curl 7.55.1 hcb0b314_2 cycler 0.10.0 py36h93f1223_0 cython 0.26.1 py36h21c49d0_0 cytoolz 0.8.2 py36h708bfd4_0 dask 0.15.3 py36hdc2c8aa_0 dask-core 0.15.3 py36h10e6167_0 datashape 0.5.4 py36h3ad6b5c_0 dbus 1.10.22 h3b5a359_0 decorator 4.1.2 py36hd076ac8_0 distributed 1.19.1 py36h25f3894_0 docutils 0.14 py36hb0f60f5_0 entrypoints 0.2.3 py36h1aec115_2 et_xmlfile 1.0.1 py36hd6bccc3_0 expat 2.2.4 hc00ebd1_1 fastcache 1.0.2 py36h5b0c431_0 filelock 2.0.12 py36hacfa1f5_0 flask 0.12.2 py36hb24657c_0 flask-cors 3.0.3 py36h2d857d3_0 fontconfig 2.12.4 h88586e7_1 freetype 2.8 h52ed37b_0 get_terminal_size 1.0.0 haa9412d_0 gevent 1.2.2 py36h2fe25dc_0 glib 2.53.6 hc861d11_1 glob2 0.5 py36h2c1b292_1 gmp 6.1.2 hb3b607b_0 gmpy2 2.0.8 py36h55090d7_1 graphite2 1.3.10 hc526e54_0 greenlet 0.4.12 py36h2d503a6_0 gst-plugins-base 1.12.2 he3457e5_0 gstreamer 1.12.2 h4f93127_0 h5py 2.7.0 py36he81ebca_1 harfbuzz 1.5.0 h2545bd6_0 hdf5 1.10.1 hb0523eb_0 heapdict 1.0.0 py36h79797d7_0 html5lib 0.999999999 py36h2cfc398_0 icu 58.2 h211956c_0 idna 2.6 py36h82fb2a8_1 imageio 2.2.0 py36he555465_0 imagesize 0.7.1 py36h52d8127_0 intel-openmp 2018.0.0 h15fc484_7 ipykernel 4.6.1 py36hbf841aa_0 ipython 6.1.0 py36hc72a948_1 ipython_genutils 0.2.0 py36hb52b0d5_0 ipywidgets 7.0.0 py36h7b55c3a_0 isort 4.2.15 py36had401c0_0 itsdangerous 0.24 py36h93cc618_1 jbig 2.1 hdba287a_0 jdcal 1.3 py36h4c697fb_0 jedi 0.10.2 py36h552def0_0 jinja2 2.9.6 py36h489bce4_1 jpeg 9b habf39ab_1 jsonschema 2.6.0 py36h006f8b5_0 jupyter 1.0.0 py36h9896ce5_0 jupyter_client 5.1.0 py36h614e9ea_0 jupyter_console 5.2.0 py36he59e554_1 jupyter_core 4.3.0 py36h357a921_0 jupyterlab 0.27.0 py36h86377d0_2 jupyterlab_launcher 0.4.0 py36h4d8058d_0 lazy-object-proxy 1.3.1 py36h10fcdad_0 libedit 3.1 heed3624_0 libffi 3.2.1 h4deb6c0_3 libgcc-ng 7.2.0 h7cc24e2_2 libgfortran-ng 7.2.0 h9f7466a_2 libpng 1.6.32 hda9c8bc_2 libsodium 1.0.13 h31c71d8_2 libssh2 1.8.0 h8c220ad_2 libstdcxx-ng 7.2.0 h7a57d05_2 libtiff 4.0.8 h90200ff_9 libtool 2.4.6 hd50d1a6_0 libxcb 1.12 h84ff03f_3 libxml2 2.9.4 h6b072ca_5 libxslt 1.1.29 hcf9102b_5 llvmlite 0.20.0 py36_0 locket 0.2.0 py36h787c0ad_1 lxml 4.1.0 py36h5b66e50_0 lzo 2.10 h1bfc0ba_1 markupsafe 1.0 py36hd9260cd_1 matplotlib 2.1.0 py36hba5de38_0 mccabe 0.6.1 py36h5ad9710_1 mistune 0.7.4 py36hbab8784_0 mkl 2018.0.0 hb491cac_4 mkl-service 1.1.2 py36h17a0993_4 mpc 1.0.3 hf803216_4 mpfr 3.1.5 h12ff648_1 mpmath 0.19 py36h8cc018b_2 msgpack-python 0.4.8 py36hec4c5d1_0 multipledispatch 0.4.9 py36h41da3fb_0 navigator-updater 0.1.0 py36h14770f7_0 nbconvert 5.3.1 py36hb41ffb7_0 nbformat 4.4.0 py36h31c9010_0 ncurses 6.0 h06874d7_1 networkx 2.0 py36h7e96fb8_0 nltk 3.2.4 py36h1a0979f_0 nose 1.3.7 py36hcdf7029_2 notebook 5.0.0 py36h0b20546_2 numba 0.35.0 np113py36_10 numexpr 2.6.2 py36hdd3393f_1 numpy 1.13.3 py36ha12f23b_0 numpydoc 0.7.0 py36h18f165f_0 odo 0.5.1 py36h90ed295_0 olefile 0.44 py36h79f9f78_0 openpyxl 2.4.8 py36h41dd2a8_1 openssl 1.0.2l h077ae2c_5 packaging 16.8 py36ha668100_1 pandas 0.20.3 py36h842e28d_2 pandoc 1.19.2.1 hea2e7c5_1 pandocfilters 1.4.2 py36ha6701b7_1 pango 1.40.11 h8191d47_0 partd 0.3.8 py36h36fd896_0 patchelf 0.9 hf79760b_2 path.py 10.3.1 py36he0c6f6d_0 pathlib2 2.3.0 py36h49efa8e_0 patsy 0.4.1 py36ha3be15e_0 pcre 8.41 hc71a17e_0 pep8 1.7.0 py36h26ade29_0 pexpect 4.2.1 py36h3b9d41b_0 pickleshare 0.7.4 py36h63277f8_0 pillow 4.2.1 py36h9119f52_0 pip 9.0.1 py36h8ec8b28_3 pixman 0.34.0 h83dc358_2 pkginfo 1.4.1 py36h215d178_1 ply 3.10 py36hed35086_0 prompt_toolkit 1.0.15 py36h17d85b1_0 psutil 5.4.0 py36h84c53db_0 ptyprocess 0.5.2 py36h69acd42_0 py 1.4.34 py36h0712aa3_1 pycodestyle 2.3.1 py36hf609f19_0 pycosat 0.6.2 py36h1a0ea17_1 pycparser 2.18 py36hf9f622e_1 pycrypto 2.6.1 py36h6998063_1 pycurl 7.43.0 py36h5e72054_3 pyflakes 1.6.0 py36h7bd6a15_0 pygments 2.2.0 py36h0d3125c_0 pylint 1.7.4 py36hb9d4533_0 pyodbc 4.0.17 py36h999153c_0 pyopenssl 17.2.0 py36h5cc804b_0 pyparsing 2.2.0 py36hee85983_1 pyqt 5.6.0 py36h0386399_5 pysocks 1.6.7 py36hd97a5b1_1 pytables 3.4.2 py36h3b5282a_2 pytest 3.2.1 py36h11ad3bb_1 python 3.6.3 hc9025b9_1 python-dateutil 2.6.1 py36h88d3b88_1 pytz 2017.2 py36hc2ccc2a_1 pywavelets 0.5.2 py36he602eb0_0 pyyaml 3.12 py36hafb9ca4_1 pyzmq 16.0.2 py36h3b0cf96_2 qt 5.6.2 h974d657_12 qtawesome 0.4.4 py36h609ed8c_0 qtconsole 4.3.1 py36h8f73b5b_0 qtpy 1.3.1 py36h3691cc8_0 readline 7.0 hac23ff0_3 requests 2.18.4 py36he2e5f8d_1 rope 0.10.5 py36h1f8c17e_0 ruamel_yaml 0.11.14 py36ha2fb22d_2 scikit-image 0.13.0 py36had3c07a_1 scikit-learn 0.19.1 py36h7aa7ec6_0 scipy 0.19.1 py36h9976243_3 seaborn 0.8.0 py36h197244f_0 setuptools 36.5.0 py36he42e2e1_0 simplegeneric 0.8.1 py36h2cb9092_0 singledispatch 3.4.0.3 py36h7a266c3_0 sip 4.18.1 py36h51ed4ed_2 six 1.11.0 py36h372c433_1 snowballstemmer 1.2.1 py36h6febd40_0 sortedcollections 0.5.3 py36h3c761f9_0 sortedcontainers 1.5.7 py36hdf89491_0 sphinx 1.6.3 py36he5f0bdb_0 sphinxcontrib 1.0 py36h6d0f590_1 sphinxcontrib-websupport 1.0.1 py36hb5cb234_1 spyder 3.2.4 py36hbe6152b_0 sqlalchemy 1.1.13 py36hfb5efd7_0 sqlite 3.20.1 h6d8b0f3_1 statsmodels 0.8.0 py36h8533d0b_0 sympy 1.1.1 py36hc6d1c1c_0 tblib 1.3.2 py36h34cf8b6_0 terminado 0.6 py36ha25a19f_0 testpath 0.3.1 py36h8cadb63_0 tk 8.6.7 h5979e9b_1 toolz 0.8.2 py36h81f2dff_0 tornado 4.5.2 py36h1283b2a_0 traitlets 4.3.2 py36h674d592_0 typing 3.6.2 py36h7da032a_0 unicodecsv 0.14.1 py36ha668878_0 unixodbc 2.3.4 hc36303a_1 urllib3 1.22 py36hbe7ace6_0 wcwidth 0.1.7 py36hdf4376a_0 webencodings 0.5.1 py36h800622e_1 werkzeug 0.12.2 py36hc703753_0 wheel 0.29.0 py36he7f4e38_1 widgetsnbextension 3.0.2 py36hd01bb71_1 wrapt 1.10.11 py36h28b7045_0 xlrd 1.1.0 py36h1db9f0c_1 xlsxwriter 1.0.2 py36h3de1aca_0 xlwt 1.3.0 py36h7b00a1f_0 xz 5.2.3 h2bcbf08_1 yaml 0.1.7 h96e3832_1 zeromq 4.2.2 hb0b69da_1 zict 0.1.3 py36h3a3bf81_0 zlib 1.2.11 hfbfcf68_1 zhenghan@zhenghan:~/Software$
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二、安装cuDNN
NVIDIA cuDNN 是用于深度神经网络的 GPU 加速库。
首先是下载CUDNN,CUDA要对应CUDNN的版本，我选择的是CUDA10.1+CUDNN7.6.4的版本。只要记住CUDA的选择要根据CUDNN的型号来选，即CUDA的版本一定要和CUDNN的版本对应，必须是CUDNN支持的版本！
官网：https://developer.nvidia.com/cudnn
cuDNN是一个CUDA的一个加速配件，可以去https://developer.nvidia.com/rdp/cudnn-archive 下载（需要注册）
我选择的是cuDNN Library for Linux,下载成功
首先解压压缩包，然后执行：
zhenghan@zhenghan:~$ cd Software zhenghan@zhenghan:~/Software$ ls Anaconda3-5.0.1-Linux-x86_64.sh google-chrome-stable_current_amd64.deb cuda_10.1.105_418.39_linux.run pycharm-2019.2.6 cudnn-10.1-linux-x64-v7.6.5.32.tgz 永久激活 zhenghan@zhenghan:~/Software$ tar -zxvf cudnn-10.1-linux-x64-v7.6.5.32.tgz cuda/include/cudnn.h cuda/NVIDIA_SLA_cuDNN_Support.txt cuda/lib64/libcudnn.so cuda/lib64/libcudnn.so.7 cuda/lib64/libcudnn.so.7.6.5 cuda/lib64/libcudnn_static.a zhenghan@zhenghan:~/Software$ zhenghan@zhenghan:~/Software$ sudo cp cuda/include/cudnn.h /usr/local/cuda/include [sudo] zhenghan 的密码： zhenghan@zhenghan:~/Software$ zhenghan@zhenghan:~/Software$ sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64zhenghan@zhenghan:~/Software$ sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn* zhenghan@zhenghan:~/Software$
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验证安装是否成功：
zhenghan@zhenghan:~/Software$ cat /usr/local/cuda/include/cudnn.h | grep CUDNN_MAJOR -A 2
#define CUDNN_MAJOR 7
#define CUDNN_MINOR 6
#define CUDNN_PATCHLEVEL 5
--
#define CUDNN_VERSION (CUDNN_MAJOR * 1000 + CUDNN_MINOR * 100 + CUDNN_PATCHLEVEL)
#include "driver_types.h"
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到此，CUDNN安装完成！
三、安装pytorch
pytorch下载网站：https://download.pytorch.org/whl/torch_stable.html
cu100表示CUDA10.0版本，cu101表示CUDA10.1版本
1.0.1和1.2.0表示具体的PyTorch版本
CP36表示python3.6版本，cp27表示python2.7版本
win_amd64表示Windows系统
官方的conda和pip安装方式我个人尝试了很多遍都没有成功，原因是下载torch文件的速度巨慢。找了清华和阿里云的多个镜像网站也没下载成功，最后在豆瓣的镜像上找到了whl安装文件。
http://pypi.doubanio.com/simple/torch/
我在https://pytorch.org/根据命令下载：
zhenghan@zhenghan:~$ pip install torch==1.4.0+cu101 torchvision==0.6.0+cu101 -f https://download.pytorch.org/whl/torch_stable.html
Collecting torch==1.4.0+cu101
Could not find a version that satisfies the requirement torch==1.4.0+cu101 (from versions: 0.1.2, 0.1.2.post1, 0.1.2.post2, 0.3.0.post4, 0.3.1, 0.4.0, 0.4.1, 1.0.0, 1.0.1, 1.0.1.post2, 1.1.0, 1.2.0, 1.2.0+cpu, 1.2.0+cu92, 1.3.0, 1.3.0+cpu, 1.3.0+cu100, 1.3.0+cu92, 1.3.1, 1.3.1+cpu, 1.3.1+cu100, 1.3.1+cu92, 1.4.0, 1.4.0+cpu, 1.4.0+cu100, 1.4.0+cu92, 1.5.0, 1.5.0+cpu, 1.5.0+cu101, 1.5.0+cu92)
No matching distribution found for torch==1.4.0+cu101
You are using pip version 9.0.1, however version 20.1.1 is available.
You should consider upgrading via the 'pip install --upgrade pip' command.
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下载速度巨慢。。。。大家还是不要尝试了。。。
在豆瓣镜像中下载好之后，在下载文件目录下打开终端即可安装。
zhenghan@zhenghan:~$ cd Software/
zhenghan@zhenghan:~/Software$ ls
Anaconda3-5.0.1-Linux-x86_64.sh
cuda
cuda_10.1.105_418.39_linux.run
cudnn-10.1-linux-x64-v7.6.5.32.tgz
google-chrome-stable_current_amd64.deb
pycharm-2019.2.6
torch-1.4.0-cp37-cp37m-manylinux1_x86_64.whl
永久激活
zhenghan@zhenghan:~/Software$ pip install torch-1.4.0-cp37-cp37m-manylinux1_x86_64.whl
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恩。。。出错了
zhenghan@zhenghan:~/Software$ pip install torch-1.4.0-cp37-cp37m-manylinux1_x86_64.whl torch-1.4.0-cp37-cp37m-manylinux1_x86_64.whl is not a supported wheel on this platform. You are using pip version 9.0.1, however version 20.1.1 is available. You should consider upgrading via the 'pip install --upgrade pip' command. zhenghan@zhenghan:~/Software$ pip install --upgrade pip Collecting pip Downloading https://files.pythonhosted.org/packages/43/84/23ed6a1796480a6f1a2d38f2802901d078266bda38388954d01d3f2e821d/pip-20.1.1-py2.py3-none-any.whl (1.5MB) 100% |████████████████████████████████| 1.5MB 8.9kB/s Installing collected packages: pip Found existing installation: pip 9.0.1 Uninstalling pip-9.0.1: Successfully uninstalled pip-9.0.1 Successfully installed pip-20.1.1 zhenghan@zhenghan:~/Software$ pip install torch-1.4.0-cp37-cp37m-manylinux1_x86_64.whl ERROR: torch-1.4.0-cp37-cp37m-manylinux1_x86_64.whl is not a supported wheel on this platform. zhenghan@zhenghan:~/Software$
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为什么呢？？？版本还是不对。。。
zhenghan@zhenghan:~/Software$ ls Anaconda3-5.0.1-Linux-x86_64.sh cuda cuda_10.1.105_418.39_linux.run cudnn-10.1-linux-x64-v7.6.5.32.tgz deepin.com.qq.im_9.1.8deepin0_i386.deb deepin.com.wechat_2.6.2.31deepin0_i386.deb deepin-wine-for-ubuntu google-chrome-stable_current_amd64.deb pycharm-2019.2.6 torch-1.4.0-cp37-cp37m-manylinux1_x86_64.whl torch-1.5.0-cp36-cp36m-manylinux1_x86_64.whl 永久激活 zhenghan@zhenghan:~/Software$ pip install torch-1.5.0-cp36-cp36m-manylinux1_x86_64.whl Processing ./torch-1.5.0-cp36-cp36m-manylinux1_x86_64.whl Requirement already satisfied: numpy in /home/zhenghan/anaconda3/lib/python3.6/site-packages (from torch==1.5.0) (1.13.3) Collecting future Downloading future-0.18.2.tar.gz (829 kB) |████████████████████████████████| 829 kB 6.3 kB/s Building wheels for collected packages: future Building wheel for future (setup.py) ... done Created wheel for future: filename=future-0.18.2-py3-none-any.whl size=493314 sha256=50fcc368ec3a68fdf90e64eabd0fb94a21835b2b9ea676b271c4287e1d26602e Stored in directory: /home/zhenghan/.cache/pip/wheels/6e/9c/ed/4499c9865ac1002697793e0ae05ba6be33553d098f3347fb94 Successfully built future Installing collected packages: future, torch Successfully installed future-0.18.2 torch-1.5.0 zhenghan@zhenghan:~/Software$
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写到最后：因为前几天我的Ubuntu19.04被我不小心搞崩了，开机后进入tty1界面，无法进入图形画界面，最后没得办法只能重新安装双系统，终于装好系统后，在安装显卡驱动的过程中，结果按照这篇博客https://jingyan.baidu.com/article/215817f738fe925fda1423a1.html，被坑的好惨。。。电脑直接进入黑屏界面，没办法，又重新装系统，装好了之后，之前配置的任何东西以及需要下载的软件都得重新来一遍，真心好累，且学且珍惜吧。。。。。。
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