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)
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
Welcome to Anaconda3 5.0.1In 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。
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.
>>>
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$
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$
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"
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+cu101Could 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.
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
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 pipDownloading 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: pipFound existing installation: pip 9.0.1Uninstalling 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$
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 futureDownloading future-0.18.2.tar.gz (829 kB)|████████████████████████████████| 829 kB 6.3 kB/s
Building wheels for collected packages: futureBuilding wheel for future (setup.py) ... doneCreated wheel for future: filename=future-0.18.2-py3-none-any.whl size=493314 sha256=50fcc368ec3a68fdf90e64eabd0fb94a21835b2b9ea676b271c4287e1d26602eStored 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$
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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