其实，看开源项目，有一个不好的地方，就是维护相对比较不太友好。
特别是依赖的环境版本一直在变动的时候，这个弊端就非常明显。
好了，万事都有两面，我们可以通过这些版本的更迭，来看到深度学习的发展方向。拿过来就用，没得挑战性。
我这次对项目第一节进行了维护，并上传到gitee上面，然后就来将我的计算机环境分享出来。
由于pytorch需要cuda这些环境，其实其他环境变动不太大，但是cuda的cudnn的api变动相当大，需要注意版本匹配。
系统版本：
$ sudo lsb_release -a
No LSB modules are available.
Distributor ID: Ubuntu
Description: Ubuntu 16.04.6 LTS
Release: 16.04
Codename: xenial
CPU信息：
$ lscpu
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Byte Order: Little Endian
CPU(s): 8
On-line CPU(s) list: 0-7
Thread(s) per core: 2
... ...
Model name: Intel(R) Core(TM) i7-7700K CPU @ 4.20GHz
... ...
显卡信息：
$ nvidia-smi
Tue Sep 17 10:08:38 2019
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 410.48 Driver Version: 410.48 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 GeForce GTX 1080 Off | 00000000:01:00.0 On | N/A |
| 38% 46C P0 40W / 250W | 1079MiB / 8119MiB | 2% Default |
+-------------------------------+----------------------+----------------------+
| 1 GeForce GTX 1080 Off | 00000000:02:00.0 Off | N/A |
| 37% 43C P8 8W / 250W | 2MiB / 8119MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 2391 G /usr/lib/xorg/Xorg 603MiB |
| 0 4291 G compiz 194MiB |
| |
+-----------------------------------------------------------------------------+
cuda版本：
$ nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2018 NVIDIA Corporation
Built on Sat_Aug_25_21:08:01_CDT_2018
Cuda compilation tools, release 10.0, V10.0.130
cudnn版本：
$ cat /usr/include/cudnn.h | grep CUDNN_MAJOR -A 2
#define CUDNN_MAJOR 7
#define CUDNN_MINOR 5
#define CUDNN_PATCHLEVEL 1
--
#define CUDNN_VERSION (CUDNN_MAJOR * 1000 + CUDNN_MINOR * 100 + CUDNN_PATCHLEVEL)
#include "driver_types.h"
python环境：
# python 版本
$ python --version
Python 3.6.8 :: Anaconda, Inc.
# conda list 参看当前python的环境和版本， 为了篇幅小一点，我删了一些，大家可以对一下环境和包版本。
# pip和conda管理的包版本兼容一般做得比较好，开发环境的搭建建议大家使用pip或者conda
$ conda list
# packages in environment at /home/lhpc04/anaconda3/envs/pytorch:
#
# Name Version Build Channel
... ...
cython 0.29.7 pypi_0 pypi
dbus 1.13.2 h714fa37_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
dgl 0.2 pypi_0 pypi
gym 0.14.0 pypi_0 pypi
intel-openmp 2018.0.3 0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
ipykernel 4.8.2 py36_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
ipython 6.5.0 py36_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
ipython_genutils 0.2.0 py36_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
ipywidgets 7.3.1 py36_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
isodate 0.6.0 pypi_0 pypi
jedi 0.12.1 py36_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
jinja2 2.10 py36_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
jmespath 0.9.4 pypi_0 pypi
joblib 0.13.2 pypi_0 pypi
jpeg 9b h024ee3a_2 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
jsonschema 2.6.0 py36_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
jupyter 1.0.0 py36_4 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
jupyter_client 5.2.3 py36_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
jupyter_console 5.2.0 py36_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
jupyter_core 4.4.0 py36_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
kiwisolver 1.0.1 py36hf484d3e_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
lazy-object-proxy 1.4.1 pypi_0 pypi
libedit 3.1.20170329 h6b74fdf_2 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
libffi 3.2.1 hd88cf55_4
libgcc-ng 8.2.0 hdf63c60_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
libgfortran-ng 7.2.0 hdf63c60_3 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
libpng 1.6.36 hbc83047_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
libsodium 1.0.16 h1bed415_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
libtiff 4.0.9 he85c1e1_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
libxml2 2.9.8 h26e45fe_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
matplotlib 2.2.2 py36hb69df0a_2 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
mkl 2018.0.3 1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
mkl_fft 1.0.4 py36h4414c95_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
mkl_random 1.0.1 py36h4414c95_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
notebook 5.6.0 py36_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
numpy 1.15.0 py36h1b885b7_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
numpy-base 1.15.0 py36h3dfced4_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
olefile 0.45.1 py36_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
opencv-python 4.1.0.25 pypi_0 pypi
openssl 1.1.1b h7b6447c_1
pandas 0.24.2 pypi_0 pypi
pip 19.1.1 py36_0
protobuf 3.9.1 pypi_0 pypi
ptyprocess 0.6.0 py36_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
pygments 2.2.0 py36_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
pyopenssl 19.0.0 py36_0
pyqt 5.9.2 py36h22d08a2_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
pysocks 1.7.0 py36_0
python 3.6.8 h0371630_0
pytorch 1.1.0 py3.6_cuda9.0.176_cudnn7.5.1_0 pytorch
qt 5.9.7 h5867ecd_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
readline 7.0 h7b6447c_5
requests 2.21.0 py36_0
s3transfer 0.2.1 pypi_0 pypi
scikit-learn 0.21.0 pypi_0 pypi
scipy 1.2.1 pypi_0 pypi
six 1.12.0 py36_0
sqlite 3.26.0 h7b6447c_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
terminado 0.8.1 py36_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
testpath 0.3.1 py36_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
tk 8.6.8 hbc83047_0
torch-cluster 1.3.0 pypi_0 pypi
torch-geometric 1.2.0 pypi_0 pypi
torch-scatter 1.2.0 pypi_0 pypi
torch-sparse 0.4.0 pypi_0 pypi
torch-spline-conv 1.1.0 pypi_0 pypi
torchvision 0.2.2 py_3 pytorch
... ...
参考：
来源：https://blog.csdn.net/u012939880/article/details/100979981