apktool需要java环境，java 1.8.0_191版本会报错，测试发现java version "11.0.1" 2018-10-16 LTS以及上版本可用
配置java环境
tar -xvf jdk-11.0.1_linux-x64_bin.tar.gz
chmod +x -R jdk-11.0.1
mkdir java_env
mv jdk-11.0.1 java_env/添加或修改配置文件.bashrc，path_to_java_env为文件夹java_env的路径
#java_env
export JAVA_HOME=path_to_java_env/jdk-11.0.1
export JRE_HOME=$JAVA_HOME/jre
export PATH=$JAVA_HOME/bin:$JRE_HOME/bin:$PATH
export CLASSPATH=$CLASSPATH:$JAVA_HOME/lib:$JRE_HOME/lib:.
加载配置文件
source ~/.bashrc查看当前java版本
java -version安装anaconda3 python3.7
bash Anaconda3-2019.10-Linux-x86_64.sh更换为清华的源
#运行以下命令
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/r
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/pytorch
conda config --set show_channel_urls yes
#或者修改用户目录下的 .condarc文件为以下内容
ssl_verify: true
channels:
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/r
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/msys2
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/bioconda
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/menpo
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/pytorch
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/simpleitk
show_channel_urls: true查看CUDA版本
cat /usr/local/cuda/version.txt安装对应与CUDA版本的pytorch 1.0.0
# CUDA 10.0
conda install pytorch==1.0.0 torchvision==0.2.1 cuda100 -c pytorch
# CUDA 9.0
conda install pytorch==1.0.0 torchvision==0.2.1 cuda90 -c pytorch
# CUDA 8.0
conda install pytorch==1.0.0 torchvision==0.2.1 cuda80 -c pytorch
# CPU Only
conda install pytorch-cpu==1.0.0 torchvision-cpu==0.2.1 cpuonly -c pytorch查看pytorch版本和GPU是否可用
import torch
print(torch.__version__)
print(torch.cuda.is_available())
torchnet
pip install torchnet
python-igraph
pip install python-igraph
fire
conda install fire
visdom
conda install visdom
pynvml
conda install pynvml
额外
pip install python-louvain
pip install tensorwatch