文章目录
- windows10 安装
- ubuntu18.04 系统安装
- 1. 制作U盘启动盘
- 2. 更改英文路径
- 3. 更新源
- 4. 设置root账号
- 5. 安装NVIDIA驱动
- 6. CUDA安装
- 7. CUDNN安装
- 8. Anaconda安装
- 9. Pytorch安装
- 10 TensorFlow安装
- 11.caffe安装
- 12. opencv安装
- 13. 科学上网
- 14. 有道词典
- 15. 搜狗输入法
windows10 安装
- 制作U盘启动盘,可以使用windows官方windows 10 media creation tool
- 安装office
- 安装Visual Studio 2017(KBJFW-NXHK6-W4WJM-CRMQB-G3CDH)
- 安装CUDA驱动
- 安装Ultraiso9.7 (Guanjiu;A06C-83A7-701D-6CFC)(安装时不要勾选:安装虚拟ISO驱动器)
- 安装anconda
- 安装tensorflow(https://tensorflow.google.cn/install/)
- 安装pytorch(https://pytorch.org/get-started/locally/)
- 推荐安装cmder wox(重启后配置.condarc .vimrc)
ubuntu18.04 系统安装
1. 制作U盘启动盘
可以使用Ultraiso刻录(启动模式为UEFI),注意选择启动引导设备时选择与windows启动相同的硬盘(如果你有很多块硬盘的话)
2. 更改英文路径
export LANG=en_US
xdg-user-dirs-gtk-update
export LANG=zh_CN.UTF-8
xdg-user-dirs-gtk-update
3. 更新源
选择清华源
4. 设置root账号
sudo passwd root
5. 安装NVIDIA驱动
5.1 卸载旧的驱动
sudo apt-get purge nvidia*
5.2 禁止自带的nouveau nvidia驱动
sudo vim /etc/modprobe.d/blacklist-nouveau.conf
blacklist nouveau
options nouveau modeset=0
sudo update-initramfs -u
5.3 添加Graphic Drivers PPA源
sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt-get update
ubuntu-drivers devices
sudo apt-get install nvidia-driver-415
sudo reboot
nvidia-smi
nvidia-settings
6. CUDA安装
(https://developer.nvidia.com/cuda-downloads)
6.1 安装依赖库
sudo apt-get install freeglut3-dev build-essential libx11-dev libxmu-dev libxi-dev libgl1-mesa-glx libglu1-mesa libglu1-mesa-dev
**6.2 gcc版本降级(注:>=CUDA9.2 支持gcc7)
g++ --version
sudo apt-get install gcc-5
sudo apt-get install g++-5
sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-5 50
sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-5 50
g++ --version
6.3 安装cuda
sudo sh cuda_9.2.148_396.37_linux.run
6.4 环境配置
sudo gedit ~/.bashrc
export PATH=/usr/local/cuda/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
source ~/.bashrc
6.5 测试CUDA Sample
cd /usr/local/cuda/samples/1_Utilities/deviceQuery
sudo make
./deviceQuery
7. CUDNN安装
(https://developer.nvidia.com/rdp/cudnn-download)
7.1 安装
sudo dpkg -i libcudnn7_7.3.1.20-1+cuda9.2_amd64.deb
sduo dpkg -i libcudnn7-dev_7.3.1.20-1+cuda9.2_amd64.deb
sduo dpkg -i libcudnn7-doc_7.3.1.20-1+cuda9.2_amd64.deb
7.2 测试
cd /usr/src/cudnn_samples_v7/mnistCUDNN
sudo make clean
sudo make
./mnistCUDNN
8. Anaconda安装
(https://www.anaconda.com/download/)
sh Anaconda3-5.3.1-Linux-x86_64.sh
source ~/.bashrc
9. Pytorch安装
(https://pytorch.org/get-started/locally/)
conda create -n pytorch-0.4_py36 python=3.6
conda activate pytorch-0.4_py36
conda install pytorch torchvision cuda92 -c pytorch
python
import torch
10 TensorFlow安装
(https://tensorflow.google.cn/install/)
10.1 pip 安装
conda create -n tensorflow-1.12_py36 python=3.6
conda activate tensorflow-1.12_py36
pip install --ignore-installed --upgrade packageURL
python
import tensorflow as tf
tf.__version__
**10.2 手动编译TensorFlow(官方没有提供CUDA9.2的包,pip能安装的话就忽略)
git clone --recurse-submodules https://github.com/tensorflow/tensorflow
sudo apt-get install openjdk-8-jdk
echo "deb [arch=amd64] http://storage.googleapis.com/bazel-apt stable jdk1.8" | sudo tee /etc/apt/sources.list.d/bazel.list
curl https://bazel.build/bazel-release.pub.gpg | sudo apt-key add -
sudo apt-get update && sudo apt-get install bazel
cd tensroflow
./configure
bazel build --config=opt --config=cuda //tensorflow/tools/pip_package:build_pip_package
1
bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg
11.caffe安装
(http://caffe.berkeleyvision.org/install_apt.html)
11.1 依赖安装
sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-serial-dev protobuf-compiler
sudo apt-get install --no-install-recommends libboost-all-dev
sudo apt-get install libgflags-dev libgoogle-glog-dev liblmdb-dev
sudo apt-get install libopenblas-dev liblapack-dev libatlas-base-dev checkinstall
11.2 配置文件修改
USE_CUDNN := 1
OPENCV_VERSION := 3
WITH_PYTHON_LAYER := 1
INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/lib/x86_64-linux-gnu /usr/lib/x86_64-linux-gnu/hdf5/serial
**11.3 编译测试
make all -j8
make test -j8
make runtest -j8
**11.4 测试MNIST数据集
cd ~/caffe
./data/mnist/get_mnist.sh
./examples/mnist/create_mnist.sh
./examples/mnist/train_lenet.sh
12. opencv安装
(https://github.com/opencv/opencv/releases)
12.1 安装依赖
sudo apt-get install cmake
sudo apt-get install build-essential libgtk2.0-dev libavcodec-dev libavformat-dev libjpeg-dev libtiff4.dev libswscale-dev
sudo add-apt-repository "deb http://security.ubuntu.com/ubuntu xenial-security main"
sudo apt update
sudo apt install libjasper1 libjasper-dev
12.2 编译安装
cd ~/opencv
mkdir build
cd build
cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local/opencv-3.4.3 -D WITH_TBB=ON -D WITH_V4L=ON -D WITH_QT=ON -D BUILD_TIFF=ON -D WITH_OPENGL=ON -D WITH_CUDA=ON -D ENABLE_FAST_MATH=1 -D CUDA_FAST_MATH=1 -D CUDA_NVCC_FLAGS="-D_FORCE_INLINES" -D WITH_CUBLAS=1 ..
make all -j8
sudo make install
12.3 配置
sudo gedit /etc/ld.so.conf.d/opencv.conf
/usr/local/opencv-3.4.0/lib
sudo ldconfig
sudo gedit ~/.bashrc
export PKG_CONFIG_PATH=/usr/local/lib/pkgconfig${PKG_CONFIG_PATH:+${PKG_CONFIG_PATH}}
source ~/.bashrc
12.4 测试
cd opencv-3.4.0/samples/cpp/example_cmake
cmake .
make
./opencv_example
13. 科学上网
(https://github.com/shadowsocks/shadowsocks-qt5/releases)
14. 有道词典
(https://github.com/yomun/youdaodict_5.5)
15. 搜狗输入法
(https://pinyin.sogou.com/linux/?r=pinyin)
sudo dpkg -i sogoupinyin_2.2.0.0108_amd64.deb
sudo apt install -f
从设置找到语言->管理安装语言,待更新安装完成,设置为fcitx
重新登入,在右上角的托盘->配置,添加搜狗输入法
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