深度学习环境搭建(Ubuntu16.04+GTX1080Ti+CUDA8.0+Cudnn6.0+TensorFlow+Caffe2(Pytorch))
OS System:Ubuntu16.04
GPU Device:GTX1080Ti
Softwares:CUDA8.0、Cudnn6.0、TensorFlow(1.4.0)、Caffe2(1.0.0)
一、win10下安装Ubuntu16.04(双系统)
1、Linux分区方案
(Lagency+MBR) /boot 512M swap 16GB(本机物理内存为32GB) / 30GB or 35GB /home 余下的(越多越好) (UEFI+GPT) efi 512M swap 16GB(本机物理内存为32GB) / 30GB or 35GB /home 余下的(越多越好) swap大小设置参考: 4GB of RAM requires a minimum of 2GB of swap space 4GB to 16GB RAM requires a minimum of 4GB of swap space 16GB to 64GB of RAM requires a minimum of 8GB of swap space 64GB to 256GB of RAM requires a minimum of 16GB of swap space
2、系统引导
Lagency+MBR:win10下使用EasyBCD添加Ubuntu引导(Grub2)
UEFI+GPT:开机按快捷键选择BOOT Menu;使用Ubuntu的Grub引导;win10下使用rEFInd引导多系统
* win10下使用rEFInd步骤:
1. 官网下载zip包
2. 打开管理员命令行
3. 输入 mountvol x: /s (挂载ESP分区到x盘)
4. 把压缩包内refind文件夹复制到 x:\EFI 目录下
5. 把x:\EFI\refind\refind.conf-sample重命名为refind.conf
6. 命令行输入 bcdedit /set {bootmgr} path \EFI\refind\refind_x64.efi
7. 重启电脑
ref: https://blog.csdn.net/qf0129/article/details/78143749
二、显卡驱动、CUDA及Cudnn安装
1、安装GTX1080Ti显卡驱动
0)到NVIDIA官网查询适配的显卡驱动版本信息或下载
1)禁用自带显卡驱动nouveau
sudo gedit /etc/modprobe.d/blacklist.conf add in the last line: blacklist nouveau sudo update-initranfs –u reboot lsmod | grep nouveau //make sure nouveau is disabled, nothing will be printed out
2)run文件安装 或 命令行安装
#1 run文件安装
sudo apt-get remove --purge nvidia-* cd Downloads sudo service lightdm stop ctrl + alt + f1, login by name and passwd sudo chmod a+x NVIDIA-Linux-x86_64-375.26.run sudo ./NVIDIA-Linux-x86_64-375.26.run --no-x-check --no-nouveau-check --no-opengl-files // –no-opengl-files 只安装驱动文件,不安装OpenGL文件,不加会导致循环登录 –no-check 安装驱动时不检查X服务,可省略 –no-nouveau-check 安装驱动时不检查nouveau,可省略 sudo service lightdm start
#2 命令行安装(推荐)
sudo apt-get remove --purge nvidia-* sudo service lightdm stop ctrl + alt + f1, login by name and passwd sudo add-apt-repository ppa:graphics-drivers sudo apt-get update sudo apt-get install nvidia-375 sudo service lightdm start
2、安装CUDA8.0及Cudnn6.0
ref: https://www.cnblogs.com/wmxfd/p/installation_of_nvidia_graphics_driver_and_cuda8_and_cudnn6.html
三、TensorFlow安装
1、使用virtualenv虚拟环境安装,避免影响系统自带Python环境,使用Python3
/home目录下: sudo apt update sudo apt install python3-dev python3-pip sudo pip3 install -U virtualenv # system-wide install
virtualenv --system-site-packages -p python3 ./venv_tf_p3 source ./venv_tf_p3/bin/activate pip install --upgrade pip pip install tensorflow-gpu==1.4 python -c "import tensorflow as tf; print(tf.__version__)" //for test
# pip安装速度慢时需要修改pip源 在home/用户名/目录下创建.pip文件夹 cd .pip 创建pip.conf文件,并输入以下内容: [global] timeout = 6000 index-url = http://mirrors.aliyun.com/pypi/simple/ trusted-host = mirrors.aliyun.com
2、安装jupyter notebook并添加virtualenv运行环境
source ./venv_tf_p3/bin/activate 1、安装jupyter notebook pip install jupyter pip install ipykernel 2、为jupyter添加kernel python -m ipykernel install --user --name=venv_tf_p3 3、运行 jupyter notebook
四、Caffe2安装
1、使用virtualenv虚拟环境安装,避免影响系统自带Python环境,使用Python2
/home目录下: sudo apt update sudo apt install python-dev python-pip sudo pip install –U virtualenv # system-wide install //安装依赖 sudo apt-get install -y --no-install-recommends \ build-essential \ git \ libgoogle-glog-dev \ libgtest-dev \ libiomp-dev \ libleveldb-dev \ liblmdb-dev \ libopencv-dev \ libopenmpi-dev \ libsnappy-dev \ libprotobuf-dev \ openmpi-bin \ openmpi-doc \ protobuf-compiler sudo apt-get install -y --no-install-recommends \ libgflags-dev \ cmake sudo apt install graphviz python-tk virtualenv --system-site-packages -p python2.7 ./venv_cf_p2 source ./venv_cf_p2/bin/activate pip install --upgrade pip //安装依赖 pip install --user \ future \ numpy \ protobuf \ typing \ hypothesis \ pyyaml \ pydot //可选库安装 pip install --user \ flask \ requests \ scikit-image \ scipy \ tornado pip install --user matplotlib==2.0.2 //这里需装旧版本的matplotlib,否则在导入matplotlib时出现 :ImportError: No module named functools_lru_cache git clone https://github.com/pytorch/pytorch.git && cd pytorch git submodule update --init --recursive export USE_LMDB=1 //声明环境变量,编译LMDB,MNIST例程用到 export USE_OPENCV=1 //声明环境变量,编译OpenCV python setup.py install //环境变量设置 export PYTHONPATH=/usr/local:$PYTHONPATH export PYTHONPATH=$home/pytorch/build:$PYTHONPATH //change $home to you home path, such as "/home/john" export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH add in ~/.bashrc source ~/.bashrc //测试是否安装成功 cd ~ && python -c 'from caffe2.python import core' 2>/dev/null && echo "Success" || echo "Failure" 终端输出Success即可
[ 在pytorch目录下运行另一个测试命令:python caffe2/python/operator_test/activation_ops_test.py,没有输出期望结果,但对实际的GPU调用没有影响 ]
2、安装jupyter notebook并添加virtualenv运行环境
[ 若按照(三、2、)方法安装会出现以下错误,估计是jupyter对Python2的兼容问题 ]
[ 解决:直接指定版本安装 ]
source ./venv_cf_p2/bin/activate 1、安装jupyter notebook pip install jupyter-console==5.2.0 jupyter-client==5.2.1 jupyter-core==4.4.0 jupyter==1.0.0 ipython==5.2.0 ipykernel==4.10.0 2、为jupyter添加kernel python -m ipykernel install --user --name=venv_cf_p2 3、运行 jupyter notebook
参考:
Caffe2官方:https://caffe2.ai/docs/getting-started.html?platform=ubuntu&configuration=compile
更新时间:
2018/10/23