ubuntu16.04 cuda9.0 cudnn Tensorflow GPU 1.10.0
ubuntu16.04 cuda9.0 cudnn Tensorflow GPU 1.10.0
Ubuntu14.04升级到Ubuntu16.04
查看目前版本 lsb_release -a
apt-get update && apt-get dist-upgrade reboot do-release-upgrade
lsb_release -a
系统备份 https://blog.csdn.net/qq_35523593/article/details/78545530
tar -cvpzf //media/zhangjun/72CCA22DCCA1EB93/Recovery/ubuntu_backup@date +%Y-%m+%d.tar.gz --exclude=/proc --exclude=/tmp --exclude=/boot --exclude=/home --exclude=/lost+found --exclude=/media --exclude=/mnt --exclude=/run /
直接操作
操作前切换到root，并且换到/根目录。tar -xvpzf /media/Disk/myDisk/ubuntu_boot_backup@2016-6-6.tar.gz -C /
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LiveCD
操作之前请确保你已经有一个制作好的ubuntu U盘启动盘。进入系统后，打开终端还是先切换到root。mkdir /mnt/sys mount /dev/sdaX /mnt/sys tar -xvpzf /media/myDisk/ubuntu_boot_backup@2016-6-6.tar.gz -C /mnt/sys
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Installation Instructions:
sudo dpkg -i cuda-repo-ubuntu1604-9-0-local_9.0.176-1_amd64.deb sudo apt-key add /var/cuda-repo-9-0-local/7fa2af80.pub # 这句命令有提示 sudo apt-get update sudo apt-get install cuda
deb安装包会安装CUDA Toolkit和Driver Package，不需要自己安装驱动 安装时好像也会自动设置环境变量
cudnn 安装： 2.3.1. Installing from a Tar File 1. Navigate to your directory containing the cuDNN Tar file. 2. Unzip the cuDNN package. $ tar -xzvf cudnn-9.0-linux-x64-v7.tgz 3. Copy the following files into the CUDA Toolkit directory. $ sudo cp cuda/include/cudnn.h /usr/local/cuda/include $ sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64 $ sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn*
GTX1080Ti LetNet-5 CPU GPU cuDNN7 时间对比
CPU模式： Makefile.config
CPU_ONLY:=1 前取消 # make clean make -j
./build/tools/caffe.bin time -model examples/mnist/lenet_train_test.prototxt Testing for 50 iterations
Total Time: 2906 ms.
GPU 模式：
Makefile.config
#CPU_ONLY:=1 make clean make -j
./build/tools/caffe.bin time -model examples/mnist/lenet_train_test.prototxt -gpu 0
Total Time: 370.198 ms.
cuDNN 模式：
Makefile.config
USE_CUDNN:=1
make clean make -j
./build/tools/caffe.bin time -model examples/mnist/lenet_train_test.prototxt -gpu 0
Testing for 50 iterations. Total Time: 68.2353 ms.
pip install tensorflow-gpu==1.10.0
安装在 python 路径下面
pip install tensorflow # Python 2.7; CPU support (no GPU support) pip3 install tensorflow # Python 3.n; CPU support (no GPU support) pip install tensorflow-gpu # Python 2.7; GPU support pip3 install tensorflow-gpu # Python 3.n; GPU support
https://pypi.org/project/tensorflow/1.10.0/#files
python2.7 python 3.5 python 3.6
Tensorflow Object Detection API https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/installation.md
https://github.com/tensorflow/models 下载不了
Tensorflow detection model zoo
打不开 https://www.tensorflow.org/tutorials/ 怎么办？ 用下面的网址！
https://tensorflow.google.cn/tutorials/
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