Ubuntu14.04升級到Ubuntu16.04

檢視目前版本
lsb_release -a

apt-get update && apt-get dist-upgrade
reboot
do-release-upgrade

lsb_release -a

tar -cvpzf //media/zhangjun/72CCA22DCCA1EB93/Recovery/[email protected]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
操作前切換到root，並且換到/根目錄。

tar -xvpzf /media/Disk/myDisk/[email protected] -C /

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LiveCD
操作之前請確保你已經有一個製作好的ubuntu U盤啟動盤。進入系統後，開啟終端還是先切換到root。

mkdir /mnt/sys
mount /dev/sdaX /mnt/sys
tar -xvpzf /media/myDisk/[email protected] -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 # 這句命令有提示
sudo apt-get update
sudo apt-get install cuda

deb安裝包會安裝CUDA Toolkit和Driver Package，不需要自己安裝驅動
安裝時好像也會自動設定環境變數

cudnn 安裝：
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 時間對比

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

安裝在 python 路徑下面

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

python2.7 python 3.5 python 3.6

Tensorflow detection model zoo

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