How to install Tensorflow under ubuntu 16.04
1、 Check if gcc is installed in the system
sudo gcc --version
If the system does not have gcc installed, it will prompt command not found. Install gcc first at this time.
sudo apt-get build-dep gcc
The command apt-get build-dep (packagename) means to install the relevant compilation environment.
sudo apt-get install build-essential
2、 Verify the System has the Correct Kernel Headers and Development Packages Installed
The kernel headers and development packages for the currently running kernel can be installed with:
( uname -r)
3、 Download cuda tookit 9.0 (version 9.2 cannot be used)
Pay attention to download the deb version, 16.04 local version.
The CUDA Toolkit can be installed using either of two different installation mechanisms: distribution-specific packages (RPM and Deb packages), or a distribution-independent package (runfile packages). The distribution-independent package has the advantage of working across a wider set of Linux distributions, but does not update the distribution's native package management system. The distribution-specific packages interface with the distribution's native package management system. It is recommended to use the distribution-specific packages, where possible.
4、 Turn off nouveau driver###
Create a file at /etc/modprobe.d/blacklist-nouveau.conf with the following contents:
blacklist nouveau options nouveau modeset=0
Can be executed on the command line
sudo sh -c 'echo "blacklist nouveau" >> /etc/modprobe.d/blacklist-nouveau.conf'
sudo sh -c 'echo "options nouveau modeset=0" >> /etc/modprobe.d/blacklist-nouveau.conf'
Regenerate the kernel initramfs:
$ sudo update-initramfs -u
$ sudo reboot
Use command
lsmod | grep nouveau
If there is no output, the shutdown is successful
5、 Install repository meta-data
If it is a non-216 machine, remount the shared folder after restarting
sudo mount -t cifs -o username=ai,password=fs95536! //172.19.62.216/download216 /home/ai/download216
$ sudo dpkg -i cuda-repo-
For example, our
$ sudo dpkg -i /home/ai/download216/cuda-repo-ubuntu1604-9-0-local_9.0.176-1_amd64.deb
6、 Installing the CUDA public GPG key
When installing using the local repo:
$ sudo apt-key add /var/cuda-repo-
For example, here we are
sudo apt-key add /var/cuda-repo-9-0-local/7fa2af80.pub
7、 Update the Apt repository cache
$ sudo apt-get update
8、 Install CUDA
$ sudo apt-get install cuda-libraries-9-0
9、 Install cuda driver###
Dependent packages that may be required to install the driver
sudo apt-get update
sudo apt-get install dkms build-essential linux-headers-generic gcc-multilib
install driver
$sudo chmod u+x /home/ai/download216/NVIDIA-Linux-x86_64-390.87.run
$sudo /home/ai/download216/NVIDIA-Linux-x86_64-390.87.run --dkms -s
The following warning can be ignored
WARNING: nvidia-installer was forced to guess the X library path '/usr/lib' and X module path '/usr/lib/xorg/modules'; these paths were not queryable from the system. If X fails to find the NVIDIA X driver module, please install the pkg-config utility and the X.Org SDK/development package for your distribution and reinstall the driver.
Test the driver after installation
nvidia-smi
If there is information output, the installation is successful
It can be tested without restarting the system
Restart the system#####
If it is a non-216 machine, remount the shared folder after restarting
sudo mount -t cifs -o username=ai,password=fs95536! //172.19.62.216/download216 /home/ai/download216
10、 Environment Setup
The PATH variable needs to include /usr/local/cuda-9.0/bin
To add this path to the PATH variable:
{ PATH:+:${PATH}}
In addition, when using the runfile installation method, the LD_LIBRARY_PATH variable needs to contain /usr/local/cuda-9.0/lib64 on a 64-bit system, or /usr/local/cuda-9.0/lib on a 32-bit system
To change the environment variables for 64-bit operating systems:
export LD_LIBRARY_PATH=/usr/local/cuda-9.0/lib64
{ LD_LIBRARY_PATH}}
11、 Install cuda patch###
The download in the code below for non-216 machines should be changed to download216
sudo dpkg -i /home/ai/download216/cuda-repo-ubuntu1604-9-0-local-cublas-performance-update_1.0-1_amd64.deb
sudo dpkg -i /home/ai/download216/cuda-repo-ubuntu1604-9-0-local-cublas-performance-update-2_1.0-1_amd64.deb
sudo dpkg -i /home/ai/download216/cuda-repo-ubuntu1604-9-0-local-cublas-performance-update-3_1.0-1_amd64.deb
sudo dpkg -i /home/ai/download216/cuda-repo-ubuntu1604-9-0-176-local-patch-4_1.0-1_amd64.deb
12、 Install cudnn
Unzip the installation package of .solitairetheme8, the package with the suffix is all Linux platforms
The download in the code below for non-216 machines should be changed to download216
cp /home/ai/download216/cudnn-9.0-linux-x64-v7.1.solitairetheme8 cudnn-9.0-linux-x64-v7.1.tgz
tar -xzvf cudnn-9.0-linux-x64-v7.1.tgz
Copy the following files into the CUDA Toolkit directory.
sudo cp cuda/include/cudnn.h /usr/local/cuda-9.0/include
sudo chmod a+r /usr/local/cuda-9.0/include/cudnn.h (not needed for this sentence)
》sudo chmod a+r /usr/local/cuda-9.0/lib64/libcudnn
13、 Install libcupti-dev library###
sudo apt-get install cuda-command-line-tools-9-0
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda-9.0/extras/CUPTI/lib64
14、 Install anacoda
sudo bash /home/ai/download216/Anaconda3-5.2.0-Linux-x86_64.sh
Update source
source ~/.bashrc
Upgrade conda to the latest version
sudo chown -R ai:ai /home/ai/anaconda3
conda update -n base conda
Upgrade the installation package to the latest version
conda update --all
15、 Create a conda environment called tensorflow to run a certain version of Python
conda create -n tensorflow pip python=3.5
16、 Activate the conda environment###
source activate tensorflow
17、 Install TensorFlow
pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.6.0-cp35-cp35m-linux_x86_64.whl (Due to network problems, this method is not recommended)
recommend:
pip install -i https://pypi.tuna.tsinghua.edu.cn/simple --ignore-installed --upgrade tensorflow-gpupip install ipykernel
conda install jupyter notebook
18、 Configure jupyter notebook remote login###
jupyter notebook --generate-config
$ jupyter notebook password Enter password: **** Verify password: **** [NotebookPasswordApp] Wrote hashed password to /home/ai/.jupyter/jupyter_notebook_config.json
Find the following line in jupyter_notebook_config.py, uncomment and modify it.
c.NotebookApp.ip='*' c.NotebookApp.password = u'sha:ce.../home/ai/.jupyter/jupyter_notebook_config.json The content in' c.NotebookApp.open_browser = False c.NotebookApp.port =8888 #You can specify a port by yourself, use the port when accessing
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