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https://github.com/williamfalcon/tensorflow-gpu-install-ubuntu-16.04

Tensorflow GPU install instructions for ubuntu 16.04 - Deep learning
https://github.com/williamfalcon/tensorflow-gpu-install-ubuntu-16.04

deep-learning machine-learning nouveau nvidia-driver tensorflow tensorflow-gpu ubuntu

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Tensorflow GPU install instructions for ubuntu 16.04 - Deep learning

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README 

        
# Tensorflow GPU install on ubuntu 16.04    



These instructions are intended to set up a deep learning environment for GPU-powered tensorflow.      

[See here for pytorch GPU install instructions](https://github.com/williamFalcon/pytorch-gpu-install)



After following these instructions you'll have:



1. Ubuntu 16.04. 

2. Cuda 9.0 drivers installed.

3. A conda environment with python 3.6.    

4. The latest tensorflow version with gpu support.   



---   

### Step 0: Noveau drivers     

Before you begin, you may need to disable the opensource ubuntu NVIDIA driver called [nouveau](https://nouveau.freedesktop.org/wiki/).



**Option 1: Modify modprobe file**

1. After you boot the linux system and are sitting at a login prompt, press ctrl+alt+F1 to get to a terminal screen.  Login via this terminal screen.



2. Create a file: /etc/modprobe.d/nouveau-blacklist.conf e.g. by 

```

sudo touch /etc/modprobe.d/nouveau-blacklist.conf

```

3.  Put the following in the above file...

```

blacklist nouveau

options nouveau modeset=0

```



4. Regenerate the kernel initramfs



```

sudo update-initramfs -u

```

5. reboot system   

```bash

reboot

```   

    

6. On reboot, verify that noveau drivers are not loaded   

```

lsmod | grep nouveau

```



If `nouveau` driver(s) are still loaded do not proceed with the installation guide and troubleshoot why it's still loaded.    



**Option 2: Modify Grub load command**    

From [this stackoverflow solution](https://askubuntu.com/questions/697389/blank-screen-ubuntu-15-04-update-with-nvidia-driver-nomodeset-does-not-work)    



1. When the GRUB boot menu appears : Highlight the Ubuntu menu entry and press the E key.

Add the nouveau.modeset=0 parameter to the end of the linux line ... Then press F10 to boot.   

2. When login page appears press [ctrl + ALt + F1]    

3. Enter username + password   

4. Uninstall every NVIDIA related software:   

```bash    

sudo apt-get purge nvidia*  

sudo reboot   

```   



---   

## Installation steps     



0. update apt-get   

``` bash 

sudo apt-get update

```

   

1. Install apt-get deps  

``` bash

sudo apt-get install openjdk-8-jdk git python-dev python3-dev python-numpy python3-numpy build-essential python-pip python3-pip python-virtualenv swig python-wheel libcurl3-dev curl   

```



2. install nvidia drivers 

``` bash

# The 16.04 installer works with 16.10.

# download drivers

curl -O http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/cuda-repo-ubuntu1604_9.0.176-1_amd64.deb



# download key to allow installation

sudo apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/7fa2af80.pub



# install actual package

sudo dpkg -i ./cuda-repo-ubuntu1604_9.0.176-1_amd64.deb



#  install cuda (but it'll prompt to install other deps, so we try to install twice with a dep update in between

sudo apt-get update

sudo apt-get install cuda-9-0   

```    



2a. reboot Ubuntu

```bash

sudo reboot

```    



2b. check nvidia driver install 

``` bash

nvidia-smi   



# you should see a list of gpus printed    

# if not, the previous steps failed.   

``` 



3. Install cudnn 



``` bash

wget https://s3.amazonaws.com/open-source-william-falcon/cudnn-9.0-linux-x64-v7.3.1.20.tgz

sudo tar -xzvf cudnn-9.0-linux-x64-v7.3.1.20.tgz

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*

```    



4. Add these lines to end of ~/.bashrc:   

``` bash

export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64"

export CUDA_HOME=/usr/local/cuda

export PATH="$PATH:/usr/local/cuda/bin"

```   



4a. Reload bashrc     

``` bash 

source ~/.bashrc

```   



5. Install miniconda   

``` bash

wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh

bash Miniconda3-latest-Linux-x86_64.sh   



# press s to skip terms   



# Do you approve the license terms? [yes|no]

# yes



# Miniconda3 will now be installed into this location:

# accept the location



# Do you wish the installer to prepend the Miniconda3 install location

# to PATH in your /home/ghost/.bashrc ? [yes|no]

# yes    



```   



5a. Reload bashrc     

``` bash 

source ~/.bashrc

```   



6. Create python 3.6 conda env to install tf   

``` bash

conda create -n tensorflow python=3.6



# press y a few times 

```   



7. Activate env   

``` bash

source activate tensorflow   

```



8. update pip (might already be up to date, but just in case...)

```

pip install --upgrade pip

```



9. Install stable tensorflow with GPU support for python 3.6    

``` bash

pip install --upgrade tensorflow-gpu



# If the above fails, try the part below

# pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.2.0-cp36-cp36m-linux_x86_64.whl

```   



10. Test tf install   

``` bash

# start python shell   

python



# run test script   

import tensorflow as tf   



hello = tf.constant('Hello, TensorFlow!')



# when you run sess, you should see a bunch of lines with the word gpu in them (if install worked)

# otherwise, not running on gpu

sess = tf.Session()

print(sess.run(hello))

```  



or alternatively



```

tf.enable_eager_execution(); print(tf.reduce_sum(tf.random_normal([1000, 1000])))"

```