Setting Up Tensorflow on Ubuntu

Step 1: Ensure system is updated and has basic build tools

sudo apt-get update 
sudo apt-get --assume-yes upgrade 
sudo apt-get --assume-yes install tmux build-essential gcc g++ make binutils 
sudo apt-get --assume-yes install software-properties-common

Step 2: Install your nvidia graphics driver.

    Search for software & update and click tab additional drivers in menu and open it. Wait for minute and select nvidia driver and hit apply and restart.

    Install your nvidia graphics driver

Step 3: Download cuda-9.0 .deb package and install it

    Choose version cuda suitable with OS

    Ubuntu 17.10 allow this guide

cd Downloads
sudo dpkg -i cuda-repo-ubuntu1704-9-1-local_9.1.85-1_amd64.deb (This is the deb file you've downloaded)
sudo apt-get update
sudo apt-get install cuda

    Open terminal, type:

cd ~
nano ~/.bashrc 

    And add 2 lines below file above:

export PATH=/usr/local/cuda-9.1/bin${PATH:+:${PATH}} 
export LD_LIBRARY_PATH=/usr/local/cuda-9.1/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}} 

    In terminal, type: source ~/.bashrc

Step 4: Download cudnn v7.1 and run following command:

    Download cuDNN v7.1.1 for CUDA 9.1

cd Downloads 
wget https://developer.nvidia.com/compute/machine-learning/cudnn/secure/v7.1.1/prod/9.1_20180214/cudnn-9.1-linux-x64-v7.1
tar -xzvf cudnn-9.1-linux-x64-v7.1.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* 

Step 5: Prepare TensorFlow dependencies

    sudo apt-get install libcupti-dev

Step 6: Download Python and then tensorflow gpu

    Install Anaconda: Because anaconda support lots of library for Python programming

wget https://repo.continuum.io/archive/Anaconda2-5.1.0-Linux-x86_64.sh
bash Anaconda2-5.1.0-Linux-x86_64.sh
pip3 install tensorflow-gpu  # for Python 3.n   

    Open terminal, type:

cd ~
nano ~/.bashrc 

    And add a line below file above:

# Add by anaconda2 5.1.0 installer 
export PATH="/home/swapnil/anaconda2/bin:$PATH"

    In terminal, type: source ~/.bashrc

  • Check anaconda2 have you installed yet?
    •     Type: python

    •     If you successful installation, you will see result:

    Check anaconda2 have you installed yet?

  •     Check tensorflow-gpu have you installed yet?

    • You type: pip list
    • If you successful installation, you will see result:

        Check tensorflow-gpu have you installed yet?

Step 7: Check gpu has been step properly or not.

    cd Downloads

    Download this git repo https://github.com/tensorflow/models and unzip it.

    Use one of statements:

    python models-master/tutorials/image/imagenet/classify_image.py

    Or

    python models-master/tutorials/image/cifar10/cifar10_train.py

    Check gpu has been step properly or not

    Step 8: Demo

    Open terminal:

python
import tensorflow as tf
hello = tf.constant('Hello Tensorflow')
sess = tf.Session()
print(sess.run(hello))

Nguồn: Viblo

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