Deep learning setup on Ubuntu


Install GPU driver, CUDA, Cudnn

sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt-get install nvidia-375
sudo reboot

GPU info can be viewed using

nvidia-smi

Download CUDA 8.0

When asked whether to install GPU driver, select No

All the other select yes

Add CUDA to system environment 

export PATH=/usr/local/cuda-8.0/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib64:$LD_LIBRARY_PATH

check version

nvcc -V

Download cudnn 6

Extract

tar -xvf cudnn-8.0-linux-x64-v6.0.tgz
sudo cp lib* /usr/local/cuda-8.0/lib64/
sudo cp cudnn.h /usr/local/cuda-8.0/include/

Tensorflow (CUDA8+Cudnn6)

Reference: https://www.tensorflow.org/install/install_linux

Install The libcupti-dev library, which is the NVIDIA CUDA Profile Tools Interface. This library provides advanced profiling support. 

sudo apt-get install libcupti-dev

Install pip and Virtualenv:

# Ubuntu/Linux 64-bit

sudo apt-get install python-pip python-dev python-virtualenv

Create a Virtualenv environment in the directory ~/tensorflow:

virtualenv --system-site-packages ~/tensorflow

Activate the environment:

source ~/tensorflow/bin/activate  # If using bash
source ~/tensorflow/bin/activate.csh  # If using csh

(tensorflow)$  # Your prompt should change

Now, install TensorFlow just as you would for a regular Pip installation. First select the correct binary to install:

(tensorflow)$ pip install --upgrade tensorflow      # for Python 2.7
(tensorflow)$ pip3 install --upgrade tensorflow     # for Python 3.n
(tensorflow)$ pip install --upgrade tensorflow-gpu  # for Python 2.7 and GPU
(tensorflow)$ pip3 install --upgrade tensorflow-gpu # for Python 3.n and GPUFinally install TensorFlow:

When you are done using TensorFlow, deactivate the environment.

(tensorflow)$ deactivate




CUDA 9

export PATH=/usr/local/cuda-9.0/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda-9.0/lib64:$LD_LIBRARY_PATH

Cudnn 7

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